The Innovation Shift in Higher Education: Human Resource Practices and Knowledge Management 9811620547, 9789811620546

Table of contents :
Preface
Acknowledgments
Contents
About the Authors
Abbreviations
List of Figures
List of Tables
1 Introduction
1.1 Evolution of Education in India
1.2 Why Is It Time Now for Higher Education to Transform?
1.3 Higher Education Today Is Facing Unprecedented Challenges
1.4 Significance of This Book
1.5 Problem Statement
1.6 The Body Behind the Education System
1.7 Research Questions
1.8 Objectives of the Research
References
2 Insights About Human Resource Practices, Knowledge Management Practices, and Innovation
2.1 Overview
2.1.1 Recruitment
2.1.2 Compensation and Reward
2.1.3 Performance Appraisal
2.1.4 Teamwork
2.1.5 Training and Development
2.2 KM Processes
2.2.1 Knowledge Diagnosing
2.2.2 Knowledge Acquisition
2.2.3 Knowledge Generation
2.2.4 Knowledge Sharing
2.2.5 Knowledge Storing
2.2.6 Knowledge Application
2.3 Innovation in Higher Education
2.3.1 Product Innovation
2.3.2 Process Innovation
2.3.3 Organizational Innovation
2.4 Literature Review Summary and the Research Gap
2.5 Summary
References
3 The Link Between Human Resource Practices, Knowledge Management Practices, and Innovation
3.1 Conceptual Model and Hypotheses
3.1.1 Overview
3.1.2 Antecedents of Innovation in Higher Education
3.1.3 The Conceptual Model
3.1.4 The Link Between HR Practices and KM Processes
3.1.5 The Link Between KM Processes and Innovation
3.2 Summary
References
4 Analysis of Results, Discussions, and Implications
4.1 A Brief Overview of the Methodology of the Study
4.1.1 Analysis of Results, Discussions, and Implications
4.1.2 Indication of Demographics of the Respondents
4.1.3 Skewness and Kurtosis
4.1.4 Overall Perceptions of the Three Dimensions of Study
4.1.4.1 Human Resource Practice (HRP)
4.1.4.2 Compensations and Rewards (CMR)
4.1.4.3 Performance Appraisal (PRA)
4.1.4.4 Teamwork (TMW)
4.1.4.5 Training and Development (TRD)
4.1.4.6 Knowledge Management Practice
4.1.4.7 Innovation
4.1.5 Comparative Analysis of the Three Dimensions
4.1.5.1 Comparative Analysis of Human Resources Practices (HRP)
4.1.5.2 Comparative Analysis Knowledge Management Practices (KMP)
4.1.5.3 Comparative Analysis Innovation (INN)
4.1.5.4 Inter-Cadre Comparisons
4.1.5.5 Cadre-Wise Perception of Human Resources Practices (HRP)
4.1.5.6 Cadre-Wise Perception of the Knowledge Management Processes (KMP)
4.1.5.7 Cadre-Wise Perception of Innovation
4.1.6 Structural Equation Modeling (SEM)
4.1.7 Hypothesis Testing
4.1.7.1 Influence of HRP Dimensions on KMP
4.1.7.2 Influence of KMP on Dimensions of INN
4.1.7.3 Influence of KMP Dimensions on OGI
4.1.8 Structural Model
4.2 Summary
References
5 Suggestions and Recommendations for Higher Education
5.1 Overview
5.2 Research Findings
5.3 Suggestions and Recommendations
References
6 Knowledge Management Innovation Model for Higher Education
6.1 KM-Based Innovation Model for Higher Education
6.2 Human Resource Management Processes (HRP)
6.3 Knowledge Management Processes
6.4 Limitations of the Study and Scope for Future Work
6.5 Conclusions
References
Appendix A: Questionnaire Before Factor Reduction
Appendix B: Questionnaire After Factor Reduction

Citation preview

The Innovation Shift in Higher Education Human Resource Practices and Knowledge Management Aftab Ara · Kishore Kumar Das

The Innovation Shift in Higher Education

Aftab Ara · Kishore Kumar Das

The Innovation Shift in Higher Education Human Resource Practices and Knowledge Management

Aftab Ara College of Excellence Al Khobar, Saudi Arabia

Kishore Kumar Das School of Management Ravenshaw University Cuttack, Odisha, India

ISBN 978-981-16-2054-6 ISBN 978-981-16-2055-3 (eBook) https://doi.org/10.1007/978-981-16-2055-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover illustration: © Alex Linch shutterstock.com This Palgrave Macmillan imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Higher education in India has gone through several changes to reach its present state of performance, but presently due to globalization and the entry of foreign universities into the domestic market, there is a tough competition to maintain standard with foreign universities. The sustainability of the Indian universities is only through the attainment of the competitive advantage in business, in which innovation has the main role. The universities have to learn from their counterparts in the western world to possess the innovative practices in the teaching-learning processes for their sustainable growth. Now steps are being taken to improve the quality of higher education and the central bodies have strict regulations regarding the quality of education. However, there is a need to innovate on the academic processes and strengthen the enablers of innovation by recognizing them. Higher Education (HE) is one of the most creative and innovative service organizations which can be converted to adapt itself to the needs of society from time to time. The higher education policymakers, as well as administrators, will have to balance the fiscal pressures of running a large organization influenced by external forces such as rankings and increased competition for students and faculty. The entire HE system will demand more transparency, responsibility, and perceptible evidence of success. So, innovation in teaching-learning processes, administration, governance, and every aspect of education will be the only way to face the enormous task of providing to the needs of the national and international v

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educational requirements. To add to this pressure each university will have to prove how it is distinctly different from the rest. Hence, innovation and creativity in the processes, systems, and practices is the only remedy. Educators have found that this is the most critical stage in which the HE has to undertake the change. The universities cannot simply rely on the conservative methods of ‘teacher-centric teaching,’ but find replacements to switch over to ‘student-centric learning’ and this modification may demand a complete overhaul of the processes, systems, and practices. The private players in HE have contributed a lot to the system of education and have worked explicitly in improving the institutional relationships, research associations, multi-dimensional system-wide support, early-stage research, entrepreneurship, leadership and management, digital learning solutions, and links with industries for the setting of incubators. So, research on the innovativeness of private universities is now the need of the hour as they are going to take a major stake in the higher education in the country. The purpose of this research is to seek empirical evidence for the influence of human resources management practices on the knowledge management processes and the influence of knowledge management processes on innovation in higher educational institutes so that suggestions can be drawn to enhance the innovativeness of the institutes through the strengthening of the enablers. The book is divided into six chaptersChapter 1 is “Introduction”, Chapter 2 is the “Insights about Human Resource Practices, Knowledge Management Practices, and Innovation”, Chapter 3 is “The link between Human Resource Practices, Knowledge Management Practices, and Innovation”, Chapter 4 is “Analysis of Results, discussions, and implications”, Chapter 5 is the “Suggestions and Recommendations for Higher Education” and Chapter 6 consists of “Knowledge Management Innovation Model for Higher Education”. Presently the service providers will have to make use of advanced management tools to ensure sustainability. So innovation has to be brought into the institutional processes, mainly the teaching-learning processes, the research and consultancy policies, and procedures, and the administrative services the authorities of higher education must take measures to improve upon their recruitment policies and procedures, provide better compensation and reward to the knowledge workers, develop an appraisal system that promotes the contribution of the employee to the corporate objectives, adopt better teamwork among the faculty members, and devote on training and development to build the

PREFACE

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domain-specific competencies among the teaching faculty. This would support the knowledge management practices, which have a significant influence on innovation. The research has opened up a new line of thinking in the higher educational institutes in terms of building a knowledge management system with robust processes. These processes include knowledge diagnosing which enables the identification of the knowledge relevant and useful in the context of higher education, promoting the acquisition of this knowledge from both the internal and external sources through appropriate mechanisms well supported through information technology and electronic communication systems, providing all the infrastructure necessary to generate the knowledge which is essential for the advanced growth of the higher educational institute, the building of a culture, norm, and value that encourages knowledge sharing for mutual benefit, building the infrastructure for storing the knowledge in such a manner that it can be easily recovered by the faculty members from anywhere in a smallest possible time, and finally, applying all the available knowledge for the promotion of innovation in the higher educational institute. This research has contributed a metric in the form of a questionnaire that can be used by future researchers in the measurement of human resource management practices, knowledge management processes, and innovation. The research has successfully developed the KM-based Innovation Model for Higher Education which can be used as a blueprint for promoting innovation in higher education. The outcome of the empirical study can be used by future researchers in the three distinct areas of Human Resources Management (HRM), Knowledge Management (KM), and Innovation (INN) as a reference for future comparisons. The generalized results in the context of higher education can also be used by other service organizations. The metric of measurement can be used in other service industries. The research has effectively recognized the mediating effect of knowledge management practices in promoting innovation and highlighted the importance of building a Knowledge Management System (KMS) in higher educational institutes to promote innovation. The outcome of this research in the form of implications, suggestions, and recommendations to the strategic managers of the higher educational

viii

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institutes would overlay the way for success in the present highly competitive business environment in higher education in the Indian context, where innovation is the primary existence tool. Al Khobar, Saudi Arabia Cuttack, India

Dr. Aftab Ara Dr. Kishore Kumar Das

Acknowledgments

The completion of this book would not have been possible without the participation and help from so many people whose names cannot be enumerated. Yet, I express my sincere thanks to the Associate Editor— Ms. Sandeep Kaur and Project Coordinator—Mr. Manikandan Murthy of Palgrave Macmillan for their valuable advice throughout my publishing journey. I am also grateful to the Collaborators who provided the data in this book. I am indebted to my mentors—Dr Kishore Kumar Das, Dr. Sanjay Satapaty, Dr. Tushar Kanta Pany and entire faculty and staff of Ravenshaw University for their support and cooperation. Having an idea and being able to convert it to book is both challenging and rewarding. I especially want to thank everybody who make this possible. My special thanks and gratitude goes to my mother—Kulsum Ara and father—Dr. Soleman whose prayers have sustained me so far. I am equally thankful to my husband—Dr. Murtaza for his patience and support. Lastly am indebted to Alim, Sabir, Jakir, Asma, Afrozy, Affreen, Ayesha, Asfaque, Abdullah and Aliza for their patience to complete my book in time. Above all thanks to the Almighty and Benevolent “Allah” for his graciousness! Dr. Aftab Ara

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Contents

1

2

Introduction 1.1 Evolution of Education in India 1.2 Why Is It Time Now for Higher Education to Transform? 1.3 Higher Education Today Is Facing Unprecedented Challenges 1.4 Significance of This Book 1.5 Problem Statement 1.6 The Body Behind the Education System 1.7 Research Questions 1.8 Objectives of the Research References Insights About Human Resource Practices, Knowledge Management Practices, and Innovation 2.1 Overview 2.1.1 Recruitment 2.1.2 Compensation and Reward 2.1.3 Performance Appraisal 2.1.4 Teamwork 2.1.5 Training and Development 2.2 KM Processes 2.2.1 Knowledge Diagnosing 2.2.2 Knowledge Acquisition

1 1 2 3 3 4 4 7 8 8 11 11 12 14 15 16 17 18 18 19 xi

xii

CONTENTS

2.2.3 Knowledge Generation 2.2.4 Knowledge Sharing 2.2.5 Knowledge Storing 2.2.6 Knowledge Application 2.3 Innovation in Higher Education 2.3.1 Product Innovation 2.3.2 Process Innovation 2.3.3 Organizational Innovation 2.4 Literature Review Summary and the Research Gap 2.5 Summary References 3

4

The Link Between Human Resource Practices, Knowledge Management Practices, and Innovation 3.1 Conceptual Model and Hypotheses 3.1.1 Overview 3.1.2 Antecedents of Innovation in Higher Education 3.1.3 The Conceptual Model 3.1.4 The Link Between HR Practices and KM Processes 3.1.5 The Link Between KM Processes and Innovation 3.2 Summary References Analysis of Results, Discussions, and Implications 4.1 A Brief Overview of the Methodology of the Study 4.1.1 Analysis of Results, Discussions, and Implications 4.1.2 Indication of Demographics of the Respondents 4.1.3 Skewness and Kurtosis 4.1.4 Overall Perceptions of the Three Dimensions of Study 4.1.5 Comparative Analysis of the Three Dimensions 4.1.6 Structural Equation Modeling (SEM) 4.1.7 Hypothesis Testing 4.1.8 Structural Model 4.2 Summary References

20 21 22 23 24 28 29 30 31 32 33 41 42 42 42 44 44 49 52 53 57 58 59 60 60 60 72 80 85 99 116 117

CONTENTS

5

6

xiii

Suggestions and Recommendations for Higher Education 5.1 Overview 5.2 Research Findings 5.3 Suggestions and Recommendations References

123 124 124 126 136

Knowledge Management Innovation Model for Higher Education 6.1 KM-Based Innovation Model for Higher Education 6.2 Human Resource Management Processes (HRP) 6.3 Knowledge Management Processes 6.4 Limitations of the Study and Scope for Future Work 6.5 Conclusions References

139 140 143 148 158 159 162

Appendix A: Questionnaire Before Factor Reduction

165

Appendix B: Questionnaire After Factor Reduction

173

About the Authors

Dr. Aftab Ara (Ph.D. in Management, MBA-HR, and B.E. in Engineering) is a Dynamic Educational Professional, Speaker, Board Member, Book Author, Researcher, and L&D Coach greatly interested in research and teaching by reinventing & radically rethinking education using technology. She has worked across multiple disciplines in colleges and universities in India and the Middle East. She has been praised by her peers, colleagues, and students for her enthusiasm for research and teaching with an experience spanning 10 years. She has significantly contributed to enhancing scientific understanding by participating in several scientific conferences, symposia, and seminars, by chairing technical sessions and invited talks. She has specialized in the fields of Human Resource Management, Data Analytics, and Business Intelligence. She pursued research in truly inter-disciplinary areas and authored and co-authored research papers and an edited book with renowned International and National publishers. She has received several appreciations for her research work. Currently, she is working as a Business Faculty in College of Excellence, Al Khobar, Saudi Arabia. In addition she is also working on several projects to create more educational opportunities by using Data Science for education. Apart from teaching, Aftab is an active participant sharing insight and perspectives through writing, consulting, and coaching with clients, practitioners, students, and fellow academicians in the field of learning.

