Industrial Revolution in Knowledge Management and Technology 3031292642, 9783031292644

Table of contents :
Preface
Contents
Ergonomics Risk Factors in Manual Handling Tasks: A Vital Piece of Information
1 Introduction
2 Ergonomics Risk Factors
2.1 Force
2.2 Posture
2.3 Repetition
3 Ergonomics Risks’ Factors in Manual Handling Tasks
4 Conclusion
References
Knowledge Management: Theoretical Considerations for High-Technology SMEs in Malaysia
1 Introduction
2 Theoretical Background
3 Methodology
4 Results and Discussion
5 Conclusion
References
Practice of Demand-Side Management for Commercial Buildings: A Case Study at a Female Residency
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
The Efficiency of GSCM Implementation in the Shipbuilding Industry in Malaysia
1 Introduction
2 Analysis of the Previous Works
2.1 Green Supply Chain Management
2.2 GSCM Within the Shipbuilding Industry Sector
2.3 IMO Convention
3 Methodology of the Research
4 Analysis of the Results
4.1 Response Rates
4.2 Reliability Analysis
5 Conclusion
References
Women and Technology: Enhancing Gender Equality in the Logistics and Transport Sector
1 Introduction
2 A Review on Technology in Logistics and Transport
3 Key Barriers of Technology Application Among Women in Logistics and Transport
4 Conclusion and Future Research
References
The Prevalence of Work-Related Musculoskeletal Disorders and Work Productivity of Aviation Maintenance Personnel
1 Introduction
2 Methodology
2.1 Industrial Survey
3 Results and Discussion
3.1 Reliability Test
3.2 Demographic Data
3.3 The Prevalence of WMSDs
3.4 Work Productivity
3.5 The Effects of WMSDs on Work Productivity
4 Conclusion
References
Stress Factors and the Impacts of COVID-19 Pandemic: A Review on the Aviation Industry
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
Development of a Pocket Alarm Security System
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
Women’s Behavior Toward the Supply Chain Roles in Malaysia
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
Measuring the Awareness on Safety Management and Behavior: A Case Study in a Service-Based Company in East Coast Malaysia
1 Introduction
2 Literature Review
2.1 Safety Management
2.2 Safety Behavior
3 Methodology
4 Results and Discussion
5 Conclusion
References
Deep CNN-Based Facial Recognition for a Person Identification System Using the Inception Model
1 Introduction
2 Related Works
2.1 Machine Learning
2.2 Face Detection
2.3 Face Recognition
3 Material and Methods
3.1 Facial Dataset Collection
3.2 Reconstruction of Face Recognition Model
4 Result and Discussion
4.1 Training and Validation Analysis
4.2 Model Selection
4.3 Testing of Face Recognition Model
5 Conclusion
References
“Hello Dr” Application for Mobile Devices
1 Introduction
2 Methodology
2.1 System Development Model
3 Results and Discussion
4 Conclusion
References
The Fundamentals of Schwann Cell Biology
1 Schwann Cells: The Glial of the Peripheral Nervous System
2 Schwann Cells
2.1 Myelinating Schwann Cells
2.2 Remak Schwann Cells
3 The Molecular Mechanism of Schwann Cell Myelination
3.1 Extrinsic Signals
3.2 Intracellular Signalings
3.3 Transcription Factors
4 Schwann Cell Plasticity
5 Conclusion
References

Citation preview

SpringerBriefs in Applied Sciences and Technology Azman Ismail · Fatin Nur Zulkipli · Jimisiah Jaafar · Andreas Öchsner   Editors

Industrial Revolution in Knowledge Management and Technology

SpringerBriefs in Applied Sciences and Technology

SpringerBriefs present concise summaries of cutting-edge research and practical applications across a wide spectrum of fields. Featuring compact volumes of 50 to 125 pages, the series covers a range of content from professional to academic. Typical publications can be: • A timely report of state-of-the art methods • An introduction to or a manual for the application of mathematical or computer techniques • A bridge between new research results, as published in journal articles • A snapshot of a hot or emerging topic • An in-depth case study • A presentation of core concepts that students must understand in order to make independent contributions SpringerBriefs are characterized by fast, global electronic dissemination, standard publishing contracts, standardized manuscript preparation and formatting guidelines, and expedited production schedules. On the one hand, SpringerBriefs in Applied Sciences and Technology are devoted to the publication of fundamentals and applications within the different classical engineering disciplines as well as in interdisciplinary fields that recently emerged between these areas. On the other hand, as the boundary separating fundamental research and applied technology is more and more dissolving, this series is particularly open to trans-disciplinary topics between fundamental science and engineering. Indexed by EI-Compendex, SCOPUS and Springerlink.

Azman Ismail · Fatin Nur Zulkipli · Jimisiah Jaafar · Andreas Öchsner Editors

Industrial Revolution in Knowledge Management and Technology

Editors Azman Ismail Malaysian Institute of Marine Engineering Technology Universiti Kuala Lumpur Lumut, Perak, Malaysia

Fatin Nur Zulkipli Information Science Studies, College of Computing, Informatics and Media Universiti Teknologi MARA Machang, Kelantan, Malaysia

Jimisiah Jaafar Centre for Women Advancement and Leadership Universiti Kuala Lumpur Kuala Lumpur, Malaysia

Andreas Öchsner Faculty of Mechanical Engineering Esslingen University of Applied Sciences Esslingen am Neckar, Baden-Württemberg, Germany

ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs in Applied Sciences and Technology ISBN 978-3-031-29264-4 ISBN 978-3-031-29265-1 (eBook) https://doi.org/10.1007/978-3-031-29265-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

This book describes the matter arising from Industrial Revolution through various theories. This revolution is directed by rapid development in several key technologies, especially on artificial intelligence, robotics, big data, the Internet of Things, nanotechnology, biotechnology, and many more. Knowledge management is one of the important and useful concepts. Modern organizations tend to rely on knowledge and its development to sustain a long-term benefit. Thus, various research avenues can produce significant impact on Industrial Revolution and its outcomes. Lumut, Malaysia Machang, Malaysia Kuala Lumpur, Malaysia Esslingen am Neckar, Germany

Azman Ismail Fatin Nur Zulkipli Jimisiah Jaafar Andreas Öchsner

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Contents

Ergonomics Risk Factors in Manual Handling Tasks: A Vital Piece of Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nurhayati Mohd Nur, Nor Aida Abdul Rahman, Zawiah Abdul Majid, Nur Faraihan Zulkefli, and Nurul Zuhairah Mahmud Zuhudi

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Knowledge Management: Theoretical Considerations for High-Technology SMEs in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Faridah Mustaffa Bakry

