Innovation and Efficiency: Strategies for a Turbulent World [Reprint 2021 ed.] 9783112528860, 9783112528853

Citation preview

H.-D. HAUSTEIN/H. MAIER

Innovation and Efficiency

HEINZ-DIETER HAUSTEIN HARRY MAIER

Innovation and Efficiency Strategies for a Turbulent World

AKADEMIE-VERLAG • BERLIN 1985

Erschienen im Akademie-Verlag, DDR-1086 Berlin, Leipziger Str. 3—4 © Akademie-Verlag Berlin 1985 Lizenznummer: 202 • 100/31/85 Printed in the German Democratic Republic Gesamtherstellung: VEB Druckerei „Thomas Müntzer", 5820 Bad Langensalza LSV 0345 Bestellnummer: 754 472 6 (6888) 03200

Contents

Introduction

7

Part One: Innovation and Efficiency 1. 1.1. 1.2.

Measuring Efficiency in the Innovation Process Principal Indicators o f Efficiency Relative Efficiency

13 13 23

2. 2.1. 2.2. 2.3.

Economic Effects o f Basic and Improvement Innovation . A Model o f the Innovation Process Classifying Innovations by Efficiency The Effect o f Jiasic and Improvement-related Innovations on Efficiency . . . .

29 29 31 33

3. 3.1. 3.2. 3.3.

Industrial Organizations and Efficiency Innovative Activities in the Life Cycles of Industrial Organizations Determinants of Innovative Activities in Industrial Organizations Innovation and the Efficiency Cycle

44 44 47 58

4. 4.1. 4.2. 4.3.

Lighting Industry. A Classical Case o f Innovation Lighting. An Energy Problem Classification of Basic and Improvement Innovations in Lighting Measurement and Evaluation of Technological and Economic Level of Innovations in the Lighting Industry Sequence of Product and Process Innovation in the Case o f Incandescent Lamps Some Thoughts about the Future o f the Lighting Industry

61 61 63

4.4. 4.5.

70 75 77

Part Two: Innovation and Human Resources 5. 5.1. 5.2. 5.3.

Innovation, Structural Change and Employment The Case o f the Printing Industry The Case of the Automobile Industry The Case of Microprocessors

79 79 85 87

6. 6.1. 6.2. 6.3.

Investment and Innovation and their Effects on Employment Innovation and Investment The Relationship between Expansionary and Rationalization Investment . . . The Influence of Basic and Improvement-oriented Innovations on Employment

92 92 95 97

7. 7.1. 7.2.

Improvement in the Quality of Human Resources and their Use 102 The Case of the German Democratic Republic 102 The Relationship between the Development of Technological Funds and Labour Productivity 106

5

8. 8.1. 8.2. 8.3. 9. 9.1. 9.2. 9.3. 9.4.

Automation, Innovation, and Skill Requirements Technological Change and Skill requirements The Impact of Different Kinds of Innovation on Work Content and Skill Requirements Innovation, Occupational Structure and the Requirements for Further Education Human Resources, Creativity and Innovation. The Conflict between H o m o Faber and H o m o Ludens Human Brain versus Development of Productive Forces General Intellect. The most Wasted Resource Economic Dimensions of Creativity. A Paradox? The Conflict between Technological Base and Creativity. A Social Problem . .

113 113 118 125 134 134 135 142 149

Part Three: Innovation and Industrial Strategy 10. 10.1. 10.2. 10.3. 10.4.

Industrial Policy, Industrial Strategy, and Policy on Innovation Types of Industrial Policy and the Stages of Industrial Development The Main Components of Industrial Policy and Recent Problems Push and Compensation Policies and their Interaction Differing Attitudes toward Innovation Policy in Various Countries

11.

Industrial Development at the Global Level. Trends, Objectives, and Structural Changes 170 Innovation and Long-term Cycles in Industry 170 Interaction between Socioeconomic Goals and Industrial Structure in Groups of Countries 177

11.1. 11.2.

156 157 158 159 167

12. 12.1. 12.2.

Innovation and Industrial Strategy at the National and Sectoral Level 187 Innovation and Industrial Development at the National Level 187 Innovation and Relative Efficiency at the Sectoral Level. The Case of the Chemical Industry in the German Democratic Republic 192

13.

The Diffusion of Flexible Automation and Robots. A Major Issue of Industrial Strategy Saturation in the Traditional Automation of mass Production The Potential for Innovation in Flexible Automation A Forecast of Robot Diffusion Robots and National Innovation Policy. The Case of the German Democratic Republic .

13.1.. 13.2. 13.3. 13.4.

199 201 205 212 218

Appendix

225

References

235

6

Introduction

Innovation, the process of creation, development, use, and diffusion of a new product or process for new or already identified needs, has become a topic of concern for both developed and developing countries. The causes and motivations for the concern differ widely from country to country. Some countries that have taken the superiority of their technological ability for granted are now faced with a slowdown in the rate of productivity advance and a tendency to stagnate. Other countries, which in the past were successful in generating social and technological chance, now have to realize that thè current economic environment, especially the resource situation, needs new technological, managerial, and social approaches in order to deal with the new circumstances. At the same time, developing countries arp faced with growing imbalances between their responsibility to secure and improve the living conditions of more and more people and their technological and social capability to use their natural and human resources. Certainly the social systems in the countries are different, but all countries share a need to manage technology in a way that will improve production efficiency in order to create goods that will satisfy human needs. Despite claims to the contrary, we do not believe that these problems'can be solved by using today's technology, much less yesterday's. We have to realize not only that it is in the nature of technological innovation that nobody can be sure that his advanced technological position can be held indefinitely, but also that many current problems (shortage of energy and other natural resources, the growing imbalance between natural and human resources, and so on) are consequences of deeper structural problems in the world economy. We believe that many of the difficulties in the present structure of the world economy reflect a reduction of social and technical innovation. Therefore, we can now find in many countries a strong desire to develop a national innovation policy in order to overcome this stagnation. Innovation is not a goal in itself, and it is not possible to measure the rate and importance of innovations by calculating their frequency or identifying the input and output characteristics of a single innovation. The main purpose of an innovation is to improve thè efficiency of the production unit that adopts the 7

innovation, in comparison with the efficiency of the entire production system. By efficiency we mean input/output ratio that the production unit can realize under the given economic circumstances. Therefore, knowledge about the development of the relationship between the efficiency of the production units that have adopted the innovation and the average efficiency of all production units that are producing competitive goods to meet special needs is quite crucial for an understanding of the different strategies of firms within the process of their development and the scope of opportunities to influence the firms through national innovation policy. The dominance of special types of innovation (basic innovation, improvement innovation, or pseudo innovation), the-role of product and process innovations, the typical barriers and stimuli, and appropriate management skills and tools very much depend on the stage of development of the ratio between these different types of efficiency. To grasp the nature of the innovation process, its impact on the economic performance of the country, and to identify the appropriate managerial actions to shape and stimulate the innovation process, it is very important to understand the stages through which the innovation process usually runs. That is the main intention of the first part of this book. The development and use of human resources is a key element in the relationship between technological and social innovations. No study of technological innovation can be complete, without an investigation of its impacts on human resources. Innovation cannot always have a positive effect on the development of human resources and on their social, cultural, and productive forces, as there are many imbalances between technological innovations and the quantitative and qualitative requirements for human resources. But without technological innovation from a long-term point of view, it would be nearly impossible to improve human working conditions and create opportunities for the development and realization of man's social, cultural, and economic capabilities. Thus the relationship between technological and social innovation is critical to the development of human society. The present situation with regard to social and technological innovations has arisen from:

1. the growing imbalances between natural and human resources in different regions of the world, 2. the inability of social institutions and their technological strategies to make better use of human resources, especially in the developing countries, 3. the inability to coordinate socially the innovation cycle of basic innovations in order to make better use of human and natural resources, 4. the need to improve the quality of human resources and to create suitable conditions for their better use. 8

Part Two of this book focuses on problems associated with the last two points. In particular, we will try to explore the following problems, critical for the industrially developed countries: — innovation, human resources, and efficiency, — investment and innovation and their effects on employment, — the relationship between technological funds and the productivity of labour, — automation, innovation, and skill requirements, — the impact of different kinds of innovation on work content and skill requirements, — innovation, occupational structure, and requirements for further educations — innovation, human resources, and creativity. In Part Three of this book we deal with the question of industrial policy and innovation. The question of industrial policy and industrial strategy is not new. The economic growth of industrialized countries has been closely linked with industrial development for more than 200 years. These ties will endure, despite the increasing importance of the tertiary sector; policymakers in advanced countries do not think in terms of post-industrialized society. What is sought is industrial policy that can ensure further growth in all sectors of the national economy. Industrial growth is a combination of push processes that eliminate equilibria and compensatory processes that create them. Sometimes, however, imbalances become so severe that they can no longer be corrected with simple compensatory measures. Several kinds of imbalance are impeding industrial growth at present: — the energy imbalance, caused by the depletion of valuable nonrenewable energy resources, — the material imbalance, caused by the depletion of valuable nonrenewable mineral resources, — the technological imbalance, caused by discontinuous technological progress, — the ecological imbalance, caused by intense commercial exploitation of our natural environment without regard to long-term consequences, — the social imbalance, caused by neglect of human resources through illiteracy, unemployment, and other factors, and — the political imbalance, caused by acceleration of the arms race and other factors. These imbalances form a complicated picture that calls for a policy of compensation to reduce bottlenecks and ensure a new equilibrium. But here we are faced with a major problem, for the present network of imbalances cannot be overcome with traditional policies of compensation or improvement. Without a major push toward basic innovations, growth rates will continue to decline as they have in the past decade. 9

In our time there are two main processes, which are influencing economic growth and structural change not only in the world economy but also in the national economics. Those two processes are: 1. The radical change of resource situation during the 70's. The most significant results of this change is the revaluation of the natural resources and the devaluation of existing products and technologies. 2. The other process is the beginning of the creation of a new combination of productive forces, constituted through such basic innovations like microelectronics, information technology, the flexible automation, new energy options, the modern biotechnology, and the new materials. This new combination of basic innovations will trigger off the next years under the pressure of the new resources situation a radical innovation push, that will produce a new economic structure of the world economy with a qualitative higher productivity level. The phenomenon of revaluation of natural resources and devaluation of existing products and technologies is the reason for the current "revolution in value" —

Figure 1 World trade price changes on the capitalistic world market in percent per year (manufactured goods, oil, and non-oil primaries) Source: Financial Times, October 11, 1982.

10

which has a deep influence on structural change in the world economy and in the national economies. Figure 1 shows the development of "revolution in value" during the last ten years' — for oil, — for the other raw-materials, — for the manufactured goods. The revaluation of natural resources indicates the fact, that the real prices for oil, world-wide till now with 42 percent the main primary energy resource, was 1983 10 times higher than 1973. The decade before the increase of oil price was only 30.5 percent (1963—1973). The devaluation of manufactured goods and technologies is reflected in the fact, that at the moment the standardized products have the lowest price level since thirty years. It is well known, that today it is impossible, for the producers of machine engineering with traditional electronic to gain any profit on the world market. On the other hand producers of machine engineering, which were able to incorporate the achievements of microelectronics in their products, could realize very high growth rates in production and value increment. Table 1 shows the very high growth rate of manufactured goods which are very strong shaped through the microelectronic. For the 2nd and 3rd generation of industrial robots the growth rate per year was 34 percent from 1972 till 1980. For the computerised NC-machines the growth rate was 56 percent, computeraided design (CAD) 69 percent, computeraided manufacturing (CAM) 40 percent, for flexible manufacturing systems 30 percent etc. In our days in the new fields of machine engineering the growth of value per unit natural resources is 100 times higher than in the traditional machine Table 1 The basic innovations of the flexible automation No.

Year of the first introduction

Introduction time

Annual growth rates in percent world wide 72-80

80-90 (estimation)

1 NC-machines

1955

17

35

20. .. 30

2 Industrial robots

1962

10

44

25.... 30

3 Computer-aided design (CAD)

1965

7

69

4 0 . ..50

4 Computerized NC-machines

1969

3

56

40. „ 4 5

5 Computer-aided manufacturing

1967

5 '

40

30. .. 35

6 Flexible manufacturing systems (FMS)

1969

3

30

35 . ..45

•

11

engineering. Till now the process of revaluation of natural resources and devaluation of the existing products and technologies is dominating over the process of the creation of a new combination of basic innovation, which could be able to reconstruct the structure of the world economy and to drive the growth of productivity. That is the reason, why growth rates of productivity in all industrial countries in the last years were declining. The present decline in productivity growth rates, which is of course not conductive to equalizing productivity levels, cannot be explained simply by the levels of productivity reached. Instead, there must be a cause having a similar effect in all countries. From historical point of view, the cause is the absorption of the efficiency potential, which was created through the basic innovations of the forties and fifties or from the present point of view the lack of basic innovations for a new wave of productivity growth. The most important growth industries of the last 30 years have been chemicals, electrical engineering, automobiles, plastics, petroleum products, and aircraft. One of the main features of basic innovations is that they allow production units, which are able to use them to realize a higher growth ratfe of productivity than production units working with the traditional technology. But this growth rate of productivity is beginning to decline, when the efficiency potential is absorbed. The future perspective productivity depend very on from the creation of a new efficiency potential through the basic innovations of our time. But there are many reasons why production units show a strong tendency to follow more a policy of improvement and incremental innovation than a policy of basic innovation. To implement the right balance between improvement and basic innovation within a production unit or on the national economy leve) we must have a better understanding of the relationship between innovation and efficiency. To explore and the better understanding of this relationship is the main purpose of this book. The authors would like to express their gratitude to their colleagues from the International Institute for Applied Systems Analysis, Laxenburg/Austria, for their cooperation and help to identify and explore the main problems of this book. This unique research institute, that includes researchers from socialist and western countries, gave us the opportunity to work in an open and stimulating atmosphere. In particular we would like to thank Walter Goldberg (Sweden), Lothar Hiibl (FRG), Gerhard Wittich (GDR), Daniel Roman (US), German Gwischiani (USSR), Wolf Hafele (FRG), Rolfe Tomlinson (UK), Erhard Ulrich (FRG), Alec Lee (Kanada) and Tibor Vasko (CSSR) for their advise and criticism. Berlin, July 1984

12

Heinz-Dieter Haustein Harry Maier

Part One: Innovation and Efficiency

1. Measuring Efficiency in the Innovation Process 1.1. Principal Indicators of Efficiency Before presenting our model of the innovation process, we would like to describe the economic environment of innovations; without knowing the needs of and possibilities offered by this environment, one cannot understand the mechanism of technological change. The results of interactions between innovations and their environment are usually measured in terms of economic efficiency. In this book, therefore, we focus our attention on the problem of efficiency. The measurement of efficiency in socioeconomic and technicaleconomic processes is a wide and comprehensively explored field. We differentiate in this book among technical efficacy, economic efficiency, and social effectiveness. Specific measures of technical efficacy are clearly defined and verifiable, but it is difficult to give general indicators for the technical efficacy of such products as automobiles, washing machines, and television sets. This generalization is even more true for measures of economic efficiency, which are by definition more aggregate than are technical indicators. Here we also encounter other problems: the difficulty of clearly adjoining elements to defined sets, the complicated procedure of statistical inquiry, and the lost contact between user and producer of data. Yet the measurement of social effectiveness is the most complicated, as social welfare and social climate cannot be measured successfully by the monetary indicators that are so useful in economics. Innovation is a complex phenomenon that involves all spheres of technological, economic, and social activity, from research and development to investment, production, and application. In the early stages there are only two general indicators of innovative efficiency, which can be evaluated and predicted in rough variants (see Figure 2). These are the level of technology and the desired range of application. These indicators are combined into certain coefficients and are connected with recognized needs, time limitations and competitive pressures, and available resources. The level of* technology and range of application determine the compatibility or interference with existing equipment and skills, degree of interdependence, degree of complexity, and scale. For these coefficients we need additional information that is not available during the first stages of research and development. As the innovation process progresses, however, we are able to 13

14

calculate the risk factor, development time, lifetime, and resource requirements. We should then gradually make the previously mentioned coefficients more precise. Later, we can calculate in monetary measures the economic benefits and expenditures and can determine other indicators of economic and social efficiency. Owing to the interference of the new technology with existing equipment and skills, however, it is not easy to isolate the efficiency of the innovation from that of the production unit introducing the new technology. The only available solution to this problem is to compare an innovating unit with a noninnovating unit, but neither the results of interference with existing equipment and skills nor the effects of new elements can be isolated. It is difficult enough to measure efficiency in comparing similar industries or countries, but we encounter many more problems in trying to compare those under different social systems; both the goals and underlying mechanisms of socioeconomic actions and the reference system for measuring efficiency are different. Table 2 suggests that, at least for some indicators, there are no great differences between market and planned economies. We must ensure, however, that similar indicators are used for different goals in both systems and that in planned economies these indicators are calculated in a uniform way within the planning process connecting all levels from the plant to the national economy. A common reference system is needed and is plausible primarily — in fields involving such cooperative action as trade, exchange of technologies and investigation of solution to world problems, — at the level of intermediate goals.

Table 2 levels Level

Company

Measures of efficiency in market and planned economies at the company and national

Measures of efliciency Market economy

Planned economy

Growth rate (sales and profits) Productivity (labour and capital) Return on book value Profit margin (as percent of sales) Earnings per share Market share

Growth rate (net product) Productivity (labour) Return on funds

— — — —

National

Growth rate (national income) Productivity (labour) Balance of payments Capital coefficient

— — —

Export profitability Cost factor Material intensity of production Capital coefficient (output per unit of funds) Growth rate (national income) Productivity (labour) Balance of payments Capital coefficient

15

One of the most important intermediate goals in both kinds of economy is productivity. It is generally accepted that productivity growth rates over a long period reflect the true economic performance of an industry or of a nation. Data on productivity growth rates are available in all countries and are more comparable than aje indicators of profitability. The development of labour productivity could be an important indicator of a country's technological innovativeness, but we must also take into account the constraints connected with this indicator. Labour productivity =

Net product Gross product or Number of employees Working hours

Statistical details show that the gross domestic product (GDP) is not the same in the Organisation for Economic Cooperation and Development (OECD) and Council for Mutual Economic Assistance (CMEA) countries. CMEA countries include material input from outside the firm, while OECD countries do not. < On the other hand, the figures of CMEA countries include only goods and socalled productive services — not banking or insurance operations, rent, and similar, factors. Figure 3 shows the principal similarities and differences in methodology, while Table 3 gives a practical example. The net product according to themethodology of planned economics is 20 to 30 percent lower than the same net product according to the methodology of market economics. On the level of the industry, the methodologies are more similar, and the production value includes sales and the changes in inventories of intermediate products. We also find differences in methodology with respect to the number of employees; while apprentices are included as employees in OECD, countries, they are not in CMEA countries. i Materiali national global

product National

V/Zy/^y/ Constant capital ot materia!/^ Z/ZZZZ, , / / / f ,, . r/,/ , / / / Z Z / Z ,

m

W / z ' / y / / / / Tränst?rred, 'raluéyyyyy/y/yy//yy/ffly/Mffl¿ffiffi%fytirtr y y y y y y

V / / / / y y / Z . Means of production y ^ ^ / Z Z / / / / / , V / / / / Z / / / / Z , Portanti materials///y/y////////WMmwpiiientM At A ) Raw materials

income

Surplus pro- YffifYariabie capitali % tirages, etc.)////, created ràlù'eWÀ ^Ûepprtmenl i/ty/y^ fteons of consumption'/

3 l Ad) \ A IB) Consumer goods Intermediatepmduàs forCapitol goods for Capita/ 1 ConsumerRenewal \ Expansion Perishable [ Durable rep/acemenr^efrimslmé goods \ goods

Het domestic product at market price ! NDP)

Terminology of planned economies

\ Physical \ stages J of production L Terminology ' of market economies

Srass domestic product t BOP!

Figure 3 Content and mutual relations of eastern and western macroeconomic concepts in the sphere of production Source: EISENDRAHT(1964). 16

Table 3 Comparison of national income per inhabitant and national income in the USA, USSR, FRG, and Japan, 1977 National income per inhabitant

National income

According to the methodology of market economies, including nonproductive sector (services)

According to the methodology of planned economies, excluding nonproductive sector (services)

At official exchange rate

At purchasing power value Billion dollars

Percent

At purchasing power value

Billion dollars

Percent

At official exchange rate

At official exchange rate

Dollars Percent

Dollars Percent

4655 2115 3270 2235

4655 2599 2265

100 56 48

100 67 13

-

100 54 19 24

1010 673 135.8

—

1010 548 196.1 242

—

—

Country

Dollars Percent

USA USSR FRG Japan

7010

100

—

—

4480 3020

64 43

100 45 70 48

Source: Statistical Yearbook of the USSR (1977)

We cannot, therefore, expect the official productivity statistics of OECD and CMEA countries to give us a complete picture. However, the differences counteract and neutralize each other in part; this is particularly evident if we investigate growth rates. In Table 4 we present industrial productivity growth Table 4

Industrial productivity growth rates in major developed countries 1963—1979

Country

Planned economies USSR Poland GDR Czechoslovakia Hungary Bulgaria Rumania Market economies USA Japan FRG France UK Canada Italy

Industrial productivity growth rate

Change in industrial productivity growth rate

Change in output growth rate

Industrial productivity growth rate 1978

1979

1980

1981

19631973

19731977

5.6 5.9 5.3 5.4 4.6 6.7 7.0

4.8 8.0 5.3 5.6 6.3 6.7 7.8

-0.8 2.1 - 0 0.2 1.7 0 0.8

-1.4 3.6 -0.3 -0.7 -0.2 -4.3 0.1

3.5 4.8 4.2 4.1 5.2 6.4 6.8

2.0 2.9 4.0 3.3 4.3 4.2 5.8

2.6 1.0 4.5 3.2 1.2 2.9 3.9

3.2 -10.1 4.3 1.8 4.1 2.8 2.6

2.1 8.9 5.3 5.2 3.9 . 3.6 5.6

1.0 3.7 3.6 4.0 1.3 0.8 0.8

-1.1 -5.2 -1.7 -1.2 -2.6 -2.8 -4.8

-3.5 -9.5 -4.4 -3.4 -3.6 -4.4 -4.1

1.8 6.3 0.8 3.4 1.4 6.2 3.2

2.0 8.4 4.7 5.3 1.2 0.4 -6.3

-1.0 4.9 -0.8 1.3 -3.7 -1.6 5.0

2.9 0 0.7 2.4 5.7 1.2

•

-

—

Source: Counted on the base of Monthly Bulletin of Statistics. United Nations. New York. October 1982, Wirtschaft und Statistik, Nr. 7/82., Statistical Yearbook of the CMEA countries, Moscow, 1963—1981. 2

Haustein/Maier

17

18

•8

w-l

—

—

—

a ja

r-

o r-

O*

ts a I p a

i

o©

„

a 1 ¡t 5 3

Os Os

ai V) Vi O

I

I >. S "fi

i

'E

• -e s? 1' £

vo

2

Si S É c

|a

3o

&

00

l í

g í 3 ^ a &

•E

= -5 « 8 00 c fr ° 1 1 1 -e c E 8'& S 1 S w E

ai E s -o 1 u S ° — 8 m b ^ £ « « jó ñ (N 00 00 0> ON O O

tU I

"8

%

5 o E o a

o

¿i

6 j 8 jj ¡5 - "8 g l i l l °E

t: I ü «c E I P I O H I ed -O « Ji ti " N N fi (

í ¡ I K ¡ 0 - s § -8 § 1 1 8 I l í l § | J g - s l s

19

rates in major developed countries for 1963—1973, 1973—1977, 1978, and 1979. Figure 4 shows the decline in productivity growth rates for the economy of the FRG for the 27 years from 1951 to 1977. The average annual decline in productivity growth for this period was 0.2 percent.

'

I I I

•

'

'

'




o ü

" Ë s o

•S 8.

Ë

13 3 s

e2

£

o. E o o.

ft c

3

00 c K

c

•s

Ë

u t- •S. op u X

|> cd« S

4 X oo oo : x

X

Ë Ë 3

3

>, Ç? >

S

S

describe technological features. The trade-offs among these indicators are significant for technological policy in an industry. For example, there is no congruence between product-related change (2) and process-related change (3), especially in the first three stages. We need to determine whether the decrease in efficiency growth rates of product-related change from take-off through decline can be compensated by the efficiency growth rates of process-related change, and if so, for how long. Numbers 9—17 describe the cycle in economic terms. Managerial requirements obviously differ over the five stages. Fluctuations in efficiency often result from managers' slow or inappropriate reaction to changes. Numbers 18—20 show a more aggregated trade-off. Growth rates of absolute efficiency (18) are normally highest during rapid growth, but the absolute sum of benefits (20) is normally highest during saturation; thus managers are often unaware of the transition threatening to lead to the last stage, decline. The main conclusion that can be drawn from the mental model of the innovation cycle is that a high degree of efficiency and output of production is not an insurance against future disadvantages through an invasion of new technological options. The highest degree of efficiency, a large market share, and a high degree of standardization and vertical integration represent the last opportunity for a production unit, if it is also to gain in future economic vitality, to search for new ways of satisfying a latent demand or to satisfy an existing demand with better and less expensive alternatives. Today's examples for this concept of missing the right moment for change are the shipbuilding and steel industries. The main concern of the innovation policy of a country or corporation should be to maintain the right mixture between business activities in the different stages of the innovation cycle. Countries or firms whose main concerns are innovation activities in the maturation and saturation stage will lose, in the foreseeable future, their advantages in dynamic efficiency and run into stagnation. Table 9 reflects the developmental patterns of leading industries in the FRG, where structural change resulted from a number of basic innovations used after Table 9 Share of innovative industries (in percent) in the net production of the manufacturing and mining industries in the FRG, 1950—1977 Industry

Share in net production of manufacturing and mining industries in the F R G (in percent) 1950

Petrochemicals Plastics Aircraft engineering Chemicals Electronics Automobile engineering Total

0.88 0.22

1955 1.30 0.40

—

—

7.05 4.84 2.94 15.93

7.06 6.84 4.53 20.13

1960

1965

1970

1975

1977

2.22 0.73 0.15 7.08 8.19 6.04 24.41

3.33 1.20 0.30 8.45 8.93 6.64 28.85

3.80 1.73 0.45 10.51 9.96 7.49 33.94

3.56 2.34 0.45 11.77" 11.06 7.32 36.50

3.47 2.57 0.40 12.23 11.72 8.13 38.52

Source: Adapted from KRENGEL et al. (1973, 1975, 1978).