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ABOUT THE AUTHORS

Dr. Kishore Kumar Das, Co-Author (Ph.D., M.Phil., M.Com., M.B.A., P.G.D.F.M., L.L.B., S.I.M.A.P. -XIMB) is an Excellent Academician, Educational Administrator, Research Mentor, Educational Professional Leader, Author, Paper Writer, Academic Board Member, Editor of the international journal, a Fellow Member of national and international academic institutions, Speaker, and greatly interested in teaching, research, and consultancy. He has worked across the academics and industry multiple disciplines in colleges and universities across India. He has been praised by his peers, colleagues, and students for his dedicated work. Currently, he is now working as Associate Professor & HeadDepartment of Commerce & Department of Business Administration, Chief Warden of Hostels, Ravenshaw University, Cuttack. He started his career as Deputy Officer (Finance) with M/s J.K. Synthetics Ltd. in 1996 and joined Odisha Education Service in 2001 and continued until 2010. He holds the different important position and responsibilities includes: Registrar, Controller of Examinations, Dean-School of Commerce, HeadDepartment of Commerce, OSD Examinations, Deputy Chief Warden of Hostels, Member: University Research Advisory Committee, Board of Studies in Commerce, Board of Studies in Management, Academic Council of Ravenshaw University. Dr. Das authored 16 books and published more than 100 research articles in various national and international journals of repute. He has more than 25 years of teaching, research, and corporate experience. He has guided 25 Ph.D. and 29 M.Phil. research scholars. Dr. Das is the recognized guide and member of different Subject Research Committee and Board of Studies of different universities. He is a Life Member of OCA, ICA, IAARF, INAAR, etc. Dr. Das is the Fellow-WBI, Australia, and Associate Fellow: Indian Institute of Advance Studies, Shimla. He is the Joint Editor of the Journal of Business Management, Commerce and Research (An International Referred Quarterly Business Research Journal ). Dr. Das has done his Ph.D. in Long Term Finance of Indian Corporate Sector and having an interest in the field of Finance and HR aspects of the corporate sector.

Abbreviations

AGFI ANOVA AVE CFA CKO CMR CoP EFA FL HE IR KAP KBT KN KNA KND KNG KNS KST MRA OGI PLSM PRA PRD PRI RBT

Adjusted Goodness Fit Index The Analysis of Variance Average Variance Extracted Confirmatory Factor Analysis Chief Knowledge Officer Compensation and Reward Communities of Practices Exploratory Factor Analysis Factor Loadings Higher Education Institutions Item Reliability Knowledge Application Knowledge-Based Theory Knowledge Knowledge Acquisition Knowledge Diagnosing Knowledge Generation Knowledge Sharing Knowledge Storing Multiple Regression Analysis Organizational Innovation Partial Least Square Method Performance Appraisal Product Innovation Process Innovation Resource-Based Theory xvii

xviii

ABBREVIATIONS

RCT RMSEA SEM TLI TMW TRD

Recruitment and Selection Root Mean Square Error of Approximation Structural Equation Modeling Tucker-Lewis Index Teamwork Training & Development

List of Figures

Fig. 3.1 Fig. 4.1 Fig. 4.2 Fig. 4.3 Fig. 4.4 Fig. 4.5 Fig. 4.6 Fig. 4.7 Fig. 4.8 Fig. 4.9 Fig. 4.10 Fig. 4.11 Fig. 4.12

Hypothetical research model (Source Author) Descriptive statistics of RCT (Source Compiled and collected data from primary sources) Descriptive statistics of CMR (Source Compiled and collected data from primary sources) Descriptive statistics of PRA (Source Compiled and collected data from primary sources) Descriptive statistics of TMW (Source Compiled and collected data from primary sources) Descriptive statistics of TRD (Source Compiled and collected data from primary sources) Descriptive statistics of KND (Source Compiled and collected data from primary sources) Descriptive statistics of KNA (Source Compiled and collected data from primary sources) Descriptive statistics of KNG (Source Compiled and collected data from primary sources) Descriptive statistics of KNS (Source Compiled and collected data from primary sources) Descriptive statistics of KST (Source Compiled and collected data from primary sources) Descriptive statistics of KAP (Source Compiled and collected data from primary sources) Descriptive statistics of PRD (Source Compiled and collected data from primary sources)

45 64 64 67 68 70 72 74 76 78 80 82 84

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LIST OF FIGURES

Fig. 4.13 Fig. 4.14 Fig. 4.15 Fig. 4.16

Fig. 4.17 Fig. 4.18

Fig. 4.19 Fig. 4.20 Fig. 4.21 Fig. 4.22 Fig. 4.23 Fig. 4.24 Fig. 4.25 Fig. 4.26 Fig. 6.1

Descriptive statistics of PRI (Source Compiled and collected data from primary sources) Descriptive statistics of OGI (Source Compiled and collected data from primary sources) Comparative analysis of the dimensions of HRP (Source Compiled and collected data from primary sources) Comparative analysis of the dimensions of KMP (percentage) (Source Compiled and collected data from primary sources) Comparative analysis of the dimensions of INN (Source Compiled and collected data from primary sources) Perceptions of HRM practice dimensions cadre-wise (Source Compiled and collected data from primary sources) Perceptions of KM practice dimensions cadre-wise (Source Compiled and collected data from primary sources) Perceptions of innovation dimensions cadre-wise (Source Compiled and collected data from primary sources) Residual plots for KMP Residual plots for PRD (Source Compiled and collected data from primary sources) Residual plots for PRI (Source Compiled and collected data from primary sources) Residual plots for OGI (Source Compiled and collected data from primary sources) Path coefficients of the proposed model t-values of the proposed model KM-based innovation model for higher education (Author)

84 85 86

87 88

88 89 90 100 102 104 106 107 111 141

List of Tables

Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table Table

4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14 4.15 4.16 4.17

Table 4.18 Table 4.19 Table 4.20 Table 4.21 Table 4.22

Demographic distribution of the respondents Skewness and Kurtosis Descriptive statistics of RCT Descriptive statistics of CMR Descriptive statistics of PRA Descriptive statistics of TMW Descriptive statistics of TRD Descriptive statistics of KND Descriptive statistics of KNA Descriptive statistics of KNG Descriptive statistics of KNS Descriptive statistics of KST Descriptive statistics of KAP Descriptive statistics of PRD Descriptive statistics of PRI Descriptive statistics of OGI Comparative analysis of the dimensions of HRP (percentage) Comparative analysis of the dimensions of KMP (percentage) Comparative analysis of the dimensions of INN (percentage) Perceptions of HRM practice dimensions cadre-wise Perceptions of KM practice dimensions cadre-wise Rank order correlation

61 62 63 65 66 67 69 71 73 75 77 79 81 82 83 83 85 86 87 89 90 91

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LIST OF TABLES

Table Table Table Table Table Table Table Table

4.23 4.24 4.25 4.26 4.27 4.28 4.29 4.30

Table Table Table Table Table Table

4.31 4.32 4.33 4.34 4.35 4.36

Table Table Table Table Table Table Table Table

4.37 4.38 4.39 4.40 4.41 B.1 B.2 B.3

Perceptions of innovation dimensions cadre-wise Rank order correlation of innovation dimensions Goodness of test results for measurement models The reliability measures of the data Factor loading after reduction Inter-item correlation and discriminant validity ANOVA showing influence of HRP dimensions on KMP Regression table—the influence of HRP dimensions on KMP The predictive power of the model ANOVA showing influence of KMP dimensions on PRD Regression table—influence of KMP dimensions on PRD The predictive power of the model ANOVA showing influence of KMP dimensions on PRI Regression table—the influence of KMP dimensions on PRI The predictive power of the model ANOVA showing influence of KMP dimensions on OGI Regression table—influence of KMP dimensions on OGI The predictive power of the model t-statistic of the integrated hypothetical research model Factor loading before reduction Factor loading after reduction Inter-item correlation and discriminant validity

91 92 93 95 96 98 99 99 99 100 101 101 102 103 103 104 105 105 108 180 184 188

CHAPTER 1

Introduction

This chapter is an introduction to a book where there is a discussion regarding the evolution of Education in India and provides the background to the significance of writing this book, presents the research areas, gives the need for this research, presents the problem statement, the body behind the education system and also lists the research questions and the objectives of the book.

1.1

Evolution of Education in India

Education is no alien in India as there is no country where the love of learning was so lasting and so powerful. India’s education has a fascinating history, through different periods leading to the modern-day education of today. During the third century, education was disciplined and organized, with learning mostly concentrating on traditional and religious thoughts. Teachers were sages and scholars and their writing pads were leaves and barks. The Gurukul system of teaching and learning was a more rigorous form of education here the teacher and the taught were boarding together, thus helping in transferring knowledge from one generation to another. The principal subjects of teaching were medicine, astrology, warfare, philosophy, and religion. The beginning of Millennium witnessed Takshashila University, Nalanda University, Vikramshila University, and Ujjain. Major subjects © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. Ara and K. K. Das, The Innovation Shift in Higher Education, https://doi.org/10.1007/978-981-16-2055-3_1

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A. ARA AND K. K. DAS

taught were Literature, Logic, Grammar Astronomy, Philosophy, Law, Medicine, Arthashastra (Politics and Economics) Hinduism, Buddhism, and Mathematics. The university focused on a subject, with Takshashila focused on medicine, the university in Ujjain on astronomy, and Nalanda with all the branches of study. Education was extensively spread with the accessibility of schools, even in the villages in India, in the eighteenth century. Medieval times also saw the founding of Madrasas, libraries, and literary societies. In the Pre-British days, education was self-controlled and both the Muslim and Hindu rulers thought to spread learning as a religious obligation. Traditionally, from the Mughal and Colonial to the postindependence period, the education system in India has undergone massive changes. During the British rule in India, the missionaries were the pioneers of education. After Independence, the Center and State Governments controlled the education sector by constitutional amendment in 1976. With the start of twenty-first-century education policy was created to give free and compulsory education to children who attained 14 years of age. The education policy planned to spend 6% of GDP on education, primarily focused on education. Even with a rich past India still faces several issues in education, from a high percentage of illiteracy to a high rate of school dropouts and a deficit of innovative systems to compete with international standards.

1.2

Why Is It Time Now for Higher Education to Transform?

Higher education in India has progressed through numerous change to arrive at its present performance level, but the sustainability of Indian Universities is at risk due to globalization and entry of foreign universities in India. To gain a competitive advantage in business universities have to be innovative. The universities have to learn from the western counterparts the innovative strategies of teaching and learning. Fresh measures are being taken to build up the quality of higher education and the governing bodies have strict regulations on the quality aspects of education by the introduction of new Educational policy NEP 2020. Since have made no justice to innovate on the academic processes and strengthen the enablers of innovation by identifying them, a new field is now open for research to both academia and policymakers.

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INTRODUCTION

3

1.3 Higher Education Today Is Facing Unprecedented Challenges The world is transforming the field of Education in the knowledge set with a range of amazing technological advancements with the introduction of big data, machine learning, and artificial intelligence. It is predicted that future jobs may be taken over by robots. In preparation for the future world, the HEI’s must mainly focus on exploring more innovative measures to create centers for technology development by carrying out research to cope up with the skill shortage. Moreover, during these times of the pandemic, it is imperative to focus on the research and development of vaccines which is the ultimate requirement for having multidisciplinary learning.

1.4

Significance of This Book

The significance of this book lies in its ability to provide empirical evidence for the relationships between the dimensions of HRP, KMP, and INN. Indian HE sector is witnessing tremendous change since the past decade (post-globalization), as it has to compete with the foreign universities of repute, and also prove its value to the rest of the world so that it can spread its wings abroad and grow internationally. The obvious answer is to introduce innovativeness into the system of HE so that it can adapt to the changes and ensure sustainability. Despite the importance innovation has gained in HE there is no systematic study that empirically examines the significance of relationships between the enablers of innovation so that the critical components can be identified and strengthened. So, this research has developed a model in which the linkages have been established between the dimensions of the three research constructs and the empirical proof has been established for the existence or absence of causal relationships. The significance of this research also lies in its ability to add to the body of knowledge in the field of innovation, human resource management, and knowledge management in service sectors in general and HE in particular. There is no model to explain the role of HRP and KMP on INN in the context of HE. Thus, this research is significant as it proposes one such model. The suggestions are given for the enhancement of the human resource management practices and knowledge management processes for the organization to be more innovative in terms of its

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processes, systems, and practices is another significant contribution of this research. Finally, there was a need for the development of a validated and tested metric for the measurement of HRP, KM, and INN in the context of HE, and this research has provided one such measurement instrument which can be readily used by future researchers.