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Practice of Demand-Side Management for Commercial Buildings: A Case Study at a Female Residency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Norhafiza Mohamad and Ruhidayu Mohd Yusof

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The Efficiency of GSCM Implementation in the Shipbuilding Industry in Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nur Alliena Ahmad Jafri, Siti Noor Kamariah Yaacob, Anis Farhani Abdul Ghafar, Ahmad Azmeer Roslee, and Wardiah Mohd Dahalan Women and Technology: Enhancing Gender Equality in the Logistics and Transport Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nor Aida Abdul Rahman, Zawiah Abdul Majid, and Nurhayati Mohd Nur The Prevalence of Work-Related Musculoskeletal Disorders and Work Productivity of Aviation Maintenance Personnel . . . . . . . . . . . . Nur Nabilah Mohd Yusof, Nurhayati Mohd Nur, and Eida Nadirah Roslin Stress Factors and the Impacts of COVID-19 Pandemic: A Review on the Aviation Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Noor Ikma Syazwana Paisan and Rita Zaharah Wan-Chik

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Contents

Development of a Pocket Alarm Security System . . . . . . . . . . . . . . . . . . . . . Nur Amirah Sabrina Luqman, Izanoordina Ahmad, Zuhanis Mansor, and Siti Marwangi Maharum

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Women’s Behavior Toward the Supply Chain Roles in Malaysia . . . . . . . Nur Khaleda Ayunni Azlin, Hairul Rizad Md Sapry, Jimisiah Jaafar, Jamilahtun Md Ghazali, and Abd Rahman Ahmad

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Measuring the Awareness on Safety Management and Behavior: A Case Study in a Service-Based Company in East Coast Malaysia . . . . . Nur Aila Syafira Norzeri, Sallaudin Hassan, Jimisiah Jaafar, Mohd Farid Shamsudin, and Waqia Begum Fokeena Deep CNN-Based Facial Recognition for a Person Identification System Using the Inception Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Isaiah Chong Kai Ean, Mohd Fadzil Abu Hassan, Yusman Yusof, and Nur Zulaikhah Nadzri “Hello Dr” Application for Mobile Devices . . . . . . . . . . . . . . . . . . . . . . . . . . . Farahwahida Mohd and Nor Izzatul Elanie Mustafah

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The Fundamentals of Schwann Cell Biology . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Nurul Husna Abd Razak, Amiza Shahira Zainey, Jalilah Idris, and Muhammad Fauzi Daud

Ergonomics Risk Factors in Manual Handling Tasks: A Vital Piece of Information Nurhayati Mohd Nur, Nor Aida Abdul Rahman, Zawiah Abdul Majid, Nur Faraihan Zulkefli, and Nurul Zuhairah Mahmud Zuhudi

Abstract Exposure to ergonomics risk factors is unavoidable and it is crucial to assess the level of the risk factors, especially in manual handling tasks. Even though automation is prioritized compared to manual handling tasks, some processes still cannot be automated and are required to be performed manually. Manual handling tasks can be risky and may increase the tendency of workers to feel pain and discomfort and being exposed to physical fatigue. The ergonomics risk factors discussed in this paper are force, posture, and repetition. The severity of the ergonomics risk factors in the manual handling tasks shall be properly identified and controlled to minimize the risk of physical fatigue and work-related musculoskeletal disorders’ (WMSDs) issues. WMSDs are known as one of the major occupational injuries in the industries. Thus, this paper provides knowledge to the industries especially in manual handling task design and manpower planning, considering the effects of different levels of the risk factors to mitigate the risk of WMSDs, have a safe and healthy working environment, and optimize work productivity. Keywords Ergonomics risk factors · Manual handling task · Physical fatigue · Musculoskeletal disorders (MSDs) N. M. Nur (B) · Z. A. Majid · N. F. Zulkefli · N. Z. M. Zuhudi Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Jalan Jenderam Hulu, 43800 Dengkil, Selangor, Malaysia e-mail: [email protected] Z. A. Majid e-mail: [email protected] N. F. Zulkefli e-mail: [email protected] N. Z. M. Zuhudi e-mail: [email protected] N. A. A. Rahman Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Persiaran A, Off Jalan Lapangan Terbang Subang, 47200 Subang, Selangor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_1

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1 Introduction Ergonomics is the study about the interaction between humans and the system. The system is identified as the job, workstation, equipment, tools, machine, and also the environment [1]. With ergonomics application, the overall performance of the system is achievable. Ergonomics is widely applied to make sure the safety, comfortability, and productivity of the working area. The product design also considered the ergonomics approach in order to make sure that the product meets the user requirements and can interact well with high performance without any hazards. Ergonomics risk factors are associated with working environment circumstances that can cause harm to the body parts. There are three primary risk factors known as posture, force, and repetition that lead to the risk of contracting musculoskeletal disorders (MSDs). MSDs usually occur due to awkward posture [2], repetitive tasks [3], and force due to lifting a heavy load [4]. It can be either one or more risk factors that can lead to physical fatigue and MSDs among workers performing manual handling tasks. MSDs are one of the serious occupational injuries [5]. MSDs involved damage to the muscles, nerves, ligaments, joints, cartilage, and spinal discs [6]. It is important to assess the tasks and workstation to mitigate the existence of ergonomics risk factors in the working area or environment. Thus, this paper discussed in detail the ergonomics risk factors in manual handling tasks, physical fatigue, and the risk of MSDs. The knowledge and information from this paper could provide awareness and reference to the industry regarding the importance to design tasks and workstations that could minimize the ergonomics risk factors and reduce physical fatigue and MSDs’ issue while simultaneously improving the work productivity of the workers.

2 Ergonomics Risk Factors Ergonomic risk factors are known as the main contributors to MSDs risks [1]. Performing manual handling tasks with capabilities above the human body’s limitation will make the musculoskeletal system at high risk [7]. In a less ergonomics environment whereby excessive force, awkward posture, and highly repetitive motion existed, the tasks are prone to cause physical fatigue and MSDs risk to the workers.