27

the Second World War. However, we should not forget that an innovation is always the fusion of economically relevant demand and technical feasibility. The higher efficiency of an entire industry no doubt accounts for rapid development in the industry's innovative sectors, but data also indicate a diminishing rate of relative efficiency (see KRENGEL et al. 1973, 1975, 1978). The growth rate of labour productivity in the innovative sectors in comparison with that in manufacturing industry as a whole was significantly higher from 1950 to 1955 than from 1973 to 1977. During the 1950—1955 time span, the growth rate of labour productivity in the petrochemical industry was 2.6 percent higher; in plastics, 2.0 percent higher; in aircraft engineering, 11.4 percent higher; in chemicals, 1.4 percent higher; in electrical engineering, 1.4 percent higher; and in automobile engineering, 3.1 percent higher than in manufacturing industry as a whole. During the 1973—1977 time span, the growth rate of this factor was significantly lower: in the mineral industry, 1.9 percent lower; in plastics, 1.5 percent lower; in chemicals, 0.46 percent lower; in electrical engineering, 1.7 percent lower; and in automobile engineering, 1.6 percent lower than in manufacturing industry as a whole. We can draw the following conclusions from these statistics and from our case studies: 1. A period of high dynamic (as opposed to average) efficiency follows the take-off stage. 2. Through better use of basic innovations the production process becomes increasingly capital-intensive and decreasingly labour-intensive. A diminishing rate of relative efficiency results, with a tendency for production units that have adopted an innovation to lose, after some time, the advantages of dynamic efficiency and to approach the average efficiency of the entire industry. 3. In the future, dynamic efficiency will depend largely on a country's ability to exploit new fields of innovation. 4. The main concern of a country in its innovation policy should be to have the optimal combination of business activities in various stages of the innovation cycle. Countries, industries, or firms concerned primarily with activities of the take-off stage may find themselves lacking sufficient economic resources to exploit these activities through improvement-related innovations. Countries, industries, or firms dominated by activities of the maturation stage, such as limitation and improvement of given technologies, incremental innovation, diversification of products, exploitation of scale economy, extension of vertical integration, and automation of production processes, will lose their advantage with respect to dynamic efficiency and experience stagnation. To find the proper mixture of business activities in various stages of the innovation cycle, we need information about the characteristics of innovations. 28

Distinctions that are important on the level of the production unit may be unimportant or impractical on a higher level. On the macroeconomic level, we think that it is important to distinguish between basic, improvement-related, and pseudo innovations. Basic innovations create new potential for efficiency and open new fields and directions for economic activities. Improvement-related innovations, many of which are incremental innovations, absorb this potential for efficiency by improving the given system and bringing it into balance. Improvement-related innovations become pseudo innovations at the point where they are unable to achieve higher efficiency in production. A crucial task to improve innovation policy at the national and company level is to provide information about future fields of innovation, which are dependent on various factors that fall into three categories: — urgency of demand for the innovation, — existence of scientific and technological solutions to meet unsatisfied or latent demand, — existence of a social environment that allows the fusion of demand-related factors and scientific-technological feasibilities. From the perspective of our current knowledge, for example, we can say that in the next two decades nations will achieve high dynamic efficiency, enabling innovation in the following fields: — The electronics complex (especially applied microelectronics), which will make further development in automation possible. — The energy and environment complex. — Biochemistry and the food production complex. — Technologies able to provide new organizational solutions to solve communication, traffic, urban, health, and recreation problems. Successful innovators will probably be those who are able to respond effectively in these fields of innovation. Once the right direction is chosen, success depends on managing the factors that influence innovative activities.

2. Economic Effects of Basic and Improvement Innovation 2.1. A Model of the Innovation Process Innovation vs. Invention

Innovation, a well-known term since the days of Schumpeter, should not be confused with invention (see SCHUMPETER 1952). Innovation includes the activities, not only of research and development, but also of technical realization 29

Distinctions that are important on the level of the production unit may be unimportant or impractical on a higher level. On the macroeconomic level, we think that it is important to distinguish between basic, improvement-related, and pseudo innovations. Basic innovations create new potential for efficiency and open new fields and directions for economic activities. Improvement-related innovations, many of which are incremental innovations, absorb this potential for efficiency by improving the given system and bringing it into balance. Improvement-related innovations become pseudo innovations at the point where they are unable to achieve higher efficiency in production. A crucial task to improve innovation policy at the national and company level is to provide information about future fields of innovation, which are dependent on various factors that fall into three categories: — urgency of demand for the innovation, — existence of scientific and technological solutions to meet unsatisfied or latent demand, — existence of a social environment that allows the fusion of demand-related factors and scientific-technological feasibilities. From the perspective of our current knowledge, for example, we can say that in the next two decades nations will achieve high dynamic efficiency, enabling innovation in the following fields: — The electronics complex (especially applied microelectronics), which will make further development in automation possible. — The energy and environment complex. — Biochemistry and the food production complex. — Technologies able to provide new organizational solutions to solve communication, traffic, urban, health, and recreation problems. Successful innovators will probably be those who are able to respond effectively in these fields of innovation. Once the right direction is chosen, success depends on managing the factors that influence innovative activities.

2. Economic Effects of Basic and Improvement Innovation 2.1. A Model of the Innovation Process Innovation vs. Invention

Innovation, a well-known term since the days of Schumpeter, should not be confused with invention (see SCHUMPETER 1952). Innovation includes the activities, not only of research and development, but also of technical realization 29

and commercialization. In looking at the great number of studies and books on innovation that are published, we noted first, the microeconomic approach used in most studies and second, the common view of innovation as a single process, a single technological change (in the narrow sense of the word technological). We think that innovation must be treated differently. The history of technology provides many examples where single important technical solutions had no socioeconomic impact (see HAUSTEIN 1974). We do not consider such solutions to be innovations. The steamboat Great Eastern, for example, was a fundamentally new solution in the mid-nineteenth century. Its motive power was 100 times stronger than that of customary ships, while its tonnage was up to 7 times greater. Such a ship was, however, inappropriate at that time, as ports and service facilities were not able to accommodate it. After several years, the shipping trade firm that owned the steamboat, unable to withstand its economic consequences, went into bankruptcy (see Herriot 1955). As a second example, many inventions in electrical engineering were well known a century ago. The 1883 exhibition of electrical products in Vienna included, for instance, electric water heaters, hearths, cushions, and motors, but there was no application for such devices in the existing complexes of needs and resources. Only one invention (the incandescent lamp) completely changed the existing system of demand (that for lighting). The Berlin power station was built in 1885, and until 1900 electrical demand was primarily for lighting. Electric lighting was accepted as a basic innovation for two reasons. First, a rapid increase in demand could be established in this field. Electrical illumination of the Munich opera, for instance, had a striking effect. Second, Edison, the pioneer in this area, was not only a great inventor but also a good systems engineer and entrepreneur. He built a complete system, from production and distribution to usage, for satisfying the demand for lighting. He initially set the price for one lamp at $ 0.40, but costs were higher — $ 1.25. After three years he was able to reduce costs to $ 0.37 and to obtain large profits from an explosion in demand. These examples suggest the difference between technological change in a narrow sense and the innovation process. Innovation always causes a change in the technological system, with a great impact on the socioeconomic system or subsystem affected. Such subsystems are — complexes and subcomplexes of needs or demand (e.g., the demand for lighting), — complexes and subcomplexes of resources (e.g., sources of enefgy), — processing cycles from primary production stages to final consumption (e.g., the wood cycle from forestry to the use of furniture). I (We also differentiate between basic and improvement-related innovations from this standpoint in Section 2.5.) 30

2.2. Classifying Innovations by Efficiency There are many possible ways to classify innovations. Looking at the production process, for example, we can differentiate among innovations related to a product, to a production process, or to manufacturing. With three types of technological change (new, improved, and existing technology), we find 33 or 27 possible combinations. One, for example, would be a new product produced by an existing process in an improved manufacturing system. Innovations might also be classified, according to their economic results, as capital-(material-, energy-, or machine-) saving or as labour-saving. We might also classify innovations according to — class of need satisfied, — kind of resource saved, — kind of resource processing system or industry affected, — change in the relation between extension or rationalization investment, — source calling for innovation, — kind of knowledge used, — cost involved, — factor determining success, — consequence, — share of research and development needed, — impact on the system's goals, — component of the production process (e.g., material, machines, manpower, product, process, organization) affected, — level of administration needed, — size of firm involved, — type of property, — degree of international competitiveness reached. Groups of interlinked innovations can be found with the help of cluster analysis; the Institute for Economic Research (IFO) study, for example, differentiated between 20 criteria and 274 features of innovation (see UHLMANN 1978). Through cluster analysis, 218 innovations were classified originally into 18 and later into the following 11 significant groups (clusters): — market-oriented basic innovations in large-scale organizations (enterprises), — cost-reducing innovations within state-owned energy-producing enterprises, — innovations within leading noncooperative technological/industrial organizations, — market-oriented innovations within leading cooperative private enterprises, — cost-reducing innovations without external transfer of technology within large-scale energy-producing enterprises, — innovations based on transfer of technology within small-scale enterprises, 31

— innovations based on transfer of technology within energy-distributing enterprises, — innovations adapted by individuals, — innovations based on trial and error, — market-oriented basic innovations introduced according to governmental policy, — routine innovations sponsored by multinational corporations. We do not think it is possible to construct an universal classification for innovations by using theories or empirically based methods. In establishing a system of classification, we must begin by asking, for what purpose are we doing this? We look at the innovation process from the standpoint of the national economy or its corresponding subsystems. These large systems have three goals: — to ensure their continuing existence and function by counteracting inhibiting factors, — to ensure the balance of the system by reducing bottlenecks, — to find new ways of ensuring efficiency in a changing environment over a long period. With respect to the impact of a given technological change on a large system, we can differentiate among three functions controlling the system: — continuation, — compensation, — push. In the energy system, for example, we find continuing use of existing primary resources. We also encounter bottlenecks in a given energy system, with increasingly negative consequences for its efficiency. It is necessary to compensate for these bottlenecks and to ensure the balance of the entire system by mobilizing new resources. We also find technological changes that not only overcome existing bottlenecks but also establish new ones. These changes act as a stimulus, pushing the existing systems over a long period and thus changing it into a new one. Table 10 shows these functions with respect to two different types of innovation. The first generally concerns giving a push to the technological level (and later, to Table 10

Types of innovation and their functions

Type of innovation

Basic (BI) Improvement-related (II)

32

Function Push

Compensation

Continuation

• • •

• • •

• • •

the efficiency) of an option and often results from overcompensating for existing bottlenecks. The second deals primarily with continuing well-known processes and compensating for bottlenecks. These two polar types of innovation, basic and improvement-related, are also known by the terminology that follows. — Basic innovation (BI): fundamental, major, strategical, radical, or discontinuous innovation; revolutionary change. — Improvement-related innovation (II): routine, incremental, minor, tactical, rationalization, or continuous innovation; evolutionary change. 2.3. The Effect of Basic and Improvement-related Innovations on Efficiency Optimization

of

Investments

The main function of a basic innovation is to give a push to the existing system of technology and to change it into a new system with higher efficiency. The principal function of an improvement-related innovation is to balance a given system by improving its efficiency. As basic innovations are a complex of smaller changes, in one sense the difference between the two types is relative. Basic innovations, however, consist of small changes leading over a decade or so to increasing returns, while improvement-related innovations, starting from the existing technology, lead over a similar time span of 10 years or more to diminishing returns. The relationship between policies of push and compensation can be demonstrated through the example of investment allocation. All investments in a given industry can be subdivided into I+ = It + I2 +

C,

(7)

where / j is the investment to overcome bottlenecks with respect to technical equipment (compensation investment), per employee, I 2 is the investment to introduce new technological solutions (push investment), per employee, C is the investment for replacement (continuation investment), per employee. Optimization is necessary only for (8)

i2 =

and 3

I2/I

(9)

+ i2 = l .

Haustein/Maier

33

If the main criterion for efficiency is labour productivity, we take the replacement coefficient 1. =

L0nP ' — L.1

100 percent,

(10)

where L0 j P' I L0 — L — L0P ' — Lx

is the number of employees at time 0 or 1, is the index of output (PJP0), are investments, is the absolute saving of labour force, is the relative saving of labour force.

The coefficient /. thus shows how many employees are replaced (relatively) by a given sum of investments. This coefficient differs for compensation and push investments, but in both cases we find an invariance: when investing more, replacement coefficient i increases up to a certain point and then decreases. Assuming a simple dependency including this invariance, we write {a = a n h ~ ai3^î • /.2 = a22 i2 a23^.

(11)

The first coefficient l n shows the relative replacement over the share of compensation investments and the second coefficient Ii2 shows the relative replacement over the share of push investments. In general, parameters a. are different in the two cases. Compensation investments initially have rather high replacement effects, which then diminish rapidly; push investments initially have rather low replacement effects, which then increase before diminishing. The relative economy of labour is the sum of both types of replacements. £ = 4

+ 4 ,

(i2)

L = Ija + I j a ,

03)

L = I.ia^

(14)

- al3if) + I2(a22i2 - a23?2).

As i'j = 1 — i2, we find L = //n(-2a12 + 3a13) + i\(al2 - 3a13 + a23) + ¿|(a13 - a23) + a fl + i2- 13> I = I(d2i2 + d3e2 + dJl + 4). (16) From

34

^ = I(d2 + 2d3i2 + 3rf4.il) = 0, di2

(17)

, 2d-, d2 '2 + r r >2 + r f = 0 •

(18)

We obtain the optimal solution ¿3

17 ¿3 V

¿2 1 1 / 2

Our assumption of two quadratic equations is arbitrary; it might be more appropriate to use an exponential function for this purpose. A more complicated problem is the actual statistical identification of the two types of replacement. We used data from the automobile industry in the G D R from 1955 to 1970, where motor production showed the typical behavior of compensation investments, with a low increase in equipment per employee. We compared investments of the two types, using the two interlinked subbranches (motor production and car production) of the automobile industry. We determined the parameters in the following equations by analyzing the time series of investments and replacements of labour: I n = 25.0/j — 52.3f?, li2 = 61.2j2 - 72.9i* . The absolute economy of labour for the 1955—1970 period was I = /(106.9i2 - 70.7^ - 27.3). The relative economy of labour was I = 106.9i2 - 70.7/j - 20.6i\ — 27.3. In 70.72

_ 70.7 2,l 2)

' -

" 6L8

+

6L8

106.9 +

6lJ '

we find an optimal i2 of nearly 60 percent. Then the optimal replacement is / = 6.86 (relative coefficient), L = 126,000 employees. The real economy of labour was I = 5.36 and L = 96,000 employees, showing a difference from the optimal solution of 30,000 employees. The share of push investments was actually 33 percent. Of course, estimating investment allocation in the automobile industry is not simply a question of determining the share of push investments by one criterion. Our example merely illustrates the opportunities offered by modeling. In general, we assume the efficiency of policies of push and compensation shown in Figure 8. Although given for only one point in time, the figures shown in Table 11 for the energy field reflect the same general pattern (see also RAY 1979). For short-term planning we prefer a policy of compensation; only for a longer perspective do we choose a policy combining push and compensation. In 3*

35

Push

BJ

/

/

Compensation

Continuation

N

\

\

Years

Years

]J Years

Years

Figure 8 Typical progression of benefits over time under three investment policies for basic and improvement-related innovations (BI and II, respectively)

practice, many basic innovations dominate the efficiency of the entire system only 10 years or more after the first commercial use (GOLD 1975). The primary problem is therefore the length of the optimization period. The shorter this period, the more important a policy of pure improvement becomes. The first long-term plan of a national economy oriented toward a basic innovation (electricity) — the so-called GOELRO-plan in the USSR — had a time frame of 10 to 15 years (1920-1935).

The distinction between BI and II, first made by historians (ZVORYKIN et al. 1962), was a qualitative theoretical approach. We give the terms BI and II (or the revolutionary and evolutionary technological changes cited by NICK, 1973) another interpretation. In many studies the distinction means only a certain degree of technological change. Our starting point is the influence of a given technological change on the socioeconomic system. In any given system, we find a tendency for the average efficiency to stagnate or to decrease. This tendency can be reduced by improvement-related innovations but overcome only by basic innovations whose efficiency is higher than average and whose share in output is sufficient. While the effects of basic innovations take longer to occur than do those of improvement-related innovations, they are higher. Of course, this does not mean that we can ignore the effects of II, which are comparable over a long period those of BI. BI and II are two sides of one coin, and the development of metallurgy proves that understimation of II is as dangerous as fear of BI. Nevertheless, II is not able to ensure the endless efficiency of a large system. 36

m "t I - « t f^ o g "g

3 S 00 p •O S C — rt «g

I

-

.2 g Oo s I o £ o G

a -S

° .2

* o ^ 8 o •'S S = S i: ? - s s e s .2 i S i l i k í

1111

C g. a H '£ - .2 § o 8 fr J = « S o ^ i 55 ?k í. ! Í1 S-g S-g S • S §

I l

s

Û U U U Û Ztua.OO^Deoii.víui-SwIti. S3 4> .g 2 13

s » -S s

0 1 g Ë

a

2

1 I ' t S

» "H 3 ë «s •§

•8 6 •a o "o a •C 8

SS V

s

1•S 3

I

"b ¡3

ja Si « & s & 3

I I ¡1 «

S e Ë SOu u

I ï §

g S

& s s s ss

1 ou bo Si

«'S -si 2

o Ë - e S S « . s ts » s « s "75 «î "rt B •fi S -B -s S l S l .s o .S s '

g

3

S S " > ®

g 'B -a 8 § g^ S u X u < ü £ S < 0 S Q ¡Í -B

s a

d- S

•S g j- U) •s M •E 3 S e " -g

I

S B

2

s.

il M 'S s C

5 8 c g

37

Limitless asymptomatic increase of efficiency through better balancing of elements is conceivable only for a closed system. When we consider the relations of a large system with the environment, we must take into account the possibility of sudden or tremendous changes, which may lead to major bottlenecks, resource deficits, and conflict situations that can be mastered only through complex, radical solutions. As a result of delay in their realization, basic innovations may have a compensatory function without stimulating efficiency during the first step of application. The energy study conducted by Hafele at IIASA showed that in using final energy we can expect many improvement-related innovations (Energy Systems Program Group of the International Institute for Applied Systems Analysis 1981). This helps us to reduce the primary energy/GDP coefficient in developed countries from the present value of 0.8 to 0.5 and in less developed countries from 1.5 to 1.0 (Maier 1979). Conversely, the same study indicates that we must be aware of a completely different development with respect to such basic innovations as nuclear energy, synthetic fuels, solar energy, and biogas. In the next two decades, we expect a rising primary energy/GDP coefficient resulting from extensive demand pull and from delay in mastering the economy of basic innovations (see Mensch 1976). Potential and Actual Outcomes We have mentioned only the functions of innovations that contribute to achieving the goals of large systems. However, some innovations that seem appropriate for meeting the goals of a socioeconomic system or subsystem actually have a generally negative influence on it over a long period. We call such an innovation, the primary or secondary consequences of which damage the system's efficiency, a pseudo innovation (PI). We find many pseudo innovations in the consumer goods industry. In American supermarkets, where about 1500 new products appear each year, less than 20 percent survive more than one year on the shelves; the rest have proved unsellable, faddish, risky, or unprofitable, or have been made obsolete by competitors with other new products. Furthermore, positive technological changes with positive socioeconomic potential can appear as innovations that have negative effects. As Table 12 shows, a major technological change (potential BI) may thus occur only as an II or as a PI. The actual outcome depends on the ability to use innovative potential by changing many conditions necessary for optimal efficiency of the new or renewed system. As all these conditions change over time, a potential BI may or may not become an actual BI. For example, automation of the production process in a given (nonautomated) industry is a BI. It may become an II if changing the traditional process is not possible, but such automation without process-related change is not efficient. It may also become a PI; solar energy, for example, is a potential BI that may actually occur only as a PI — as in cases where solar heating systems are installed in existing buldings without changing other conditions. Similarly, an innovation planned as an II 38

Table 12 Examples of potential and actual outcomes of basic, improvement-related, and pseudo innovations (BI, II, and PI, respectively) Potential outcome

BI II PI

Actual outcome BI

II

PI

Automation in connection with new production processes Oxygen process in metallurgy Does not occur in reality

Automation without changing the established production process Improved performance characteristics of machines Change in advertising made for the benefit of the manufacturer but eventually useful to the consumer

Retrofitting residential buildings with solar heating systems Higher speed and motive power of automobiles Change in product with no real effect on the consumer

might actually function as a BI; we often do not clearly realize the qualitative or quantitative potential of an innovation. A PI might become an II as a result of learning induced by negative results. As many innovations are closely linked over time, it is important to realize and to promote positive feedbacks in the innovation process. For example, the introduction of the railway system led to higher coal demand, and higher coal demand required better transport, which was possible through the railways. The prehistory and history of basic innovations are made up of groups of small innovations. The incandescent lamp, for example, was a BI in which many small changes were needed, and from Edison's time on, its development has been a complex of improvement-related innovations. We can differentiate between improvement-related innovations leading to basic innovations and improvementrelated innovations using the efficiency potential of basic innovations. BI is the result of a long process of selection in a wide field of smaller innovations that are competing with each other; it is essentially a package of technological changes creating a new system. A new BI establishes a greater potential for efficiency that can be more or less fully mobilized only through many improvement-related innovations. We call this incremental innovation. A More Detailed Approach to

Classification

The technological level, range of application, and impact on the national economy of basic innovations differ greatly. The technological level is closely connected with the necessary type and amount of mission-oriented fundamental research, applied research, and development, so it is understandable that the authors of the IFO study proposed to call basic innovations all technological changes that go through research and development stages ( U H L M A N N 1978). Another extreme is to use the term only for the main historical breakthroughs in technology, such as the steam engine, tool machine, and electricity. We cannot call pure scientific or technical results (inventions) basic innovations, as they are only first steps; their eventual classification depends on the availability of resources, 39

socioeconomic needs, and capability of a given society for mastering the inventions. Thus it is not possible to speak about BI without considering social factors. We propose calling basic innovations major technological changes that — are based on fundamental and applied research, — have a well-defined high range of application — that is, modify essentially the existing demand or application complex (e.g., synthetic fibres), establish a new demand or application complex (e.g., television), or change the entire system of needs (e.g., production and consumption of electricity), — are connected with new scientific/technological principles of a higher order. BI greatly stimulates the entire socioeconomic system, has an enormous potential for efficiency, and is able to arrest or alter the tendency to decreasing efficiency in using resources. The technological level of innovations is also an important indicator, but its connection with the efficiency of the system affected is not linear. Some basic innovations of the past, such as Hargreaves' machines, were not based on new scientific/technological principles. On the other hand, some innovations of a high scientific/technological level, such as the coal arc lamp of the nineteenth century, have not found a wide range or field of application. Tables 13 and 14 illustrate various kinds of BI and II. We can also distinguish among three kinds of PI: PI 1 — Simple product-related innovations that do not improve the efficiency of the user's system (e.g., many modifications in automobiles), PI 2 — Innovations that improve the efficiency of one process but reduce the efficiency of the system as a whole (e.g., plastic materials that are inappropriate for practical needs), PI 3 — Innovations that improve the system's efficiency in a short term but eventually lead to large losses or imbalances (e.g., process-related innovations in the chemical industry that later have a negative influence on the environment). Classification of three kinds of BI, four kinds of II, and three kinds of PI gives us the following ten kinds of innovation (I 1—I 10): I BI II PI BI 1 BI 1 BI 3 II 1 II 2 II 3 II 4 PI 1 PI 2 PI 3 14 15 16 17 18 19 110 II 12 13 Looking at the ocean of innovations of course reveals a continuum not measurably by one clear indicator. Rather than considering this only as a continuum, however, we must take into account the obvious turning or break-even points in complexity, efficiency, and manageability in the total field of innovation. For instance, in socialist countries each scientific/technological task of one planning cycle is 40

l |

a S

3 a B •o o S c Ü — 3 O

i i 00 o

.§ s J u- a s

l ï

1

S

o S O "S g U

U O.U XI

1 1 c i «6 0 w S i

fr 3 3 "O .a o

.S

§

gï t .1 E * _ s f i 2 "O t .2 ^ c 25 5

1 1 1

!

8

"o ï S U S B g • * 4)

o i

« V) U Ui 4) .2 S S "H..2 5 6 o w 8 o.