1.5

Problem Statement

The success of innovative measures in product-oriented industries has made the service sectors emulate the same to improve their business performance and gain a competitive advantage in the market. One of the leading service sectors in India is higher education because the majority of the future generation is going to be below the average age of 25 years. Having realized this, the premier institutes of HE have imbibed innovative measures to better establish themselves in the years to come, and many are adopting the same. There are several research studies (Lee & Eom, 1990; Ubeda-Garcia et al., 2013) that have revealed that innovation has human resources management practices and knowledge management practices as its drivers; if these two enablers are made more efficient, the organization would be more innovative. But most of these studies are qualitative, and there is no adequate empirical evidence to support the linkages between the dimensions of the three research constructs. To fill this gap, the following has been the problem statement of this research.

1.6

The Body Behind the Education System

Higher Education (HE) is one of the most creative and innovative service organizations which have the fundamental requirement of being transformed to adapt itself to the needs of the society from time to time. According to figures, it is predicted that 500 million people in the next decade or maybe more may plan to study abroad so there is a need to be innovative and creative in the approach to higher education. The policymakers and administrators of higher education have to gauge the fiscal pressure of running institutions that influence the ranking and competition for both faculty and students. The entire HE system will require more precision, accountability, and a substantial indication of success. So, innovation in teaching–learning processes, administration, governance, and every aspect of education will be the only way to face the herculean task of catering to the needs of the national and international educational

1

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requirements. To add to this pressure, the days of going for international accreditation for the institutes of higher education (HE) is coming closer, and each University will have to prove how it is distinctly different from the rest in trade. Again, innovation and creativity in the processes, systems, and practices is the only remedy. National Education Policy 2020 is one of the foremost of its kind in education policy of the twenty-first century which aims to tackle the growth imperative of our country. The Policy suggests a review as well as revamp of complete areas of education, to create a novel structure in alignment with twenty-first-century goals for education. Relatively Knowledge Management (KM) is a newer concept to the higher education in India; however, the NEP 2020 has emphasized the need for effective KM systems in the university set Up which can diagnose the most modern knowledge in interest to the faculty and the students, have an appropriate technology to gain this knowledge and develop mechanisms in the university to generate the newer knowledge in the university. The NEP has explicitly stated that each university should be multidisciplinary and HEI clusters/Knowledge Hubs near or in every district with the medium of instruction in local/Indian languages (NEP, 2020). Another feature in KM is knowledge sharing, which is supported by the most appropriate which is user-friendly and fast. The NEP guideline is important on the augmentation of Information and Communication Technology infrastructure by setting incubation centers and technology development centers. Presently the regulatory system of the Higher Education Commission of India has four independent units under its wing with a robust National Accreditation Council (NAC) as an important component of assessment. Another feature is a knowledge repository in the university set up which stores all the archival knowledge in the university for future use. Some universities have already allocated several terra-bites of storage memory for storing the knowledge generated in the university in the form of papers published, projects are undertaken, books published, patents filed, etc. Knowledge application is the most important part of a university which is emphasized by the NEP. The teaching faculty needs to be the knowledge disseminators to a great extent without exception, but their duty ends only when the students whom they teach and train end up applying the knowledge which is accumulated during their course of learning in the university. Educators have found that this is the most crucial stage in which the HE has to transform. The future generation youth are computer

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savvy before they enter higher education and their exposure to the world through the internet will make them very choosy about the program they wish to undertake at the level and will also be choosy about the courses they wish to study to build their career. The universities cannot rely on the conventional methods of ‘teacher-centered teaching,’ but find alternatives to switch over to the ‘student-centric learning’ and this shift of paradigm demands a complete overhaul of the processes, systems, and practices. It is alarming to note that India ranks 129 nth of 187 countries according to the Human Development Index (HDI). As per the HDI (2020) report score is 0.647 (Human Development Report, 2020) so the time has come for the government and private sectors to work collaboratively in educating the youth of the country. The private sector has a 59% stake in terms of enrollment to tertiary education, and its role is to increase further in the years to come to BCR (2014). The private players in HE contributed a lot to the system of education and have worked specifically in improving the institutional collaborations, research collaborations, multi-dimensional system-wide support, early-stage research, entrepreneurship, leadership and management, digital learning solutions, and links with industries for the setting of incubators. So, research on the innovativeness of private universities is now the need of the hour as they are going to take a key stake in higher education in the country. 1. There are 958 universities (as of now) across the country with 29 states and 9 union territories, with the state public universities having the highest share (43.42%). The first five states with the highest number of universities include Rajasthan (83 universities of the total in India), Gujarat (75), Uttar Pradesh (74), Karnataka (65), Madhya Pradesh, and Maharashtra (63) as quoted by (UGC, 2020). The major concern has been the innovativeness and the quality of education in these many numbers of universities as none of them are listed even in the top hundred lists of the world-renowned ranking agencies such as QS World Ranking (QSR, 2020). Due to regional imbalances, 20% can enroll only 100 students annually and 4% of colleges thus leading to the low quality of education. India’s reasons for the disintegration of the higher education (HE) systems are (Aithal & Aithal, 2019).

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• Surge of students into various disciplines. • Socio-economically backward areas are unable to access HE. • Innovations in HE is the utmost requirement to engage and retain students, but the teachers and institutions have no say in the matter. • Inadequate system for the professional development of teaching and non-teaching professionals. • Requirement for research in most educational institutions. • Insignificant measures of governance and leadership at HEI. • A manipulative procedure allowing fake colleges to grow, innovative institutions. According to NEP 2020, in Higher Education there is a need to embrace technology in professional education by introducing technology to speed-up 100% literacy and introduce quality technology-based options for adult learning. The policy acknowledges the importance of technology in various societal concerns. So, innovation has been one of the objectives in the agenda of the HRD developmental plan. The Ministry of HRD has been working to improve fields of research innovation as well as to improve the quality of higher education with premier institutions like the + IISc, IITs & IIMs as the benchmark. So, it is clear that research-based specifically on higher education for the upgrading the policies, processes, and practices is in the forefront of the national agenda, and in the backdrop of this prevailing scenario of the country, this research has emerged with a motive to study and make suggestions to enhance the innovativeness of higher educational institutes by strengthening the two key enablers: which are the human resource management practices and the knowledge management processes.

1.7

Research Questions

The statement of the problem given leads to the following series of research questions which are as follows. RQ1. What are the dimensions of HRP, KMP, and INN in the context of higher education? RQ2. What would be the interrelationships between the dimensions of the above-referred research constructs?

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RQ3. What would be the statistical significance of relationships between the various constructs mentioned above? RQ4. What would be the suggestions and recommendations to the policymakers and stakeholders of higher education? RQ5. What would be the KM-based innovation model for higher education and how can it be made operational?

1.8

Objectives of the Research

This research aims to find the means to enhance innovativeness in higher educational institutions. To accomplish this aim, the following objectives have been developed. OB1. Identify the dimensions which constitute HRP, KMP, and INN. OB2. Establish the interrelationships between the dimensions of the above constructs in the form of a hypothetical model. OB3. Empirically investigate the significance of interrelationships between these constructs. OB4. Make suggestions and recommendations to the policymakers and stakeholders of higher education. OB5. Develop a KM-based innovation model for higher education and provide the procedure for operation.

References Aithal, P. S., & Aithal, S. (2019). Analysis of higher education in Indian National education policy proposal 2019 and its implementation challenges. International Journal of Applied Engineering and Management Letters (IJAEML), 3(2), 1–35. https://doi.org/10.5281/Zenodo.3271330. Human Development Report. (2020). http://hdr.undp.org/en/countries/pro files/IND,2020. Lee, S. M., & Eom, H. B. (1990). Multiple-criteria decision support systems: The powerful tool for attacking complex, unstructured decisions. Systems Practice, 3(1), 51–65. National Education Policy. (2020a). https://innovate.mygov.in/wpcontent/upl oads/2019/06/mygov15596510111.pdf. National Education Policy. (2020b). https://www.mhrd.gov.in/sites/upload_ files/mhrd/files/nep/NEP_Final_English.pdf referred on 10 August 2020. National Education Policy. (2020c). https://www.bloombergquint.com/opi nion/nep-2020-an-interplay-of-education-and-technology.

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QSR Ranking. (2020). https://www.topuniversities.com/university-rankings/ rankings-by-location/india/2020. Ubeda-Garcia, M., Marco-Lajara, B., Sabater-Sempere, V., & Garcia-Lillo, F. (2013). Does training influence organizational performance? Analysis of the Spanish hotel sector. European Journal of Training and Development, 37 (4), 380–413. UGC. (2020). https://www.ugc.ac.in/oldpdf/Consolidated%20list%20of% 20All%20Universities.pdf.

CHAPTER 2

Insights About Human Resource Practices, Knowledge Management Practices, and Innovation

Abstract A detailed discussion on the research constructs Human Resource Practices (HRP), Knowledge Management Processes (KMP), and Innovation (INN) is discussed in this chapter, and contemporary research is analyzed to define the dimensions and relevant variables. To perform empirical studies on the three research constructs, this chapter provides the necessary theoretical framework for the analysis. The identification of the research gap that has culminated in this chapter is also narrated. Keywords Human Resource Practices · Knowledge Management Practices · Innovation

2.1

Overview

The importance of Human Resource Management Practices (HRP) has been realized in the twenty-first century much more than ever before owing to the advent of the era of the knowledge-based economy. HE institutions had realized that staffing had become strategically important to them and the search for the best faculty is highly competitive and increasingly international. Having realized this, the HE institutions had resorted to the HRM practices that were very well established in © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. Ara and K. K. Das, The Innovation Shift in Higher Education, https://doi.org/10.1007/978-981-16-2055-3_2

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the other service and production-oriented organizations. Fundamentally speaking, HRM concepts were introduced in the HE mainly to build an institutional culture that can be used to characterize a particular institute. It was accomplished mainly through the conduct of the recruitment, selection, orientation, and placement programs in line with the HRM principles. Further, the new terms were introduced in the HE such as academic competency, skills, attitude, behavioral psychology, organization structure, administration, outcomes, objectives, strategy, tactics, policies, procedures, systems, practices, etc. Ultimately, these changes introduced in the HE transformed the universities into an ‘organic entity’ characterized by business performance aiming toward sustainability. The contribution of HRM was in terms of productivity and efficiency gains aiming at the creation of competitive advantage in business. Concepts such as performance indicators, quality assurance, vision and mission statements were all derived from the HRM literature and today they have become a part of the HE governance. Today, most of the HE institutes have implemented the HRM activities in a full-fledged manner. The functions such as staffing, training and development, promotion policies, support staff, appraisal, mentoring, welfare, and grievance handling have been in practice in almost all the well-established universities. Advances concepts of HRM such as HR Planning, HR policies, HR payroll systems, and HR administration are also in practice in the HE institutes. In the perspective of this research, it was important to narrow down to those specific human resource management practices which have a direct bearing on the knowledge management issues and eventually the innovation in the organizations. A thorough literature review has narrowed down to five dimensions of human resource management practices which have been discussed in the subsequent sections. 2.1.1

Recruitment

The recruiting and retaining process of the top talent in the market is crucial for the sustainability of any institution (Zhao, 2006). Trained candidates are recruited in this knowledgeable economy to contribute to the growth of the institution (McDermott et al., 2006). Retaining the top talents is a challenge in the institution including the higher educational sectors (Anantatmula & Shrivastav, 2012; Broadbridge et al., 2007; Martin, 2005; Shaw & Fairhurst, 2008; Valentine & Powers, 2013).