2.1 Force Force is related to the effort that is physically needed to complete specific tasks. The movement of the human body while performing tasks is linked with muscle movement, either a single muscle or coordination of movement of a few muscles [8]. The high force used in the manual handling tasks could cause muscle injuries such as

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inflammation, irritation, muscle tear. Force is directly transferred from the physical contact with the tools or any objects used in the manual handling tasks. The transferring process happened in multiple directions. The excessive force applied while performing tasks has been found to associate with work-related musculoskeletal disorders (WMSDs). Thus, in any work environment, to control the WMSDs risk, it is crucial to quantify force exposures [9]. Force also involved push–pull activities due to the interaction between two objects in the workstation. The interaction between two objects caused the existence of force upon both objects [10]. Furthermore, force is the mechanical effort that is required to carry out a movement or to prevent a movement. Lifting a heavy object is much easier instead than holding it in place because the high force is required or the internal force increased if holding a relatively light item [11]. There are two types of force known as internal and external forces. Internal force happened when there is the development of tension within the working muscles, tendons, and ligaments due to movement during performing tasks. Force is identified as external when it is voluntarily or involuntarily applied to the body. In addition, external forces are more easily measured and tend to be at the forefront of recommendations to reduce injury. External forces are the loads exerted on or by the surface of the body, such as pushing, pulling, lifting, grasping, and handling objects. While the internal force is much more difficult to assess and measure, internal force refers to the tension generated by the muscles, tendons, ligaments, and body tissues, as an external force is applied [11]. Vibration is also one of the common external forces that existed while performing tasks using hand-held tools such as the drilling and riveting process. Exposure while using the tools is found to be associated with the MSDs’ risks known as hand-arm vibration syndrome (HAVS) [12]. The level of comfort for the workers on the handoperated interface can be quantified by the force through grip strength measurement and surface pressure distribution [13]. Force has been found to have a consistent relationship with physical fatigue and the risk of WMSDs. The exploration of a proper method to quantify the exposure to the force in the manual handling tasks is important. The factors such as the type of tools, criteria of tasks to perform, and task duration influenced the level of the force applied while performing the task [9]. The combination of force with other ergonomics risk factors may cause more serious issues related to physical fatigue and WMSDs.

2.2 Posture The posture while performing manual handling tasks is related to the body orientation [14]. The working posture is assessed from the workers’ characteristics, workstation design, and the process involved. Posture assessments should be done on the body parts involved in the process or task performed. Humans can perform various tasks

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due to their unique and complex muscles and bone structure. The hand can facilitate various and diverse activities such as picking objects, drawing, playing musical instruments, manipulating and handling devices, and climbing [15]. The awkward posture combined with high repetitive motion task that is performed at or above the shoulder level has been found to have a relationship with shoulder pain which is called shoulder posture disorder [16]. The existence of the external load and awkward posture disturbed the well-accepted inverse dynamics solution and often does not provide a precise indicator of the internal loads for the specific elements of the shoulder complex. For instance, dynamic shoulder exertions with precise hand movement caused shoulder muscle activity, while hand gripping has been found to increase the activity of some shoulder muscles and decrease the activity of other muscles [17]. Awkward posture can occur due to working in a prolonged position such as prolonged sitting or standing with the extreme movement of the body parts which caused the nerves and tendons to be stretched and compressed. Physical fatigue may occur due to awkward posture from prolonged sitting such as while performing tasks with bending, twisting, neck flexion, and arms position at or above shoulder height [18].

2.3 Repetition Manual handling tasks that need to be performed in repetitive motion with the same pattern and little variation in a specific time are called repetition. The task is considered high repetitive if the completion time is less than 30 s, while for the low repetitive task, the completion time required is more than 30 s [19]. Repetitive manual handling task is found to be associated with the MSDs related to hand, wrist, and forearm [20]. Repetitive tasks caused the emergence of occupational diseases resulting from increased movement while shortening the task completion time or cycle time. The MSDs associated with repetitive tasks are identified as tendon-related disorders, carpal tunnel syndrome (CTS), and cramping of the hand and forearm [21]. There is the occurrence of kinematic changes in the upper extremity due to muscle fatigue from repetitive tasks. The mobility afforded by the human shoulder and the upper extremity may allow workers opportunities to use kinematic and muscle recruitment strategy changes to adapt to the demands of repetitive tasks, especially when compromised with muscle fatigue issues [22]. Improper control of muscle activities leads to muscle fatigue, which is associated with WMSDs [20]. Manual handling tasks are synonyms for repetitive motion and prolonged tasks. The repetitive task performed with the elevated posture of the arm in a confined space and limited time that needs to sustain the muscle activity should consider the need to understand the muscle and kinematic response to avoid the development of shoulder pain and disorders [21]. Repetitive strain injuries (RSIs) affect manual handling workers, in a physical and psychological state [22] from repeated exertions and movements of the body part and/or with the maintenance of constrained

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postures resulting in abnormal fatigue, ache, discomfort or pain, and reduced work productivity. Physical fatigue is the consequence of the difficulties in repetitive tasks performed whereby the workers are unable to maintain the specified level of force used and work above their capabilities and limitation [23]. Muscle fatigue is the acute response to MSDs [24].

3 Ergonomics Risks’ Factors in Manual Handling Tasks Manual handling tasks involve activities such as holding, lifting, pulling, pushing, carrying, and putting down loads [25]. The application of force is required while performing manual handling tasks. Injury due to manual handling tasks has been recognized as one of the main occupational diseases that affect the quality of life [26]. Performing manual handling tasks in prolonged awkward positions will lead to body pain and discomfort [27]. Previous studies showed that there is an association between manual handling tasks and MSDs [28] such as suffering a back injury while at work [29]. Several factors make manual handling hazardous and increase the level of body pain and discomfort that is exposed to the risk of injury. Body pain, discomfort, and injury on the back has usually happened due to the factors of load or external force utilized while performing the tasks, the environment, and the workers’ health history [25]. Performing manual handling tasks with appropriate ergonomics settings is the main concern of health professionals to make sure that task-related injury can be prevented [30]. The repetitive motion of heavy lifting tasks is found to be associated with injuries due to back pain and WMSDs. Repetitive MMH activities, awkward posture as well as heavy loads or force (internal and external) could risk the workers of a serious case of WMSDs [31, 32] As discussed, force is one of the ergonomics risk factors while performing manual handling tasks and could cause physical fatigue that leads to the risk of WMSDs. However, it is also important to know other factors that could also influence the existence of force in the MMH task. Some studies investigated the factor of age related to handling external force or load while performing manual handling tasks [33]. The manual handling tasks involved lifting and lowering loads with different methods. The results revealed that elder workers could do the lifting tasks with a safer method. However, they are prone to the risks of MSDs due to their body strength and capability of them which are lesser than the younger workers. On top of that, the manual handling of repetitive tasks regarding lifting a load showed that the younger group had a larger increase in peak lumbosacral and trunk angular velocities during extension [34]. Thus, the results indicated that even the younger group was also exposed to physical fatigue which showed that all manual handling tasks which have the intensity of force (load) must be properly designed to make sure the application of the proper method while performing the task in order to mitigate the risks of MSDs.