.S

H I I

s

I

•a o u

& S3 6 .1

»

. X ' 5 CU > e — •O O g= "§ S E ïî "3 M — S- e .S % Ë 8 w

« . Jä ^ o O" a

c

e e

a

s S» g S

ì §"E § 1 § . S 6s S g g o. S «O D o s e -g9 S? = o: u .S " > o M • s =3 Sw O. S3 ä — '3 B S i I tñ S .S Ì J

a

§

l M c s

I

o ea s i

B o z

s o J

•a a

s

= a « e s

T5 -8 íO. S V s Iß cd C a

cd C

a

T3 s

s 5

•a c«> e o

c o CL

•ca. 8

s

s

— 5

OJ S

o Z

I -I

I X

° r st i•§ u *

I

£

c S S 4» •o :»

•o c

r/l i " ¡T

Ö

I I U 3

O 4> O & .2 S

J"5 "sS uS

•C o 3 E

3 •8 o-, ï :

l ' i l i

o S cd J: Vi

1 1

u

S u i "o s § « ï-S » I ¿ s» .S I .2g >-)

s iO. I-M

ja S

8. & I I

s & u

—

e 1 1

a

.S1 V .S S o s a ¿ I S

41

associated with one level of administration, from the firm to the national economy. Each type of task has various prerequisites in management and planning. These are the most important relationships from our viewpoint; we do not want a complete or eclectic classification of all kinds of innovation. Instead, we concentrate on the process of transition from a given structure of technologies to a new structure that is able to overcome socioeconomic bottlenecks and major gaps in resource processing systems. Table 15 shows a more sophisticated classification by technological level and range of application that enables us to differentiate among 49 kinds of innovation. An Innovation Level Index The next step in establishing an innovation classification could be a quantitative evaluation by a technology level index. This step was made in an OECD investigation of 1246 innovations in five countries from 1953 to 1973 (see Table 16). While the linear level index used by the OECD study is given in column (1) of Table 16, we think that an exponential level index (column (2) is more appropriate because the distance between basic and improvement-related innovations should be greater than the distance between different kinds of improvementrelated innovations. The frequency distribution in column (4) also points to an exponential pattern. Another argument is the exponential growth of technological parameters during the transition to new principal solutions and the exponential saturation in the period of improvement. If we assume that the importance of innovations w (a coefficient between 1 and 100) follows an exponential function and the two parameters ik and vk are connected in a multiplicative form, we can write W = ikvk ,

(20)

w = e°V* ,

(21)

Taking a simple symmetrical scheme (a = b), we then have w = e2"* k = 0, 1,..., 6. According to 1 ^ w ^ 100 (percent), we find for k = 6 100 = e12a , a =

In 100 12

= 0.38376 .

From this we find the coefficients of importance for each level within the 7 x 7 = 49 field (see Table 16). When we try to adjoin one innovation to the 7 x 7 = 49 field, we realize that we often have difficulty in making an exact estimation; we thus find it inappropriate 42

Sg SP E

§a

E "O ^ ¡Sol a E « §• oS « E •3 a fi £ Í S js S ë SS

I

2

t

js i •8

2 Í&

I

^ 53

Si & > •«t g f- 4 b 00

° -3 W-! ft.

^5 S.S O es. 2V _ 2 O T) B 5 •S e ö 01.2 3 s .2 i g s •§ û 8 -S S o S.

E § 2U

g S I Io"8 •Hi ï 1 I I a &g

i •s&- S-S. ì 'S. !

SS •S

©

5 j3 T3 SS S

-a •. s 'S M I s i i' s la If s * » • s s S0 s i s ï e o .0 1 i 8 I ¡y S^ g 5 15 § .2 2 U ï c ï Ü aïM O S •äaU ©

'S

-

o

3

E

4> «9

a

m

¿2

CA

3

«

. S >> S g. g s & a &.2 6 g-« 5es-a I ff! * U g -3 cUm en s 6 6 '3 p.

S

a

e -S s e

1

S

a

i2 S

Il M. •s

s

I f l 00 E o " -9 a a"3• S ä g £.211 3 1 1 B s e> aS e w . — «« BW S*. a e e l> 9M o S t¡. t

s ° Htì l ~ - O2 'S e Sa e

—

o 2

o o o o o

3

Ü JS

.2

S

l - l8 sI lS •9 .a ? a > 4) si S £ « C-i I

2

.2 i g sia«g í

g

a o e '3 e 'S -5 u S S CO tG « o 3 S OiZ g a • 1 1 1 «MS ?2 £ £ Q ¿I u S

o» oo r«o o ^ P

g i A io

g U E .a m s -a O rt §•8 ¿ä I

Ov ^t

**) O ^ C< ®0 "O

>

— m Tf

fo 'a s s e

N O— (N «— ^—-,

-w

jn ¡o o N oo Tf n

S2 »iK2 •c « a

oo ys — hv fs ÍÑ"

V)

«

«

l l - i

¡s -S tm CS C s -S •f-èi -.3 U - «§ R.s°

QS 3 « U a S I." e > I- s & « O 'S O rt 3 b S I I I Î5 > S g «s -o Js c — a10 o ? M C CMS s S 2 i 1 i l l Im ft _

.2

SS

2o .t:1 °s S S 2* .rt _ o 2S-S 'C 'C g 3 J™ Sz. •• « « Í s > > I 3 Ë° 3 H il s Z 6, » Z H Z ?

55

of variables promoting innovative activities. We identified three other important determinants, the economic mechanism (including price relations, planning mechanisms, and 'other incentives), know-how, and cost. Our improved scheme for factor analysis is shown in Table 22, which illustrates the complexity of innovation management. Using Factor Profiles in Comparing Enterprises While the number of innovations analyzed was too small allow us to draw further conclusions, it became clear to us that the 32 firms we investigated did not sufficiently develop innovative potential. The influence of both factors inhibiting innovation and factors promoting innovation in a given firm can be described by a profile. We also discovered that the objective factor configuration is far more unified than is the specific behaviour of firms. This finding suggests that we should pay more attention to the objective factor configuration of the innovation process according to industry, to the national economy, and to basic innovations and improvement-related innovations. On the other hand, we should analyze the individual behavior of firms and compare our results with the objective factor configuration on the level of the industry or society; this could provide us with information, not only about the firm's management, but also about national policy for innovation. The consequences of an inadequate policy for innovation in an industrial firm are not always immediately. It may also take a long time to develop and Evaluation coefficient

Figure 12 Profile of the strength of factors inhibiting innovative activities ( ) and factors promoting innovative activities ( ) in 32 firms (average), where I is innovative potential, S is strategic orientation, C is cooperation and coordination, O is capacity for mastering on-going processes, E is economic mechanism, K is know-how, and M is mean value

56

to use creative potential. Managers should give the greatest attention to the human factor and to the appropriate combination of important factors. We propose investigating this problem by a specific profile showing the strength of factors inhibiting innovation and of a firm's own activities in promoting innovation during the innovation process. Figure 12 shows such a profile for the sampled 32 firms in sectors of the consumer goods industry. We note the greatest differences between the strength of factors inhibiting innovative activities and the strength of the firm's own capabilities in the following determinants and stages: — — — —

cooperation and coordination: research and development, innovative potential: production, know-how: production, capacity for mastering on-going processes: marketing.

Therefore, a long-term development program for a given industry should include measures for improving organization in research and development and for increasing the qualification level in production. Current organizational changes in industry in the GDR have the explicit goal of mastering the complexity of the innovation process and enabling firms to implement their new products and processes without bureaucratic delays. In this process, exchange of experience between enterprises plays an important role. Comparison of enterprises is an effective tool for recognizing both bottlenecks and opportunities. For example, Figure 13, which compares a single firm's profile Evaluation

Figure 13 Difference between strength of factors inhibiting and strength of factors promoting innovative activities for average of 32 firms ( ) and 27 firms ( ), where / i s innovative potential, S is strategic orientation, C is cooperation and coordination, O is capacity for mastering on-going processes, E is economic mechanism, K is know-how, and M is mean value

57

with the average of the investigated sample, shows, that the firm under consideration might have experience in marketing that would be useful for other enterprises. Comparison of enterprises was formerly oriented primarily toward technical and economic indicators. Comparison of determinants of the innovation process, innovative potential, and know-how could be a useful addition to these traditional tools of management. Profiles enable us to trace major gaps and bottlenecks and to discover possible directions for further investigation of obstacles and factors blocking innovative activities, thus providing an instrument for management at the corporate level. Under a planned economy, exchange of experience and competition between teams of workers in outbidding planned figures play an important role. A firm's profile further explains the quantitative indicators of efficiency. On the other hand, we can assume that profiles show significant differences among branches of industry and among stages of the efficiency cycle. Progression through take-off, rapid growth, maturation, saturation, and decline is connected with structural changes, which should be planned at upper levels of management.

3.3. Innovation and the Efficiency Cycle Our investigation of roles of basic and improvement-related innovations and our analysis of the life cycles of industrial organizations can help us to understand better why the innovation process is not continuous as we might first assume; rather, it is interrupted by the effects of stimulation or its absence. The relationship between basic and improvement-related innovations drives the process of technological and economic development. This relationship is at the core of the special circumstances surrounding the birth, growth, and decline of each successive new branch of industry. Simple demand pull models or technology push models are therefore inadequate explanations of the innovation process — in specific branches of manufacturing industry or in the economy as a whole. The interaction between science, technology, and the economy varies in its nature and intensity over time and among various industries. We cannot say that inventions are always the simple result of demand pull. Need and demand are the main driving factors in the diffusion process. When we look at the innovation process in retrospect, we find that inventions are all caused by an existing need, but the more important ones came from a rather probabilistic cognitive process that led to the achievement of goals that had not previously been realized. Penicillin, saccharin, and synthetic rubber are examples. At the end of the invention process, needs that were not the original targets of research and development were satisfied. Often demand pull is the main reason that incremental innovations use the efficiency potential of basic innovation. But fundamental inventions are less (or not as directly) connected with market demand or concrete needs. Basic innovations create new fields for production and 58

efficiency through, say, a series of new scientific discoveries and technological advances. The connection between these advances and the developing needs of society is often realized slowly. The role of basic innovations in the development of efficiency is demonstrated through Figure 14.

Figure 14 Role of basic innovations in the development of efficiency, where e is relative efficiency, BI is basic innovation, and p is given by eqs. (28) and (29)

We turn now to the impact of basic and improvement-related innovations on the economy. Efficiency in general is e

o = E0/C0,

(22)

where E0 is the sum of benefits or revenues at time t = 0, C0 is the sum of costs or expenditures at time t = 0. At t = 1 we find 1

E0 + AE

1 +

A£/£o

C0 + AC

1 + A C/C0

ì ^ •oa taS a" '

e •a «

g o. 3 * 1 S •§ -fi o Ëat.2 g -eVX Mi: 3 » ?« -2

.g o

•E 0 1

a. u> a Ü > o a c

'S I o a o. e e. a O. _ vi "O S®

I l 1 1 . 1 -s¡52 s il u. wo o a S « 2. Sì > ï « 8, J « s-S ê I-s-S ¿ 3> O o si s « 15 .-So»

00 co v> m ! S : "â Ss » >S .2 ;-I p c

e « ëa' B S!

l i s «co s & 6 S * B o

m S i» X 5r i Sü ^ ü > ïû

ä «O d2 G V 00 6 ed S

• J)o & S s £ ta C f'uS J&2 btO

f lCSf tí Os VI i, o o« co -S a

&

1 «Jh ô ,S o 8>S c •Is - a 2 o\ •S o

o •a -2 5oá d M c»'S 9 S S» ß A « 3 « t/ u u *0 T3 § a .o c3 «o Wi M Ö $

ö •» _• sg 3 G 1 o 5b

pE Ka e •s .S- u > a y o s u «Il ri et £

64

o» 2 Í o tí"""o tí u —os c S Î C i/i•2, 3 i s 5 f l -g » J t 5 u •o -n s t- a «- -S CS ja g tt i £400,000 BC 1802 (1843) around 1900 1887 (1905 Einstein)

Combustion processes Temperature radiation Gas discharge processes Radiation transformation in solid states

* In principle, the theoretical perception may also precede the discovery of the effect.

In view of our present situation it is also conceivable that plasma physics can be applied for light technology purposes. Furthermore, the phenomena of tribo-, chemi- and bio-luminescence have been known for a long time. But only the first three fundamental principles of action have so far been technologically exploited. Thus, only part of the total vector of light energy in the matrix of possible energy transformation processes has yet been used. A decisive factor for the classification of innovation processes is the intensity 66

of the innovation, i.e. its scientific and technological level. Here, the main point is the degree of change of the technological principle applied. A technological principle is a functional relationship which results from the application of physical action principles to a certain technological need; and one principle of action may be used for a great variety of technological principles. Thus, the action principle of underpressur, e.g., explains the technological principle of the windmill, of the hydraulic screw, of sailing, etc. The action principle of temperature radiation is applied in lighting technology, heat technology, and many other fields. Thus, a technological principle solution is understood to be the practical application of the technological principle. The light bulb is a principle solution, which is based on the technological principle of resistance heating of a wire. Within this principle solution various technological generations can be distinguished: carbon filament lamp, metallic filament lamp, gas-filled coiled-up filament lamp, halogen bulb. Table 27 suggests a classification according the degree of change of a technological principle. In this classification, a transition towards the utilization of another fundamental principle of action rates highest. In this sense the light bulb and the gas discharge lamp are equivalent innovations. It shall, however, be noted that this is a very rough classification which does not take account of the various degrees of penetration into new functional technological relationships of such innovations. An assessment of future prospects would therefore require a more detailed representation. Figure 16 gives the possible action elements of light emission and their characteristic properties as well as the types of radiation energy in relation to known, conceivable or blank technological principle solutions. The evolutionary development in this sector of light sources comprises a wide range within the field of temperature radiation and gas discharge principles. The bulb serves as a good example to illustrate this phenomenon in its historical diversity. The corresponding historical data are given in Figure 15 and in the Appendix. The light output of the bulb has grown since 1880 in the form of a logistic time function, which started at about 3 lm/W, then reached its turning point in 1913 at 8 lm/W (the highest increase), and did not exceed the 12 to 13 lm/W limit over the 1925—1960 period. All partial improvements within the course of this S-shaped curve are to be characterized as evolutionary or partial changes. They were mostly related to the availability and utilization of new, suitable, and fairly inexpensive materials (krypton lamp, 1938). In 1959, however, a new technological solution was found: the halogen lamp. It presented a breakthrough to a light output two or three times higher than that of the conventional bulb. It is based on two earlier patents of 1882 (Scribner, USA) and 1933 (van Liempt, Netherlands). By means of this technological principle a maximum of 58 lm/W can be obtained. For the bulb in general, 5*

67

Table 27 Classification of innovations according to their scientific-technological level Main Categories

Partial Changes

B. Basic Changes

Categories General

technological

material

1. Quantitative change of the elements of the inner system structure and their proportions

Quantitative development of the existing technological basis

Quantitative changes of material application

2. Restructuring of the elements of the inner system structure, supplementation and adaptation

Further development within known principle solution without major changes

Further improvement of known material properties without major changes

3. Qualitative changes of individual inner characteristics or functions

Further development within known principle solution, however with major changes of one factor (matter, technology, function, construction)

Major change of one specific property of a known material, substitution by other known materials

4. Qualitative change of all inner characteristics, however without change of the fundamental functional concept

Further development within known principle solution, however with major changes of several factors

Major changes of several properties of a known material, new processes for known materials

5. Qualitative change with change of basic concept, however without change of the principle of the concept

New principle solutions, 1st order, i.e. within the scientific action principle applied

Extraction of new materials from nature, empirical discovery and production of new elements and materials

6. Qualitative change with change of the basic functional principle in the same field of perception

New principle solutions, 2nd order, i.e. replacement of the basic principle so far applied by a new one, however within the same motion pattern and the same structural level of the matter

Development of new materials on the basis of molecular processes, major increase of the degree of material utilization

New principle solution, 3rd order, i.e. transition to a different structural level or a different motion pattern of the matter

Development of new materials on the basis of elementary processes in the atom range. Fundamental increase of the degree of material utilization

7. Qualitative change of the basic functional principle by transition to a new field of perception

68

69

95 lm/W are assumed to be theoretically feasible. (Theoretical limit of the Planck radiator at 6000 °K.) The halogen lamp presents a step ahead in bulb development. Thus it is regarded to be a principle solution of the first order, i.e., within the action principle of temperature radiation, as has so far been known and applied. Similarly, fluorescent lamps are only a new principle solution of gas discharge lamps, which were later produced in the form of high pressure lamps, at first exceeding the former in light output, and consequently lagging behind. Of course, there is a chance of new technological principles to be discovered in the field of the gas discharge system. In such a case the corresponding innovation would have to be classified as a principle solution of the second order. In view of the historical development of light technology the carbon arc lamp can be specified as a principle solution of the second order.

4.3. Measurement and Evaluation of Technological and Economic Level of Innovations in the Lighting Industry It can be assumed that the scientific-technological level will develop exponentially beyond the seven stages described above. The relative increase in light output in the seven stages is (in percent): 1. 1 - 10 2. 1 0 - 30 3. 3 0 - 80 4. 6 0 - 1 0 0

5. 200-300 6.

-

7. 1000-2000

From 1890—1975 the light output developed according to the function of time 265 M

=

lm/W.

Thus, in the year t = 2000 a light source of an output of 196 lm/W will be available (see Figure 17). It must, however, be taken into consideration that the useful life is another essential parameter in the scientific-technological level of light sources. While a higher light output saves energy, a longer useful life may contribute to a reduction of manpower, material requirements, financial means, and raw material resources. The scientific-technological level presents, however, only one side of the innovation process. Its economic counterpart is the actual extent of application or the effect on meeting demands (see Table 28). From an historical point of view the bulb has created a new demand structure and has contributed to qualitative changes in the national economies. 70

Figure 17

Development of efficacy of light sources II (265 lm/W = 100 percent)

The gas discharge lamp, on the other hand, has led to a major modification of the existing demand structure. Both sides, the scientific-technological level and the level of application, together characterize the importance of an innovation. Accordingly, Table 26 distinguishes 7 x 7 = 49 kinds of innovation processes. Their importance shall be defined as

ik — scientific-technological level of the k"1 degree, vk — range of application of the kA degree. For an exponential assessment V = eak • y _

eik,

e(a+b)k

If we assume symmetry of both factors (a = b) for reasons of simplification, then V=e2ak,

k = 0,1,... , 6 .

71

Table 28 Classification of innovations according to their range of application or their effect on meeting needs Main Categories

Categories

A. Partial changes

B. Basic changes

General

Meeting Demand

1. Simple qualitative extension of existing elements or processes

Quantitative extension of existing demand

2. Quantitative extension of existing elements or processes

Modification of existing types of demand Quality improvements of existing products

3. Changed proportions and new characteristics of known elements or processes

Major modification of existing types of demand (new characteristics of known utilization values)

4. Development of individual new processes and process results in existing economic sectors

Development of a new type of demand (of a new utilization value) in the existing demand structure

5. Qualitative changes of economic sectors (development of new industrial sectors and subsectors)

Major modification of the structure by the new utilization value

6. Qualitative changes of the total economy. Development of new groups of industrial sectors

Development of a new need structure. Major changes of proportions

7. Qualitative changes of the total social and natural environment

Reorganization of the existing system

Since V is defined as 1 ^ V ^ 100 (percent), we find via 100 = a

=

e12a, l n

| ° = 0.38376,

which is the basis for calculating the evaluation coefficient V in Table 26. Importance is a general historical and not an operational characteristic. For a comprehensive evaluation of light-technological solutions the following factors have to be considered (see Table 29). — — — — 72

the age of a technological solution, the average annual development of the scientific-technological level, the average annual decrease of expenditure per unit of performance, the scientific-technological level achieved,

o S u Où e '3 je

í?

S I B

'SS

£ £ u u a I S

» I , S§ C M g •g w 2L c V « e o, V «

.g I

S

| g < e o •a j3 Ô

e •c a

'9 "o e J3

w

•S 3*8

r - oo f î ri

v? ®x

ó 2 c. . i

p « U S S -5 o. e § y

n

-V Cl. Q. — S E g ri 3 -2 J r i s û t ? " ftÇasI * .a1 a 2 gS Ss 2ï X

i

X M

— (N r i t— so O so f i

f i r - t-r~- f i •—i Os ^ (N o"

as r - — r os r j .os so os oo -h os os m so Os f i

oo — TT ÇN f i Tf

f i P- »O t* Os « í Os v> f »

i

& O.

— Tf r - r f i m Tt — O ^ Os ^ — f i


_

l e

» S f g Ü sí « S ts í " t a 4 I «r-v í l - o í § jfw U B C ..HB . -O 3 ï ss . a & g 2 .8 » E o " 2 •

r i « oò

S « 3 ! » g « TS JB ^ T! « Í . Í — S3 ^ S u a 4> s > f J: u •3 o M 3 S S 'S "2 ei 'S S S.

(N r— r ON r ON f i (S p- *rt

so Z ^ H i w « Û. MMCU 5^ OU OU CW L ! j s u e o u o o j x S

g Ó Í •S ^ o o S i u 3 T3 g ^ c S •» 8 -2 &73 « « - a m e o fí a U c6 .5

.s s a i > "s OO - c 2 * I «-s ^ •s o ï o 3ni u 5 =

improvement-oriented innovations is significantly high and positive. On the other hand, medium-sized improvement-oriented and incremental innovations are closely linked with the release of the work force. But there is also a short-term reaction involving a dwindling of orders and a general slowdown of economic activities with incremental and pseudoinnovation, and they are unable to create new working places or protect existing ones. Table 36 demonstrates that 79 percent of the new working places created in the four industrial branches at the time of the investigation were connected with the implementation and diffusion of basic innovations and major improvementoriented innovations. But only 19.3 percent of the new working places are connected with medium improvement and incremental innovation and 0.7 percent of the new working places are the results of small incremental and pseudo innovation. On the other side, the elimination of working places was only 18.4 percent due to basic innovations and major improvement innovations, but 65.4 percent of the eliminated working places were due to medium improvement innovations and incremental innovations and 16.2 percent the result of small incremental and pseudoinnovations. According to Table 36 in the four industries of the Federal Republic of Germany which were investigated 3.1 times more working places were created due to the technological change than old places eliminated. However, the employment effect of the different types of innovation was rather differentiated. This is

-

19.61.

'

-

SI. '

7X

\

\ \

1 .29,67*

—

\ \

1

as

Labour productivity effect (Percent of the totol increase ofproductivity)

\

i

Employment effect (Factor, relation batmen newly created and diminuatedworkplaces!

t,f%

i.lx

V-— T

2,2%

-a 1

Cx

Basic & Major improvement innovation

Q

c

-3,1

te

si

ssp

Wc

Improvement and incremental innovation

R SO Incremental and pseudoinnovation

Figure 32 Employment effect and labour productivity effect of different kinds of innovation (Results of an investigation of 2260 technological changes within 909 firms in 4 industrial branches of the FRG, 1970—1973.)

7*

99

displayed in Figure 32. With the employment effect we are labelling the capability of innovation to create new working places in comparison with their capability to eliminate working places. It is obvious that the highest employment effect is with basic innovation and major improvement innovation. For example, capacity extension created 31.7 times more working places than it eliminated, in the case of the implementation of new products 12.6 times more and in the case of product quality 5.9 times more. Interesting and in many respects important is the improvement and incremental innovation connected with the improvement of working and production conditions which also have a significant positive employment effect. In the case of improvement of working conditions the employment effect is 4.4 and to overcome the shortage of space 3.9. The highest release effect of labour is with improvement and incremental innovation which are directed toward the improvement of efficiency (employment effect —3.1), to overcome shortage of labour (employment effect —1.6) and cost reduction (employment effect —1.4). However, maybe some of the most interesting results of this empirical study is that the highest release effect of workers (—3.3) occurs through short term reactions on shortage of orders and slowdown of business activities. But it is interesting that the types of technological change which are connected with basic innovation and major improvement innovation have not only a high employment effect but also contribute significantly to labour productivity growth caused by technical change. Data in Table 36 and Figure 32 demonstrate that basic and major improvement innovation contributed 38.8 percent to this entire growth of labour productivity based on technological change. In all four industrial branches the annual labour productivity growth due to technological change was 3.7 percent. It is especially interesting that the extension of capacity was the overwhelming contributing factor with 29.6 percent, that is an activity in the second and third phase (rapid growth and maturation stage) of the innovation cycle. However, activities in the first (take-off-stage) and in the beginning of the second phase (rapid growth phase) were much less able to contribute to labour productivity growth. The implementation of new products, an activity in the take-off-stage of the innovation cycle, contributed only 2.4 percent and activities in the second stage of the innovation cycle to improve the quality of the product could only contribute 6.8 percent to labour productivity growth. Maybe one of the most important results of our investigation is that the highest contribution to the productivity growth is through technological change which is connected with improvement and incremental innovation — these are the activities in the maturation and saturation phase of the innovation cycle. Their contribution to labour productivity growth based on technical change was 59.8 percent. But it is very important to note that the overwhelming part (83 percent) of this contribution is the result of improvement and incremental innovation directed towards cost reduction. Short term activities to improve efficiency or to overcome labour shortage were not so successful. 100

Technological change directed to immediate improvement of efficiency contributed only 0.9 percent and to overcome labour shortage 1.2 percent to labour productivity growth based on technological change. The same situation can be noticed in the short term reactions on shortage of orders and slowdown of business activities due to incremental and pseudoinnovation. They could only contribute 1.4 percent to the development of productivity growth caused through technological change. Figure 32 demonstrates that basic and major improvement innovation have the highest employment effect and a high contribution to productivity growth too. But the more innovation becomes medium and incremental the more we have the situation where the low employment effect and the low contribution to labour productivity growth go together. That proves our hypothesis that the low employment effect is not so much the result of the development of labour productivity which is what some of the economic text books claim, but rather the result of the dominance of medium improvement and incremental innovation in business activities. Or the other way around: it is the result of absorption of efficiency and employment potential which was created through basic innovation. This is an important confirmation of our innovation model. For national innovation policy and cooperations strategy we can draw from our model and from the empirical results displayed in Table 36 two important conclusions : To secure the better use of human resources we need efforts to coordinate the innovation cycle. If the main industries are approaching the saturation stage then there will necessarily be a gap between the release of working places and the reemployment capability of industry. It is without doubt that this is one reason for the employment problem in some market countries. However, the coordination of the innovation cycle calls for planning and coordination of the innovation process. In this way innovation policy is becoming more and more unified with structural innovation and employment policy. The situation in countries with different social systems is certainly rather different. For example, the European socialist countries are currently faced with the problem of providing a high rate of release of manpower through improvement and rationalization innovation as a pre-condition of innovation in the field of energy, microelectronics and the machine-tool industry. Thè other lesson we can learn is that it is pointless to maintain a high share of skilled experts and experienced workers when production is shifting from the maturation to saturation stage. It is much better to use these skilled workers for the preparation of new innovations, otherwise society will waste the most important resource : the creativeness of man. But this requires high flexibility in the organizational pattern and high mobility within the labour force. This stresses the importance of establishing initiatives from the move of special kinds of skilled workers from one stage of the innovation cycle to the other and to create organizational patterns which allow the application of workers capabilities according to the requirements of the different phases of the innovation process. 101

7. Improvement in the Quality of Human Resources and Their Use Most of the developed countries have had a significant improvement in the quality of human resources in the last two decades. On one side the higher quality of human resources is an important pre-condition for technological and social innovation, and on the other it is not possible to approach a higher quality in human resources without social and technological innovations. The creation of social conditions in which the quality of human resources can grow and become a decisive social and economic force is a crucial point for the further social progress of mankind.