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Teaching faculty in HE is the edifice of knowledge creation because they generate newer knowledge that will ultimately contribute to the national GDP through improved products and services. The faculties also contribute to the knowledge repository and transform the HE institutions into learning organizations (Sarwar et al., 2012). So, their recruitment and selection must be free from favors, nepotism, and bias of any kind, and also the teaching faculty must be available in adequate numbers in the universities with a wide range of specializations to meet the diversified interests of the students. Many research studies, particularly in India, have found that recruiting teaching faculty of high caliber is very difficult because attracting the talent to teaching itself is a challenge. This is because of the poor pay scale, very little promotion opportunities, lesser international exposure, lesser opportunities to relocate, not considered to be in the elite class, etc. (Altbach, 2006; Anandakrishnan, 2006; Modi, 2014). It is only the well-motivated and knowledgeable teaching faculty who can inspire the students to dream big, learn more, work more, and produce better results. Thus, there is a need to have a very well-designed recruitment and selection practice in the universities so that talent can be attracted and placed well with the right kind of responsibilities and challenges with an attractive monetary benefit package. The faculty recruitment must consider the future orientation required in the HE which includes the transformation of the universities in terms of: a differentiated university system with the students being able to visualize the socio-economic impact of their action, provide them the option for inter-university credit transfer possibility; transition to a learner-centric learning paradigm where the teacher just acts as a facilitator and the students learn what is defined in the curriculum through innovative ways; use of technology intensively such that the students learn faster, better and effectively through multiple sources of information using the information and communication tools, Massive Open Online Courses (MOOC) which are available free of cost in the internet; reforms in governance which includes the lessening of the government involvement and increasing the role of alumni, external experts, promotion of performance-linked funding, transformation from monitoring the inputs to the regulation of the outcomes, making accreditation compulsory, encouraging the private and foreign participation, thrust toward an international collaboration. To achieve all these the faculty should possess a vision of the future and a holistic approach toward education. This is possible only through the appointment of the faculty

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with a future orientation toward education. Thus, it is very clear from the research literature that the recruitment and selection of the universities should be very well designed on par with the international standards so that it attracts the best of the talent who can build a knowledge base to promote all the innovative plans of the universities. 2.1.2

Compensation and Reward

Compensation & Reward (CMR) is defined by the American Compensation Association as the cash and non-cash payment offered by an employer for services provided (Osibinjo et al., 2014). For those workers who are happy, inspired, and drawn to work, CMR is the human resource management element. The incentive for performing organizational tasks is granted to these workers, with the desired result of achieving organizational objectives (Ivancevich, 2004). Direct compensation requires salaries, incomes, incentives. CMR to be the strategic tool for employee performance and retention claims Osibinjo et al., (2014). Falola et al. (2014) have linked CMR to the employee attitude toward work and job satisfaction. For the universities to take off and achieve their strategic goals, it is essential to attract, retain, and maintain competent and satisfying teaching faculty who are qualified, experienced, and committed to their job. Hartman (2011) spells out the point that the faculty package must be communicated to them and be made transparent with the salaries, bonuses, incentives, allowances, promotion, recognition, and reward systems. The changes brought about in these benefits from time to time must be updated and circulated to the faculty members. Research evidence exists that CMR affects results. The Operant Conditioning Theory was developed by the behavioral psychologist B. F. Skinner (Hitchcock & Willard, 1995; Kohn, 1993). If an employee’s success is rewarded, he is more likely to repeat the same acts by applying this principle to the organizational sense. Some scholars, however, do not adhere to this theory (Kohn, 1993). These scientists argue that more indepth research is needed to understand the role of compensation as a tool for employee satisfaction, efficiency, and retention. Researchers believe that companies must carefully plan the CMR to keep it competitive in the same company to ensure equity or else it will negatively impact the output of workers as they would have in their minds that they do not get

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what they want and it may act as a deterrent for top-quality performance (Lawler, 1996). Incentives are calculated in the CMR package to have a significant impact on employee results (Osibinjo et al., 2014). It is the award granted by an employee for the achievement of certain predetermined goals that are explicitly related to results and positively linked to organizational goals. Incentives have been related to the Vroom (1964) Valence Principle quoted in Osibinjojo (2014). According to this theory, if the expectancy matches the outcome and the performance through the effort is appropriately rewarded satisfaction occurs or else dissatisfaction occurs. So the CMR in organizations should be prepared to provide the employee with the reward for their outcome. Incentives are the extra payment given in recognition of the additional effort exerted by the employee so that he/she is encouraged to contribute more to the organization and get benefitted further. This will also motivate other employees to perform in a similar manner and on the whole the organization gets benefitted. Another theory which predominantly influences the CMR is the theory proposed by the behavioral psychologist B.F. Skinner has the Theory of Operant Conditioning (Hitchcock & Willard, 1995; Kohn, 1993). According to this theory, if a particular behavior is rewarded the organism replicates that behavior again and again and in the contrast, if the behavior is punished, that behavior is not repeated. 2.1.3

Performance Appraisal

In organizations worldwide, performance evaluation (PRA) is performed (Palethorpe, 2011). The foundation for promotions, salary, bonuses, increases, thorough and meaningful reviews, and career advancement are PRA. Boswell and Boudreau (2002) found that PRA values, abilities, and experiences that workers can acquire (e.g., training and development needs). Organizations have discovered in today’s knowledge-based economy that it is the intangible assets that add value to the product or the server. PRA gives a distinct opportunity to the immediate supervisor direct feedback to the employees about their performance. Each factor will be rated separately and is independent of other factors. The employee will be allowed to perform a self-appraisal of performance and compare the same with the evaluation of the supervisor. It is a very good opportunity for the employee to compare the desired state of performance and the current

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state of performance so that the gap can be identified and appropriately filled. At the same time, it also provides a unique opportunity to set the performance goals for the next year. This process will repeat and the employee’s performance level over some time can be made available for the benefit of both the employee and the immediate supervisor. The PRA is grounded well in principles that are designed to manifest the corporate vision into reality. The principles include the translation of the organizational goals into divisional, departmental, team, and individual level; it provides strong support to the organizational goals; it is designed to evolve over some time; it believes in the shared understanding of the manifestation of corporate vision into reality; it encourages selfmanagement of the employees; it encourages the management to have two-way communication at all levels of operation; it provides permanent feedback; the system provides an opportunity to develop the corporate objectives further; it provides a means to measure all the performance of the employees against the set goals; and it applies to all the employees of the organization (Armstrong, 2000). 2.1.4

Teamwork

Teamwork is a supportive process that helps ordinary people to achieve extraordinary results (Scarnati, 2001, p. 5). Teamwork depends on individuals to share their expertise and talents by sharing their skills and information. The literature consistently emphasizes that the basic element of the team is to concentrate on a simple and shared objective (Fisher et al., 1997). Some researchers have also provided empirical evidence for this purpose (Fay et al., 2014). Even though creativity can be an individual effort for innovation to take place a group-level input will be required (Hulsheger et al., 2009). This is because there are socio-cultural issues in the context of innovation when individuals interact with each other concerning a common problem. In such a situation, relatively speaking, there will be lesser power distance and people will be free to communicate with each other and it forms an ideal situation to bring out individual creativity. It is important to note that diversity, flexible boundaries, and collaboration that make teamwork succeed (Hemlin et al., 2008). Research studies have shown the demographic variables of the team also have a positive correlation with knowledge creation and innovation.

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Teamwork is a multidimensional construct because innovative organizations need to be flexible and increasingly rely on all kinds of teams for knowledge creation and the organization has to have the natural ability of adaptation and renewal (Vivas-López, 2014). In the framework of higher education, the business scenario is becoming competitive and the intangible knowledge-based assets that can be generated through creative teams become important for the gaining of the competitive advantage. Effective TMW and strategic team management are considered to be essential elements to foster knowledge management and promote organizational learning processes which are the key enablers of innovation. This once again underscores the importance of TMW. 2.1.5

Training and Development

By enhancing the KM among the faculty members in institutions of higher education, the TRD plays a crucial role in fostering creativity. There is TRD, as established by this research, which takes place in higher educational institutions, but it is not professionally carried out based on human learning theories. The starting phase should be the identification of the knowledge and skill gaps between the desired state and the current state of performance of the employees. This will identify specific skills and competencies which need to be developed among the faculty members to accomplish the corporate objectives, which in turn enable the manifestation of the vision of the institutes. Even though there could be some common training programs across the institutes, there could be many other institute specific programs necessary based on the skill and competence pool available in the institute and the specific vision of the institute (Bird, 2015; Longenecker et al., 2014; Maley, 2013; Rowland & Hall, 2013; Tuytens & Devos, 2012). The TRD is perceived in many different ways as far its implementation and effectiveness are concerned. According to Tharenou et al., (2007) conceptualizes training to have four major measures of effectiveness which are: Absolute measure which refers to the quantifiable dimensions such as the amount of training imparted to the employees; Proportional measures which refer to the percentage of the workforce trained; Content measures which refer to the type of the training provided; Emphasis measures which refer to the relative importance of the training to the organization. According to researchers knowledge workers in an organization have to up-skill themselves time to time to develop a wide range of skills that

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are essential to the success of their organizations as the demand from the external environment changes. This makes it imperative that TRD is the ultimate solution to keep the employees adequately responsive to the changing demands of the customers (Grossman & Salas, 2011; Slavi´c & Berber, 2014; Tregaskis & Heraty, 2012). Researchers also claim that TRD can accelerate knowledge acquisition and make learning easy and that is the reason why it is effective in preparing the knowledge workers for the future (Lekovi´c & Šušnjar, 2010). Organizational performance in a knowledge-intensive service sector such as a university is based on the intellectual capital they possess and the innovation they can bring about in the teaching–learning processes. This is where the mediating effect of knowledge management processes becomes important. The TRD as a part of the HRP will have to add to the efficiency of knowledge management to drive innovation in the university.

2.2 2.2.1

KM Processes Knowledge Diagnosing

Alderfer (1981) defines knowledge diagnosis (KND) as a process that involves collecting data regarding human experiences and giving this input in the system to encourage organizational performance. Some managers have natural abilities to rightly diagnose the knowledge which contributes to the organizational performance based on their personal experience and some may have to be trained to seek knowledge. Several researchers have contributed, particularly knowledge enablers, to the diagnosis of organizational knowledge formation, e.g., Nonaka and Takeuchi (1995) have five enablers to convince the SECI systems, five enablers to enhance creativity by Krogh et al. (2000), and nine obstacles to knowledge tackiness by Szulanski (2003). Another category is the evaluation of knowledge creation capability (KCC). Considering that knowledge creation is a result of the SECI modes that can be measured and scored, weakness in or absence of any mode has been found to prevent the knowledge spiral from moving forward. In universities, the most relevant knowledge which is important for future use must be diagnosed by the knowledge workers in the institutes. To increase competitive advantage in the market through innovation it is very much essential to diagnose the most appropriate kind of knowledge. There is research evidence to prove that the organizational

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failure is attributed to its inability to diagnose the appropriate knowledge (Delong, 2004). At the same time, researchers have found that superior performance is possible only through the diagnosis of the right kind of knowledge (Suorsa & Huotari, 2014). All these studies adequately support the point that for the success of the organization it is essential to diagnose the right kind of knowledge so that it would be useful in promoting innovation. It is also clear that ultimately the HR support makes KND work in an organization because you need the right kind of people who have the foresightedness to look into the future and seek the relevant knowledge. 2.2.2

Knowledge Acquisition

Knowledge acquisition is the ability of an organization to trace, understand, value, and develop external knowledge that is very important for its operations (Hoarau, 2014). Information acquisition at an individual level is a set of items, one of the two essential characteristics of the cognitive or mental model is (Alavi & Leidner, 2001; Gray & Meister, 2004; Nonaka, 1994). Awareness is the agreed belief in the truth (Nonaka, 1994), knowledge is gained by people adapting to their healthy agreement by altering their faith that the acquired knowledge is correct, which was also noticed by Nonaka, Gray, and Meister. The object of practicing knowledge is the second aspect. The true trust of individuals must enhance their capacity for actual achievement (Alavi & Leidner, 2001) and achievement isn’t achievable without a strategy to apply information. Pattinson and Preece (2014) analyzed interviews taken by six sciencebased SMEs and observed that both Communities of Practices (CoPs) were influenced for different purposes which were intra- and interorganizational, containing the KNA and educating the firm’s capability toward creating innovative results. This study has shown the importance of KNA in supporting innovation in an organization. It is vital to note that the establishment of a CoP is essential for the success of KNA because a group of like-minded people are required to be connected well and have several rounds of deliberations to arrive at the exact kind of knowledge to be acquired to meet the corporate purpose and manifest the vision of the organization into reality. How information can be gained is an important topic because it is unique to the company. In certain organizations, internal and external information development is a requirement for the process of innovation.

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Individual learning is typically informal, and CoPs encourage the acquisition, sharing, and distribution of information that they have acquired as an intern as well as in the organization. CoPs focusing on apprentices in these organizations were better choices for developing their existing skills and promoting informal pieces of knowledge. Individual learning is necessary for the acquisition and innovation of information, but the perspective of the manager was to be connected to the commercial objectives of the business. Although managers understood the importance of individual learning for knowledge acquisition and innovation, they believed it had to be connected with the firm’s commercial goals. By limiting the knowledge realm, could stifle the emergence or cultivation of CoPs. Because some specific knowledge that employees would like to acquire may not have been of immediate commercial value and its relevance may emerge after a significant length of time, one cannot expect an employee to acquire knowledge just from a commercial standpoint as the managers desire. In general, every organization would have potential and realized absorptive capacity (Hoarau, 2014). 2.2.3

Knowledge Generation

To sustain it, knowledge generation in higher education is a store of knowledge and its distribution. Consequently, knowledge sharing is the transfer of knowledge between various departments and organizational members (Griese et al., 2012). Knowledge transfer facilitates the university’s multidisciplinary and interdisciplinary dissipation of knowledge. For subject-related exchanges of information, communication between individuals or groups is necessary in the first place. These practices of information exchange are in implicit form. The synthesis of a variety of abilities and expertise of individuals creates new knowledge (Madhavan & Grover, 1998). Knowledge is often exchanged via electronic, written records, or registered data, which can be accessed as needed by other employees (Haas & Hansen, 2007). Like traditional management, knowledge generation also requires these four practices to be effectively implemented to create knowledge, such as organizing, arranging, managing, and staffing. It requires teamwork to recognize, analyze, interpret, and share knowledge among the knowledge workers so that it becomes an essential fragment of organizational knowledge. According to some researchers use of knowledge by the employees is required for converting discrete knowledge into collective knowledge (Nonaka, 1991). Therefore, knowledge

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generation is a result of skills, practices development, and application of knowledge in the organization by its employees (Lane et al., 2006). In a customer-based organization, the processes, activities, behaviors, and actions of organizational members help in knowledge generation, and here the participation of HRP becomes important (Lane et al., 2006). There is little chance to succeed in the KNG unless the knowledge workers develop the right attitude toward knowledge sharing and build a cohesive environment that nurtures organizational learning. Freeman (2010) was the first to note that KNG can only be sparingly prosperous if an innovation scheme is in place. All these studies have ultimately linked KNG to the innovative output of the organizations the direct measure of which is the number of patents filed. Freeman has established a strong linkage between KNG and innovation and he claims it to be a cyclic process and the complex the knowledge generation the advanced will be the rate of innovation. The study revealed that with each cycle the KNG rate will increase. It was also observed that with the cycles of operation, the complexity level of innovation and the corresponding knowledge generation will also increase. The research makes the point clear that with the cycles of operation of KNG and innovation the competency level of the employees must also increase and the tools used for knowledge generation must also be advanced. Time shows a very vital role here as the KNG mechanism in the organization should reduce the time taken to generate new knowledge at the end of each cycle should reduce. 2.2.4