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Instead of force applied, the body posture used to perform manual handling tasks should be in a position with less exertion to avoid severe pain or discomfort on the body parts. Different workers will have different abilities and limitations. Some studies investigated the differences between the two age groups on ground reaction forces, the motion of the center of pressure, and trunk kinematics, at three levels of destination height at 0 degrees [35]. It is shown that the older group is more likely to choose a stable or proper posture compared to the younger group. The study on the comparison between left-hand and right-hand postures showed that most of the workers used their right hand instead of the left hand during working related to the hand posture activities [15]. Thus, either using of right or left hand on the manual handling tasks depends on the individual’s choice and comfortability as long as it could reduce the physical fatigue and the risks of WMSDs. Repetition is the type of task commonly related to MMH. There is a study that investigated shoulder muscle activities as acute responses to muscle fatigue during a simulated repetitive light assembly task [24]. The risk of muscle fatigue is observed mainly in the shoulder region, but not in the upper limb muscles, which possibly the main reason is to maintain the shoulder position due to the task requirements. The result indicated that the task should be properly designed to make sure that all the body parts involved can be moved comfortably to avoid muscle fatigue. Studies also found that a manual repetitive high-precision task with a short cycle time showed no notable changes in joint kinematics variabilities of the shoulder or elbow joints [36]. The results indicated that for repetitive MMH tasks, it is important to have a limitation of time for the tasks, and implementing job rotation is also useful to reduce the risk of physical fatigue and WMSDs. The exposure to ergonomics risk factors while performing repetitive MMH tasks should be assessed accordingly. The combination of the ergonomics risk factors such as repetition and force, repetition and posture, or all in (repetition, force, and posture) could cause body pain or discomfort, higher risk of physical fatigue, and lead to the risk of WMSDs.

4 Conclusion Even though automation is the priority, many processes cannot be fully automated which make manual handling tasks still common and relevant in all industries. Manual handling tasks involved activities of pulling, pushing, lifting, lowering, and repetitive. These tasks have the potential to cause injury due to exposure to the taskrelated ergonomics risk factors. There are three primary ergonomics risk factors which are known as force, posture, and repetition. Different levels of force, posture, and repetition result in different physical fatigue levels and work performance. It is crucial to assess the tasks and workstation to identify the level of ergonomics risk factors that existed in the working area or environment. This paper provides information to the industries on the exposure to ergonomics risk factors in manual handling tasks. The knowledge could be used as a reference to design tasks and manpower planning to overcome issues related to physical fatigue and the risk of MSDs.

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25. K. Kay, A. Evans, N. Glass, Moments of speaking and silencing: nurses share their experiences of manual handling in healthcare. Collegian 22(1), 61–70 (2015) 26. J. Zurada, Classifying the risk of work-related low back disorders due to manual material handling tasks. Expert Syst. Appl. 39(12), 11125–11134 (2012) 27. R. Azevedo, C. Martins, J. Cardoso et al., Obstacle clearance while performing manual material handling tasks in construction sites. Saf. Sci. 62, 205–213 (2014) 28. H. McDermott, C. Haslam, S. Clemes et al., Investigation of manual handling training practices in organisations and beliefs regarding effectiveness. Int. J. Ind. Ergon. 42(2), 206–211 (2012) 29. N. Goode, P.M. Salmon, M.G. Lenné et al., Systems thinking applied to safety during manual handling tasks in the transport and storage industry. Accid. Anal. Prev. 68, 181–191 (2014) 30. E. Nurmianto, U. Ciptomulyono, S. Kromodihardjo, Manual handling problem identification in the mining industry: an ergonomic perspective. Procedia Manuf. 4, 89–97 (2015) 31. B.H. Whit, P.A. Costigan, J.M. Stevenson et al., Effect of an on-body ergonomic aid on oxygen consumption during a repetitive lifting task. Int. J. Ind. Ergon. 44, 39–44 (2014) 32. B.M. Deros, D.D.I. Daruis, I.M. Basir, A study on ergonomic awareness among workers performing manual material handling activities. Procedia Soc. Behav. Sci. 195, 1666–1673 (2015) 33. I. Shojaei, M. Vazirian, E. Croft et al., Age-related differences in mechanical demands imposed on the lower back by manual material handling tasks. J. Biomech. 49(6), 896–903 (2016) 34. M.G. Boocock, G.A. Mawston, S. Taylor, Age-related differences do affect postural kinematics and joint kinetics during repetitive lifting. Clin. Biomech. (Bristol, Avon) 30(2), 136–143 (2015) 35. G. Shin, Differences in trunk kinematics and ground reaction forces between older and younger adults during lifting. Proc. Human Factors Ergon. Society Ann. Meet. 49, 177–181 (2005) 36. D. Srinivasan, S.E. Mathiassen, A. Samani et al., Effects of concurrent physical and cognitive demands on arm movement kinematics in a repetitive upper-extremity precision task. Hum. Mov. Sci. 42, 89–99 (2015)

Knowledge Management: Theoretical Considerations for High-Technology SMEs in Malaysia Faridah Mustaffa Bakry

Abstract The notion that SMEs can enhance their innovation ability by developing knowledge resources has become important for achieving competitive advantage and long-term survival. Building upon theoretical work on the knowledge-based view, this study shows how the importance of knowledge management influences business practices for high-technology SMEs in Malaysia. This study emphasizes a firm’s ability to acquire and assimilate knowledge in relation to the life cycle of its technological assets: from technology, through human skills and knowledge development to the expansion of technological resources and know-how, and the consolidation of this acquired knowledge into the management system. By distinguishing between four sets of knowledge resources such human knowledge, skills and learning, technological skills and knowledge, information management, organization values and norms, which affects the success of SMEs. The results show that technological skills and knowledge and also organization values and norms are important to foster business performance for high-technology SMEs in Malaysia. Keywords Knowledge · Management · Technology · High technology · SME

1 Introduction The existing literature shows that the development of high-technology-based firms has been actively encouraged as a source of competitive advantage and job opportunities [1]. Furthermore, high-technology-based firms also classify as indicators for technological or knowledge intensiveness [2]. High-technology industries have a greater dependence on highly advanced technological development and devices that lead to new or improved products and services [3]. However, studies of knowledge development at small high-technology SMEs are very limited and have not received F. M. Bakry (B) Engineering Business Management, Malaysia Italy Design Institute, Universiti Kuala Lumpur, Cheras, Kuala Lumpur, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_2

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enough attention to date [4]. SMEs that are engaged at a high-technology level are classed as high-technology SMEs. The level of firm performance at high-technology SMEs increases depending on their concentration on product change, market, and technology [5]. Despite their limited resources in relation to high-technology SMEs, they are able to develop their innovation abilities through learning and knowledge networks, helping them to adapt to technological change and thus innovate [6].