7.1. The Case of the German Democratic Republic In the GDR for example, the number of working people has risen consistently in spite of the fact that the total population has decreased (see Figure 33). This was mainly caused by two factors: a) The development of possibilities enabling women to work, both in full and part-time employment. The level of female employment has steadily increased and is now approaching 87 percent, it's natural constraint.

Thousand persons

18000 -

17000 '

Population

16000 \

10000 -

Population of »airing age 9000 -

8000 -

7000 -b 0

fmployees

1

I960 62

102

1—i

Si

66

i

68

i

'

70 72

. . .

74 76

78 Year

Figure 33 Development of the population, the population of working age, and employees in the G D R

b) The increase in life expectancy meant that the country was faced with the necessity of creating working places for older people who might wish to continue working after approaching retiring age. In the GDR 18.1 percent of pensioners use this possibility, 25 percent of them are male and 15 percent female. Through this the number of employed people increased by more than half a million. With the increasing degree of employment it was possible to extend the free time, of all employees, especially through such social measures as: a) Reducing the working time for all employees, especially for shift workers and mothers with more than two children. b) Implementation of the five day working week. c) Extension of vacation time. d) Extension of maternity leave. e) Extending mother-care for women with more than one child. The free time which was obtained by these measures is equivalent to the working value of one million people as under the working hours in 1960. This is equivalent to 35 working days per employee, per year, in comparison with 1960. The reduction of working hours to this extent was possible only through the fact that the increase in employees was connected with the increase in labour productivity. More than 90 percent of the production growth in the period from 1962 to 1978 was caused by the increase in labour productivity, which was in turn connected with better use of capital and material resources. The basis for this was the increase in the scientific-technological level of production. One important factor in the scientific-technological basis of the production was the rise in the quality of labour resources.

59,6%

( | f | ) Unieersily graduates

(JJJJJJ) Figure 34

2000

mo

1955

Technical school graduates

/s,sr.

o

Skilled mrkert ) Unskilled and ami skilled workers

Qualification structure in the socialist economy of the G D R (in percent)

103

In the economy of the GDR the quota of graduates of technical schools and universities increased from 6.8 percent of employees in 1955 to 18.8 percent in 1980. During the same period the quota of skilled workers and foremen rose from 33.6 percent to 61.4 percent and the quota of semi-skilled and unskilled workers declined from 59.6 percent to 19.2 percent. More than 90 percent of pupils who passed through the 8th form continued their schooling in the 9th and 10th forms and claimed their constitutional right to receive vocational training. It can be foreseen that up to the end of this century the quota of graduates of technical schools and universities will increase to about 20—25 percent, the quota of skilled workers to "about 65 percent. The quota of semi-skilled and unskilled workers will decrease to about 10—15 percent (KORN and MAIER 1977) (see Figure 34). Therefore today's educational outlays are by no means of slight importance when it comes to the distribution of national income, as was actually the case even in the developed industrial countries at the beginning of this century. At that time, they amounted to only 1 to 2 percent of national income, but today in countries like the GDR, more than 5 percent of national income is devoted to education (see Table 37). The increasing importance of qualified labour in the production process can be seen in the rising volume of educational funds (human capital) in the G D R economy. The educational funds (human capital) are the expenses of society for Table 37 Development of public expenditures on education as a percent of gross national income (market economies) or national income (planned economies) Country

1955

1960

1965

1970

1975

2.82

4.5' 5.3 5.1 3.8 7.3 5.4

4.9 4.4 5.3 3.6 6.8 4.5

5.35 4.5s 5.8 4.0 7.2 5.6s

3.7 4.2 3.4 5.2 5.1 4.3 5.3 6.2

4.6 4.7 4.0 4.3 5.0 3.9 6.4 7.7

5.7 5.6 4.5s 5.0 6.2s • 5.5 6.2 7.4

Planned economies 1. Bulgaria 2. Czechoslovakia 3. GDR 1 4. Poland 5. USSR 6. Hungary

4.7 3.73 5.8 5.02

5.0* 4.2 5.1 4.6 5.9 4.4

Market economies 1. Austria 2. France 3. FRG 4. Italy 5. UK 6. Japan 7. USA 8. Sweden

4.0 2.0 3.5 2.5 3.2 6.1 4.0 2.6

3.7 3.4 3.7 3.9 4.2 6.5 6.2 4.5

—

1 = Without investment. 2 = 1954. 3 = 1954 estimate. 4 = 1961. 5 = 1972. Sources: Unesco Statistical Year Book(1963—1977), Paris; Statistisches Jahrbuch der DDR, 1956, 1961,1966, 1971, 1976; Rocznik Statystyczny Poland, Narodnoji chozjaistvo SSSR. 104

education and qualifications, materialized in the qualification level of the employees. The educational funds in the GDR increased from 66.5 billion marks in 1962 to an amount of 250.8 billion marks in 1975. That is about one quarter of the founds of fixed assets (material capital) of today's GDR economy. Figure 35 displays the fast growth of educational funds during the period 1962—1975 in comparison with material funds. Billion Marks 576.8

150.9

I I • I I I I j I I I I I ' I 1962 63 Si 65 66 67 SS 69 70 71 72 73 7i 75 Year

Figure 35 Development of educational funds (human capital) and funds of fixed assets (material capital) in the G D R (in billions of German marks)

In the period between 1962 and 1975 the growth rate of educational funds (human capital) was essentially higher than that of the funds of fixed assets (material capital). During this time the educational funds increased to an amount of 227 percent, compared with an increase of 165 percent of the funds of fixed assets. The research funds in the material sphere — the research expenses materialized in the scientific level of production — increased to an amount of333.5 percent. Occupational educational funds, production funds, and research funds are 1975

Production

funds

73%

Research Education funds „ „ 21%

Figure 36 Composition of the technological funds of the G D R economy (in percent)

105

the technological funds of a society, which gain more and more importance for the scientific-technical revolution. In 1972 the technological funds of the GDR consisted of 73 percent production funds, 21 percent educational funds, and 6 percent research funds (see Figure 36) (HAUSTEIN 1976).

7.2. The Relationship between the Development of Technological Funds and Labour Productivity In most of the developed countries technological funds are becoming more and more important for the development of labour productivity. Currently each percentage of the labour productivity growth is connected with the extension of technology funds. This is because until now the development of technological funds has been in the extensive phase, that means that each additional improvement of the labour productivity needs an extension of investment, occupational educational and research funds. There exists no indication of a change in this trend, especially if we think of investment requirements in energy, environment, etc., skill and research requirements for the new fields of innovation which arise from the current research situation and technological possibilities. Such new innovation fields like — the electronic complex and especially applied microelectronics to create a new step in automation, — the energy and environment complex, — biochemistry and food production complex, — technologies which are able to provide new organizational solutions to solve communications, traffic settlements, health and recreation problems, — the creation of technologies appropriate for the requirements of developing countries, especially the technological system which includes advanced, medium and traditional technologies, are connected with the extension of technological funds in society. That means that the extension of technological funds will also be in the future an important pre-condition for the improvement of labour productivity. A break of the links between labour productivity growth and the extension of technological funds could only be the result of the improvement of the efficiency of the technological funds itself. Maybe this will be one of the most important problems for the developed countries in the next 10—20 years in their battle for a higher economic performance. Higher efficiency of technological funds could only be the result of high innovativeness of the machine-tool industry, the educational system, and the efficiency of R & D activities. Especially important in this connection is the improvement of efficiency of the service sector. To explore the links between labour productivity and the development of technological funds we are using data from the GDR. Table 38 shows us the 106

Table 38 Labour productivity and efficiency of the technological funds between 1960 and 1975 in the GDR NI

NI II

Year

NI i* = rB T

Aqr

%

NI i* = rR T

(in Mark)

%

%

1960 1961 1962 1963 1964 1965 '

11015 11213 11572 12081 12638 13221

1.8 3.24.4 4.6 4.6

0.4418 0.4241 0.4099 0.3990 0.3944 0.3898

-4.0 -3.3 -2.7 -1.1 -1.2

8.291 7.982 7.687 7.646 7.611 7.504

-3.7 -3.7 -0.5 -0.5 -2.4

11.356 9.689 8.580 7.804 7.173 7.307

-15.7 -11.4 - 9.0 - 8.1 1.9

1966 1967 1968 1969 1970

13896 14589 15376 16157 17067

5.1 5.0 5.4 5.1 5,6

0.3879 0.3921 0.3932 0.3969 0.3967

-0.5 + 1.1 + 0.3 +0.9 -0.1

7.435 7.241 7.110 7.031 6.908

-0.9 -2.6 -1.8 -1.1 -1.7

6.686 6.292 5.865 5.427 4.209

- 8.5 - 5.9 - 6.8 - 7.5 -22.4

1971 1972 1973 1974 1975

17863 18892 19939 21133 22128

4.7 5.8 5.5 6.0 4.7

0.3912 0.3919 0.3909 0.3927 0.3882

-2.4 0.2 -0.3 0.5 -1.1

6.816 7.008 6.946 6.967 6.981

-1.3 2.8 -0.9 0.3 0.2

4.488 4.156 3.916 3.730 3.533

+ -

6.6 7.4 5.8 4.7 5.3

Source: Juergen Wahse/Reinhard Schaefer, Zentralinstitut für Wirtschaftswissenschaften, Berlin, Akademie der Wissenschaften der DDR, (Studie).

development of labour productivity, production funds efficiency, occupational educational funds efficiency, and research funds efficiency. Labour productivity is the coefficient of national income per employee (PL — NI/E), production funds efficiency is National Income per unit of production funds {qp = NI/Fp), occupational educational funds efficiency is National Income per unit of occupational educational funds (qE = NI/FE), research funds efficiency is National Income per unit of research funds (qR = NI/FR). We are trying to connect the development of labour productivity with the development of the efficiency of technological funds. For this we use the following equations : in _ NI/E0 I0

/NI0/E0\ a

NIJEn

/NI0/FE0\

fNI0/FR0\

P

\ N l J F j

7

\N1JFeJ

\ N I J F J '

where subscripts 0 and n denote the base year and another year, or AI = A(NI/E) = APl

± A(NI/Fq)

±*Aqp

± PA{NI/FE)

±

yA(NI/FR),

± pAqE ± yA qR{I) ,

where a, P, y are weighting coefficients « = FpJNIn

,

P = FJNI

n

,

y = FRJNIn

.

107

The more funds per unit national income needed, the more significant is the change in funds efficiency for the development of labour productivity (see Table 39). A change in the fund quotes qp, qE, qR by 1 percent resulted, over the period from 1960 to 1975, through the different weights of the funds, that means through the correction coefficients a, /?, y, for different impacts on the developTable 39 Development of labour productivity and efficiency of technology funds from 1960 to 1975 in the GDR

National Income NI Working People E Production Funds FP Occupational educational Funds FE Research Funds F s Technological Funds (FR + FE + FR) ANI

AE

A F„

MF, + FE + FR)

1960

1965

1970

1975

71540 6495 161932 8629 6300

84760 6411 217466 11445 11600

109470 6414 275985 16047 22300

142370 6434 366704 20588 40300

Mio. M. '000 Persons Mio. M. Mio. M. Mio. M.

176861

240511

31433

427538

Mio. M.

+29.15

+ 99.01 + 30.05

%

% %

(a) (b)

+ 18.48

(a) (b)

-

1.29

+ 0.05

+

(a) (b)

+34.29

+ 26.91

+126.46 + 32.87

% %

(a) (b)

+ 32.63

+40.21

+ 138.59 + 28.30

% %

(a) (b)

+84.13

+92.24

+ 539.68 + 80.72

V /o

(a) (b)

+ 35.99

+ 30.69

+ 141.74 +36.01

V /o V /o

'

0.94 0.31

%

%

A = FP/NI ß = FEINI y = FR/NI

2.264 0.121 0.088

2.566 0.135 0.137

2.521 0.145 0.204

2.576 0.145 0.283

PL = NI/E

11015 0.4418 8.291 11.356

13221 0.3898 7.504 7.307

17067 0.3967 6.908 4.909

22128 0.3882 6.981 3.533

M

+20.03

+ 29.09

%

-11.77

+ 1.77

-10.67

-

+100.89 + 29.65 - 12.13 2.14 - 16.00 + 1.01 - 68.89 - 28.03

Ir = NHFp

qE = NI/FE QR =

WL AQR

A?,

NI/FK

(a) (b) (a) (b) (a) (b) (a) (b)

-35.66

(a) Basis — 1960. (b) Basis — previous five year period.

108

7.90

-32.82

% %

% % %

% %

ment of labour productivity. The improvement of the capital efficiency (Aqp) by 1 percent would wave improved the labour productivity by 2.6 percent, the improvement of the efficiency of educational funds (A^£) by 1 percent would have improved the labour productivity by 0.7 percent. The improvement of the research funds (AqR) by 1 percent would have resulted in an increase of labour productivity of 0.3 percent. By comparing the labour productivity -development (APj) with the development of the efficiency of technological funds (Aqv, AqE, AqR) it is possible to identify the part of the labour productivity growth which is necessary for the extension of the technological funds and which is available for the fulfillment of individual and social requirements. Before we present some results of our investigation, it may be helpful to explain in more detail the definition of the funds we have used in our calculation. Production funds in our formula is the capital in the production field (production equipment, buildings, etc.) but without floating funds. Occupational educational funds include expenditure for occupational and professional training but not expenditure on general education. Occupational funds are only a part of the entire educational funds. For example in 1975 the entire educational funds in the GDR was 110,556 million M in the production sphere of the GDR, but the occupational funds only accounted for 20,588 million M. To avoid double counting we include in our estimation only the change in qualification structure but not the extension of the labour force, because of the fact that the quantitative extension of the labour force was taken into account in the labour productivity coefficient. Research funds is the expenditure for research embodied in research results. They include research expenditures for successful as well as unsuccessful research activities. In the concrete case of the GDR, they include approximately 70 percent of expenditures for applied industrial research and 30 percent of expenditures for fundamental scientific research. Using the key data in Table 39 from our investigation of the relationship between labour productivity and technological funds for the period 1960—75, we have the following results according to equation (/): 60/65 A/ = = = 65/70 AI = = = 70/75 A/ = = = 60/75 A/ = = =

+20.03 - 2.566 • 11.77 - 0.135 • 10.67 - 0.137 • 35.66 20.03 - 30.20 - 1.44 - 4.89 -16.50 +29.09 + 2.521 • 1.77 — 0.145 • 7.90 — 0.204 • 32.82 29.09 + 4.46 - 1.15 - 6.70 +25.70 +29.65 - 2.576 • 2.14 + 0.143 • 1.01 - 0.283 • 28.03 29.65 - 5.51 + 0 . 1 4 - 7.93 + 16.35 +100.89 - 2.576 • 12.13 - 0.145 • 16.00 - 0.283 • 68.89 100.89 - 31.25 - 2.41 - 19.50 +47.83 109

We have calculated that during 1960—1975 the labour productivity increase was 100.89 percent (see Figures 37/38). To extend technological funds, 52.6 percent of the increase in labour productivity were absorbed and 47.4 percent of the increase in labour productivity was available for improvements of labour payments, t7A V. For the improvement of labour payment, housing, health core, cultural and government activities

\ \ J J

100,0 %

Increase of labour productivity 19S0-197S by 100,9% in SOU

52.SV. For the extensive N. technological funds: \ production funds (31,0%) 1 occupation and education funds J (i3v.) y and research funds Î/9.3X),—

Figure 37 Development of labour productivity and their distribution for wages, cultural and government activities and the extension of technology in the period 1960—1975

311. Bxponsion of production funds Expansion of persona! income, residential accommdation, cultural and social expenditures other \oovernment activities 47, t %

110

Occupational educational funds 2.3%

Expansion of research funds 19,3 '/.

Figure 38 Distribution of 1 percent labour productivity growth for the development of technological funds and the living conditions of men (1960—1975) in GDR

social and cultural expenditure and government activities. 31.0 percent was used for the extension of production funds and this absorbed the largest amount of the increase of labour productivity devoted to the extension of technological funds. 19.3 percent was used for the extension of research funds and this was second largest in absorbing the economic benefits of the labour productivity improvement. The extension of occupational funds absorbed 2.3 percent of increased labour productivity. 47.4 percent of the labour productivity increase was available for higher wages, health care services, improvement of residential accomodation, culture and social expenditure and expenditure for other governmental activities. The essence of our findings is as follows: for the period 1960 to 1975 in the GDR, for a 1 Mark increase in labour productivity, 0.53 Marks were used for the extension of technological funds and 0.47 Marks for the extension of individual and societal consumption. In the period 1960/65 the extension of technological funds is much higher than the economic potential available for individual and societal consumption, which was created through the increase of labour productivity. Expenditure necessary to extend technological funds has to be mobilized through reallocation resources. This investment in technological funds allowed in the period 1965—1970 a much higher increase of labour productivity than the increase of expenditure for the extension of technological funds. In this period the share of economic potential, created through higher labour productivity, available for individual and societal expenditure was 88 percent. In the period 1970—1975 it was again necessary to expend a greater part of the productivity Percent Share of persons with indentions and proposals in all employees

40

Accepted ¡mentions and proposals per too employees

0

Mlr-

1.2

1.3

1J

1,5

1,S Qualification coefficient

Figure 39 Variation of innovative activity with qualification coefficient for the GDR national economy in 1975 (The qualification coefficient is the ratio of highly skilled work to unskilled work. The reproduction costs associated with labour forces at different levels of qualification, were used as weights for work at different levels. MAIER et al. (1975) describe the method of estimation the qualification coefficient.)

Ill

gains for the extension of technology funds. The share of additional economic potential available for individual and societal consumption was less than in previous times. The GDR and other developed countries are now faced with the problem of increasing the efficiency of technological funds. This will be the extent of the share of productivity growth available for an increase in the material and cultural living conditions of man. The high efficiency of social expenditure for education and qualifications can also be seen in the close connection between the increased qualification level and a growing contribution of the innovator's movement to the efficiency of the national economy. The benefit of the innovator's movement (more than 50 percent of prime cost reduction in the national-owned economy of the G D R result from it) 1975

SS,8%

Transport, post and telegraphs

Other proXT ] -N y 'dicing and TiTi: [ I ' 1111 ^non-producing i 11111 111111 'branches Ç ) Agriculture

Distribution of university graduates to branches of socialist economy of the GDR (in percent) 1975 Ì2.9V.

35.0% Figure 40 D i s t r i b u t i o n o f technical s c h o o l graduates t o b r a n c h e s o f socialist e c o n o m y o f the G D R (in percent)

112

per unit of educational funds was 2.5 times higher in 1971—1975 than during the period 1960—1965. Figure 39 shows us the connection between adoption of innovation and the level of qualification. In 1976 alone 1.6 million employees participated in the innovator's movement with a benefit of 3.6 billion marks. The majority of these activities were concerned with improvement-oriented and rationalization innovations. The increasing importance of qualified labour in the production process is an essential productive and social power. This power must be utilized in a better way than at present for both the development of production and for the further formation of the quality of life. Thereby the demands of production and way of life become more and more interfaced. This means realizing a structural policy that utilizes the high level of working people's qualifications in order to decrease the raw material and energy intensity of production by a higher rate of intelligence intensity. An important problem thereby is the employment of working people according to their qualifications and the use of these qualifications to implement and control technical innovations. Only by an effective use of qualified labour can the productive potency created by educating and qualifying people be transformed into real and productive development forces. Therefore the employment of qualified people in the national income producing spheres — that means in the material production — has great importance. But this industry could nearly double its share in the total of university graduates in the period 1962 to 1975. In 1962 every tenth university graduate of the G D R economy worked in industry, today it is every fifth. Building industry, transport, and the post and telegraphs could even more than double their share in the total of university graduates. A similar development can be seen in the field of employment of technical school graduates (see Figure 40).

8. Automation, Innovation, and Skill Requirements 8.1. Technological Change and Skill Requirements There is a disagreement about how structural and technological change will affect the skill requirements. Theories about "deskillization", higher skills, and polarization are being discussed at the same time (see Figure 41). Our investigation about the impact of structural and technological change came to the conclusion that neither Blauner's theory — according to which mechanized production requires low skills and automated production high skills — nor Bright's theory — according to which mechanized production requires high skills and automated production low skills — are appropriate. 8

Haustein/Maier

113

per unit of educational funds was 2.5 times higher in 1971—1975 than during the period 1960—1965. Figure 39 shows us the connection between adoption of innovation and the level of qualification. In 1976 alone 1.6 million employees participated in the innovator's movement with a benefit of 3.6 billion marks. The majority of these activities were concerned with improvement-oriented and rationalization innovations. The increasing importance of qualified labour in the production process is an essential productive and social power. This power must be utilized in a better way than at present for both the development of production and for the further formation of the quality of life. Thereby the demands of production and way of life become more and more interfaced. This means realizing a structural policy that utilizes the high level of working people's qualifications in order to decrease the raw material and energy intensity of production by a higher rate of intelligence intensity. An important problem thereby is the employment of working people according to their qualifications and the use of these qualifications to implement and control technical innovations. Only by an effective use of qualified labour can the productive potency created by educating and qualifying people be transformed into real and productive development forces. Therefore the employment of qualified people in the national income producing spheres — that means in the material production — has great importance. But this industry could nearly double its share in the total of university graduates in the period 1962 to 1975. In 1962 every tenth university graduate of the G D R economy worked in industry, today it is every fifth. Building industry, transport, and the post and telegraphs could even more than double their share in the total of university graduates. A similar development can be seen in the field of employment of technical school graduates (see Figure 40).

8. Automation, Innovation, and Skill Requirements 8.1. Technological Change and Skill Requirements There is a disagreement about how structural and technological change will affect the skill requirements. Theories about "deskillization", higher skills, and polarization are being discussed at the same time (see Figure 41). Our investigation about the impact of structural and technological change came to the conclusion that neither Blauner's theory — according to which mechanized production requires low skills and automated production high skills — nor Bright's theory — according to which mechanized production requires high skills and automated production low skills — are appropriate. 8

Haustein/Maier

113

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. A.

Simple manual tools, hand and foot driven machinery and equipment. Energy driven machinery tools. Manual steered and regulated machinery. Manual steered and regulated machinery or equipment, mechanisms for subsidiary processes. Long distance controlled machines or equipment, manual and long distance steering or regulation, mechanisms for subsidiary processes. Through regulating mechanisms driven and controlled machinery and equipment, mechanized subsidiary processes. Machinery with flexible program steering, mechanized subsidiary processes. Machinery with flexible program steering, subsidiaries are steered manually by workers. Subsidiary process machines with flexible program steering. Machinery and subsidiary processes of great complexity with flexible program steering and the possibility of self optimization of the steering program. Stages of technological development, features of production tools. a) Blauner (USA), b) — O — O — O — Richta (tSSR), c) Kern/Schumann (FRG) d) | | | | 1 Sociological Analysis (GDR), e) Bright (USA)

Figure 41 Different opinions from the literature about the influence of mechanization/automation on the qualification structure S o u r c e : LANGEN e t al. ( 1 9 7 8 ) .