Knowledge Sharing

Sharing expertise will greatly support the university by constantly bringing up-to-date science, curriculum, and consulting services to the university. Some technologies such as SalesForce.com, BMC Software, DCASoft, and Atlassian are used in educational institutions, government, and business sectors as information sharing applications (Hedgebeth, 2007). Designed Behaviour Theory (TPB) (Ajzen, 1991) is ideal for the success of information sharing that can be defined precisely in the knowledge worker. Each of the basics of a TPB containing behavioral defiance, individual customs, the alleged behavior behavioral mechanism as well as its intent is considered to be part of real action (Ajzen, 1991; Tohidinia & Mosakhani, 2010). An approach to a particular action is the evaluation

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of that behavior by an individual while deciding to achieve it (Kim et al., 2009). An organization should persistently inspire knowledge sharing since knowledge is the establishment’s scholarly investment and driver to gaining a competitive advantage. Hence employees must share knowledge with co-workers and jointly apply it in problem-solving and innovating. Most of the researchers have found that one of the difficulties of knowledge management is to share their knowledge with their peers (Moses & Ifeoma, 2014). While some organizations are found to share knowledge as it is their survival, some are not tuned well to it. Innovation comprises varying the technique, imagination, restoration, and enhancement from existing practices in the organization. Bottlenecks in KNS may be both at individual and organizational levels. Real knowledge sharing happens when proper appliances are put together in an organization and the culture of KNS is established in the organization. Speaking in terms of the universities as they are the institutions of higher learning there is a natural process of KNS in the form of conferences, discussion forums, debates, symposiums, bulletin boards, etc. These are the forums for explicit knowledge sharing, but the problem is in the sharing of the tacit knowledge of the teaching faculty. Some of the premier institutions have developed a full-fledged knowledge management system in which all the individual components of KM are very well supported and a Chief Knowledge Officer (CKO) is appointed whose primary role is to coordinate all the knowledge sharing and related activities and make the right kind of the knowledge reaches the right person at the right time. However, KNS is considered to have still some barriers as the teaching faculty live in ‘silos’ and the professional jealousy makes them hoard knowledge (Lam, 2000). This tendency will have to be overcome if KM has to lead to innovation. 2.2.5

Knowledge Storing

The purpose of KM is to stock the organizational knowledge for the coming generation as there are several changes in the organizations from time to time as there is continuous hiring, firing, and changing of jobs by the people but the company is committed to growing. Hence a robust way of storing the knowledge precisely is requisite to retrieve it with ease in the least time. Recruitment and training practices considerably bring changes in the practice of knowledge sharing and storage (MagnierWatanabe & Senoo, 2008). Data warehouses are the main unit of the

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KM structure. Organizations store data in several records and the data warehousing process extracts data captured by multiple business applications and organizes it in a way that provides meaningful knowledge to the business, to access it for future reference. Data in knowledge bases can be imperfect, fuzzy, and comprise a cause of ambiguity. The knowledge in the knowledge bases is stored based on instructions. There are other forms of database such as data mart, data repository, and document management systems (Hsu et al., 2006; Pérez et al., 2002; Sukula, 2006; Rah et al., 2010; Roknuzzaman, 2009; Yulong et al., 2012). Resource-Based Theory (RBT) is a widely accepted theory according to which any firm which has the most current resources will have a natural ability to increase competitive advantage in business (Kozlenkova et al., 2014). The RBT is a multilevel perspective and has been discussed in the research literature at three different levels. The first is the marketing domain which includes marketing strategy, international marketing, and marketing innovation. The second level is market-based resources which include the building of the brands, customer dealings, and knowledge is different from the resources studied under non-marketing contexts. This includes the intangible and complementary resources whose effect will be mainly on the gaining of competitive advantage in the market. The third level is the exchange level of analysis which mainly focuses on the theoretical inconsistencies. This deals with the effectiveness of the various processes, policies, and the skills of the employees at the exchange versus the firm level. So, the theory points to the fact that the organization should be able to store knowledge systematically and ensure that the knowledge applies to the current situation and should exploit the skills and competencies of the knowledge workers to enable them to encourage innovation and gain the competitive advantage in business (Fang et al., 2011). The extension of RBT is the Knowledge-Based Theory (KBT) according to which knowledge possessed by the firm is considered to be the most strategically significant resource. It is the knowledge-based resources that provide a competitive advantage in the market as it is difficult to duplicate, complex, and heterogeneous. 2.2.6

Knowledge Application

While businesses actively develop resources for the exchange of information and its circulation within organizations, it is unclear if this tool enhances

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the application of knowledge. Knowledge application is the knowledge gained from other employees or units that are practically implemented in a specific organizational unit. The next step after information sharing in the Knowledge Management cycle is proposed by knowledge application (Dalkir, 2005).

2.3

Innovation in Higher Education

The first fundamental question that may arise in this kind of research is, ‘why innovation in the service sector in general and higher education in particular?’ The fact is that in the knowledge economy post-globalization, there is a growing awareness that to sustain the stiff competition, there is a need to meet the challenges offered by the society, as well as to anticipate the future challenges and be prepared with innovative solutions to these problems. Speaking in terms of higher education, for the higher educational institutes to be creative and innovative in their approach to the challenges posed by society in the scientific, technological, cultural, social, political, and economic fronts there is a need to radically examine the drivers of innovation and strengthen them so that the universities are transformed into knowledge repositories which can adapt to the societal changes. Innovation is a new concept, process, or device and transformation that can improve the organization’s efficiency, based on principles of management through Peter Drucker (Hesselbein et al., 2002). The word output can also have various dimensions here. It can be the operational performance, business performance, marketing performance, human resource performance, knowledge management performance, technological performance, financial performance, non-financial performance, R & D performance, and many such performances essential for the survival of the organization. The same meaning is also applicable to the higher educational institutes, and it could be just an innovative way of doing things to increase the performance in terms of its efficiency. The higher educational institute’s performance could be on administrative performance, teaching–learning process performance, and product and services offering performance, placement performance, support services, operations, etc. Higher education institutions may need to balance the operation of a large organization affected by external factors such as competition, ranking requirements, market rankings, accreditation requirements. Therefore,

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some transition has led to new approaches to enhance the performance of higher education institutions. White and Glickman (2007) consider flexibility to be one of the most important aspects to be considered as a product of innovation. From Plato’s academy in 1249 AD to Morril Act in 1862 in the United States, the landscape of higher education has been continuously changing and the most striking observation is that the flexibility in terms of curriculum, teaching–learning processes, and the courses offered is constantly on the rise. Universities have been continuously looking into the quality aspects, novel technologies in learning, ways to reach students with learning disabilities of different kinds, and curricular innovations. It is significant to note that the terms ‘quality’ and ‘innovation’ as per the literature (e.g., White & Glickman, 2007) are ongoing processes even in the context of higher education for the products and services offered. But it is interesting to note that initiating a quality drive such as Baldrige National Quality Program in higher education in specific areas such as curriculum design; pedagogy; student services; and support operations for conducting admission, examination, lectures, etc., helped in driving innovation (Donofrio, 2006). Technology focus is another widely discussed area for innovation in higher education according to White and Glickman. Universities are continuously trying to exploit technology to enhance the performance efficiency in the operations to be managed in the higher educational institutions. These operations could include the processes involved in student admission where technology can be exploited in the form of its capability of online entrance and seat offering, or teaching–learning processes, assessment processes, and a whole lot of such activities and the processes. Innovations are also required in meeting the specific requirements of the students who have many different learning styles. The learning styles of the students are mainly based on their learning preferences: visual, auditory, and kinaesthetic. Some learners who can learn faster by visual information, learn faster through graphs, pictures, and overheads, however, an auditory learner chooses to learn through talks, loud reading, and dialogue. Kinesthetic learners can learn better by doing it themselves (Bandler et al., 1981). Technology can be of immense help to each of these styles and can provide innovative solutions to the problems encountered with the regular mode of teaching. In the case of students with dominant visual preference technology in the form of multimedia can be used and the animation can provide them the visual effects which makes

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studies more interesting. Those dominated by the auditory style can make use of the podcasts and listen to the lectures. The students dominated by kinaesthetic styles may be facilitated through educational electronic games wherein they work on the specific tasks which are exclusively designed to learn a particular topic. There are several organizations like Universal design for learning, which implement new innovative technologies for the creation of content, its presentation, and delivery. Curricular innovation is another area in which the higher educational institutes have focused on late as per White and Glickman. The most important aspect for building the market standing is the accreditation of the governing bodies both at the national and international levels and the accreditation bodies look for innovation in curriculum design and how an educational institute is distinctly different from its counterparts. Curricular innovation includes almost all the academic aspects of a university and its constituent colleges. Lawson (2005) has recommended that the curriculum of the future has to have a student-centric focus instead of the teacher-centric approach to learning, the issue-based focus instead of logic and competence-based instead of performance-based, and the approach should be trans-disciplinary instead of single discipline-based understanding. The most important aspect according to this paradigm is to meet the personal learning goals of the students in addition to the societal requirements to be fulfilled through higher education. Technology can again be a tremendous driver to innovation in curricular innovation (JISC, 2012). Technology can enhance the information flow, information can be made authentic and reliable, administration aspects can be made more efficient, approvals can be streamlined, access for the sources of pedagogical guidelines can be made easier, and consistency in quality assurance can be guaranteed. So, the universities may have to take a stand on the augmentation of their technological requirements in the curricular aspects. In addition to all the innovation areas in higher education, some general aspects require innovation such as ancillary operations. The present generation of students are techno-savvy and expect a lot to be learned through electronic gadgets and multimedia usage rather than the traditional classroom environment. This will require a lot of hardware and software requirements and a paradigm shift on the part of the faculty members to facilitate the usage of the electronic media to supplement their lectures. Innovation is also required in student performance assessment and grading by the usage of technologies so that the human factor

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involved may be eliminated to the extent possible. Content and knowledge management systems are other technological supports that can be used by the universities for making the knowledge generation process more streamlined and also save the intellectual property for future use. Knowledge innovation must be the objective of every university worldwide. By the process of Innovation, there is a creation of novel products and services. Innovation has gained importance in both product and service-oriented industries and has become a survival tool in the present business world and it happens due to the interaction of many heterogeneous systems, but most studies have emphasized methods that result in tangible innovation (de Zubielqui et al., 2015) rather than the activities and connections among the enablers of innovation. In the context of innovation of higher education, the emphasis must shift to the enablers and the drivers of innovation because there is a need to produce a robust mechanism that can support innovation in the teaching–learning processes, general service processes, courses offered as well as marketing techniques. Researchers have identified that studying innovation in isolation will not improve the system much, instead, the heterogeneity of the innovation as a construct needs attention and it has to be studied for its association with knowledge workers, processes, systems, practices, technology, and all the drivers and the enablers (Cantù et al., 2012). Research studies have revealed that innovation is reliant on the ‘external knowledge’ that enters into the organization via the systems and tools which facilitate inter-organizational networking (Seely-Brown & Duguid, 2001; Westerlund & Rajala, 2010). When we speak about the inter-organizational relationship in the context of a university, it can be either formal or informal but as long as there is knowledge in bringing the purpose remains solved. This again reiterates the importance of human resources because it is they who have to make things happen so the HRP has a role to play in driving innovation. At the second stage, having realized the importance of inter-organizational relationships and the establishment of the linkages there must be appropriate knowledge management mechanisms that emphasize the need to have the appropriate KMP. The term knowledge in different contexts can also be for an economic product, strategic supply, or a social concept (Assudani, 2005) and when it comes to university it could be all three depending upon the program of study. However, strictly speaking, the purpose of HE institutions must exist for the social construct as it is more of the moral responsibility the universities have in building a better society with

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morally upright, ethically abiding, environmentally sensitive citizens who can think ahead of their times and contribute to the GDP of the country. So, to spur this kind of innovative spirit among the students, universities must be equipped with the necessary systems and practices in place with the right kind of knowledge workers to manage their operations. This makes it imperative that the universities must be the hubs for the product, process, and organizational innovations which are discussed in the subsequent sections. Research on service innovation (or process innovation) has increased along with the growth of the service sector post-globalization (Miles, 2000). The demarcation approach postulates that service and product innovation cannot be having a common theoretical foundation, and process innovation requires its theoretical framework to fully understand the concept. This research is based on the assimilation approach and hence considers both the innovation to be under one theoretical framework. 2.3.1

Product Innovation

The innovation of goods is different when the expansion is driven by a need to advance the products’ properties and efficiency. Innovation is about improving new goods, their characteristics, or their efficiency (Bergfors & Larsson, 2009). While the radical innovations are unique the first of their kind, and a previously unknown product have been successfully invented, manufactured, and distributed into the market. Incremental innovation, on the other hand, takes the shape of tiny enhancements to an existing product that adds value to the same old product, as the name suggests. The literature stresses information technology, the company’s design strategy, and leadership and culture are all facets of product innovation (Valencia et al., 2010). Further research results are found in the product and service areas, but not in the service organization of the university. Product aids from universities are marketed as projects, inventions, patent files, etc. A university should adopt an innovative approach to its goods and services to be sustainable. Whatever may be the approach to product innovation, it must apply a new idea to the product and most importantly it must add value to the product concerning the existing ones. Even though universities may be compared to the process industries because they mainly deal with the