2 Theoretical Background One theory that has recently gained eminence is the knowledge-based view, which emphasizes how a firm’s innovation functions as the ability to obtain, manage, sustain, and develop knowledge [7]. To date, knowledge-based view researchers have tended to focus on how a company’s knowledge strategies affect overall innovation [8]. These scholars also acknowledge that different types of knowledge seem to play a significant role in a firm’s innovativeness [9]. For SME managers, the challenge is how to identify, organize, and implement their scarce resources in unique ways, so as to provide their organization with innovation capability, and thus superior business performance [10]. Knowledge is linked with uniqueness, complexity, and tacitness; it is an important source of innovation capabilities, product improvement, and sustainable performance advantages; as such, it can lead to incremental and breakthrough innovation. Knowledge is the most important resource for high-technology industries due to the dynamic work environment and employees’ typically specialized technological knowledge [11]. Most high-technology scholars often examine questions such as: ‘What makes SMEs innovative and distinctive?’ and ‘Why do some SMEs perform better than others?’. The expected responses to these questions might refer to a firm’s knowledge, management abilities, technical know-how, and/or resources. A common theme in these responses is that the management believes that some firm-specific knowledge resources and abilities are essential to explain innovation and firm performance. At least four knowledge-related resources that are potentially important to innovation and firm performance remain relatively unexplored within the knowledge-based view. Adapted from Leonard-Barton [12] and Sharif [13], this study distinguishes between four sets of knowledge resources such as human knowledge, skills, and learning; technological skills and knowledge; information management; and organization values and norms. For small high-technology firms, effectively exploiting new market opportunities and concentrating on niche markets are important to create a competitive advantage. According to Thornhill [14], industries with positive stabilized scores for both research and development (R&D) and knowledge level can be classified as high technology. Clustering and developing knowledge networks with external partners are possible means of encouraging high-technology SMEs to continue to innovate [15]. The development of the learning process through adopting the knowledge-based view to acquire new knowledge resources is potentially of considerable use to SMEs in high-technology sectors.

Knowledge Management: Theoretical Considerations …

11

3 Methodology A web-based survey was designed and administered using Qualtrics. The survey results were analyzed based on statistical analysis methods. The targeted respondents were operations’ directors/managers from high-technology SMEs in Malaysia. These samples were chosen in order to meet the study objective, and the companies actively participate in technological and process innovation in maintaining their competitiveness [16]. The sampling frame consisted of 133 randomly selected high-technology Malaysian firms all listed in the Malaysian SMEs’ directory who participated in this study. The majority of the SMEs were high technologies related, with 1–250 employees and with minimum 1 and 10 years and above experience.

4 Results and Discussion The analysis is based on data collected from 133 Malaysian high-technology SMEs, and the dataset result shows that, in between four sets of knowledge resources, technological skills and knowledge and also organization values and norms are important to foster business performance for high-technology SMEs in Malaysia. Meanwhile, human knowledge, skills, and information management have an indirect impact toward high-technology industry sector. This study shows the relationship between the firm’s human aspects such as employee’s knowledge, skill, and learning which are not supported to firm performance; therefore, companies need to invest in improving employees’ knowledge and skills in order to create a learning environment that enhances a firm’s performance positively. This view is supported by the previous literature. Crook et al. [17] stated that daily interaction among the employees (learning environment) can gradually build the necessary trust and knowledge about the technological trends which can help to reduce the uncertainty [18] and assist the different team members toward goals of common interest [19]. In addition, the development and transformation of human capital program such as knowledge, skills, and implementation of the policies for new technology and innovation are still under way [20]. This result shows the relationship between the firm’s technological skills and knowledge supported, and technology provides mobility, flexibility, and speed by transforming workplaces and the habits of the knowledge worker into new structures. It also changes the ways people work and encourages collaboration. These results are similar to those of Sher and Lee [21], who state that IT applications (such as groupware, online database, intranets) within organizations can facilitate organizational tasks, decision-making processes, and the exchange of innovative ideas more efficiency. This view is also supported by Porter [22], who explains that the technologies embodied in a firm’s knowledge were demonstrated in their products and services and their potential for innovation. Moreover, in support of Diawati et al. [23], the new technology development process requires new skills, an appropriate

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educational level for local workers, and improvements to entire systems such as labor and management division support. The third knowledge resources are knowledge sharing and information management which can enhance problem-solving abilities when a crisis arises in the implementation stage of innovation [24]. This view is supported by Gobeli et al. [25], and even, healthy disagreements between different functional groups can be beneficial as they may result in more insightful thoughts, which can be turned into creative new technological ideas. In the context of top management support, it can be clearly shown that team goals and good group relationships reduce conflict and that this may positively influence the outcome of innovations. Moreover, the complexity of decisionmaking process in the organization influences the efficiency of internal communication. This is aligned with Edvardsson et al. [26] who state that one possible explanation for a negative relationship is that when a communication problem arises between employees during the technological development process due to a power struggle, the chances of success of innovative management activities/processes diminish and the development of new management practices takes longer. Contrarily, the result shows that an organization values and norms have positive relationship toward high technology and SMEs’ performance. A company can sometimes use a management structure to improve the workplace, job design, and decision-making process. Small companies will often have a less complex organizational structure and faster decision-making process. This view is aligned with that of Canibano et al. [27] who see the effective integration between organizational arrangements as providing useful information involving managerial aspect at all levels. Knowledge creation is of fundamental importance in the process, either to do something different (radical innovation) or improve what already exists (incremental innovation) in the current market [28]. In addition, the knowledge perspective also covers the fields of ability transfer and product development [29]. Technology can help companies to shape their strategies to develop innovation, exploit new market opportunities, and make the company more competitive [30]. Recently, SMEs have faced challenges in adopting multiple innovative technologies that can have a major impact on their daily operation and performance. However, it is difficult for SMEs to increase their speed of adoption and to adapt to these new technologies without prior knowledge. The acquisition of technological knowledge via investment in related areas is a key aspect for SMEs to consider, such as investment in R&D, workers’ skills, and new equipment for the production process. The notions of innovation abilities are embedded in the process of integration and linkages with external parties to acquire new knowledge to enhance the firm’s technological ability to innovate [31]. Furthermore, strategic alliances with industry partners in product development will improve technical and social factors, as well as cost efficiency [32]. Moreover, external knowledge can result in improvements in performance and production activity that positively influence the firm’s internal technological development ability [33]. Connections with external parties such as large companies, corporations, the government, universities, research institutes, labor

Knowledge Management: Theoretical Considerations …

13

unions, others in the same industry, and stakeholders are needed for the acquisition and assimilation of R&D, for example [34]. This process also relates to the learning capacity derived from acquired knowledge carried from one domain to another through formal and informal linkages with SMEs [35]. Integration with others can result in positive outputs, such as the development of technology and/or resources, knowledge acquisition, policy intervention, and R&D support for SMEs. In addition, the merging of new technological advancements and innovations comes from the blending of ideas from external knowledge and internal invention [36]. This organizational ability assumes that firms are able to make use of their knowledge to improve their business activities and processes and recognize the implications for knowledge management [37].