It must be assumed that technological and structural change sometimes have the tendency to lead to a polarization of job functions and job requirements with a growing dominance of higher skills and knowledge requirements. On the one hand, very simple and usually monotonous jobs were created on a lower level, while on the other hand, activities requiring higher skills remained the same or were newly created — by increasing their importance. At the same time the proportion of complex activities demanding a medium level of qualification declined. It can be seen that even if the requirements of manpower differ widely depending on the level of technical development the basic tendency is the rising importance of qualified labour in connection with the increasing degree of mechanization and automation. The levelling mechanization and automation process in general include the following main categories (see Figure 42). Studies on methods for determining the development of technological equipment show that there is not only the possibility of mere description but also of scaling, 114

Figure 42

levelling and in some cases of measuring it. By grading and splitting complicated development which normally are difficult to assess in their entirity, it is easier to identify certain innovations in technology, production, or economic units. However, instead of a single lined development we have in reality a branched and well distributed network of wellknown traditional equipment and innovations. The relationship between labour requirements and technological development is often investigated. The following general trends are usually analysed: — the decrease in unskilled workers and increase in skilled workers, — possible polarization of qualifications — the number of highly qualified people increases and unqualified people decreases. The net growth of qualified people is positive despite the fact that the number of jobs for unqualified people increases as a result of innovation (e.g. vacancies for perforators in data processing). Figure 43 shows, in principle, changes in qualifications. It explains how polarization may take place as a result of changes in the amount of unskilled and skilled personnel. It indicates the qualification patterns at distinct points in time — past, present and future. But we should not overlook the fact that the qualification structure of a society and the distribution of work with high and low skill requirements of different groups in human society, is not so much the result of the technological development but more of societal structure. The creation of equal possibilities for all members of society to develop their capabilities and realize them in socially and individually useful work is an important criterion for the progress of society. In Figure 44 we have collected data about requirements and existing skills in the GDR industries according to the different technological levels of industrial production. (This analysis includes more than 2.5 million workers of the GDR — i.e., more than 50 percent of the workers involved in production in the GDR.) The data show us that we have, especially in the partly mechanized workplaces (T2), fully mechanized workplaces (T3) and partly automated workplaces ( r 4 ) a higher share of skilled workers than in jobs with lower technical levels. At the same time there is a shortage of semi-skilled workers and a surplus of unskilled workers. This last problem requires the training of unskilled workers to become semi-skilled workers. In the GDR there exist well established procedures to deal \Vith this problem. A more serious problem is the existence of a problem which could at the first glance be termed "overqualification". Does this so-called "overs'

115

Intermediate stages

Traditional qualification pattern pyramidoid

Qualification ,butb'

Equal distribution

Slight polarization

Future stage

qualification" exist? From our point of view it is not possible to reduce the number of skill requirements only at a certain level, which is necessary from the technical point of view. We must also take into account that a high proportion of skilled workers could be the cause for an important movement in the reduction of unskilled workers and the development of new options for the better use of the skilled workers through new organizational arrangement and the development of an innovative movement of workers. The conclusion of this finding is not that we have to make the level of qualifications of the workers appropriate to the changing technological demands on the different technological levels. Such technocratic solutions are inappropriate for the nature of the socialist society. The problem is to use the higher quality 116

places (W Y/Z/Askilled writers

places (T3) |

places IW

places (T5)

| Semi-skilled mrkers 11111111 Unskilled mrkers

Figure 44 Existing and needed qualification structure of production workers in various stages of technological development in industry (in percent)

of human resources also in situations in which the technological demand for qualifications is relatively low. They must be employed for the creation of conditions to eliminate unskilled working places. The change in the technical demand for a qualified labour force indicates that society faces the never ending task of overcoming the contradiction between the existing structure of work places and the emergence of new work places. The solution of this contradiction in the interest of society and the individual worker is possible on the basis of a higher level of disposability and mobility of workers on all levels of qualification. Disposability of this kind can only be produced on the basis of a sound general education and the development of specialized capabilities, in order to arrive at a continuous appropriation of new knowledge, to assimilate it, to expand it, and to apply it in an effective manner. There are no limits to the development of these capabilities on the basis of a comprehensive general education, but to gain purely factual knowledge does in fact meet with objective limits. Views and corresponding practical endeavours which aim to reduce the school to a pure supply of factual knowledge that is not connected with the development of the capability to independent thinking, with the production of sound educational motives, then exactly these faculties remain underdeveloped, which are decisive for dealing with social and technological innovation. Innovative learning demands the development of the capability of independent and creative thinking and an optimistic attitude in participating in the solution of technical, social and cultural problems. 117

8.2. The Impact of Different Kinds of Innovation on Work Content and Skill Requirements Our innovation model pointed out that it is impossible to equate innovation with automation. Automation is a process that often occurs only in the maturation and saturation stages. That is why the skill requirements of the automation process are not typical for the entire innovation process. Up until now, there has been no attempt in the literature to find out how different kinds of innovation influence the work content and skill requirements. On the basis of empirical data about technological change in 900 firms of four industrial branches in the Federal Republik of Germany over the period 1970—1973, we discovered some interesting facts. Unfortunately, it was impossible with the given data to identify the relationship between the different kinds of innovation, the skill requirements and the work content in a clear cut way. For this the distinction between high innovative working places as shown in Tables 40 and 41 is too rough. The high innovative working places correspond with basic innovation as well as with improvement

Table 40 Impact of high innovative and low innovative technological changes on the work content* Work Content

Work by hand

Work with/ on machines (operating machines

Impact + higher — lower

+

+

~

Control of machines

Sum of

High innovative working places**

Low innovative working places**

places

%

absolute 1073 35.4

1872 63.6

2947 100

absolute 12620 70.8 /o

5218 29.3

17838 100

%

absolute 10695 79

2851 21

13546 100

absolute 2100 56 %

1628 44

3728 100

6619 38.9

17017 100

absolute 795 70.5 %

333 29.5

1128 100

absolute 2646 77.3 %

775 22.7

3421 100

absolute 159 76.4 %

49 23.6

208 100

/

absolute Ì 0 398 + 61.1 %

~

Adjusting machines -

118

Type of technological change

Requirement coefficient high1

low'

-11.8

-2.8

5.1

1.8

13.1

19.9

16.6

15.8

Work Content

Transportation by hand

Impact + higher — lower

+

absolute

Type of technological change

Sum of

High innovative working places**

places

Low innovative working places*"

760

1124

1884

./ /o

40.3

59.7

100

absolute

6979

3995

10974

63.6

36.4

100

Requirement coefficient high1

-9.2

Maintenance

~~

%

+

%

absolute

absolute ~

Checking

+

%

absolute

%

absolute ~

Planning of process

+

%

absolute

%

absolute ~

Office work (registration, tabulation)

+

%

absolute

%

absolute ~

Steering, Advisory

+

%

absolute

%

absolute ~

Total

+

%

absolute

%

537

626

1163

46.2

53.8

100

207

78

285

72.6

27.4

100

2374

1100

3474

68.3

31.7

100

906

431

1337

67.8

32.2

100

1728

862

2590

64.7

33.3

100

149

0

149

100

-3.6

2.6

8.0

2.6

2.6

11.6

0.0

-1.7

-1.6

137.3

105.8

1.24

1.39

100

1651

226

1877

88.0

22.0

100

2715

350

3065

88.6

11.4

100

1098

823

1921

57.2

42.8

100

8

4

12

66.7

33.3

100

32960

16878

49838

66.1

33.9

100

absolute

26638

12086

38724

%

68.8

31.2

100

59598

28964

88562

Total of investigated new working places

low1

I

1287

* This table is the result of an investigation of about 900 firms in various industrial branches of the FRG over the period 1970 to 1973. The data are published in: Datensammlung (1977), p. 11, Table 10. * * In this table high innovative working places are working places created by the following types of technological change: new plants for extension of production and replacement of old plants, new equipment, computerisation, new processes. Low innovative working places according to our definition are: replacement of existing plants, replacement of used equipment, shut-down of production facilities, organizational change and the use of other materials or energy. 1 High innovation; low innovation.

119

innovation. Low innovative working places are mostly connected with medium improvement and incremental innovation. However, it is possible from this data to identify some interesting relationships between innovation and the development of work content and skill requirements: 1. The new places created in the four industrial branches during the period of the investigation included 56.3 percent working places with a higher work content and 44.7 percent with a lower work content. 2. 67.3 percent of the new working places were connected with high innovative working places and only 22.7 percent with low innovative working places. From the high innovative working places 55.3 percent had a higher work content and 44.7 percent a lower work content than before the technological change. From the low innovative working places 58.3 percent, had a higher work content than before the technological change and 41.7 percent had a lower work content. It is evident that on an average, we cannot see any significant difference in the development of work content through high innovative technological change in comparison with low innovative technological change.

Table 41 Impact of high innovative and low innovative technological changes on the skill requirements of the labour force* Skill requirements

Education

Impact + higher — lower

+

Vocational training

~

places

100

-

100

-

-

-

absolute

1472

675

2147

7.

68

32

100

absolute

528

242

69

31

100

11626

4213

15839

27

100

absolute %

18

high1

low1

18

,73

„

1631

849

2480

/o

66

34

100

5212

2142

7354

/o

71

29

100

absolute

730

295

1025

71

29

100

%

2.8

2.8

7.1

5.0

7.1

7.3

770

absolute absolute

~

120

7„

/o

Responsibility for their own work

High innovative working places**

Requirement Coefficient

%

absolute

Vocational experience

Sum of

Low innovative working places**

absolute ~

Type of technological change

-

Skill requirements

Impact + higher — lower

Responsibility for the process

Type of technological change

Sum of

High innovative working places**

Low innovative working places**

places

3955 41 197 90

5648 59 22 10

9603 100 219 100

6592 68

3063 32

9655 100

-

-

-

absolute o/ /o

124 38

204 62

328 100

absolute

215 95

12 5

227 100

15883 59

11057 41

26940 100

absolute

1142 78

329 22

1471 100

absolute

28999 64.5

15945 35.5

absolute

3301 69.9

absolute

%

absolute 0/ absolute

Responsibility for equipment & facilities

%

absolute /o Responsibility for security of others

%

Sum of the four categories

+ absolute

%

+

+

20.1

256.7

very high

very high

-1.7

17.0

44944 100

8.8

11.2

1420 30.1

4721 100

Z

9.2

32300

17365

49665

65

35

100

absolute

%

16809 71

6836 29

23645 100

absolute y/o

6675 75

2264 25

8939 100

2.52

3.0

absolute

1701 36

3061 64

4762 100 -20.5

-7.5

absolute

34906 60

22888 40

57794 100

%

Total of new work places investigated

Physical strain

low1

283.0

%

Mental stress

high1

10.4

y/o

Total skill requirements for new work places

Requirement coefficient

%

%

* This table is the result of an investigation of about 900 firms in various industrial branches of the Federal Republic of Germany over the period 1970 to 1973. The data are published in: Dostal et al. 1977, p. 10, Table 7. ** In this table high innovative technological change include the following types of technological change : new plants for extension of production and replacement of old plants, new equipment, computerisation, new processes. Low innovative technological changes are: replacement of existing plants, replacement of used equipment, shut-down of production facilities, organizational change, the use of other materials or energies. 1 High innovation; low innovation.

121

3. The high innovative technological change eliminated many more working places requiring manual work (work by hand, transportation by hand) than that of low innovative technological change. It is interesting that 55.4 percent of the working places with a higher work content created through high innovative technological change were connected with such activities as control and adjusting of machines, checking and planning of products and processes, steering and advisory. The share of these kinds of activities was in the case of new working places, created due to low innovative technological change, 60.3 percent. That means that both kinds of technological change significantly extended the work contents which need higher vocational levels connected with vocational experience and high motivation for more responsible attitudes (see Figure 45).

wh = Work by hand cm = Control of machine p = Planning of process

th = Transportation by hand am = Adjusting machines ow = Office work

wm = Work with/on machines ch = Checking ste = Steering, advisory

Figure 45 Impact of high innovative and low innovative technological change on the work content Source: Computation; DOSTAL et al. (1977).

High innovative technological changes eliminated 11.8 times more manuel working places than it recreated working places with manual work content. Low innovative technological changes were only able to eliminate 2.8 times more manual working places than they were able to recreate. On the other hand, the elimination of simple office work (registration, tabulations, etc.) was only 1.6 times higher than the creation of such working places due to high innovative technological change, and through low innovative technological change 1.3 times higher than the recreation of such kinds of working places. 122

From the entire reduction of the work content due to high innovative technological change, the most significant was the reduction of work by hand, transport by hand and simple office work totalling 83.8 percent. In the case of low innovative technological change, the share of the reduction of that kind of job content in the entire reduction of work content was 55.4 percent. That means that both types of technical change eliminate working places with low skill and vocational requirements to a significant extent. High innovative technological change especially is a strong killer of such kinds of places. The findings about the influence of technological change on the work content is also confirmed through the skill requirements which occur due to innovation. Figure 46 shows that more than 90 percent of the working places that were created due to technical change need higher labour skills and only 10 percent lower skills. This share is approximately equal in the case of low innovative and high innovative technical change. 95 percent of the higher skill requirements for all new working places are connected with higher vocational experience and responsibility. Also, in this case we cannot find any significant differences in the low or high innovative changes. This is why we have taken into account here only new working places created and not the entire sum of working places, that is, both the newly

iO

tResult of empirical innstigation within 909firms of four imlustrial branches of the FRO including 2266 different technological changes)

High innonatim ttchnoiogka/ change lo* inneratire technological change

V Ve Ro Rp Re Rs M P

= = = = = = = =

Vertical training Vocational experience Responsibility for own work Responsibility for the process Resppnsibility for equipment and facilities Responsibility for the security of others Mental stress Physical strain

•20,5x

Figure 46 The impact of high-level innovative change on the skill requirements of the labour force S o u r c e : C o m p u t a t i o n f r o m DATENSAMMLUNG (1977).

123

created and eliminated working places. The above findings indicate that high innovative technological change to a much greater extent, eliminated working places with low skill requirements than that of low innovative technological change. That means that high innovative technological change triggers-off much more high skill requirements than is reflected in Table 40. The high share of vocational experience and responsibility for skill requirements as a whole, does not mean that formal education and vocational training are less important. Vocational experience and responsibility can only occur on the basis of a broad formal education and efficient vocational training. Higher education and vocational training is also an important precondition to overcome the problems of higher mental requirements. Our results demonstrate that high professional and vocational training is a necessary, but not a sufficient condition, for innovation. But the better use of human resources is calling for a more detailed investigation of the different skill requirements in the particular stages of the innovation process. Based on the data presented above, we can assume that the following relationship exists:

Implementation Stage — Highly skilled experts are decisive. These are people who have access to information necessary to implement the innovation and the capability to manage the technological and organizational problems. Here the technological and managerial skills are decisive. The openess of the organization and productive relationships between knowledge and power promoters are important preconditions. — Very important in this stage are skilled workers with handicraft experience. That is why in this stage we have a domination of universal production equipment and very few process innovations to unify the production process. — Through the low scale of the production process we have medium requirements for skilled and semi-skilled workers and a low employment effect.

Rapid Growth Stage — Highly skilled experts maintain their importance to overcome the problems of extension of production and the implementation of product and process improvements. — The extension of production requires more specialized production equipment, through which we have a very high demand for skilled workers, semi-skilled workers and a high employment effect. — The demand for skilled workers with handicraft experience is decreasing. 124

Maturation Stage — — — — —

High level of mechanization and automation. Very high demand for semi-skilled workers. High demand for skilled workers. Very low demand for highly skilled experts. Low or negative employment effect.

Saturation Stage — — — —

Automated and standardized production process. High demand for skilled workers and semi-skilled workers. Low demand for unskilled workers. Negative employment effect.

The lesson we can learn from our findings is that it is pointless to maintain a high share of skilled experts and experienced workers when production is shifting from the rapid growth to the maturation and saturation stages. It is much better to use these skilled workers for the preparation of new innovations, otherwise society will waste the most important resource: The creativeness of man. But this requires high flexibility in the organizational pattern and high mobility within the labour force.

8.3. Innovation, Occupational Structure and the Requirements for Further Education Only a part of basic innovations are able to trigger off the development of new occupations which require new forms of education. Most occupations are able to broaden their outlook and make appropriate changes within the occupation profile. Figure 47 shows the frequency of occupations created in connection with innovation. For 40 basic innovations, only 13 have triggered off particular professions and occupations over the period 1970 to 1980. That is why only a small part of ,the entire contemporary occupations are new. In the US for example only 3 percent of the entire occupations have been newly developed since 1950. The existing- occupations were mostly able to adopt the new skill requirements within the existing occupation. This very much enriches the features of the existing occupations and changes the internal structure of the occupation. This means that vocational training is not challenged so much through the emergence of new occupations but through new requirements for and within existing occupations. Howev.er, we should also not neglect the importance of the educational system and vocational training in the process of implementation and diffusion of innovation. The "stock" of well educated chemistry engineers in Germany at the beginning of this century was an important factor for the initial development of the 125

Process inrmhon Moteria! intention System intention Element intention

P ft S E

Silicon planar technology p Freeze (trying P Antibiotics M Integrated circuits E Synthetic fibres M Radar S Vitamins M Semiconductors M Teterision S Plastics M Indigo synthesis ft Vacuum tubes E Ariotion fairfoil) S Diesel engine S Rubber synthesis M Hydrogénation of coat P Telephone S Ferro • concrete M Incandescent tamps E Radio S Internal combustion engine S Electric generator Cinematography Ammonia synthesis Aluminium Computer processing Magnesium Titan Mobile steam engine Ariotion tballoon) Frozen foods Automobile Cement Hydraulic turbine Photography HC machines Steamship Municipal gas Steam turbine Steam engine

teso t7oo

Uraundmrit phase Intention phase Innotatiaoal phase Appearance of a nem occupation

0

KWNB

E3]

IWvW" H

in

19501970 rear

Figure 47 Innovations and new occupations Source: DOSTAL et al. (1977).

chemical industry and the fast diffusion of chemistry technologies in Germany at the beginning of the century. A contemporary example is the development of computing technology. Figure 48 demonstrates that the vocational and professional training occured at the beginning of the 1950's, a long time before the existence of a significant number of working places and before most of the important technological breakthroughs were managed. The early reaction of the educational system was obviously an important momentum in computer technology. It is important not to neglect that besides the vertical connection between the level of mechanization and automation and the level of qualification, there also exists a horizontal connection between occupations and the level of mechanization and automation. That means that the different occupations at the same level of qualification are in a special way connected to the level of mechanizations and 126

00

_o "o e

a e R S P S 2 O.Co . S «

kc 00

127

automation. Figure 49 demonstrates this relationship by using the example of 21 occupations and their relationship to low, medium and high levels of mechanization.

Lo* leni Middle lertl

/

/

Figure 49 Stage of mechanization of various occupations as reflected by the proportions of persons working at low, middle, and high levels of mechanization in the FRG in 1970 Source: DOSTAL et al. (1977).

The educational and vocational training system is only able to play an important role in the innovation process if it does not neglect the tendencies of integrating the various educational aspects and the tendencies working in the direction of their differentiation. On the one hand the role of theoretical training and the role of basic subjects is growing and we arrive at the stage where new basic occupations emerge. On the other hand, the requirements with regard to specialized knowledge on the part of the workers, the combined intellectual-physical aptitudes, the capability of mastering new technologies and machinery in a short time and of attaining the envisaged technicaleconomic parameters are growing. 128

Under the pressure of accelerated technological change, the tendency to integrate a part of the narrowly specialized vocations into more basic vocations is obvious. In the GDR for example, the number of trained vocations decreased from 972 in 1957 to 658 in 1964 and 305 in 1971. The growing role of scientifictechnical training and basic vocations is by no means an expression of the reduced significance of specialized knowledge and training. It would be a great mistake to believe this. On the one hand all existing occupations are of great importance for the proportionate development of the national economy and they underestimate certain occupational groups which are necessary components of social division of labour and this must inevitably lead to effective losses in the national economy. It must be emphasized on the other hand that a broad differentiation in trained and basic occupations is the very precondition for the specialization. Thus in the GDR at present, there are 49 broadly differentiated trained occupations and 28 basic occupations which form the basis for about 700 specializations. We should not neglect the fact that the effectiveness of theoretical vocational training and basic occupations depend to a decisive degree on how they are connected with practical occupational activities and how they contribute towards facilitating the appropriate required specialized knowledge. There is a close connection between the increase of qualification requirements and the decrease in hard physical work. The relatively high share of production workers who do not work with machines and equipment, show the great importance of mechanization in the present stage of development. Mechanization does not only essentially contribute to abolishing hard physical and unskilled labour but creates decisive preconditions for automation. The relatively high share of unskilled workers on automated equipment results from the fact that at present automation does not completely cover the whole production cycle. At present mainly directed machining tasks are automated so that feeding and emptying of automatic machines as well as the connection to other sections of the production cycle has to be done manually. In increasing the importance of qualified labour, attention has to be paid not only to mechanization and automation of the main production processes but increasingly to auxiliary and subsidiary processes. Here especially mechanization and automation make it possible not only to release manpower on a large scale but also to increase the importance of qualified labour essentially. This is particularly true for the mechanization and automation of processes of transport und turnover. For the better use of the quality of human resources it is necessary that management has to be concerned with the following problems: 1. At the stage of projecting and constructing new equipment, targets have to be set as to what degree of unskilled and hard physical work can be reduced and what kinds of qualifications are needed. In this field there are real sources for an increase in efficiency. The exact determination of contents and extent of necessary qualifications can contribute essentially to raise productivity. 9

Haustein/Maier

129

2. Planning and realization of investments requires a welltimed determination of the necessary abilities and knowledge for operating new equipment. The enterprises must be given programs for additional training, as far as possible in programmed form. Underestimation of this aspect of investment preparation leads to economic losses such as breakdowns, etc. with an amount of some hundreds of million marks a year. 3. The high quota of women in unskilled labour is still a fact. Therefore everything has to be done to prevent the negative effects of differentiation in qualification requirements concerned with scientific technical progress. By means of organization of scientific work everything has to be done in order to reduce such operations which only require simple and unskilled work, as well as reducing the monotony of work, and one-sided physical and psychological burden. It is necessary to analyze and generalize experiences in organizing job rotation and in improving the mental climate within working teams. In cases where equipment still requires one-sided and unskilled operations, large scale possibilities have to be found and realized for creating substantial operations by applying new combinations of labour, of planned job rotation and of j o b enlargement. 4. The better utilization of the increased education and qualification level does not mean blocking such lines of technological innovations which are connected with a reduction of qualification requirements. Doing so would mean conserving mentally complicated technologies which are difficult to master. So for instance, qualification requirements for operating the first computer generation was incomparably higher than the present qualifications necessary for operating equipment with microprocessors. Simplification of operation and reduction of the training period are without doubt an essential aspect of scientific-technical progress and substantially contribute to its rapid extension and to an increase in economic efficiency. The reduction of mental requirements can of course have positive consequences for the development of personality. With that a considerably higher number of working people are able to gain the necessary qualifications for operating automatic equipment in the shortest possible time, and so to have knowledge in various fields. In order to emphasize the problem: the way we have to go is not to conserve mentally difficult operations, but far more, by means of organizing work — which takes the increased qualification level into account — we have to give working people the possibility of using their physical, social and mental abilities in various ways in the process of increasing the efficiency of labour. Management and planning of production have to guarantee such a scientific work organization that brings into action modern technology as well as an increased qualification level of working people for the growth of social labour productivity and efficiency. ' It is necessary to consider the different situations which skilled workers have to manage in the various stages of mechanization and automation. In mechanized production the qualification of a skilled worker is needed permanently for producing a special product. In this case qualifications are a precondition for the 130

machining operation. Though in automated production skilled worker qualification is an absolute precondition for production, it is not directly needed for carrying out the typical operations in automated production, such as steering, regulating and controlling. So skilled worker qualifications in automated production are not permanently used. In order to prevent a permanent undercharge of skilled workers scientific work organization has to find new kinds of division of labour and with this to enrich and enlarge the work (Langen 1977). So scientific work organization has to guarantee: — formation of new kinds of combinations of labour for creating substantial and ambitious operations, — planned j o b rotation, — increase of responsibility of working people in management and planning of the production process, — possibilities of identification with the final product, — balance between physical and mental requirements, — job enlargement, — possibilities for communication and cooperation, — possibilities for realizing ideas and initiatives, — pleasant working environment. An important component of securing a higher quality in human resources is the creation of conditions for lifelong learning for working people. In the past, the educational system was able to confine itself largely to the role of transfering the existing knowledge of the active generation to the following generation. It concentrated its efforts on that stage in the life of a person which precedes the adult stage. One learned and taught " f o r a lifetime", and therefore in the early stages of life. This approach is outdated. Today, a modern educational system is unthinkable without conditions for the education of already trained personnel. Thus, for instance in the G D R , about 20 percent of the outlay for education is devoted to further training, and almost every fourth person employed in industry takes part in an organized training course (50 percent of them are women). Without doubt a permanent in-service training will in future play an important role in the system of needs of a socialist society and in the further development of the socialist way of life. Recently adult education has essentially contributed to the increase of the number of skilled workers and of university and technical school graduates. 30 to 40 percent of today's skilled workers in the G D R got their qualifications by adult education. Every third university graduate and every second technical school graduate got his diploma by way of external studies. Taking the now reached high qualification level into account, adult education will in future take up its actual function, reproduction of the existing qualification level (see Figure 50). Under the conditions of speeding up scientific technical progress, we are confronted with the obsolescence of knowledge. The scale of necessary requirements for in-service training can be illustrated by the following considerations: 9*

131

In-service training 77.5%

I97S

[Ovation 77. S %

UX

11 Systematic genera! education In-service training of ^ ^ university graduâtes I I In-service training of foremen ffffffffl In-service training of ümíu ' skilled Htorkers i1 11 In-service training of technical school graduates

Training for a partió! trade lllllig Trainingtbrstitted 1111111 mrker k\Vj Training for fonLxxal men UUn Training for unímJ-U nrsi/y graduales 1 Training tbrteeh' nicat schoot graduales

Figure 50 Various measures of qualification in adult education in the socialist economy of the GDR (only industry, building industry, transport, posts and telegraphs, in percent)

assuming a 3 percent progress rate of knowledge, you come to the following expenditure of time needed for in-service training during the whole period of working life: skilled workers 2.8 years, technical school graduates 6.7 years, university graduates 7.8 years. This means 6.3 percent of the working life period of skilled workers, 18 percent of that of technical school graduates, 22 percent of that of university graduates (see Figure 51). Of course, there exists no "law of increasing expenditure" for in-service training. But these figures show how important it is to make measures in time in order to meet the process of obsolescence of knowledge and to care for an interlacing of education and work processes so that in-service training will get an adequate place in the socialist way of life. All this emphasizes the importance of general education which sets the preconditions for a permanent interlacing of existing knowledge with new knowledge, for a permanent transformation of existing knowledge to the socially necessary level by in-service training. This emphasis also gives more consideration to innovative learning, to improve the ability of man for self-education. The requirements resulting from the rate of progress of knowledge show that we need an effective combination between three components of in-service training: — in-service training in an organized form, — in-service training according to own interests and initiatives, 132

— in-service training by an active participation in various forms of the intellectualcultural life of society. Of course, these three forms are mutually connected. They influenced each other to a very high degree. The organized form of in-service training can only fulfill its actual task if it is based on the other two components and vice versa if they support it effectively. At present the organized form of in-service training in the GDR is realized to about 80 percent during working hours. That does not only bring along high economic expenditure in direct and indirect forms, but it is furthermore connected with another danger: if in-service training is too tightly bound to the direct operations and tasks of the working place, it cannot fulfill its life. Therefore organized in-service training has not only to give working people knowledge directly applicable to working tasks, but also to contribute to the enrichment of intellectual and cultural life. At the same time new possibilities for the two other forms of in-service training have to be found be a higher efficiency of the spare time of working people.