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processes of student learning, thorough product offerings in a university which comprises all the hardware supply to facilitate learning or the students themselves who enter as the raw material to the university go out as the finished products who are saleable in the market for the knowledge, skills, and competencies they possess. So, what innovations the industries look for in their products could be thought of in the context of HE also. If the university has a specific method to enhance learning in terms of the magnitude of learning or the speed with which learning takes place, it could be put under the group of product innovation. The same principles of product innovation in the context of the industries are applicable in the educational institutions also as the students who graduate themselves are the products of the institution. 2.3.2

Process Innovation

Improving processes introduces new and enhanced delivery methods that are beneficial to the client. Method creation entails substantial changes in production processes, equipment, and/or applications (Ashok et al., 2014). Thus, process innovation (PRI) is the growth determined by its internal production aims, such as reducing the cost of production in goods, having higher income by production, enhancement of volumes, recoveries, as well as producing environment-friendly products. PRI work is mainly focused on the requirements of production by its customers who are primarily driven by efficiency. Process innovation is a key enabler of product innovation according to Bergfors & Larsson. The sources of IT process innovation relate to innovation studies, socio-technical colleges, and science management. Through research on the diffusion of innovation (Rogers, 1962), process innovation has adapted technology and organizational structures and processes to implement innovation. Process innovation uses IT to improve the work processes and productivity of an enterprise (Porter & Millar, 1985). As a service company, process innovation has a primary role to play in a university. Hence, innovativeness is necessary for the sustainability of the university (Decter et al., 2007; Drabenstott, 2008). Distribution of the mobile/cloud environment has removed the limitations of time and space, enabling us to work in ways that are free and cost-effective in the HE. Frishammar et al. (2012) emphasized the need to focus on firm-level factors to enhance the rate of PRI; however, ignoring the external resources would not be a good idea as the progress

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in the external environment has to be one of the factors to be considered in the context of HE. Ashok et al. (2014) analyzed the usage of the quantity of end-user partnerships and external associations in the PRI and found that teamwork plays a key role in service sector innovation, while several external alliances provide alternate processes to make the system more effective. The main result of the study is ‘value identification’ of the external knowledge had a great influence on the eminence of PRI. Further, Ashok et al. (2014) highlighted that internal resources are typical to encourage collaboration and encourage learning with associates, and interpret cherished external knowledge into a competitive advantage for the organization. 2.3.3

Organizational Innovation

An organizational advancement (OGI) is characterized as a cutting-edge organizational approach within the sector of the company that sharpens the organization of the working environment or external relations. OGI may be orchestrated to improve the execution of a company by minimizing administrative costs or trade costs, advancing the fulfillment of the work environment (and thus labor efficiency), the execution of a company Achieving the acquisition of non-tradable properties (such as non-codified external data) or reducing supply receipts. Exchange sharpens include organizational components such as expert, culture, organization of human resources, organizational shapes monitoring the progress of exchange, structures of execution and spurring drive and defiant learning, and corporate contact from outside and within. Organizational change can lead to either ‘new-to-the-state-of-the-art’ or ‘new-to-them-business’ (Mol & Birkinshaw, 2009). Organizational changes can result from overwhelming diffuse organizational factors, but also more popular handling of innovations within a specific company in an exact setting (e.g.,). Organizational growth, following Hamel (2006), creates longstanding competitive points of interest. Different researchers have hypothetically associated forms of information management with organizational success. Organizational performance is typically influenced by strategies, interventions, and intensive human data (Badaracco, 1991). O’Dell et al. (1998) suggested that an organization’s knowledge makes a difference in the execution of organizational errands. Subsequently, it is important to use mental resources within organizations effectively to increase organizational development,

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to advance the knowledge forms of the individuals of the organization, and to enable employees to always contribute to the information sharing (Villadsen, 1995). The best prerequisite for trade competitiveness is the ability to make great use of information and properly achieve and implement this information internally within a business (Leonard-Barton, 1995; Prahalad & Hamel, 1990). The OGI includes a coordinated impact through several HRP which incorporates execution administration that gives the proper signals appropriately advancement prospects to each worker inside company; compensate and acknowledgment that rouses the workers; ability administration for a personal representative that guarantees that all the workers get it the unique aptitudes and practices required to effectively enhance; ability administration for groups that produce the workers break working in silos; talent management for leadership that makes the people getting dissatisfaction with the keeping of status quo; categorizing the serious roles that certifies full proficiency in innovation processes; organizational design that designs the organization to maintain the innovation strategy, fast-tracking the idea lifecycle and encouraging collaboration; internal communication that encourages cross-organizational networking and collaboration for innovation; and change management that facilitates the application of new operational practices that drive innovation (KPMG, 2013).

2.4 Literature Review Summary and the Research Gap The literature review has given an awfully clear understanding of the research constructs and the individual dimensions of each construct. A detailed review of literature on human resource management practices has provided linkages between HR practices with knowledge management which is again a pride driver of innovation. Whereas there are a few measurements of Human Resource Practices, it was found that recruitment and selection, emolument and remunerate, execution evaluation, cooperation, and training and development risen as the most donors to the management of information within the higher instructive organizing. In the research construct, knowledge management practices the dimensions of knowledge diagnosing, knowledge acquisition, knowledge generation, knowledge sharing, knowledge storing, and knowledge application played vital roles.

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Contemporary research in connection to innovation in higher education has indicated that there are quite a good number of studies that have explained the fundamental question of why innovation is required in higher education. Several aspects have been highlighted by a group of researchers which include flexibility, technology, learning styles, and circular innovation. The literature review also indicated that the research construct innovation had product innovation, process innovation, and organizational innovation as the three distinct components of innovation in the perspective of higher education. The literature review has shown that HRP had an influence on the KMP in the context of HE and KMP in turn influences the innovation that takes place in the higher educational institutions. The main research gap is that most of these studies are theoretical and subjective and there’s no observational prove (empirical evidence) for the relationship between the measurements of the three research constructs HRP, KMP, and INN in the form of causation. Even though some studies have established empirical evidence for the linkages between some specific dimensions there is no evidence for the presence of a single study that linked the individual dimensions of the three research constructs under investigation. So this emerges out as the research gap and an attempt has been made to fill this through an appropriate hypothesis and testing using the empirical study.

2.5

Summary

This chapter has recorded systematically the contemporary research on the three research constructs which were of focus in this research. The literature on HRP indicated that it had a role to play in the innovation of HE, and there was evidence to prove that various HR interventions were already in practice in the HE. Among the various interventions, it was found through an extensive literature review that recruitment and selection, compensations and benefits, performance appraisal, teamwork, and training and development were most relevant in the context of service sectors in general and were selected to be the dimensions of interest to this research. It was observed that the concept of knowledge management was not very dominantly practiced in all the universities but was the chief enabler of innovation in many premier universities in the world. The literature provided a clear foundation for defining the process for

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knowledge management that included: diagnosis of knowledge, acquisition of knowledge, generation of knowledge, exchange of knowledge, storage of knowledge, and application of knowledge. The literature on innovation in HE was rich in enumerating the efforts taken to modernize the education system and the felt need for innovation was very dominant in the research studies. The awareness about the alternative ways of teaching–learning was depicted by several researchers as it was the need of the knowledge-driven world. Certain key elements of innovation were observed in the research studies which included mainly flexibility, technology focus, and accommodating different learning styles of students. Circular innovation was observed dominantly in HE as the mode of innovation. The importance of ancillary operations was also highlighted by several researchers. Innovation had different orientations and was context-specific as per the literature; however, the three main components were process innovation, product innovation, and organizational innovation as applicable to the service sectors. There were adequate articles which had linked the HRP and KMP to innovation, but the purpose of this chapter was to give a clear dimensionality for the research constructs and the linkages between the individual dimensions are reported in the next chapter in the form of a structural model which forms the basis for the hypothesis development. ∗ ∗ ∗

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Mol, M. J., & Birkinshaw, J. (2009). The sources of management innovation: When firms introduce new management practices. Journal of Business Research, 62, 1269–1280. Moses, O. S., & Ifeoma, E. J. (2014). Overcoming cultural barriers to innovation and knowledge sharing: An organization perspective. International Journal in Management and Social Science, 2(9), 22–36. Mumford, M. D. (2000). Managing creative people: Strategies and tactics for innovation. Human Resource Management Review, 10(3), 313–351. Nelson, R. R., & Winter, S. G. (1982). An evolutionary theory of economic change. Belknap Press. Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company. Oxford University Press. Nonaka, I. (1991). The knowledge creating company. Harvard Business Review, 69(6), 96–104. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5, 14–37. O”Dell, C. S., Grayson, C. J., & Essaides, N. (1998). If only we knew what we know: The transfer of internal knowledge and best practice. Free Press. OECD (2007). Innovation strategy for education and training innovation: The OECD definition. International Journal of Sustainability in Higher Education, 1(1), 124–136.http://www.oecd.org. Osibinjo, O. A., Adeniji, A. A., Falola, H. O., & Heirsmac, P. T. (2014). Compensation packages: A strategic tool for employees’ performance and retention. Leonardo Journal of Sciences, 25(1), 65–84. Palethorpe, R. (2011). Learning and development. Industrial and Commercial Training, 43(6), 394–395. https://doi.org/10.1108/00197851111160531. Pattinson, S., & Preece, D. (2014). Communities of practice, knowledge acquisition and innovation: A case study of science-based SMEs. Journal of Knowledge Management, 18(1), 1–29. Pérez, M. P., Sánchez, A. M., de Luis Carnicer, M. P., & Jiménez, M. J. V. (2002). Knowledge tasks and teleworking: A taxonomy model of feasibility adoption. Journal of Knowledge Management, 6(3), 272–284. Porter, M., & Millar, V. (1985). How information gives you competitive advantage. Harvard Business Review, 63(4), 149–160. Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–93. Rah, J. A., Gul, S., & Wani, Z. A. (2010). University libraries: Step towards a web based knowledge management system. Vine, 40(1), 24–38. Rogers, E. (1962). Diffusion of innovations. Free Press. Roknuzzaman, M., Kanai, H., & Umemoto, K. (2009). Integration of knowledge management process into digital library system: A theoretical perspective. Library Review, 58(5), 372–386.

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Rönnblom, M., & Keisu, B. (2013). Constructions of innovation and gender (equality) in Swedish Universities. International Journal of Gender and Entrepreneurship, 5(3), 342–356. Rowland, C. A., & Hall, R. D. (2013). Perceived unfairness in appraisal: Engagement and sustainable organizational performance. EuroMed Journal of Business, 8(3), 195–208. Sarwar, S., Aslam, H. D., & Muhammad I. R. (2012). Hindering factors of beginning teachers’ high performance in higher education Pakistan. International Journal of Educational Management, 26(1), 27–38. Scarnati, J. T. (2001). On becoming a team player. Team Performance Management: An International Journal, 7 (1/2), 5–10. Seely-Brown, J., & Duguid, P. (2001). Knowledge and organization: A socialpractice perspective. Organisation Science, 12(1), 198–213. Shaw, S., & Fairhurst, D. (2008). Engaging a new generation of graduates. Education and Training, 50(5), 366–378. Slavi´c, A. & Berber, N. (2014). The impact of training on organizational outcomes in the CEE region—Focus on hungary, Serbia, Slovenia and Slovakia. In Conference proceedings, Management, Enterprise and Benchmarking—In the 21st Century Budapest, Hungary. Sukula, S. K. (2006). Developing Indigenous knowledge databases in India. The Electronic Library, 24(1), 83–93. Suorsa, A., & Huotari, M. (2014). Knowledge creation and the concept of a human being: A phenomenological approach. Journal of the Association for Information Science and Technology, 1(5), 1042–1057. Szulanski .G(2003) Sticky knowledge barriers to knowing in the firm. Sage. Teece, D. (2000). Strategies for managing knowledge assets: The role of firm structure and industrial context. Long Range Planning, 33(2), 22–34. Tharenou, P., Saks, A. M., & Moore, C. (2007). A review and critique of research on training and organizational-level outcomes. Human Resource Management Review, 17 , 251–273. Tohidinia, Z., & Mosakhani, M. (2010). Knowledge sharing behaviour and its predictors. Industrial Management & Data Systems, 110(4), 611–631. Tregaskis, O., & Heraty, N. (2012). Human resource development: National embeddedness. In C. Brewster & W. Mayrhofer (Eds.), Handbook of research on comparative human resource management (pp. 164–184). Edward Elgar. Tuytens, M. & Devos, G. (2012). Importance of system and leadership in performance appraisal. Personnel Review, 41(6), 756–776. Valencia, J. C. N., Valle, R. S., & Jiménez, D. J. (2010). Organizational culture as determinant of product innovation. European Journal of Innovation Management, 13(4), 466–480. Valentine, D. B., & Powers, T. L. (2013). Generation Y values and lifestyle segments. Journal of Consumer Marketing, 30(7), 597–606.