5 Conclusion Knowledge, such as technological knowledge, is important in generating competitive advantages in a business. For SMEs, the knowledge transfers between networks and through strategic alliances increases the level of the firms’ innovation abilities [38] and also creates new sources of knowledge and learning advantage [39]. This kind of knowledge, also known as a firm’s tacit knowledge in terms of innovation ability and leadership, plays a significant role in innovation. However, in the previous literature, the relationship between knowledge and the development of innovation in SMEs is not broadly addressed. Nonetheless, SMEs need to be aware of the importance of knowledge for the development of innovation. Indicating that the most important manifestation of the different knowledge resources leads to the success of innovation and performance for SME success in the high-technology industry.

References 1. S.M. O’Regan, Identifying high technology small firms: a sectoral analysis. J. Technovation 28, 408–423 (2008) 2. H.J. Steenhuis, E.J. Debruijn, High technology revisited: definition & position, in IEEE International Conference on Management of Innovation & Technology, 2006, pp. 1080–1084 3. K. Schwab, in The Global Competitiveness Report 2010–2011 (World Economic Forum, 2010) 4. S. Saarenketo, K. Puumalainen, O. Kuialainen, K. Kylaheik et al., Dynamic knowledge related learning processes in internationalizing high-tech SMEs. J. Prod. Econ. 89, 363–378 (2004) 5. T.M. Pavia, Product growth strategies in young high-technology firms. J. Prod. Inno. Manage. 7, 297–309 (1990) 6. K. Mohannak, Innovation networks and ability building in the Australian high-technology SMEs. J. Inno. Manage. 10, 236–251 (2007) 7. R.M. Grant, Toward a knowledge-based theory of the firm. Strateg. Manag. J. 17, 109–122 (1996) 8. P. Bierly, A. Chakrabarti, Generic knowledge strategies in the US pharmaceutical industry. J. Strategic Manage. 17, 123–135 (1996)

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9. C.K. Prahalad, G. Hamel, The core competence of corporation. Int. Lib. Crit. Writings Econ. 163, 210–222 (1990) 10. R. Stringer, How to manage radical innovation. J. California Manage. Rev. 42, 70–88 (2000) 11. H.E. Lin, E.F. McDonough, S.J. Lin, C.Y. Lin et al., Managing the exploitation/exploration paradox: the role of a learning ability & innovation ambidexterity. J. Prod. Inno. Manage. 30, 262–278 (2013) 12. B.D. Leonard, Core capabilities & core rigidities: a paradox in managing new product development. J. Strategic Manage. 13, 111–125 (1992) 13. N.M. Sharif, Strategic role of technological self-reliance in development management. J. Technol. Forecast. Soc. Change 44, 219–238 (1999) 14. S. Thornhill, Knowledge innovation & firm performance in high & low technology regimes. J. Bus. Venturing 21, 687–703 (2006) 15. E. Wever, E. Stam, Clusters of high-technology SMEs: the Dutch case. J. Region. Stud. 33, 391–400 (1999) 16. R.C. Yam, J.C. Guan, K.F. Pun, E.P. Tang et al., An audit of innovation capabilities in Chinese firms: some empirical findings in Beijing, China. J. Res. Policy 33, 1123–1140 (2004) 17. T. Crook, S. Todd, J. Combs, D. Woehr, D.J. Ketchen et al., Does human capital matter? A metaanalysis of the relationship between human capital and firm performance. J. Appl. Psychol. 96, 443–456 (2011) 18. J. Allen, Information systems as technological innovation. J. Inf. Technol. People 13, 210–221 (2000) 19. R.K. Moenaert, W. Souder, A. DeMeyer, D. Deschoolmeester et al., R&D-Marketing integration mechanisms, communication flows, & innovation successes. J. Prod. Inno. Manage. 11, 31–31 (1994) 20. H. Awang, Human capital and technology development in Malaysia. J. Int. Educ. 5, 239–246 (2004) 21. P.J. Sher, V.C. Lee, Information technology as a facilitator for enhancing dynamic capabilities through knowledge management. J. Inf. Manage. 41, 933–945 (2004) 22. M.E. Porter, Technology & competitive advantage. J. Bus. Strategy 51, 60–78 (1985) 23. L. Diawati, H. Kawashima, Y. Hayashi et al., Skill formation and its impact on the adaptation process of new production systems. J. Syst. Dyn. Rev. 10, 29–47 (1994) 24. J. De Jong, A. Bruins, J. Dolfsma, J. Meijaard et al., Innovation in services firms explored: what, how & why? EIM report (2003), pp. 1–65 25. H. Gobeli, F. Koenig, I. Bechinger et al., Managing conflict in software development teams: a multilevel analysis. J. Prod. Innov. Manag. 15, 423–435 (1998) 26. B. Edvardsson, L. Haglund, J. Mattson et al., Analysis, planning, improvisation and control in the development of new services. J. Service Indus. Manage. 6, 24–35 (1995) 27. L. Canibano, M. Covarsi, M. Sanchez et al., The value relevance & managerial implications of intangibles: a literature review. Proyecto Meritum OECD (1999) 28. N. Amara, R. Landry, N. Becheikh, M. Ouimet et al., Learning and novelty of innovation in established manufacturing SMEs. J. Technovation 28, 450–463 (2008) 29. K. Eisenhardt, C. Schoonhoven, Resource based view strategic alliance of information: effects strategic and social firms’ entrepreneurial firms. J. Org. Sci. 7, 136–150 (1996) 30. T. Hill, R. Westbrook, Linking innovations to strategic needs. Technovation 17, 109–117 (1997) 31. D.J. Teece, Capturing value from knowledge assets: the new economy, markets for know-how, & intangible assets. J. California Manage. Rev. 40, 55–79 (1998) 32. K. Eisenhart, F. Santos, Knowledge based view: a new theory of strategy, in Handbook of Strategy & Management, ed. by A. Pettigrew, H. Thomas, R. Whittington (The Sage, 2011) 33. M. Bell, M. Albu, Knowledge systems and technological dynamism in industrial clusters in developing countries. World Dev. 27, 1715–1734 (1999) 34. K.F. Meyer, G. Reger, New perspectives on the innovation strategies of multinational enterprises: lessons for technology policy in Europe. J. Res. Policy 28, 751–776 (1999) 35. R. Smith, N. Sharif, Understanding and acquiring technology assets for global competition. J. Technovation 27, 643–649 (2007)