133

9. Human Resources, Creativity and Innovation. The Conflict between Homo Faber and Homo Ludens 9.1. Human Brain Versus Development of Productive Forces When one looks at the long history of productive forces the predominant role of human individuality and capability in all technological progress can be perceived. In the working process all human labour functions were developed in two main classes: the technical, and the creative functions. Technical functions are the energetic, the operational, the control and the logic (or preparatory) functions, and the creative functions are empirical improvement, invention of new techniques, and theoretical analysis and goal setting. Technical functions of labour are replaced by technical means in various directions, starting with the lowest level (energetic functions) up to higher functions and giving man more opportunities for creative work. And so a feedback to human abilities is realized. According to archaeological studies technological development can be compared with an increase in the volume of the human brain (see Figure 52). 1,800,000 years ago when production of clumsy flint weapons and instruments began, an increase in brain volume from 500 to 800 cm3 occurred. 75,000 years ago the homo sapiens neanderthalensis reached a maximum with 1500 cm3 up to 1700 cm3. At present, the human brain has an average volume of 1400 cm3. The great memory requirements needed for acting without any background of abstract and of theoretical thinking may be the reason for the enormous brain capacity of the homo sapiens neanderthalensis. On the other hand, the transition to abstract thinking was enabled by the quantitative growth of the human brain. Physiologists say

„

wo -

I 1000 -

\

7504 500 2000

¡000

—j I I I I i_ 500 400 300 200 10050 Year

Figure 52 Development of productive forces and brain capacity over a period of 2 million years Source: Herrmann, J., Spuren des Prometheus, Leipzig—Jena—Berlin 1975, p. 33.

134

that we use only 5 or 10 percent of the capacity of our brain. At present under the conditions of the information explosion, we again have high memory requirements. But this is also a question of further progress in theoretical thinking. Discovery of new laws and theorems frees us from the necessity of remembering a large number of facts. Example, at the time when electricity was a well-known but not a theoretically explained phenomenon, the old textbook of Wiedermann had more than 1000 pages about galvanism. After Maxwell's theory the same information could be given without unnecessary detail and was more applicable, and took up only 50 to 100 pages. 9.2. General Intellect. The Most Wasted Resource When considering the individual brain, the high capacity utilization gap was mentioned. However, a greater gap is found if the general intellect of mankind is investigated. The general intellect of mankind is not as simple as the sum of 4000 million brains. It is a social resource potential which is realized through socioeconomic interaction of people. Creativity is the ability to find an idea which is both new and useful from the social standpoint. It has a highly concentrated social dimension both from the side of its emergence and genesis and from the side of its consequences. The social character of creativity is the most important point in studying the economic implications of creativity. Most of the material resources could be used in the past in an economic efficient social way, that was connected with ownership rights. Fixed capital, like other physical capital can be owned, bought and sold. Ownership rights are well defined with fixed capital, but the output of creativity is new knowledge and ownership rights are imperfect in new knowledge. Creative work is general work, using the results of a long chain of predecessors and having far-reaching, often incalculable, social consequences. If we include in creative work not only the efforts of basic research, but also the new and helpful thoughts on all stages of the innovation process, we can also realize the social dimension of creativity. Thus creativity as a social potential is not the same as the creativity of an individual. In reality there is no homo ludens; but an interaction of people with creative and routine abilities under given socio-economic relations towards social goals and objectives. If one wants to talk about the present creative potential of society or mankind it is not quite exact to speak about a human gap, because this is liable to misinterpretation. Individual learning ability and creativity is only a single element and not the main point in changing social creativity potential. Otherwise, it wouldn't be enough to state that if we taught mankind better then all problems would be solved. Therefore our conceptual approach is the following: if we look at societal development from the standpoint of human forces, we can distinguish between societal learning and societal creativity push (see Figure 53). Societal learning 135

i

> u

•o "3

o S

CA tst

J3 CA 3

O.

'5 CÖ

T3 e ta

•è

136

is a very complex phenomenon which is very generally defined as adaptation of social man to a changing environment. Societal learning consists of a dynamic and static element. The static element is called by the authors of "The Human Gap" (The Club of Rome, 1979) "maintenance learning" or acquisition of fixed outlooks, methods, and rules for dealing with known and recurring situations. The dynamic element is also called by these authors "innovative learning", a type of learning that can bring change, renewal, restructuring, and problem reformulation. This is a very useful distinction within the learning process. But of course we cannot reduce the "human gap" to a "learning gap" and also not extend the learning term to all human activities. As we stated in another context, the "learning boom" in literature is only a mental reflection of the "improvement approach" in general. Human activity is closely connected with learning, but at the same time it has a creative component leading to breakthroughs and to the beginning of entirely new learning curves, not comparable with the former. Societal learning cannot be reduced to a certain sum of individual learning. Dynamic societal learning is connected with improvement of material capacities, of social relationships, institutions and values as well as the improvement of individual learning. Another side of human activity is creative change in productive forces, in social relations and in institutions and values, connected with an upswing in societal creativity. A societal creativity push cannot be reduced to a small number of Nobel Prize winners or representatives from basic research. It can be a very complex phenomenon in science, the arts or in technological progress. The elitist approach to creativity gives main attention to leading key people in creative change, but this approach does not take into account the social background of the individual forerunners, as well as the social backing and implementation of thenideas which is also a process which needs the creative support of many people. Societal learning is a very powerful means of adjusting societies to evolution of needs and natural conditions, but it is not enough to overcome global resource crises and other global problems. For this we need a real societal creativity push connected with overcoming social barriers which inhibit the solution of global problems. When we pay most attention to the creativity push this does not mean that we can forget about the interdependence of creativity and learning. There is no creativity without learning and conversely learning is influenced in many ways by creative pushes. In various societies the relationship between learning and creativity was quite different. The birth and upswing of a society brought an important creative push, mainly on the side of the leading forces, further progress was supported less by creativity, and more by dynamic learning; and a lack of creativity and dynamic learning was the environment for stagnation and decline for a given social structure. Learning and creativity can be realized in a conscious or in an unconscious way, from the standpoint of a societal or historical consciousness. 137

Unconsciousness, or not being aware of global problems which threaten mankind's existence, is a great danger today because it leads to a long delay in feedback and reaction time. Therefore the authors of "The Human Gap" are right when they call for more anticipation and participation activities. In our opinion only a real creativity push in accordance with fundamental changes in societal goods and values can solve the problems that mankind is now faced with. This means a co-evolution of social relations, goals and values on the one hand and means of production on the other, not only by adaptation but also through creative restructuring of the whole system (see Figure 54). This is the logical conclusion that can be drawn from the statement by the Club of Rome, that the problems of mankind are now fundamental.

We cannot say that great philosophers of the past have not foreseen the danger for mankind, it had an important anticipatory power, when for example, Marx stated "the devaluation of the world of Man increases in direct proportion to the overvaluation of the world of things" (Marx 1844). Similar statements were made by Rousseau, Diderot and Saint-Simon before Marx. It is indeed a great paradox, that human creativity can bring about at the same time both positive results and those which are socially devaluing such as the arms race, unemployment and social and mental degredation. Over 500,000 scientists (nearly half the world's total) are engaged in anticreative weapons research. We have to look at the obstacles to creativity in three stages and in four levels (see Figure 55). The three stages are: — formation of creative personalities, — creation period and — realization period. 138

N.

Obstacles

Levels Level and growth of productive forces

Economic relations and interests

Institutions

Mental and ideological factors

Formation of creative personalities

Nutritional déficiences.

No economic in te rest in formation of creative personalities.

Insufficient educational system, illiteracy.

Elitist theories and ideologies. Ignorance about creativity.

Creation

Unsatisfactory material conditions. Too l i t t l e free t i m e .

Economic incentives leading to brain d r a i n . Economic conditions leading to f r u s t r a t i o n Unemployment.

Socially anticreofive goals and tasks of institutions. Organizations in the saturation stage.

Attitudes against creative people. Uncreative atmosphere. Anxiety for the future. Alienation.

Material constraints for realization.

Not enough incentives for the innovation. Too narrow division of labour. Unemployment-

Institutions inhibiting innovation.

No understanding between R&D andproduction.

Stages

Realization

Figure 55

period

period

Obstacles to creativity over three stages and four levels

The four levels are: — — — —

growth of production forces, economic relations and interests, institutions and mental and ideological factors.

In the formative period of creativity it is very important that the human being is properly fed during the first two years of his life as well as the nine months before birth. In many developing countries more than 50 percent of the population have suffered from nutritional deficiencies and therefore, as societies, loose a large part of their creativity potential. One of the most striking problems is the world's illiteracy rate and the disproportionate distribution of rational knowledge and learning capabilities over countries, races, sex and social strata. This can be measured by simple statistical data. Table 42 shows the share of groups of countries in material resources, but also in human resources and their utilization. Developing countries which have a 48 percent share in the population and 49 percent in the world's surface can use their human capital only 4—12 times lower than their raw material, if we look at their numbers of scholars and engineers and their patent notifications. In 1970 the world had more than 670 million illiterate people of age fifteen and over. (The population age 15 and over was roughly 2200 millions). Most of these live in the developing countries and UNESCO 139

Table 42 Share of groups of countries in surface, population, raw materials, energy consumption, industrial production, illiteracy, scholars and engneers, R & D personnel, and patents (in percent) Surface

Population

Illiteracy

Industrial production

Energy consumption

Scholars & engineers

19771

Raw material production 19702

19771 Planned economies

19706

1975*

19763

1970- 735 1 974

26

33

28

11

40

31

49

30

CMEA countries

18

9

35

23

—

—

Developing countries

49

48

27

40

10

13

6

2

Developed market economies

25

20

45

2

50

56

45

68

—

0.5

Patent notification

Patent notification abroad 1974 3.5

—

0.5

96

1

Sources: Statistisches Jahrbuch der DDR (1978), p. 29. 2 Spröte, W./Thiele, G. Internationale Wirtschaftsbeziehungen und Entwicklungsländer, Berlin 1978, p. 24. 3 UNESCO Statistical Yearbook (1977). 4 Kuczynski, J., Die Krise der kapitalistischen Weltwirtschaft, Berlin 1976, p. 10. 5 East-West Technological Cooperation, Brussels 1976, p. 207. 6 Estimation according to UNESCO Statistical Yearbook (1977).

estimates that in 1980 there will be 820 millions illiterate adults, a full one-fifth of the world's total population. In addition to this, we have the phenomenon of the brain drain from developing countries to developed market economies. Within various developing countries we also have large differences (see Table 43). Education enrollment ratios for the 3rd level differ from 0.13 for Benin up to 14.23 for Argentina. On the other hand enrollment ratios for developed market economies are not an exact measure. They not show the so-called functional iliteracy — the inability to read or write well enough to apply for a job. In the US where public expenditure on education is twenty times higher than in the African states (see Table 44) some 23 millions adults (10 percent of the population) seem to be functionally illiterate. Human intelligence and human creativity are the main economic resources. But we can state that their utilization level is very low according to formal measures (enrollment ratios, expenditure on education, unemployment ratios and others). In the creation period, which follows that formation of creative personalities, the main negative factors are unemployment, the brain drain, insufficient material conditions, monotonous work without creative requirements, and all kinds of alienation of productive people. But at the moment the world seems to be more concerned about the oil crisis than about the tremendous losses in creative potential. 140

It is a great paradox that human abilities are the most important economic resource, but at the same time they are the most wasted resource of all. There are many studies and books written about the energy gap, but far fewer studies about the creativity usage gap. In the long period of human history, only in the earliest Table 43

Education enrollment ratios in varipus countries Education enrollment ratios 1970 1st and 2nd levels Reference years

3rd level Percent

Country Planned economies Bulgaria USSR GDR Cuba Developing countries Argentina Brazil India Algeria Angola Benin Egypt Ethiopia Somalia Developed market economies US Japan Canada UK Austria FRG

Percent (20—24 years)

7-17 7-17 7-18 6-18

95 92 93 74

14.47 25.30 32.77 3.69

5-17 6-18 5-15 6-18 10-14 6-18 5-16 7-18 6-17

75 55 50 45 38 23 52 11 6

14.23 5.26 6.39 1.70 0.47 0.13 7.92 0.21 0.38

6-17 6-17 6-19 5-17 6-17 6-18

101* 93 88 88 84 78

49.43 17.01 34.59 14.07 11.76 13.41

* The number of 101 is not so surprising if we take into account the so-called secondary illiteracy: the numerator can be higher than the denominator, which includes only the number of people between 6 and 17 years. Source: UNESCO Statistical Yearbook (1977).

Table 44

Estimated per capita public expenditure on education (in US dollars)

Region

1965

1975

Index (1965 = 100)

1. 2. 3. 4. 5.

187 62 9 13

480 230 57 46

257 371 633 354

5

17

340

38

109

287

Northern America Europe Arab States Latin America Africa (excluding the Arab States)

World total

Source: UNESCO Statistical Yearbook (1977), p. 103.

141

times of new progressive societies was there a clear tendency to improve the use of creativity. Alternatively we know of the excesses in wasting human creativity over long periods in wars or in unproductive work. According to Herodot 100,000 men worked for 20 years to erect the Cheops Pyramid. This enormous expenditure and loss weakened the economic power of the first ancient class structured society and led to a deep social crisis in the 22nd century B.C.

9.3. Economic Dimensions of Creativity. A Paradox? Human intelligence is generally assumed to be a normal distribution in a given population. Some empirical studies found a standard deviation of 16 in the American IQ. So 68.26 percent may have an IQ of 100 ± 16, 95.44 percent an IQ of 100 ± 32, and 99.74 percent an IQ of 100 + 48. The real frequency distribution of intelligence is very difficult to determine. It is only possible by special tests, having limited importance for the phenomenon as a whole. But the concrete parameters of the frequency distribution as a whole are mainly determined by social and educational factors. It is much more difficult to estimate any frequency distribution of creativity. It may be possible by special creativity tests. The IQ tests are not appropriate for this purpose. It was found that people with a relatively high IQ were not as creative as people with a lower IQ. It is more difficult to make an economic measurement of creativity. One knows how a mechanic calculates for instance, For work done $ 5.00 For knowing how $ 45.00 Total $ 50.00 and of a lawyer, Woke up in the night and thought about your case Say $ 500.00 From this illustration one can humorously show the fundamental problem of measuring creativity in economic terms. Creativity is in general the human ability to find new thoughts, which are goal-orientied and directly or indirectly connected with the improvement of human existence. So we consciously define creativity in a positive sense. The question is, is there any possibility of measuring creativity in economic terms? Measurement in market terms presupposes comparability and exchangeability but creative results are not comparable per definition. There is no strong correlation between labour time, labour value, and creative results. There is only a social correlation between free or disposal time and other conditions for creative work, and the probability of creative results. But this correlation includes a lot of social factors. Having free time at ones disposal, creative work is often not the main option for people. A wide range of hopes is connected with the future of communication systems. 142

The use of mini-computers at home could be a perspective for learning and creative gaming. But at the same time it might be a way of restricting homo faber or homo ludens to pure man-the-player. Development of societal and group relations between learning and becoming creative people is much more important than any isolated game with nature in the way Robinson Crusoe acted, and even Robinson Crusoe needed a colleague. Despite the complexity we believe that an economic measurement of creativity is possible. Our main idea is that active participation of working people in the innovation field is a farily good indication of creativity in the production area. In this area we have to differentiate between the following fields of creativity (see Figure 56). Creativity in research as an economic and social phenomenon can be indirectly measured by the number of discoveries, the number of Nobel prize winners (a very limited approach!), the share of fundamental research or the time-structure of research work. But most of these measures are very weak. For example, a forecast of 1969 gave the following figures for the time-structure in R & D in the GDR (percent):

1970 Man-machine dialogue Creative work without modern auxiliary means Planning and management Reading, qualifying Routine work without modern instruments

1990

0

16 (12. .. 20)

30 10 12

32 (20 . ..50) 15 (10. ..20) 20 (15.,..25)

48

17 (10..,.40)

However, such figures are very vague. The problem is that creative work and routine work are closely interconnected. We can say that for complex practical problems there is always a certain mixture of routine or simple know-how and creativity needed. Without routine there is no success in practical problems, and without creativity there is only little or diminishing success. Lord Rutherford mentioned: "Every man depends on the work of his predecessor. When you hear of a sudden unexpected discovery — a bolt from the blue as it were — you can always be sure that it has grown up by the influence of one man or another, and it is this mutual influence which makes the enormous possibility of scientific advance." The mutual influence of know-how and creativity is a great driving force. But at the same time creativity is the opposite of routine. Through creativity it is possible to substitute a great amount of routine work. 143

~ ~~-^0imensions Results

Stages

Process ond organization

Personal characteristics

Participation

Research

Number of discoveries

Time structure

Psychic and intellectual features of personnel

Share of .prize winners

Development

Patents

rime structure

Psychic and Intellectual features of personnel

Share of inventors with high productivity

Introduction ond improvement

Number of innovations

Psychic ond Intellectual features of personnel

Share of innovative groups

Psychic and intellectual features of personnel

Share of employees with inventions and proposals

Tota1

Figure 56

Share of netr results in all technological changes, benefits from inventions

Creative potential of an organization

Dimensions for economic measurement of creativity

We analysed this interconnection using the example of 35,945 technological changes in four industries on the basis of published data of the Institut for Labour Market and Vocational Research, Nürnberg. We defined a creativity coefficient as the share of changes with new tasks and results and compared them with such indicators as economic effectiveness, routine experience and the labour saving factor (see Figure 57). It is very interesting to note that the demand for routine experience is increasing with higher creative requirements. In this way the assumptions made on the relation between the two indicators could be checked. There is no sense in underestimating the importance of routine experience even in creative tasks. Economic effectiveness is obviously the highest in less creative technological changes. This is a well-known phenomenon. We can describe this also in terms of innovation theory. In the saturation stage there are the highest absolute benefits and technological changes are of a minor, incremental type. In the stage of rapid growth and increasing imitation relative efficiency is very high and the absolute benefits are increasing very quickly. In this stage we find relatively high creativity requirements and the highest need for routine experience. It may be the special mixture between routine experience and creativity which makes the Japanese industry so powerful as competitor at present. The innovation and reinnovation cycle of an industry requires an appropriate combination of creativity and routine experience in Research, Development and in the introduction and improvement phases in stages: Take-off, Rapid Growth, Imitation, Maturation and Saturation. An important approach to measurement of creativity is the Homo Faber concept, which was developed by Henri Bergson in 1907. This concept was needed 144

A : Other materials or energies B: Mechanization and rationalization C : Organizational changes 0: Replacement of enisling equipment E. Nerr equipment F: Me/r processes 0 : Mm plants

Percent' 70

60

SO

30

20 10

0

Figure

A B

57

C

D

£

F

6

Creating coefficient (in percent)

C h a r a c t e r i s t i c o f 3 5 9 4 5 t e c h n o l o g i c a l c h a n g e s in f o u r i n d u s t r i e s ( m e t a l w o r k i n g , f o o d ,

timber and plastics)

by Bergson to bring out the distinction between instinct and intellect. Intellect he characterized as the ability to produce artificial objects and, in particular, to create tools out of tools and to vary their production indefinitely. Human labour is a natural as well as a social process, in which man performs technical, creative technological and social functions. Technical functions include all tasks which can be substituted by technical means under our present horizon and knowledge. Creative technological functions cannot be substituted by technical means at present and social functions simply do not underlie technological substitution. Figure 58 gives an extended overview to, and hierarchical structure of labour functions. Statistical measurement of these functions is rather difficult because of this overlapping. Communication functions are in our scheme part of complex logic and technical functions but in the same time communication is a social phenomenon. Thus a clear-cut distinction between technical, creative technological and social functions cannot be made. Table 45 is showing statistical data on 29 labour functions. They illustrate in its first part (number of technological changes in metalworking industry 1973, in food industry 1972, in woodworking industry 1971 and in plastics industry 1970), that most of the technological changes were concentrated on transport within factory, manual work supervision of machines and operating machines. A clear substitutive character of technological 10 Haustein/Maier

145

£ 11 •sis .1

ì

¡!

'S § I s II «s? ^ös

tM i § 5J

ist d I3IS fil l

f

i t-

II

I

11

il .oO

I 1

3

It

h s>

3

ja

l! e

il

146

t I 1*1

ü3

•I

changes can be seen in the functions Administration, Transport within factory, Manual work and Moving by hand. A clear extensive character of technological change can be seen in the functions Supervision of machines, Operating machines, Scheduling and Quality Control. Thus in the past change in labour functions could be observed mainly in the executive and in the Control function. But there exist also statistical data on labour functions of all working places, which are presented in the other part of Table 45. They were obtained by adjoining available data on professions to labour functions and are therefore only a relatively rough measure. Using them with necessary precaution the following result can be derived: Group of labour function

Number from Table . . .

1. 2. 3. 4. 5.

2, 3, 4, 6, 10, 12 5 6, 7, 9, 10, 11, 12 13, 15, 22, 23—29 17, 18, 19

Social Creative technological Complex logic Control Manual executive

1977 34.4 4.7 35.5 30.0 22.3

1980 (27.1) (3.7) (28.0) (23.6) »

-o 3^ e so s|.s s .S 3o c-BSm s ä s | | JS »" aö c1 e-oo3a) os « S u -s 3 o £ 13 a I I he .s 5 1 1 J -a á s _ « o 3 ts S 2 • o « S 6 S Í 3.5 S 2 e . la- o 3Ji o 'S S t » S « S S £ & S 3 * * 4>~ 2-5 c d S d 2 nSSuHU S H£E iS OU < U V ££

Table 62

G r o u p s of countries

1. Developed market economies 1.1 USA 1.2 Western Europe 1.3 Japan 1.4 Others 2. Planned economies 2.1 CMEA (COMECON) member countries 2.2 Other planned economies 3. Developing countries 3.1 Major developing countries with market orientation and middle income 3.2 Developing countries with low income

We find quite a different situation in the planned economies. In these countries there is an urgent need for increased rationalization in production. We find still another situation in the developing countries. In Brazil, Mexico, Argentina, South Korea, and India, which account for more than 58 percent of value added in manufacturing in the developing countries, a number of societal problems have arisen as a result of fast and uneven industrialization. Many of the countries with the lowest per capita GDP (less than $ 265) also have the lowest growth rates for production. Over the past 15 years, there has been rapid change in world shares of value added among the groups of countries (see Table 63) and there has been much speculation about the relative shares of value added that can be expected by these groups of countries in the years to come. For developing countries, a share of 14—18 percent by 1990 seems plausible. The Lima target of 25 percent by the year 2000, however, will be difficult to attain. The centrally planned economies might increase their share to 32—35 percent by 1990, due to their rapid growth rates. To some extent, the goals of industrial strategy conflict among the groups of countries. A systems analysis of these goals would be very useful. Table 63 Shares of g r o u p s of countries in w o r l d total of value a d d e d (based o n 85 developing a n d 35 developed countries) Developed market economies

Centrally planned economies

Developing countries

I960

73.3

18.1

6.9

1975

61.9

27.7

8.6

-11.4

+ 10.4

+ 1.7

A 1960- 1975 1990 A 1975- 1990

47... 54 -8... -15

32... 35 +4... 7

14... 18 + 5 ...9

Source: World Industry Since 1960 (1979); own estimates for 1990. 12*

179

While it is difficult to estimate and compare the progressiveness of industrial structures, such an assessment is essential for industrial strategy, as only a progressive structure can meet the goals set forth. Sometimes a given structure must be radically altered. The following are indicators of industrial structure at the national level: — growth rate of production, — level of productivity P, — variance of elasticities SE (elasticity E = kjk, where — growth rate of the i-th industry, k — growth rate of the whole industry), — coefficient for satisfaction of social and economic goals G.

Table 64 Goals for industrial strategy in groups of countries with their weights and the contribution coefficient of selected industries (1)

A l

(2)

(3)

1

s 'S M ¡3

(5)

« i

s

2

3 -à

(4)

2. 2

! !

Ï

* I

(6)

(7)

(8)

(9)

-Sg-S "S-B "S

* §

3 -a a§

1J

a! 3o

•c s3

(14)

(15)

(16)

(17)

o

2 a

¿> a S3 2 •B . 2 I § a a o .6 U ¿1 U ¡3 .2 S

J> g.

2J 8 M C 4> o a Se '3 3 .a > > oo oç

32 136 64 174 219 143 114 231 154 248 117 125

46 159 80 183 244 147 121 245 251 255 132 152

35 129 63 174 216 133 110 220 139 130 206 146

43 129 78 168 201 123 109 198 211 122 197 127

1757

2015

1701

1706

S-i

42 115 62120 149 98 84 150 86 140 103 113 1262

•3.2 eu

1.8 7.7 3.6 9.9 12.5 8.1 6.5 13.1 8.8 14.1 6.7 7.1 100

ft

* o

•O S

1 § i l 2 j| 55 "o.

2.0 7.9 4.0 9.1 12.1 7.3 6.0 12.2 12.5 12.7 6.6 7.5 100

S

%•cVioe eo

» ?3 •8 oo uH .ss "O •c •s g. O .o 1 IM cId s & Cfi T3s

2.1 7.6 3.7 10.2 12,7 7.8 6.5 1.3 8.2 7.6 12.1 8.6 100

I g> 51

-E O

< .S

"a.

'I Ä 1 s Si I s* a 3 3 00 3 « il II î s a. S^-

8 fS8 "•i + S % & 11 1 1 o-J u

-a

i i e S ? §

h K

3 "8 •M £ i

210

S 3^ S. f.-s « G rt S S. S

E S*

3u >¡ 5 «

H.9E

The early slow diffusion of NC-machines and robots seems to point to many hindrances in their socioeconomic and technological environment. But microprocessors are bringing about environmental changes, and with them, new potential for FA. The future will bring new applications for robots: machining robots, assembly robots, maintenance robots for reactor furnaces, robtots that are movable under water. Before FA can be introduced, at least the following factors must be taken into account : — — — — — — — — — —

capital demand, special needs of the user, policy regulations, the market situation, standards, type of production organization, type of manufacturing, engineering base, qualification requirements, labour conditions.

Hindrances and stimuli to the diffusion of FA can be identified (1) at the micro-level, or market stage, where there is resistance to change by employers and employees and in the organization of production, and (2) at the macro-level, where international competitiveness and governmental policy toward science and technology play a role. Flexible and universal automation has been developed for many industries. The leading industry in the use of robots is the automotive industry, followed by electrical machinery, molded plastics, iron and steel, and precision machines. Current applications for robots include: — — — — — — — — — — — — — 14»

die casting, spot welding, investment casting, forging, presswork, spray painting, molding of plastics, foundry, machine tool loading, heat treatment, palletization, brick manufacture, glass manufacture. 211

In the future robots will be able to take over activities suitable to special purpose automation. Robots have the avantages of shortened reaction time (i.e., shortened cycle time for introduction of new models), lower debugging costs, and resistance to obsolescence.