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CHAPTER 3

The Link Between Human Resource Practices, Knowledge Management Practices, and Innovation

Abstract This chapter has established the linkage of the five dimensions of the human resources management practices with the six dimensions of knowledge management processes and then the linkage between the knowledge management processes dimensions with the three dimensions of innovation with the support of the research literature in the framework of higher education. This linkage development is one of the objectives of this research. Several views and opinions of the researchers have enabled the building of the relationship which is portrayed in the conceptual research model. While some linkages have empirical evidence, some have a strong grounding in theory. This chapter provides the foundation for the development of the structural model. The subsequent chapters would deal with the identification of the appropriate research methodologies and the testing of the relationships in the form of the hypotheses developed in this chapter. Keywords Human resource practices · Recruitment · Teamwork · Training and development · Compensations and reward · Performance appraisal · Knowledge management · Knowledge diagnosis · Knowledge acquisition · Knowledge generation · Knowledge sharing · Knowledge storing · Knowledge application · Innovation in higher education · Product innovation · Process innovation · Organizational innovation

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. Ara and K. K. Das, The Innovation Shift in Higher Education, https://doi.org/10.1007/978-981-16-2055-3_3

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3.1

Conceptual Model and Hypotheses 3.1.1

Overview

At the outset, the chapter highlights the current state of innovation in higher education (HE) and the role of HRM and HRP in this framework. The conceptual model developed in this research has been explained giving the details of the linkages between the individual components. Following the links between various dimensions of the research constructs, the hypotheses have been developed and listed. The research hypotheses formed in this chapter will be the basis for the construction of the structural model that will be empirically tested in this research, which will be discussed in the subsequent chapters. 3.1.2

Antecedents of Innovation in Higher Education

Innovation is seen as the process of turning opportunities and challenges into new ideas and adapting them to new or enhanced goods, processes, or business models (Teece, 2010; Tidd et al., 2005). Innovation in higher education has been the survival tool post-globalization and liberalization. Innovative organizations are characterized by better products and services, adoption of advanced technologies, and are repositories of the latest knowledge in their field (Bjornali & Støren, 2012). For the technological and organizational developments, it is important to educate the workforce and provide them with higher education because there is a need to bring out original ideas and advanced economies have solely banked on the higher educational institutes for driving the innovation (Paul, 2011). Knabb and Stoddard (2005) argue that for the dissemination of innovation on the market, a sufficient number of knowledgeable persons in possession of the updated technological skills needed to apply the newly available information should be available and that responsibility lies with institutions of higher education. The first critically acclaimed innovation model in higher education was developed by Lucas (2009), where it has been shown that individual productivity has grown through the capacity and initiative of change agents who pursue and process new ideas. This rare ability has been attributed to their investment in education and to the average quality and diversity of economic ideas, which in turn, are largely dependent on overall educational investment by the government. Thus, higher education innovation has a key role to play in a nation’s development.

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However, there are challenges which the universities have to face in the promotion of innovation. First of all innovation in an industry takes place as a group activity but in the university, the students work individually and memorize the concepts, theories, and formulae and pass the examinations (Kettunen et al., 2013). So the learning of one type may not be applicable in another environment. This calls for the need to make the curriculum extremely flexible, and the students should feel the type of knowledge accumulation and application same as in the organizations which demands a very high level of innovation to get into the current universities. The second challenge to be tackled would be the issue of collaboration across countries because innovation in the real world takes place through this form and educational institutes are seldom practicing this (Jung, 2011). Thus, the students may have to be provided with an environment to work with a team from across the countries through the usage of technology but this has not come in a way it should be except in a few universities. A group of researchers very strongly recommend collaborative group-based learning built on the theory of constructivism (Kirschner et al., 2009). Researchers have rightly identified that not much work has been undertaken to establish the linkage of innovation to its drivers particularly in the context of higher education (Amo, 2006; Bjornali & Støre, 2012). Tidd et al. (2005) established key internal factors that can drive innovative practices, including promoting an innovative culture within organizations through leadership, flattering organizational frameworks, a supportive organizational culture, teamwork, external customer focus, and the involvement of innovation champions or entrepreneurs. Bessant (2003) claims that employee involvement, continuous improvement, and a higher level of performance efficiency are the key factors that drive innovation. Cerinsek and Dolinsek (2009) emphasize the role of employees in bringing out innovation and expect the employees to be proactive and open to newer methods, processes, and challenging encounters. From this collection of innovation enablers, it is crucial that ‘better sharing of information and communication’ is the key to fostering innovation in an organization. All these findings converge to the point that human resource management and knowledge management are the main antecedents of innovation in higher education and will have to be seriously considered for their contribution into the competency development of the employees and exploitation of the collective knowledge from

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internal and external sources for bringing out the best possible innovations in higher educational institutes. This was discussed in the conceptual research model presented in the next section. 3.1.3

The Conceptual Model

Several research studies are linking Human Resource Management Practices (HRP) to Knowledge Management Processes (KMP) and further KMP to Innovation (INN) in an organization. The general perception of academics as well as the practitioners in service and product industries is that the efficiency of the HRP would determine the efficiency of the KMP, which in turn, influences the INN in a product or service-oriented organization. These links between the three constructs are discussed separately in the following sections. The hypothetical research model linking the three constructs is shown in Fig. 3.1, and the relations between the constructs are discussed in the following sections. 3.1.4

The Link Between HR Practices and KM Processes

A large number of research papers have linked HR practices to KM and have strongly argued and empirically demonstrated that most HR practices have an impact on the effectiveness of KM processes (Currie & Kerrin, 2003; Edvardsson, 2006, 2008; Evans, 2003; Hislop, 2003; Robertson & Hammersley, 2000). But the individual dimensions considered in these studies vary depending upon the context where the model has been developed. In the context of higher education, the main aspects of HR activities that are relevant include recruiting and selection, compensation & reward, performance & evaluation, teamwork, and training and development (Barney, 1991; Huselid, 1995; Wright et al., 2001). Today’s higher education organizations operate under uncertainty, instability, and change that cause different challenges to emerge due to the globalized environment wherein foreign universities establish their campuses in India either directly or through collaboration with wellestablished Indian universities (Bimpitsos & Petridou, 2012; Obeidat, 2014). Technological change and the increasing need for qualified employees and improved performance also characterize these innovative environments (Vanhala & Stavrou, 2013). This forces higher education

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Fig. 3.1 Hypothetical research model (Source Author)

institutions to gain a competitive advantage by updating information and knowledge and using the available knowledge to make the best use of the institution (Savaneviciene & Stankeviciute, 2011). Many researchers see the HRP as a crucial component of the company that contributes to the success of an organization by improving the intellectual capital to improve the efficiency of the system and helping to bring new products and services into existence (Dominguez, 2011). Researchers have also found that organizations can effectively deal with the challenges of the surrounding environment via innovative products and services that meet customer demands only through effective

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HRM practices that can impact the organization’s knowledge management through the right strategies (Fong et al., 2011; Juhdi, 2011; Lew, 2011; Othman, 2009). Ortega-Parra and Sastre-Castillo (2013). To help the organization adjust to the evolving world by grading information at regular intervals, the organization must provide a wide variety of human resource management activities. All these studies demonstrate that by managing human resources, organizational expertise can be improved by successful recruiting and selection, compensation and benefits, performance monitoring, collaboration, and training and growth to turn the organization into a high-performing and creative organization. Despite these recent research findings in the recent past, there is no strong evidence for the empirical analysis to test the significance of the relationship between the dimensions of HR practices and KM processes, and thus the following conclusions have been postulated. Main Hypothesis: HAa : HAo :

There is a significant influence of HRP on KMP. The influence of HRP on KMP is not significant.

Sub-Hypotheses: H1a: H1o: H2a: H2o: H3a: H3o: H4a: H4o:

The influence of recruitment on the diagnosis of knowledge is significant. Recruitment has no major influence on the diagnosis of knowledge. The influence of recruitment on the acquisition of knowledge is significant. Recruitment seems to have no significant influence on the acquisition of knowledge. Recruitment has an important influence on the generation of knowledge. Recruitment has no important influence on the generation of knowledge. The influence of recruitment on knowledge sharing is significant. Recruitment has no important influence on the sharing of knowledge.

3

H5a: H5o: H6a: H6o: H7a: H7o: H8a: H8o: H9a: H9o: H10a: H10o: H11a: H11o: H12a: H12o: H13o: H14a: H14o:

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The influence of recruitment on the storage of knowledge is significant. Recruitment has no significant influence on knowledge storage. Recruitment has a significant influence on the application of knowledge. Recruitment has no major influence on the application of knowledge. There is a substantial influence of compensation & reward on knowledge diagnosing. There is no significant influence on the diagnosis of knowledge by compensation & reward. There is a major influence on the acquisition of knowledge by compensation & reward. Compensation & reward has no significant influence on the acquisition of knowledge. There is a major influence on the generation of knowledge by compensation & reward. Compensation & reward has no significant influence on the generation of knowledge. There is a major influence on the sharing of knowledge by compensation & reward. There is no significant influence on knowledge sharing by compensation & reward. There is a significant influence on the storage of knowledge by compensation & reward. Compensation & reward has no significant effect on the storage of knowledge. Compensation & reward has a major impact on the application of knowledge. Compensation & reward has no significant influence on the application of knowledge. There is no significant influence on performance assessment on the diagnosis of knowledge. There is a significant impact of performance assessment on the acquisition of knowledge. There is no significant influence on performance assessment on the acquisition of knowledge.

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H15a: H15o: H16a: H16o: H17a: H17o: H18a: H18o: H19a: H19o: H20a: H20o: H21a: H21o: H22a: H22o: H23a: H23o: H24a: H24o:

Performance appraisal has a significant influence on the generation of knowledge. There is no significant influence on performance appraisal on the generation of knowledge. The impact of performance appraisal on knowledge sharing is significant. Performance appraisal has no significant influence on the sharing of knowledge. Performance appraisal has a significant influence on the storage of knowledge. Performance appraisal has no significant influence on the storage of knowledge. There is a significant influence of performance appraisal on the application of knowledge. There is no significant influence on performance appraisal on the application of knowledge. Teamwork has a significant impact on diagnosing knowledge. Teamwork has no significant impact on diagnosing knowledge. The influence of teamwork on the acquisition of knowledge is significant. The influence of teamwork on the acquisition of knowledge is not significant. The influence of teamwork on the generation of knowledge is significant. Teamwork has no important influence on the generation of knowledge. The influence of teamwork on the sharing of knowledge is significant. Teamwork has no important influence on the sharing of knowledge. The influence of teamwork on the storage of knowledge is significant. Teamwork has no significant influence on knowledge storage. The influence of teamwork on the application of knowledge is significant. The influence of teamwork on the application of knowledge is not significant.

3

H25a: H25o: H26a: H26o: H27a: H27o: H28a: H28o: H29a: H29o: H30a: H30o:

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The influence of training & development on knowledge is significant. The influence of training & development on the diagnosis of knowledge is not significant. The influence of training & development on the acquisition of knowledge is significant. The influence of training & development on the acquisition of knowledge is not significant. The influence of training & development on the generation of knowledge is significant. Training & development has no important influence on the generation of knowledge. There is a significant influence on the sharing of knowledge by training & development. Training & development has no important influence on the sharing of knowledge. The influence of training & development on the storage of knowledge is significant. The influence of training & development on the storage of knowledge is not significant. The impact of training & development on the application of knowledge is significant. Training & development has no major influence on the application of knowledge.

3.1.5

The Link Between KM Processes and Innovation

A group of researchers has established the theoretical link between the KM processes and innovation (Desouza & Evaristo, 2003; Lee et al., 2012; Ooi et al., 2009; Rademakers, 2005; Teece, 2010). The twentyfirst century is now a century of knowledge (Jelenic, 2011). Information generation organizations should be at the forefront of their objectives for survival in this century (Akhavan et al., 2013), and this can only be accomplished by the successful creation of human capital through wellestablished practices (Ortega-Parra & Sastre-Castillo, 2013). Knowledge is as such considered to be a strategic asset (Pinho et al., 2012), and if it is managed effectively, it can act as an enabler to achieve higher organizational innovation (Tan & Nasurdin, 2011.

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Researchers have found that the most critical factor to be considered for organizational innovation in the new information-based economy is the provision of the right kind of knowledge to the right people at the right time, which is only possible through efficient knowledge management processes and the knowledge thus accessible to employees will drive innovation (Ubeda-Garcia et al., 2013). Fong et al. (2011) assume that information exists in the minds of staff in an implicit form and that it needs to be translated into an explicit form and preserved in the knowledge repository of the organization for potential use in the organization, or that it can easily be lost if staff wish to leave the organization and this will impede organizational innovation. To avoid this loss of memory, organizations have evolved into learning organizations through well-established knowledge management processes: such as knowledge: diagnosis, acquisition, generation, sharing, storage, and application (Griese et al., 2012; Jimenez-Jimenez & Sanz-Valle, 2013; Pacharapha & Ractham, 2012; Tohidinia & Mosakhani, 2010; Yulong et al., 2012). It has to be noted that concepts like KM and innovation are yet to catch up within the education in India while they need has been well established within the western world. But a number of the premier institutes of the country have already initiated these processes and practices. It’s important to review this linkage because every institute of upper education within the present scenario where education is globalized is making an effort to achieve competitive advantage in business. To check the empirical relationship among KM practices and innovation the following hypotheses had been postulated. Main Hypothesis: HBa: HBo: HCa:

The effect of KMP on PRD is significant. The influence of KMP on PRD is not significant. The influence of KMP on PRI is significant.