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36. A.A. King, K. Lakhani, The contingent effect of absorptive capacity: an open innovation analysis (2011) 37. G. Dosi, M. Faillo, L. Marengo et al., Organizational capabilities, patterns of knowledge accumulation and governance structures in business firms: an introduction. J. Org. Stud. 29, 1165–1185 (2008) 38. D.C. Mowery, J.E. Oxley, B.S. Silverman et al., Strategic alliances and interfirm knowledge transfer. J. Strategic Manage. 17, 77–91 (1996) 39. B. Kogut, U. Zander, Knowledge of the firm, combinative capabilities and the replication of technology. J. Org. Sci. 3, 383–397 (1992)

Practice of Demand-Side Management for Commercial Buildings: A Case Study at a Female Residency Norhafiza Mohamad and Ruhidayu Mohd Yusof

Abstract The demand-side management (DSM) objective is to adjust the consumer demand for energy via possible various methods. The statistics from the Suruhanjaya Tenaga (ST) shows the demand for energy which is increasing rapidly hence the hike in price of energy. Commercial buildings are one of the examples that require high usage of electricity. This study recommends an alternative solution for commercial buildings for energy saving that is shown via a deduction in the monthly electricity bill. The case study takes place at a female residency of the Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI). The alternative solution that is recommended from this study is to replace the existing fluorescent lamps to light-emitting diode (LED) lamps for the locations with 24-h operating hours. This shall be taken as the first phase toward a better energy efficiency considering that the LED lamps are expensive. In general, the LED tube lights can save up the energy up to 50% and that feature makes the LED suitable for 24-h electricity consumption at the location. With these replacements, the electricity consumption and electricity bill are reduced at a significant amount. Although, at the beginning, the investment made toward replacing the existing tube lights to LED is high, the saving gained from this solution can be seen in the second year of usage that is proven from the simulation of calculation done in this study. Nevertheless, what more important is, in the long run, this practice is able to benefit not only the consumers but also the environment. Keywords Demand-side management · Renewable energy · Electricity · Light-emitting diode

N. Mohamad (B) · R. Mohd Yusof Universiti Kuala Lumpur British Malaysian Institute, Batu 8 Jalan Sungai Pusu, 53100 Gombak, Selangor, Malaysia e-mail: [email protected] R. Mohd Yusof e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_3

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1 Introduction The term DSM or load management has been highly considered in electricity starting mid of 1980s. Therefore, demand-side management practices have continued to persevere. DSM has also recently regained a considerable and growing influence on the demand for energy resources [1–3]. It aims to reduce energy consumption and at the same time improve the overall electricity usage efficiency through the implementation of policies and methods that control the electricity demand [4, 5]. One method to achieve a lower energy consumption is by replacing the fluorescent tube lights with the LED [6, 7] tubes as what has been explored in this study. Based on the Malaysia Energy Information Hub (MEIH), the consumption of electricity for commercial buildings is increasing rapidly from the year 1990 to the year 2010. It can be seen that lot of commercial buildings, for example, university buildings, shopping mall, or office buildings are built, and these will lead to a high demand of electricity. Indirectly, the situation will force the price of raw materials, for example, fuel or coal to be increased as to cope with the electricity generation volume [8]. Therefore, resources from renewable energy have become the new spotlight to support the quality of power and stabilize the global demand. However, the renewable energy equipment, installation, and setup are very costly. In UniKL BMI, particularly at female hostel, high and long hours’ usages of electricity are demanded. From observation, 42 units of 36-W fluorescent tube lamps installed at corridors, washrooms, drying rooms, and toilets are continuously operating for 24 h. Other locations such as at the staircases and foyers also use 36-W fluorescent tube lamps and operate for 12 h from 7 pm to 7 am. In general, the energy cost is calculated by: Energy cost = average cost applied(RM0.312) × kilo watt hour.

(1)

The comparison of energy cost between fluorescent lamps and LED lamps for 24-h operation is displayed in Table 1. UniKL BMI spends such a significant amount to pay the utility bills, e.g.: water and electricity bills. Due to the tariff of electricity which is increasing over the years, the institute is burdened to pay expensive electricity bills every month. Therefore, this study is expected to assist and recommend a long-term alternative solution to ease the financial burden in paying the electricity bill. Usually, the electricity bill is increasing during the peak time which is from January to May and August to December, while off-peak duration is between June and July which is during the semester break. During the peak times, the electricity bill is around RM120,000 and Table 1 Comparison energy cost for 24-h operation

Fluorescent

LED

Wattage per lamp (W)

36

18

Total cost per month (RM)

339.66

169.83

Practice of Demand-Side Management for Commercial Buildings: …

19

reduces to RM60,000 during off-peak time. It can be seen that the billing drops to half of the actual amount due to students’ absence in the hostel. In fact, the electricity charged from the residency contributes to 33.33% from the total electricity bill. Therefore, any saving that can be made from the lighting will essentially assist to reduce the electricity cost. Although the amount of electricity bill for lamps is smaller than air conditioners, however from the comparison made in Table 1, the replacement to LED tube lamps will definitely assist UniKL BMI financially. Looking from an environmental aspect, fluorescent tube light contributes to carbon dioxide emission and produces some ultraviolet (UV) light. Carbon dioxide emission may lead to global warming and UV light shall give a minor side effect to the consumers as they may expose to skin irritation, eye strain, or migraine. While for LED tube light, it is free from mercury and environmental friendly. LED tube lights are easy to be recycled compared to fluorescent. LED tube lights suit for long hour usage as they have a longer lifespan which is up to 50,000 h. That is equivalent to 4–5 years compared to fluorescents’ lifespan that can last up to 8000 h, which is around 2 years.

2 Methodology In conducting the study, daily observation toward current situation for electricity usage at the female residency, data collection, and analysis are adapted. From observation, almost every corner at the female residency requires the fluorescent tube lamps to be lighted on continuously for 24 h. The washrooms, toilets, drying rooms, and corridors are the locations with 24-h lighting. Figure 1 shows one of the examples for 24 h’ usage at the washroom. To summarize, lighting operating hours at this residency can be classified into three groups as follows: i. 24 h. ii. 12 h. iii. Upon required.