13.3. A Forecast of Robot Diffusion Man has long dreamed of creating a being similar to himself (but not too similar!). This dream has been the source of hope and fear from the threatening Golem to Homunculus accompanying Faust on his way to Helena's cheerful world. The age of machines produced a new version of the old Homunculus story. In Karel Capek's play Rossum's Universal Robots, (1920), the rebellion of the robots destroys the human world. Capek gives us exact figures: there are 347,000 robots in stock and the price of one robot is 150 dollars. One robot could replace 2.5 workers at an operating cost of 0.75 cent per hour (at a time when one pound of bread cost 2 cents). At present prices, one robot would cost 4,500 dollars or 22.50 dollars per robot hour. Capek's figures are no longer purely science fiction. The age of programmable industrial robots began in 1962 when the first commercial robot was installed. There *are now about 17,500 robots in the world, costing nearly 80,000 dollars a piece; maintenance costs amount to about $ 1.30 per robot hour. While the robot business is still very unpredictable, interest in forecasts is great. Governments are interested because their technological policies try to ensure international competitiveness. Corporations are interested because they are always looking for ways to make business more profitable. And unions are concerned about job security, safe working conditions, and job content. Tables 78 and 79 show some forecasts of the diffusion of robots. There are several reasons for the uncertainty in forecasting robot application: 1. There is uncertainty about future applications for the present types of robots. 2. The range of applications may change due to improvements in robots. Table 78

Predicted increase in the n u m b e r of r o b o t s in the U S

Forecaster

Annual growth 1980-1990

Annual growth 1980-1985

Joseph Engelberger Laura Conigliaro Arthur D. Little Co. International Resources Development, Inc.

30% 50% (max.)

—

—

50%

11-14%

—

212

—

Table 79 World diffusion of robots Robots in use (in units) Country

Period

Percent

Western Europe Japan

1980-1990 1980-1985

23.6% 71.9%

Robot Sales World World Japan Japan

1980-1985 1979-1990 1980-1985 1979-1990

Million $ 44.3% Million $23.3% Million $ 29.9% Bil. Yen 22.8%

3. Future prices of robots are uncertain, as they depend not only on the development of production, but on other factors as well. 4. The future growth of wages, a main factor in the decision to apply robots, is difficult to anticipate. Reliable statistics on robots are not available. One has to collect figures from various sources and compare them with the definition used by each source. Simons (1980) understands the definition of robots to be "reprogrammable multi-axis mechanical manipulators". The Robot Institute of America defines an industrial robot as "a reprogrammable, multifunctional manipulator, designed to move materials, parts, tools or specialized devices through variable programmed motions for the performance of a variety of tasks" (ENGELBERGER 1980, p. 8). In 1979, Japan had 70,000 industrial robots, including the simpler "pick-andplace" devices. But only 7,000 of these are freely programmable. Table 80 shows the number of robots and other simpler manipulators in 1977. Table 80 World distribution of robots and simpler manipulators (1977) Number

I. "Pick and place" devices II. Robots — Category 1 (3 degrees of freedom and a maximum of 6 programmable positions per degree of freedom) III. Robots — Category 2 (3 or more degrees of freedom, freely programmable) IV. Robots — Category 3 (as category 2 but with optical sensors and optimization) Total robots Total including simpler "pick and place" devices

Percent of total

8,000

40

9,000

45

2,600

13

400

2

12,000 20,000

60 100

Source: PÄSSLER et al. 1977.

213

An international comparison and forecast of robot diffusion is possible only if robot application is measured in relative terms. This can be done using the following relationship: ^

number of jobs replaced by IR

^

number of jobs replaced or replaceable by IR ' (3)

' p• k • E c-R + s•c where R — number of programmable robots, E — number of employees in manufacturing, mining, and construction, p — share of production workers in all employees, k — share of work places that in principle can be replaced by robots, 5 — shift factor, c — number of jobs replaced or replaceable by one robot. And one obtains 1

F

(4)

s c2

R

The diffusion rate is sc2R

F 1 -F

pk

-E

(5)

According to (4) the real diffusion rates in 9 countries and the world total for 1968—1980 were computed (see Figure 83). Assuming a logistic model, one can expect In

F

+

(6)

These functions were computed and are shown in Figure 83 as straight lines. The model can answer the following questions: —. What will be the diffusion rate in a given country at a given year? — What will be the number of robots in a given country in a given year using the equation

1- F 214

s-c2

(7)

F t-r

A

10°

0 '

GOR USSR Japan

O • + • •

Sweden FRO France World Italy

— —

A US

••—

— to-

S

o

S

*

o /y /y

,

-

/

/

/ / ¿/ S x^of?.

X m

ro'

/

/

y

*

*

to-

7 rn

_

v /

trorking

,7.V

Working places replaced to robots places replaced and replacable by robots

V

JZ_

1970

mo

1975

1985

1990

Figure 83 Diffusion of programmable industrial robots in nine countries Source: BELJANIN (1975), COOPER (1980), YONEMOTO (1978), ENZELBERGER (1980), World Casts (1980), PÂSSLER et al. (1977), Yearbook of Labour Statistics (1980).

Year

SIMONS (1980),

— What time lag or time lead (6t) exists between two countries i and j in the diffusion of robots using the equation ai

+

St =

b

r

t

=

a

+

j

b p

V*'~

+

S t ) ,

•

(8) (9)

j

b

Table 81 shows the time-lags or leads of countries in comparison with the US for 1975, 1980, and 1985. Let us look at the results of our investigation. Although the data are scattered, we can compare the different countries and get an interesting overview. In terms of the relative diffusion rate, Sweden shows itself to be the most advanced country. But Sweden also shows a lower growth rate for the past five years. When measured by the diffusion rates, Japan and the US have nearly the same growth rates. 215

Table 81 National time-lags or time-leads (—) in the diffusion of programmable industrial robots (PIR) in comparison with the US Country

1975

1980

0

0

0

-4 -5 2 1 3 2

-5 -2 5 5 8 4.

-2 0 8 6 12 4

USSR GDR

6 7

5 5

0 0

World total

3

5

6

US Japan Sweden France Italy UK FRG

1985 (forecast)

Japan is becoming the world leader in robot application, not only in terms of number of robots but ajso in relative terms, i.e., in relation to the national work force. Japan's secret is R.U.R.: Robots Unbagging Robots, again a realization of one idea of Karel Capek. In the firm FANUC (Fujitsu Automatic Numerical Control) three engineers and 70 robots produce 350 robots a month. The FANUC Corporation is typical for an industry of the future: an industry producing means for Flexible Universal Automation (FUA)! As can be seen from the data, the diffusion rates slowed between 1975 and 1980. It is not yet clear why this has occurred in the advanced countries. One explanation is the much slower growth in real wages. The USSR and the GDR, on the other hand, have a very fast growth. They tend to catch up with the advanced countries. Taking the past growth rate for all countries in the next five years, the USSR will reach the level of the US in 1985 (see Table 81). The extrapolation of the diffusion rate could be the first and simplest approach. It could be improved by including more important causal factors for the diffusion of robots. One economic factor for the diffusion rates of robots are wages. We compared hourly wages with the diffusion rates of robots in eight countries and obtained the following regression:. In—^—- = a + bw,

(10)

In —

(11)

1— F

-

1— F

1.42966 + 0.02495w.

where w hourly wages relative to the FRG level in DM (German marks) in percent (FRG = 100). This applies to all of the eight countries except Japan (not included in the regression) and Sweden (see Figure 84). But maybe in the future Japan and Sweden will move nearer to the general tendency. 216

The same dependency can be analyzed by using a time series. In Figure 85 the diffusion of robots in the US is shown over the index of hourly real wages of production workers in manufacturing. (Data on real wages are from the Statistical Abstract of the US 1974—1979). Over a time period, this dependency becomes more stable because of the lower growth in both directions. We can now further develop our formula for robot development. The logarithm of (4) is: In R

In

=

1

+ In

p • k • E

(12)

sc1

Using (6), we obtain In R

= a

+ In

p •k •e

(13)

p • k • E 0a + bw . R = e' 2 s• c Diffusion of robots F TF 300 Japan

(14) o

Smden //?—-7.429658379+00219199771W R-67. S9percent N-S (trithout Japan)

200

Figure 84 Diffusion of robots as a function of hourly wages (1978) iO

50

Diffusion rate F IO'*

100 150* Hourly mages in manufacturing, re!atire

1-F

* -37-41S0H57*0.387H736Ì3#

Figure 85 Diffusion of robots as a function of hourly wages (US) Source: US Statistical Abstract (1980). 115 inda»

217

In this formula, the diffusion of robots depends on five more or less statistically identifiable factors: — — — — —

wages, number of production workers, range of application, number of shifts, substitution rate.

To give ^n example, according to formula (7) the number of robots in the US in 1985 could be: R = 1300 10

0.68 0.15-29 • 106

,

4

R = 52967. This would mean a growth rate of 57 percent, which is certainly an overestimation. Assuming that the trends of the last five years continue we get: R = 550 10 — 4

0.68 - 0.15 -29 • 106 » 1 5 . 4 8 4

R = 22409. This would mean a growth rate of 36.3 percent, which is more reasonable. A second forecast is possible on the basis of formula (14). If one assumes for 1985 w = 110, and slightly other values for c and k, then one gets: „ 0.68 • 0.20 • 29 • 106 R = 183.49 • 10" 4 r-r—: > 1.5 • 4 R = 12061. This would mean a growth rate of 22.9 percent. While this seems rather high from the standpoint of real wages and the trends of the last five years, strong competition from the Japanese and the development of other factors might change the situation considerably. Perhaps our first attempt to measure robot diffusion could be the core of a learning system for analysis and forecasting.

13.4. Robots and National Innovation Policy. The Case of the GDR In the GDR economic strategy for the 1980s, the industrial robot is regarded as a basic innovation, which together with the biotechnologies, other basic innovations such as microelectronics, and sources of energy such as nuclear power and coal liquefaction, will be decisive in building up a new level of productivity during the 1980s and 1990s. 218

An essential feature of basic innovations is that they reward those who create and implement them with increased productivity while punishing those who were unable to recognize their potential for efficiency, or who were unable to use them, by undermining their existing productivity level. National economic performance will very much depend on the ability of basic innovations to contribute to this new productivity level.

The Role of Robots in GDR Economic Strategy

In the GDR economic strategy for the 1980s, industrial robots are playing an important role in efforts to attain high productivity growth and reduce hard manual and unskilled work. The production and installation of industrial robots is an integral part of the program to improve labour conditions. For this program we must devise goals and rules for the installation of robots. Critical to the planning and management of robots as an innovation is the relationship between the implementation of robots and the development of socioeconomic efficiency. We must ask the same very critical questions about robots as we would ask about any other basic innovation: 1. What is their potential for increasing efficiency? 2. What is required economically and socially in order to use this potential for efficiency? 3. What are the technological alternatives to robots? Clearly, robots are now at the beginning of the rapid growth phase. If we look at the predicted growth rate of robot installations from now until 1990 as they were quoted in Chapter 4, it would appear that we are approaching a "robot revolution". However, there have been many similar predictions during the last two decades, and yet the expected high diffusion rates has not occurred. Obviously conditions have not been conductive to securing a dynamic efficiency above that of other forms of automation and mechanization. If we to successfully forecast the future development of robots, it will be necessary to investigate the changes needed for the application of industrial robots and their influence on the development of the efficiency of robots. During the next years, the installation of industrial robots will play an important role in the economic strategy of the GDR. It is hoped that there three main goals will be achieved by this rapid increase in robot application: 1. A higher level of automation in small and medium-sized production systems. 2. The creation of conditions prerequisite to the implementation of other basic innovations. 3. A significant reduction of the share of heavy manual and unskilled labour. 219

Increasing Automation Levels in Small and Medium-Sized Production Systems Let us look at first of these three goals. 84.8 percent of production in the GDR mechanical engineering and vehicle industries and 75.2 percent of production in the electrical and computer industries is currently being carried out on a small or medium scale basis. In the last decade, through the introduction of numericalcontroled machinery, it has become possible to automate much of the manufacturing process. But for the most part, handling and transportation of working components and tools have not yet been automated. The industrial robot holds great potential for integrating the main handling and auxiliary processes. In other words, the robot is not an alternative to the existing types of automation. It represents an important step toward overcoming the bottlenecks hindering improved efficiency in automation. The industrial robot is an important result in a long chain in the development of manipulatory equipment incorporating the achievements of microelectronics and data processing. It is a key technology in current attempts to improve — the efficiency of the entire manufacturing system, — product quality, — technological discipline and continuity in production. In some enterprises in the GDR machine tool industry, the installation of robots has made it possible to release 50 to 70 percent of the working forces. Labour productivity has increased by 200 to 400 percent and production space has been reduced by 50 percent in comparison with customary workshop production. Industrial robots are not only important as an innovation; they are also a very important factor in increasing the innovativeness of many branches, especially mechanical engineering production. Their high flexibility allows a reduction in the time needed to modify production systems to produce new products and the efficient production of these products on a small and medium scale. Analyses of GDR industry have shown that firms producing 1,000 to 100,000 units per year (accounting for more than 40 percent of all GDR enterprises) were unable to apply the traditional form of automation in an efficient manner. Here the industrial robot has proved very important for promoting dynamic efficiency. Creating the Preconditions for Other Basic Innovations With regard to the second main goal named above, it should be noted that the high employment-release effect helps to establish important preconditions for the implementation of basic innovations that have a high employment effect. This is especially true in the fields of energy, environment, and biotechnology. Normally, basic innovations have a high employment effect and a low efficiency effect in the first two phases of the relative efficiency cycle. The industrial robot is one of the few basic innovations that continue to show relatively high employment-release and productivity effects in the second phase. This means that they are suitable for creating the preconditions for innovations 220

with a high employment effect in the first phase of the relative efficiency cycle. This attribute is very important for the industrial strategy of the GDR. One of the strategic goals of the five year plan for 1981—1985 is to release the working time of 300,000 workers. A quarter of this is to be achieved through the installation of industrial robots. Experience has shown that it is possible to release 1.4 to 3 workers per industrial robot, depending on the type of robot. These figures have been confirmed through studies in other countries (see Table 82). It has been estimated that in the GDR 40 percent of manual production work and 70 percent of assembly work could be reduced significantly through the use of industrial robots. Table 82

J o b substitution f a c t o r of industrial r o b o t s

Industrial robots

1 shift

2—3 shifts

B S

1.5 1.4

4.0 3.0

Component manipulators

s

B

2.1 1.6

6.2 3.3

Tool manipulators

B S

0.9 0.43

1.7 0.8

B = Battelle Frankfurt. S = Sociological Institute Goettingen. S o u r c e : LEHMANN 1980.

Reducing the Need for Heavy Manual and Unskilled Labour Finally, let us look at the third goal. During the 1970s, the share of automated industrial equipment in all industrial equipment increased significantly. Such branches as the chemical industry, the energy and fuel industries, the electrical industry, light industry, and the textile industry now have a share of automated equipment above 50 percent. The current trend in automation is toward a polarization of employment requirements. The number of jobs for skilled workers is increasing and at the same time many unskilled and hard manual labourers are being replaced. Figure 86 shows the results of an empirical study in the GDR that included 50 percent of all industrial workers. Here we see that as automation takes over many of the more highly skilled jobs, many of the workers' qualifications are no longer needed. The industrial robot is an important tool for eliminating jobs with low skill requirements involving hard manual labour. In Figure 87, which shows a comparison of the technological costs of a welding robot in the GDR and the cost of manual welding, we can see that one important result of the application of robots is a reduction of labour costs (due to the high replacement effect). But fixed costs must also be taken into account. These are much higher for robot installation than for manual handling. Depending on the type of robot, they may be between 4 and 10 times the cost of manual working places. To compensate, normative efficiency achieved through the use of the robot 221

Exist

Manual jobs

m

Partly mechanized jobs

Fully mechanized jobs

Skilled workers

Partly automated Jobs

Semiskilled workers

fully automated jobs Unskilled markers

Figure 86 Existing and needed job qualification structures for production workers at various levels of technological development (in percent)

must be much higher than where the normal investment is required (SCHILLING 1980). In the GDR, for the normal capital investment, the lowest efficiency normative is 6 percent; this means a return of the capital within 12 years. For robot installation the lowest efficiency normative is 35 percent; this means a capital return within 3 years. To secure this very high efficiency normative, it is necessary to use the robots in 2 or 3 shifts. A third important part of the robot's costs are variable and fixed peripheral costs. The creation of the appropriate working environment for the robot incurs Costs per unit H/n t.O

I

I Mechanical

M***

n

Depreciation Maintenance Wages

222

Figure 87 Comparison of the costs units for the robot welding and C 0 2 mechanical IHnm. welding Wire-gas

Energy

a great deal of additional expense, ranging from 50 to 100 percent of the fixed costs of installing the robot. The benefits include quality improvement, reduced costs, increased continuity in production, and the labour-replacing effect. The average cost for replacing one worker in the GDR economy is currently 100,000 marks. If we consider that the cost of one welding robot is approximately 300,000 marks, and that it can replace 2 to 3 workers per shift, we see that from the point-of-view of releasing labour forces, the robot is a very good investment indeed. The New Generation of Robots

One can describe an innovation as the fusion of a relevant economic demand with a technological feasibility. From this standpoint, it is not difficult to foresee that the current generation of robots will soon approach its outer limits. Limitations upon the growth of robots can only be overcome with a new generation of robots. This new generation is urgently needed for automating assembly work. The present generation of robots must follow a fixed program; it will be incapable of learning from its specific working situation. The new generation of robots, on the other hand, is able to adapt to changing situations, as it will be equipped with tactile, visual, and/or acoustic senses. In the GDR, this will be especially important for the mechanical engineering and vehicle industries, where more than 30 percent of the work is assembly work, and for the electrical and electronics industries, where more than 40 percent is assembly work. As only 1 —2 percent of assembly work has been automated, this is likely to be an important area for the application of the second generation of robots. The future of robots and the role they can play will very much depend on their ability to adopt improvement innovations, which in turn can help overcome the present barriers to broader application of robots. The demand for improved capabilities in industrial robots is very high. It is not yet clear whether the next generation of robots will be able to meet these requirements.

Appendix

A: Historical data illustrating the technological means of meeting the lighting demand (for white light)

Year

7000—8000 BC 2700 BC 1000 BC

500—400 BC 230 BC

200 BC 100 BC

ca. 300 1650

1783

15

Haustein/Maier

Event

Hearth fire Terracotta oil lamps in Mesopotamia Egyptian and Persian • copper and bronze lamps Wick of vegetable fibre burning in a saucertype vessel holding olive or nut oil Oil lamps had come into general use Lamps with automatic refill — Philon of Byzantium Candles The Romans developed the first true lantern of horn, cylindrical in form with a perforated top Street lighting (Asia) Stearin candle Otto von Guericke discovered that light was produced by electricity or by electrical excitation. He also invented the vacuum pump Kerosene lamp with flat wick — Leger Paris.

Efficacy lm/W

Lifetime hours

0.13

225

Year

1792 1802

1836

1840

1845

1845 1848—1860 1850

1854 1859

1859

226

Event

Kerosene lamp with hollow wick and glass cylinder — Argand, Paris Gas lighting — Murdoch Davy made a platinum filament glow by galvanic current "Courier beige" first mentioned the possibility of using a vacuum for electric lighting Grove. First experiments with platinum incandescent lamp Starr — English patent for a "continuous metallic or carbon conductor intensely heated by the passage of electricity for the purpose of illumination" Thomas Wright, London. First patent for arc lamp Swan — Several experiments in England H. Geissler, Germany, discovered that an electric current passing through a rarefied gas, causes the gas to glow . Goebel — bulb with bamboo filament Discovery of petroleum. Trude crude oil lamp was superseded A. E. Becquerel — First electric lamp

Efficacy lm/W

1.00

0.80

Lifetime hours

Year

1866

1872 1876 1877 1877 1879 1880

1881

1882

1883 1884 1885

1885

is-

Event

containing fluorescent materials very low efficiency and short life Werner von Siemens developed the dynamoelectrical machine Hodyguine, Graphite lamp Jablochkov candle (arc lamp) Beginning of Edison's experiments Edison began his work on electric lamps Edison's first lamp (carbon filament) Steamer "Columbia" was equiped with 115 Edison lamps with Edison sockets. Lamp price 1 dollar Edison's improved lamp cost 70 0 Johann Kremenezky, Vienna — Bulb with carbon filament Edison lost a patent infringement action against Swan Edison and Swan founded a company Edison lamp cost 22£ Auer von Welsbach invented the gas mantle, a strong competitor to electric lighting Sprengel mercury pump reduced exhaust time from 5 hours to 30 minutes

Efficacy lm/W

Lifetime hours

1.60

300

1.68

600

3.4

400

227

Year

1888 1891 1892 1892 1893

1896

1901

1902

1904 1904 1904

1904

1904

228

Event

Asphalt-treated filament Tungsram Austria founded Incadescent gas light Auer von Welsbach Invention of mercuryvapour lamp by L. Arons Fast growth of gas lighting with Auer gas mantle lamp price 1 2 - 1 8 t Phosphorus exhaust method reduced exhaust time to less than a minute Mercury arc lamp, Peter Cooper Hewitt 19 lm/W, remained a popular light source for factories for - 40 years Osmium lamp — Auer von Welsbach (Osmium too expensive and rare) Metallized carbon Non-ductile tungsten Moore tube first used commercially. Commercially successful high-voltage gaseous-discharge lamp with nitrogen yellow light with carbon-dioxide white light Steinmetz, US arc lamp, remained a popular street lighting source in US until 1930 Just, Hanamann, Austria Tungsten filament lamp

Efficacy lm/W 3.0

Lifetime hours 600

1.50

3.5

4.40 4.0 7.85

5.0 2.00

600 800

Year

Event

1905

Production of lamps in flexible jobshop configuration, involving more than 11 separate operations with mainly manual labour Tantalum lamp, W. v. Siemens (on the market 1906-1913) Tungsten filament lamp Edison patent on fluorescent lamp W. D. Coolidge, US developed ductile tungsten by drawing it through a series of dies Beginning of reduction in gas lighting Ductile tungsten Tungsten drawn filament lamp Langmuir developed the use of inert gases inside the incandescent lamp (nitrogen and later argon). First gas-filled coiled-up filament lamp 100 Watt filament lamp Lamp price 37 p Living costs 51 % (1940 = 100) 100 Watt filament lamp Price 22 p Living costs 72 % (1940 = 100) High-intensity sodiumvapour lamp

1905 1906 1907 1908

1909 1910 1911 1913

1915 1920

1930

1931

Efficacy lm/W

3.70 5.50

Lifetime hours

800 800

6.3

1000

10.0

1000

10.30 10.0

1000

11.0

1100

229

Year

1932 1935 1935

1935-1938 1938

1938 1938 1939

1939 1940

1949 1950

1954 1959 230

Event

not satisfactory for commercial use Mercury lamp Wound coil filament lamp Phosphorus with good response to ultraviolet radiation had been developed Development work by General Electric and Westinghouse April 1st. — first commercially successful fluorescent lamps were introduced in the US 20,000 fluorescent lamps in the US Krypton lamp Productivity: 1250 bulbs per hour (15 man hours) highly mechanized process Fluorescent lamp — 80 Watt 100 Watt filament lamp Price 10 p Living costs 100% 80 Watt fluorescent tube Price £ 1.97 Fluorescent lamp — 80 Watt 80 Watt fluorescent tube Price 95 p Living costs 135 % (1940 = 100) Mercury lamp with quartz First halogen lamp — tungsten

Efficacy lm/W

Lifetime hours

23.0 11.6

2000

27.0

2000

43.0 38.0

4000 3000

1160

41.0 30

2000

Year

Event

1959

Fluorescent lamp — 80 Watt 80 Watt fluorescent tube Price 76 p Living costs 200 % (1940 = 100) 261.5 million fluorescent lamps in the US Productivity: 3750 bulbs per hour (5 man-hours) Fluorescent lamp — 80 Watt 85 Watt fluorescent tube Price 70 p Living costs 305 % (1940 = 100) Reached level Halogen bulb Mercury high pressure lamp Sodium high pressure lamp Fluorescent lamp Halogen metal vapour lamp Prospective empirical limits : Bulb Fluorescent lamp High pressure lamp

1960

1968 1969

1969 1970

1975

Efficacy lm/W

Lifetime hours

57 54.0

5000 5000

61 74.0

7500 7500

32 50... 60 90 ... 130 70 ... 100 70... 110

40 120 150

B: Output of lamps in the US 1898—1970 Year

Large incandescent Mil

Fluorescent, hot cathode Mil

Coefficient of lmh**

Share of fluorescent light in lmh %

1

2

3

4

1970 1969 1968 1967 1966

1582 1476 1467 1391 1394

267 261 258 224 256

39.9 38.7 37.6 36.4 35.2

87.1 87.3 86.9 85.4 86.6

1965 1964 1963 1962 1961

1320 1264 1254 1238 1155

225 198 179 164 142

34.0 32.9 31.7 30.5 29.3

85.3 83.7 81.9 80.2 78.3

1960 1959 1958 1957 1956

1142 1212 1052 1112 1132

140 131 113 119 126

28.2 27.0 25.8 24.6 23.4

77.6 74.5 73.5 72.5 72.3

1955 1954 1953 1952 1951

1057 960 1028 864 1070

104 93 92 65 111

28.2 . 21.1 19.9 18.7 17.6

68.7 67.1 64.0 58.5 64.6

1950 1949

1200 975

98 71

16.4 15.2

57.3 52.5

232

Year

Large incandescent Mil

1948 1947 1946 1945

1030 999 774 787

1939 1937 1935 1933 1931 1929 1927 1925 1923 1921 1919 1914 1909 1905 1899 1891

Fluorescent, hot cathode Mil

94 89 52 37

Coefficient of lmh**

Share of fluorescent light in lmh%

14.0 12.9 11.7 10.5

56.1 53.5 44.0 33.0

517 501 388 306 320 352 335 267 233 155 225* 89* 67* 113* 25*' 1.5'

* Not strictly comparable with later years because of changes in classification. ** Estimated relationship between lmh of fluorescent lamps and lmh of incandescent lamps. *** BRIGHT 1949, p . 4.