HCo: HDa: HDo:

The influence of KMP on PRI is not significant. The influence of KMP on OGI is significant. The influence of KMP on OGI is not significant.

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Sub-Hypotheses: H31a: H31o: H32a: H32o: H33a: H33o: H34a: H34o: H35a: H35o: H36a: H37a: H37o: H38a: H38o: H39a: H39o: H40a: H40o:

Knowledge diagnosis has a significant influence on product innovation. Knowledge diagnosis has no significant influence on product innovation. Knowledge diagnosis has a significant influence on innovation in processes. Knowledge diagnosis has no significant influence on the innovation of processes. The impact of knowledge diagnostics on organizational innovation is significant. Knowledge diagnosis has no significant influence on organizational innovation. There is a significant influence on product innovation from the acquisition of knowledge. There is no significant influence on product innovation from knowledge acquisition. There is a significant impact on knowledge acquisition on the innovation of processes. Knowledge acquisition has no significant influence on the innovation of processes. Knowledge acquisition has a substantial influence on organizational innovation. There is a significant influence on product innovation by knowledge generation. Knowledge generation has no significant influence on product innovation. There is a significant influence on process innovation by knowledge generation. Knowledge generation has no significant influence on the innovation of processes. There is a significant influence on organizational innovation by knowledge generation. Knowledge generation has no important influence on organizational innovation. Knowledge sharing has a substantial influence on product innovation. Knowledge sharing has no important influence on product innovation.

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H41a: H41o: H42a: H42o: H43a: H43o: H44a: H44o: H45a: H45o: H46a: H46o: H47a: H47o: H48a: H48o:

There is a significant impact of knowledge sharing on the innovation of processes. Knowledge sharing has no significant influence on the innovation of processes. Knowledge sharing has a substantial influence on organizational innovation. Knowledge sharing has no important influence on organizational innovation. The influence of knowledge storage on product innovation is significant. Knowledge storage has no significant influence on the innovation of products. Knowledge storage has an important influence on the innovation of processes. Knowledge storage has no major influence on the innovation of processes. The impact of knowledge storage on organizational innovation is significant. Knowledge storage does not have any significant influence on organizational innovation. The application of knowledge has a considerable influence on product innovation. The application of knowledge does not have any significant influence on product innovation. The application of knowledge has a significant influence on the innovation of processes. Knowledge application has no significant influence on process innovation. The application of knowledge has a considerable influence on organizational innovation. Knowledge application has no significant influence on organizational innovation.

3.2

Summary

This chapter has established the linkage of the five dimensions of the human resources management practices with the six dimensions of Knowledge management processes and so the linkage between the knowledge management processes dimensions with the three dimensions of

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innovation with the support of the research literature within the context of Higher Education. This linkage development is one of the objectives of this research. Several views and opinions of the researchers have enabled the building of the relationship which is portrayed in the conceptual research model. While some linkages have empirical evidence, some have a strong grounding in theory. This chapter provides the foundation for the development of the structural model. The subsequent chapters would deal with the identification of the appropriate research methodologies and the testing of the relationships in the form of the hypotheses developed in this chapter.

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CHAPTER 4

Analysis of Results, Discussions, and Implications

Abstract This chapter thus provides the base for the following chapter in which the research findings, suggestions, and recommendations to the policymakers of higher education, and the conclusions will be presented. It narrates the stepwise analysis undertaken in this research. The descriptive statistics have described the demographics and indicated a fair distribution of the respondents into the section of the sample. Skewness and Kurtosis measures have indicated the normalcy of distribution and the suitability of the sample for inferential statistics. The overall perceptions categorized the response into the ordinal scales ranging from bad to very good and adequately described the data so that a fair understanding may be obtained in terms of the distribution of the response. The comparative analysis of the dimensions enabled the describing of the response to the three research constructs under investigation on relative terms. Inter-cadre comparison was also undertaken to study in detail how the faculty under various cadres responded to the dimensions of the three research constructs. Further, the rank order correlation tested the interrelationships between the rankings. The results obtained through inferential statistics mainly through hypotheses testing using regression analysis and structural equation modeling have provided adequate inputs to this research. These analyses have led to discussions and comparisons to the earlier research in this field and the similarities and contrasts have been explained.

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 A. Ara and K. K. Das, The Innovation Shift in Higher Education, https://doi.org/10.1007/978-981-16-2055-3_4

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Keywords Statistics · Regression analysis · Inferential statistics · Structural equation modeling · Higher education · Policymakers

4.1 A Brief Overview of the Methodology of the Study Before the analysis, a quick description of the analysis methodology chosen during this study and also the principle of why a specific method was chosen rather than the opposite method. There have been three research-interest constructs (HRP, KMP, and INN) the HRP had five dimensions, KMP had six dimensions, and INN had three dimensions. The organization, universities, and institutions where the questionnaire survey was conducted were from Odisha, India. The major sectors in higher education were private and government as per the classification supported their governance. The research framework indicated the eight stages within which the research was conducted. The survey questionnaire is then subjected to a pilot check for a sample length of 34 for the content, construct, and criterion validity. It’s also subjected to factor analysis and also the authentic 70 objects questionnaire (Appendix 1) is reduced to 42 items (Appendix 2). This questionnaire is used for the primary data collection for the sample size of 453. The information for this reason collected is subjected to analysis which includes descriptive statistics and inferential statistics by the use of IBM SPSS 19 and two models were analyzed: measurement model and structural model using SEM package using SmartPLS 2.0 and therefore the inferences were drawn. This has led to the event of the model for innovation enhancement through powerful human resource management practices and knowledge management practices. This entire process is depicted in Fig. 4.2

4

ANALYSIS OF RESULTS, DISCUSSIONS, AND IMPLICATIONS

Research Area HRP

Research Area KMP

59

Research Area INN

Develop Survey Questionnaire

Pilot Run, Test & Consolidate (n = 34)

Factor analyze and reduce questionnaire from 70 to 42

Draw Inferences & Implications and Build Model

4.1.1

Descriptive & Inferential statistics

Obtain Primary Data (n = 453)

Data Analysis

Analysis of Results, Discussions, and Implications

As mentioned both qualitative and quantitative approaches have been used to arrive at specific conclusions. The field visit to the institutions resulted in a series of discussions with the knowledge workers and very fruitful information has been elicited from them which are used in the analysis undertaken in the subsequent sections. Qualitative analysis in the form of informal interviews during the field visits has also provided meaningful insights into this research and they have been used to justify the results obtained through inferential statistics. The quantitative analysis which is a causation study using both first- and second-generation statistical tool is used to provide empirical evidence to the qualitative conclusions which have been arrived at based on the discussions with the employees of the various institutes. The following paragraphs narrate the analysis of the research results and attempt to seek answers to the research questions.

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4.1.2

Indication of Demographics of the Respondents

The demographics of the respondents suggest that the marginal majority of the respondents are male and are of a mature age group (35–45 years of age). Qualifications: The wise majority are graduates and Ph.D. and the highest salary range is Rs. 40,000–50,000, followed by Rs. 50,000– 75,000. The majority are Lecturers (45%) led by Assistant Professors (37.3%). One half of the response came from information staff with 6–10 years of experience, followed by those with more than 10 years of experience (26.5%). The sample size was chosen in 453, which is acceptable for this form of empiric analysis. Respondents are therefore the appropriate option in terms of their knowledge of demographics to respond to the problem situation found in this research and the findings obtained can be generalized to a considerable extent as mentioned above in Table 4.1. 4.1.3

Skewness and Kurtosis

Skewness and Kurtosis measures have endorsed the normality of the information and therefore the parametric nature of knowledge ensures its subjectivity to inferential statistical analyses. Also, the negative Skewness has indicated that on the basis the respondents are on the upper side of the agreement with the indications of the study. The general perception as indicated within the Skewness results on the upper side of the agreement with the indications while the degree varies from one construct to the other as shown in Table 4.2. 4.1.4

Overall Perceptions of the Three Dimensions of Study

4.1.4.1 Human Resource Practice (HRP) In terms of the descriptive statistics, all the dimensions of human resource practice (HRP) are poorly perceived by the respondents. On the Likert scale the 5 points were assigned to the rating as 1-Bad; 2-Poor; 3-Average; 4-Good, and 5-Very good. Recruitment (RCT) In Recruitment (RCT) more than one-half of the respondents are in the category of Bad, Poor, and Average level of agreement with the indicators of this dimension and all other dimensions: Compensation and

4

Table 4.1 Demographic distribution of the respondents

ANALYSIS OF RESULTS, DISCUSSIONS, AND IMPLICATIONS

Attributes

Frequency

Gender Male Female Age Less than 25 years 25–35 years 35–45 years 45–55 years Great than 55 years Educational qualification Graduate Postgraduate PhD Others Income per month Less than Rs. 20,000 Rs. 20,000–30,000 Rs. 30,000–40,000 Rs. 40,000–50,000 Rs. 50,000–75,000 Rs. 75,000–100,000 Above Rs. 100,000 Designation Lecturer Assistant Professor Professor Experience in the present institute Less than two years 2–6 years 6–10 years More than 10 years

61

Percentage

245 208

54.1 45.9

3 158 201 61 30

0.7 34.9 44.4 13.5 6.6

9 228 192 24

2.0 50.3 42.4 5.3

35 82 50 94 92 4 96

7.7 18.1 11.0 20.8 20.3 0.9 21.2

204 169 80

45.0 37.3 17.7

10 96 227 120

2.2 21.2 50.1 26.5

Source Compiled and collected data from primary sources

reward, Performance Assessment, Teamwork, and Training and Development, more than 60% of the respondents are in the category of Bad, Poor, and Average (As analyzed in Table 4.3 and Fig. 4.1).

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Table 4.2 Skewness and Kurtosis N Statistic VAR1 VAR2 VAR3 VAR4 VAR5 VAR6 VAR7 VAR8 VAR9 VAR10 VAR11 VAR12 VAR113 VAR14 VAR15 VAR16 VAR17 VAR18 VAR19 VAR20 VAR21 VAR22 VAR23 VAR24 VAR25 VAR26 VAR27 VAR28 VAR29 VAR30 VAR31 VAR32 VAR33 VAR34 VAR35 VAR36

453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453 453

Mean

Std. deviation

Skewness

Kurtosis

Statistic

Statistic

Statistic

Std. error

Statistic

Std. error

2.82 3.15 3.03 2.85 2.70 2.97 2.75 2.79 2.97 2.78 2.75 2.88 2.83 3.13 3.12 3.18 3.14 3.04 3.07 3.12 3.24 3.08 3.00 2.93 3.02 3.02 3.18 3.02 2.96 2.96 2.99 2.68 3.15 3.08 3.09 2.70

1.29 1.73 1.45 1.33 1.26 1.26 1.30 1.27 1.40 1.40 1.18 1.27 1.11 1.14 1.07 1.18 1.17 1.10 1.18 1.14 1.08 1.21 1.09 1.04 1.13 1.21 1.05 1.16 1.15 1.15 1.10 1.14 1.06 1.22 1.17 1.12

−0.08 −0.17 −0.09 0.13 0.07 −0.08 0.05 −0.05 −0.10 0.10 0.11 0.03 0.06 −0.38 −0.31 −0.11 −0.04 0.11 0.00 −0.11 −0.35 −0.15 0.16 −0.06 0.01 −0.02 −0.20 −0.01 −0.04 0.00 0.00 0.53 −0.35 0.13 −0.22 0.24

0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11

−1.19 −1.70 −1.36 −1.11 −1.16 −0.90 −1.11 −1.17 −1.32 −1.29 −0.93 −1.16 −1.02 −0.71 −0.58 −0.89 −0.91 −0.65 −1.03 −0.80 −0.64 −1.00 −0.59 −0.50 −0.81 −1.16 −0.68 −1.07 −0.87 −0.98 −0.93 −0.61 −0.53 −1.22 −1.02 −0.99

0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23

(continued)

4

ANALYSIS OF RESULTS, DISCUSSIONS, AND IMPLICATIONS

63

Table 4.2 (continued) N Statistic VAR37 VAR38 VAR39 VAR40 VAR41 VAR42 Valid N (listwise)

Mean

Std. deviation

Statistic

Statistic

Statistic

Std. error

Statistic

Std. error

3.06 3.01 3.10 3.19 3.12 3.14 3.00

1.16 1.04 1.00 1.02 1.11 1.06 1.18

−0.13 0.15 −0.33 −0.34 −0.19 −0.25 −0.05

0.11 0.11 0.11 0.11 0.11 0.11 0.11

−1.05 −0.61 −0.66 −0.68 −0.97 −0.91 −0.94

0.23 0.23 0.23 0.23 0.23 0.23 0.23

453 453 453 453 453 453 453

Skewness

Kurtosis

Source Compiled and collected data from primary sources

Table 4.3 Descriptive statistics of RCT Item

Mean

Std. dev

Bad (1) (%)

Poor (2) (%)

Avg. (3) (%)

Good (4) (%)

V. good (5) (%)

Favoritism is not evident in any of the recruitment decisions made Interview panels are used during the recruitment and selection process in this institution All appointments in this organization are based on merit Average

2.82

1.29

23.2

16.1

24.5

28.0

8.2

3.15

1.73

33.3

5.1

13.5

9.5

38.6

3.03

1.45

22.5

15.9

18.3

22.7

20.5

3.00

1.49

26.3

12.4

18.8

20.1

22.4

Source Compiled and collected data from primary sources

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45.0 40.0 35.0 30.0

Bad(