Source: Historical Statistics of the US, p. 696—697 (column 1 & 2).

C : The production of bulbs and discharge lamps in the GDR since 1950.

Year

1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 234

t

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Production of multi-purpose lamps

Production of discharge lamps

Total production of light sources

mil pieces

Glm

mil M

Glm

Glm

(1)

(2)

(3)

(4)

(5)

27 35 44 18 31 44 55 62 65 68 60 58 65 70 75 83 89 92 100 111 111 100 98 93 82 73 76

18.9 24.5 30.5 12.9 21.7 30.5 38.6 43.3 45.8 47.3 42.0 40.3 45.6 49.1 52.6 58.1 62.3 64.4 70.0 77.7 77.7 77.0 68.6 65.1 57.4 51.1 53.2

2.6 4.5 3.7 2.8 4.8 7.5 10.5 13.7 17.8 20.4 22.9 23.4 32.3 41.2 44.9 55.0 69.0 74.2 84.9 83.5 114.1 137.7 155.6 158.9 177.1 183.1 189.3

1.53 20.43 2.65 27.15 2.18 32.68 1.65 14.55 2.83 24.53 4.41 . 34.91 6.18 44.78 8.06 51.36 10.48 56.28 12.01 59.31 13.48 55.48 13.77 54.07 19.01 64.61 24.25 73.35 26.43 79.03 32.37 90.47 40.61 102.91 43.68 108.08 49.97 119.97 49.15 126.85 67.16 144.86 81.05 151.05 91.59 160.19 93.53 158.63 104.24 161.64 107.78 158.88 111.42 164.62

Share of discharge lamps

(6) 7.5 9.8 6.7 11.3 11.5 12.6 13.8 15.7 18.6 20.2 24.3 25.5 29.4 33.1 33.4 35.8 39.5 40.4 41.7 38.7 46.4 53.7 57.4 59.0 64.5 67.8 67.7

References

ABERNATHY, W. J. (1978) The Productivity Dilemma. Roadblock to Innovation in the Automobile Industry. Baltimore and London: Johns Hopkin University Press. ABERNATHY, W. J., and J. Utterback (1978) Patterns of Industrial Innovation. Technology R e v i e w 80 (7). 4 0 - 4 7 .

ARISTOTLE (1948) Topik (Part V). (in German) Leipzig: Felix Meiner Verlag. AUSTIN, J. H. (1978) Chase, Chance of Creativity, the Lucky Art of Novelty. New York: Columbia University Press. BELJANIN, P. N. (1975) Industrial Robots. Moscow: Engineering Publishing House. BLATTNER, N. (1977) Industrial Policy: A Skeptical View. Paper presented at the Fourth European Conference on Industrial Structure in Berlin. BONO, E. de (1971) Laterales Denken (Lateral Thinking). Hamburg: Rowohlt. BOWLES, S. (1969) Planning Educational Systems for Economic Growth. Cambridge, Mass.: Harvard University Press. BRAUN, E. (1979) Homo Faber, Homo Ludens, and the Future of Work. World Future Studies Federation. P. 353. In: Science and Technology and the Future. Proceedings and Joint Report of the World Future Studies Conference and DSE, edited by H. Buchholz and W. Gunelin. Part 1. Preconference held in Berlin (West), May 4—10. Munich: V. B. Saur. BRIGHT, A. J. (1949) The Electric Lamp Industry. Technological Change and Economic Development from 1800 to 1947. New York: Macmillan. BRODBECK, B. (1976) Wirtschaftlichkeitsuntersuchungen bei der Automatisierung und Handhabung, Montage- und Handhabungstechnik (An Economic Assessment of Automatic Handling). Nr. 3. Mainz: Krausskopf. BUSINESS WEEK (September 3, 1979)' 50th Anniversary Issue. New Growth Industries: How U. S. Business Will Change in the Next 50 Years. BUZACOTT, J. A. and Shanthinkumar, J. G. (1980) Models for Understanding Flexible Manufacturing Systems. Reprinted from AIIE Transactions. Vol. 12. 4/1980. Norcross, Georgia: American Institute of Industrial Engineering. CAPEK, K. (1968) R. U. R. (Rossum's Universal Robots). Wien 1968: Universal Edition A. G. Prag: Reprint from 1920. CARNEX, R. B. (1978) Productivity and Technology in the Electric Lamp Industry, Mon. Labor Review 101 (8): 15. CAUDLE, P. (1978) Chemicals and Energy. The Next 25 Years. Futures 10 : 361—379. CHARLISH, G. (1981) How Siemens Makes Consumer Durables. In: Financial Times, September 29, 1981.

COOPER, J. (1980) Industrial Robots in the USSR. CREES Discussion Papers. Birmingham, U K : University of Birmingham. CSIKOS-NAGY, B. (1980) Industrial Policies and Strategies, 3.: Hungary. CP-80-39. Laxenburg, Austria: International Institute for Applied Systems Analysis. Current and Prospective Issues in Science and Technology Policies. Developments in Science and Technology Policies. Review of National Policies in the Field of Technological Innovation. 1980. Paris: UN Economic Commission for Europe.

235

DÖRFER, G., Dostal, W., Köstner, K., Lahner, M., and Ulrich, E. (1977) Technik und Arbeitsmarkt: Auswirkungen technischer Änderungen auf Arbeitskräfte (Technology and the Labour Market: Consequences of Technological Changes on the Labour Market). Quint AB 6/77. Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit. DOSTAL, W., Lahner, M., and Ulrich, E. (1977) Datensammlung zum Projekt Auswirkungen technischer Änderungen (Data File of the Project "Consequences of Technological Changes"). Beiträge 17. Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit. DUBOIS, R. A. (1906) Erfindung und Erfinder (Inventions and Inventors). Berlin: Springer Verlag. EHENBAAS, W. (1972) Light Sources. Philips Technical Library. Macmillan. EISENDRAHT, E. (1964) Brutto- und Nettoprinzip in der westlichen und östlichen Wirtschaftsforschung (Gross and Net principle in the Western and Eastern Economic Research). In: Vierteljahreshefte für Wirtschaftsforschung. Berlin (West): Duncker und Humblot. EKONOMIKA (1975) Organisacija promyslenogo proizvodstva 6/75. Energy Systems Program Group at the International Institute for Applied Systems Analysis, W. Häfele, Program Leader. 1981: Energy in a Finite World. A Global Systems Analysis. Cambridge, Massachusetts: Ballinger. ENZELBERGER, J. F. (1980) Robotics in Practice. Management and Applications of Industrial Robots. London: Page in Association with Avebury Publ. Co. Factors Related to the Implementation and Diffusion of New Technologies (1979) A Report to the NSF. No. 80978. June. Washington, D. C : Arthur D. Little, Inc. FAJNSILBER, F. (1980) Industrialization, Capital Goods, and Labour in Advanced Economies. Paper presented at the Sixth World Congress of Economists in Mexico City. GOLD, B., ed. (1975) Technological Change. Economics, Management and Environment. Oxford: Pergamon Press. GOLDBERG, W. (1980) Stagnation and Innovation. Relevant Policy Questions. DP-80-12. Berlin (West): International Institute of Management. GRAHAM, A. K., and Senge, P. M. (1980) A long-wave hypothesis of innovation. Technological Forecasting and Social Change 17, 283—311. GREGORY, C. E. (1967) The Management of Intelligence. Scientific Problem Solving and Creativity. New York: Mc Graw-Hill. GROSS, A. T. (1933) Die Glühlampe als Wegbereiterin der Elektrizitätswirtschaft (The Bulb as the Pioneer of Electrification). Technik-Geschichte, Beiträge zur Geschichte der Technik und Industrie. 22. Berlin. HAMILTON, I., ed. (1978) Industrial Change. International Experience and Public Policy. New York and London: Longman Press. HATVANY, J. (1980) Possible Consequences of the Intensive Computerization of Industrial Production and Management. CP-80-25. Laxenburg, Austria: International Institute for Applied Systems Analysis. HAUSTEIN, H.-D. (1964) Die Messung und ökonomische Analyse des technischen Niveaus unter besonderer Berücksichtigung der Anforderungen der Perspektivplanung (The Measurement and Economic Analysis of the Technical Level under Special Consideration of the Requirements of Perspective Planning). Habilitation. Hochschule für Ökonomie. Berlin (GDR). HAUSTEIN, H.-D. (1974) Die Proportionalität der technischen Basis (The Proportionality of the Technical Basis). Berlin (GDR): Akademie Verlag. HAUSTEIN, H.-D. (1975) Die Proportionalität der technischen Basis im Sozialismus (The Proportionality of the Technical Basis in Socialism). Berlin (GDR): Akademie Verlag. HAUSTEIN, H.-D. (1976) Messung der volkswirtschaftlichen Intensivierung (Measuring the Intensification of the National Economy). Berlin (GDR): Akademie Verlag. HAUSTEIN, H.-D. (1979) Innovations in the Lighting Industry. WP-80-12. Laxenburg. Austria: International Institute for Applied Systems Analysis.

236

Maier, H . , Uhlmann, L. (1981) Innovation and Efficiency. RR-81-7. Laxenburg, Austria: International Institute for Applied Systems Analysis. HAUSTEIN, H . - D . , and Hartmann, W. D. (1979) Leitung der industriellen Forschung und Entwicklung (Management of Industrial Research and Development). Berlin (GDR): Akademie Verlag. HEINZE, J. (1979) Strukturwandel in der Bundesrepublik Deutschland. Eine Auseinandersetzung mit der Drei-Sektoren-Hypothese (Structural Change in the Federal Republic of Germany: A Debate on the 3-Sector Hypothesis). Munich: IFO Schnelldienst. HENNINGS, H . von (1979) Quantitative and qualitative Veränderungen der Arbeitsplätze der Angestellten (Quantitative and Qualitative Changes in the Working Places of Employees). Beiträge 32. Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit. HENRIOT, I. (1955) Geschichte des Schiffbaus (History of Shipbuilding). Leipzig—Jena: Urania Verlag. HINTERHUBER, H . , ed. (1978) Innovationspolitik in Österreich (Innovation Policy in Austria). Vienna: Federal Ministry of Science and Research. HIRSCHHORN, J . ( 1 9 8 0 ) Federal Industrial Policy. Washington: Office of Technology Assessment. Historical Statistics of the US Colonial Times to 1870. Part 2. 1975. Washington. D.C. HOFFMAN, W. G. (1965) Das Wachstum der Deutschen Wirtschaft seit der Mitte des 19. Jahrhunderts (Growth of the German Economy since the Middle of the Nineteenth Century). Berlin and Heidelberg: Springer Verlag. HONKO, J. (1980) Developing a Finnish Industrial Strategy. In: Industrial Policies and Strategies 1. CP-80-4. Laxenburg. Austria: International Institute for Applied Systems Analysis. Interfutures (1979) Facing the Future: Mastering the Probable and Managing the Unpredictable. Paris: Organization for Economic Cooperation and Development. KLEINKNECHT, A. (1979) Basisinnovationen und Wachstumsschübe. Das Beispiel der westdeutschen Industrie (Basic Innovations and Growth Spurts: the Example of West German Industry). Konjunkturpolitik 25: 5—6. Duncker und Humblot. KNESCHAUREK, F. (1973) Arbeitskräftepotential und Arbeitskräftebedarf in der Schweiz (Labour Potential and Labour Demand in Switzerland). St. Gallen. Switzerland: Arbeitsgruppe Perspektivstudien. KNIGHT, K . E. (1967) A Descriptive Model of the Intra-Firm Innovation Process. Journal of Business. 40. October: 478 —496. KOPS, L. ( 1 9 8 1 ) Innovation in Management. Computer Integrated Manufacturing Systems. In the Proceedings of the Workshop on Innovation Management. June 1981. Forthcoming. Laxenburg. Austria: International Institute for Applied Systems Analysis. KRAIS, S. ( 1 9 7 9 ) Produktion und Qualifikation (Production and Qualification). MPI-Berlin. Berlin (West): Max-Planck Institut für Bildungsforschung. KRENEZKY, J. (1917). Die Geschichte der elektrischen Glühlampe (The History of the Electrical Bulb). Wien: Selbstverlag. KRENGEL, R., Baumgart, E., Boness, A., Pischner, R., and Dröge, K. (1973, 1975, 1978) Produktionsvolumen und -potential. Produktionsfaktoren der Industrie im Gebiet der BRD (Production Volume and -potential. Faktors of Production of Industry in the FRG). Statistische Kennziffern. Berlin (West): Deutsches Institut für Wirtschaftsforschung. KUCZYNSKI, J. (1967) Die Geschichte der Lage der Arbeiter unter dem Kapitalismus (The History of the Situation of the Working Class under Capitalism). Vol. 37. Berlin (GDR): Akademie Verlag. KUCZYNSKI, J. (1976) Die Krise der kapitalistischen Weltwirtschaft (The Crisis in the Capitalist World Economy). P. 10. Berlin (GDR): Dietz Verlag. KURENKOV, Y . ( 1 9 7 9 ) Scientific and Technological Progress and Structural Change in World Industrial Production. Budapest: Industrial Development and Industrial Policy. LAHNER, M. and Arabiszewski, R. (1978) Datensammlung zum Projekt „Auswirkungen technischer Änderungen auf Arbeitskräfte" (Data File of the Project "Consequences of Technological Changes on work forces".) Teiluntersuchung: Druckerei und VervielfaltigungsHAUSTEIN, H . - D . ,

237

industrie (Partial Investigation: Printing and Copying Industry). Beiträge AB. Band 22. Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt fur Arbeit. Lamps and Lighting (1972) Henderson and Marsden eds. Edward Arnold. LANGEN, E. (1979) Technisierungsgrad der Arbeit und Qualifikation der Produktionsarbeiter (The Technical Level of Labour and the Qualification of Workers). Berlin (GDR): Akademie Verlag. LEHMANN, H. D. (1980) Industrieroboter — Kollege oder Konkurrent (Industrial Robots: Colleague or Competitor). In: Schweizer Technische Zeitung. Wabern 11. LIEWALD, H. (1977) Die analytisch-prognostische und langfristig konzeptionelle Arbeit für Forschung und Entwicklung als Bedingung für die planmäßige Erhöhung des wissenschaftlich-technischen Niveaus der Produktion — dargestellt am Beispiel der Lichtquellen-Industrie der DDR. Dissertation A. Lighting. Encyclopaedia Britannica. Volume 14. 1973. LOESER, F., and Schulze, D. (1973) Kreativitätslogik (The Logic of Creativity). Berlin (GDR): VEB Deutscher Verlag der Wissenschaften. MAIER, H . ( 1 9 7 7 ) Das Wechselverhältnis von Bildung und Ökonomie in der entwickelten sozialistischen Gesellschaft (The Interdependency between Education and Economy in the Developed Socialist Society). In: Ökonomie und Bildung im Sozialismus (Economy and Education in Socialism). Berlin (GDR): Verlag Die Wirtschaft. MAIER, H. (1979) Some Conclusions for International Technology Assessment from the IIASA Energy Study. Presented at the Twenty-fourth International Meeting of the Institute of Management Sciences, Honolulu, Hawaii, 18—21. July 1979. MAIER, H. et al. (1975) Wissenschaft, Produktion, Effektivität (Science, Production, Efficiency). Berlin (GDR): Akademie Verlag. MAIER, H. (1977) Gibt es Grenzen des ökonomischen Wachstums? (Are there Limits of Economic Growth?). Berlin (GDR): Akademie Verlag. MAIER, H. et al. (1978) Ökonomische und soziale Wirksamkeit des wissenschaftlich-technischen Fortschritts (Economic and Social Efficiency of Scientific—Technical Progress). Berlin (GDR): Akademie Verlag MARX, K . ( 1 9 7 4 ) Ökonomisch-philosophische Manuskripte (Economic-Philosophical Manuscripts). In: Marx/Engels, Werke, Ergänzungsband, 1. Teil. Berlin (GDR): Dietz Verlag. MENSCH, G. (1975) Das Technologische Patt (The Technological Statemate). Frankfurt am Main: Umschau Verlag. MENSCH, G., Kaasch, K., Kleinknecht, A., and Schnopp, R. (1980) Innovation Trends and Switching Between Full- and Under-Employment Equilibria, 1950—1978. Discussion papers IIM/dp. 80-5. Berlin (West): International Institute of Management. Monthly Bulletin of Statistics (1980) Vol. 34. No. 10. New York: United Nations. MYERS, S., and Marquis, D . G. ( 1 9 6 9 ) Successful Industrial Innovations: A Study of Factors Underlying Innovation in Selected Firms. NSF 6 9 - 1 7 . Washington, D C : US National Science Foundation. NABSETH, L. and Ray, G. F. (1978) Neue Technologien in der Industrie: Eine Internationale Studie über die Verbreitung von acht Produktionsverfahren (New Technologies in Industry : An International Study of the Diffusion of Eight Production Processes). Schriftenreihe Nr. 97. Berlin (West), Munich: IFO Institute for Economic Research. NELSON, R. R., and Winter, S. G . ( 1 9 7 7 ) In Search on Useful Theory of Innovation. Research Policy 6(1): 3 6 - 7 6 .

NICK, H. (1973) Die Wechselwirkung revolutionärer und evolutionärer Veränderungen (The Correlation of Revolutionary and Evolutionary Changes). In: E. Gatovskij, H. Maier, F. Kutta, Wissenschaft, Ökonomie, Fortschritt. Berlin (GDR): Akademie Verlag. NYSTRÖM, H. (1979) Creativity and Innovation. Chichester: John Wiley and Sons. OECD Economic Outlook (1979) 25. July. OPPENLÄNDER, K.-H. (1980) The Impact of Technical and Structural Change on the Structure and Employment of Manpower. Munich: Ifo-Institute.

238

The Impact of Technological and Structural Changes on the Structure and Re-employment of Manpower. Invited paper for the Sixth World Congress of the International Economic Association, 4—9. August 1980. Mexico City. OSTWALD, W. ( 1 9 0 9 ) Große Männer (Great Men). Berlin (West): Springer Verlag. PÄSSLER, E., MÜLLER, D., Otto A., and Schellenberg, D. (1977) Industrieroboter (Industrial Robots). In: Die Wirtschaft 13/1977. Berlin (GDR). PAVITT, K. (1979) Technical Innovation and Industrial Development in the 1980's: the Dangers of Divergence. Sussex, England: University of Sussex. PAVITT, K. (1980) Innovation in Western Europe: A Challenge and an Example. Sussex, England: University of Sussex. POLLOCK, F. ( 1 9 5 6 ) Automation: Materialien zur Beurteilung der ökonomischen und sozialen Folgen (Automation: Data for Evaluating its Economic and Social Consequences). Frankfurt am Main: Europ. Verlagsanstalt. POLYA, G . ( 1 9 4 5 ) How to Solve It. Princeton, New Jersey: Princeton University Press. RAY, G . F . ( 1 9 7 9 ) Der Innovationsprozess in Westeuropäischen Industrieländern (The Innovation Process in Western European Countries). Innovation in der Energiewirtschaft. Band 3. Berlin (West): Duncker und Humblot. ROMAN, Z., ed. (1979) Industrial Development and Industrial Policy: Proceedings of the Second International Conference on Industrial Economics. Budapest: Akademai Kiado. ROTHWELL, R . (1979) The Relationship Between Technical Change and Employment. Sussex, England: University of Sussex. SCHENK, W. (1979) Technologiebedingte Strukturschwächen in der österreichischen Wirtschaft (Technologically Induced Weaknesses in the Austrian Economy). In: Perspektiven, Berichte, Analysen. Neue Technologien und Produkte für Österreichs Wirtschaft. Wien: Zentralsparkasse und Kommerzbank. SCHILLING, D. (1980) Nutzensnachweis beim Einsatz von Schweißrobotern (Proving the Profitability of Welding Robots). ZIS-Mitteilungen 9/80, J. 1023. Halle: Zentralinstitut für Schweißtechnik. SCHOLZ, L. (1977) Ursachen und Ausmaß sektoraler Strukturwandlungen in der verarbeitenden Industrie bis 1985. (Causes and Dimensions of Sectoral Structural Changes in the Manufacturing Industry until 1985). Munich: IFO-Schnelldienst. SCHOLZ, L. (1978) Zukunftsinvestitionen zur Bewältung des Beschäftigungs- und Strukturproblems (Future Investments for Solving Employment and Structural Problems). Munich: IFO-Schnelldienst. SCHUMPETER, J. A. (1952) Theorie der wirtschaftlichen Entwicklung (Theory of Economic Development). Berlin (West): Duncker und Humblot. Science Policy. A Working Glossary (1978) Forth Edition. Washington, D. C.: Library of Congress. Science Policy Research Unit of the University of Sussex (1972) Success and Failure in Industrial Innovation: Report on the Project SAPPHO. London: Centre for the Study of Industrial Innovation. SPRÖTE, W., and Thiele, G. (1976) Internationale Wirtschaftsbeziehungen und Entwicklungsländer (International Economic Relations and Developing Countries). P. 24. Berlin (GDR): Staatsverlag der DDR. Statistical Yearbook of the CMEA Countries (1979) Moscow: CMEA Secretariate. Statistical Yearbook of the FRG (1953, 1967, 1980) Wiesbaden: Federal Office of Statistics. Statistical Yearbook of the GDR (1955—1979) Berlin (GDR): Central State Office of Statistics. Statistical Yearbook of UNESCO (1977) New York: United Nations. Statistical Yearbook of the USSR (1977) Moscow: Statistika. Technisch-wissenschaftliche Abhandlungen aus dem Osram-Konzern (1936) Berlin: Julius Springer. TESSARING, M . ( 1 9 7 7 ) Qualifikationsspezifische Arbeitslosigkeit in der Bundesrepublik Deutschland (Qualification-Linked Unemployment in the Federal Republik of Germany). Vol. 2. OPPENLÄNDER, K . - H . ( 1 9 8 0 )

239

Report to the Institute for Labour Market and Vocational Research. Stuttgart: Kohlhammer Verlag. The Blue Collar Robot (1980) Special Report V. IEEE Spectrum, 17:9. New York. The Chemical Industry in Eastern Europe, 1975—1980 (1976) Fourth Edition. London: Chemical Data Services. The Human Gap (1979) The Learning Report of the Club of Rome. London: Pergamon Press. Toward the Factory of the Future (1980) New York: The American Society of Mechanical Engineers. UHLMANN, L. (1978) Der Innovationsprozess in Westeuropäischen Industrieländern (The Innovation Process in Western European Industrial countries). Band 2. Der Ablauf industrieller Innovationsprozesse. Berlin (West): Duncker und Humblot. ULRICH, E (1968) Stufung und Messung der Mechanisierung und Automatisierung (Stages and Measurement of Mechanization and Automation). Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit. ULRICH, E. (1978) Arbeitsplatzveränderungen bei betrieblichen Umstellungsmaßnahmen und Rationalisierung (Changes inWorking Places Caused by Rationalization Measures in the Enterprise). In: Ratioanlisierung Heute: Veränderungen und Folgerungen (Rationalization Today: Changes and Conclusions). P. 23—30. Munich: Hanser Verlag. ULRICH, E., Dörfer, G., Dostal, W., Lahner, M., and Köstner, K. (1977) Technik und Arbeitsmarkt (Technology and the Labour Market). Quintessenzen aus der Arbeitsmarkt- und Berufsforschung. Nuremberg: Institut für Arbeitsmarkt und Berufsforschung der Bundesanstalt für Arbeit. UMETANI, Y. (1980) Outline of Research and Development of Industrial Robots in Japan. November. Internal manuscript. Tokyo: Tokyo Institute of Technology. US Energy Research and Development Administration (1976) A National Plan for Energy Research, Development and Demonstration: Creating Energy Choices for the Future. ERDA-48 Washington, DC: US Government-Printing Office. US National Science Board (1977) Science Indicators 1976: Report of the National Science Board. NSB-77-1. Washington, DC: US Government Printing Office. US Statistical Abstract (1980) Washington, D.C.: Department of Commerce. Uvazatele Hospodarskeho Vyvoje v Zahranici (1976) Prague. WAHSE, J . , and Schaefer, R. ( 1 9 8 0 ) : Das gesellschaftliche Arbeitsvermögen. Bedingungen seiner qualitativen Entwicklung und seiner Nutzung (Social Labour Potential: Conditions for Qualitative Development and Utilization). Berlin (GDR): Akademie Verlag. WILLOUGHBY, A. H. (1969) The Evolution of Electric Lamps. Lighting Research and Technology. 1(2): 77. World Casts (1980) Issue 60. November 20. Cleveland, Ohio: Predicasts, Inc. Yearbook of Labour Statistics (1980) Geneva: International Labour-Organization. YONEMOTO, K. (1978) The Present Status and Future Outlook of Industrial Robot Utilization in Japan. Tokyo: Japan Industrial Robot Association. ZERMENO-GONZALEZ, R. ( 1 9 7 9 ) A Conceptual Framework for the Study of the Adoption of Robots in Manufacturing Industry. W P - 7 9 - 1 2 3 . Laxenburg, Austria: International Institute for Applied Systems Analysis. ZINCHENKO, V. P., and Munipov, V. M. (1980) The Future of Homo Faber. PP 143-149. In: Homo Faber, Vol. 30, Nr. 2, April—June. ZVORYKIN, A. A., Osmova, N. I., Chernyshev, V. I., and Shukhardin, S. V. (1962) Istorija techniki (History of Technic). Moscow: Gospolitizdat. ZWICKY, F. ( 1 9 6 7 ) Entdecken, Erfinden, Forschen im morphologischen Weltbild (Discovering, Inventing, and Researching with a Morphological View of Life). Berlin (West), Heidelberg: Springer Verlag.

240