Fig. 1 Lamp is switched on at 9.00 a.m. (right) and still switched on at 10.00 p.m. (left) at washroom

20 Table 2 Total fluorescent lamps installed according to the location

N. Mohamad and R. Mohd Yusof Location

Number of fluorescent lamps installed (for one level)

Corridor

20

Washroom Drying room

4 4

Toilet

14

Total

42

At the same time, number of fluorescent lamps for every location specified earlier are also observed and tabulated as in Table 2. Based on Table 2, each floor at the female residency requires 42 units of 36-W fluorescent lamps. Therefore, the overall total of fluorescent lamps installed for every floor or level at the premise is 168 units. Since the residency building has four levels or floors, the total number of 36-W fluorescent lamps installed throughout the building is 724 units. Breaking down into percentage, it is simplified as the graph in Fig. 2. It is also essential to compare the technical specifications of the existing fluorescent lamps with the recommended LED lamps. This is to highlight on how the saving can be made by changing to the LED lamps. The technical specifications’ comparison between the two types of lamp is highlighted in Table 3.

168 units 23% 496 units 69%

24-hour

12-hour

60 units 8%

Upon required

Fig. 2 Summary of fluorescent lamps installed according to operating hours

Table 3 Comparison of technical specifications between fluorescent and LED lamps

Item

Fluorescent lamp

LED lamp

Wattage (W)

36

18

Life span (h)

8000

50,000

Starter

Needed

No need

Rated lumens (%)

45

77

Practice of Demand-Side Management for Commercial Buildings: …

21

The biggest challenge in adapting the new recommendation is the one-off cost that cannot be waived. The one-off cost meant here is the cost incurred in purchasing and installing the LED lamps themselves. Since UniKL BMI has its own service and maintenance team, installation cost can be easily wiped off. Now, the focus of this study is to replace the 36-W fluorescent lamps that are switched on for 24 h. Based on the graph in Fig. 2, for the first phase of this energy saving project, 168 units of LED lamps are required. The price of LED lamps is varied depending on the brands and warranty, and an average price of RM60 is chosen. For overall replacements of 168 lamps for all levels, the total of one-off cost for the installation is RM10,080. After the observation and identifying number of fluorescent lamps involved, the simulation of electricity consumption and electricity cost are conducted and measured using multifunctional mini ammeter. The data from this ammeter are recorded for 14 days both for fluorescent lamps and LED lamps. For LED lamps, the data are monitored from April 1, 2019, 10.00 p.m. until April 15, 2019, 10.00 p.m. The readings are consistently collected at 10.00 p.m. daily. While for fluorescent lamps, the data is monitored from April 16, 4.30 p.m., until April 30, 4.30 p.m. with the data is consistently taken at 4.30 p.m. daily. These data are detailed out in Table 4. In calculating the energy or electricity cost using an ammeter, an electricity tariff of RM0.31 is set up. This is to resemble the actual electricity tariff from TNB for the commercial building which is RM0.312. The discrepancy of RM 0.002 that is not recorded by the ammeter is manually calculated and added in. The total energy cost is then calculated using the following equations: Energy cost(ammeter) = electricity consumption × RM0.31,

(2)

Table 4 Total electricity consumption and energy cost for fluorescent and LED lamps Day

Electricity consumption (kWh)

Energy cost (RM)

Electricity consumption (kWh)

Energy cost (RM)

1

1.8870

0.5837740

0.4201

0.1308402

2

2.4047

0.7548094

0.8311

0.2616622

3

3.3783

1.0567566

1.2300

0.3824600

4

4.5195

1.4090390

1.5758

0.4931516

5

5.5913

1.7411826

1.9966

0.6239932

6

6.7060

2.0934120

2.4029

0.7448058

7

7.7963

2.4355926

2.7432

0.8554864

8

8.9965

2.8079930

3.1627

0.9863254

9

10.0567

3.1401134

3.5369

1.1070738

10

11.1731

3.4823462

3.9590

1.2379180

11

12.3181

3.8446362

4.3355

1.3486710

12

13.4345

4.1868690

4.7401

1.4794802

13

14.5866

4.5491732

5.1448

1.6002896

14

15.6938

4.9013876

5.4915

1.7109830

22

N. Mohamad and R. Mohd Yusof

Energy cost(discrepancy) = electricity consumption × RM0.002.

(3)

3 Results and Discussion

Total electricity consumption (kWh)

The result for the energy cost for the fluorescent lamps and LED lamps is tabulated in Table 4. The total energy cost is calculated from Eqs. (2) and (3) derived in the previous section. As stated earlier, the ammeter is only able to record up to two decimal places, i.e., RM0.31 for the electricity tariff compared to the actual TNB tariff which is RM0.312. An analysis of the actual energy cost by using the TNB tariff is developed to counter check the reliability outputs of the ammeter. The discrepancy analysis done proves that the difference is only 0.65% for the LED lamps and 0.84% for fluorescent lamps. In order to investigate the energy saving made, the electricity consumption and energy cost incurred between the LED lamps and fluorescent lamps are compared. Obviously, the LED championed the two factors as illustrated in Figs. 3 and 4 due to lower wattage it has. This indirectly leads to lower electricity consumption, hence lower energy cost. To further simulate the energy saving that the LED lamps can offer, the one-off cost to replace and install the LED lamps must be calculated. From Table 5, although the cost of installation to change for 168 units of LED lamps worth RM10,080 has been taken into account, still the difference of the total cost is not more than RM2000. In fact, this extra cost only incurs for the first year due to the installation cost. Now, looking for the first five years after the replacement, the saving in terms of financial starts to be experienced in the second year. The projection of saving made for the first five years after installation of LED lamps is estimated in Table 6.

1

2 LED

3

4

Fluorescent

5

6

7

8

9

10

11

12

13

14

Day

Fig. 3 Comparison of total electricity consumption (kWh) incurred for LED and fluorescent lamps for 14 days

23

Total energy cost (RM)

Practice of Demand-Side Management for Commercial Buildings: …

1

2 LED

3

4

5

Fluorescent

6

7

8

9

10

11

12

13

14

Day

Fig. 4 Comparison of total energy cost (RM) incurred for LED and fluorescent lamps for 14 days Table 5 Total cost incurred for fluorescent and LED lamps

Table 6 Projection of annual total saving made when changed to LED lamps

Item

Fluorescent LED

Total energy cost per level per month 339.66 (RM)

169.83

Total level at female residency

4

4

Total energy cost per month (RM)

1358.64

679.32

Total energy cost per year (RM)

16,303.68

8151.84

Total installation cost (RM)

0

10,080.00

Overall cost incurred per year (RM)

16,303.68

18,231.84

Year

Fluorescent total cost (RM)

LED total cost (RM)

Saving (RM)

1

16,303.68

18,231.84

− 1928.12

2

16,303.68

8151.84

6223.72

3

16,303.68

8151.84

8151.84

4

16,303.68

8151.84

8151.84

5

16,303.68

8151.84

8151.84

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N. Mohamad and R. Mohd Yusof

4 Conclusion Evidently, the electricity bill is one of the biggest ‘overheads’ for commercial buildings. Due to this, any new buildings built may adapt to green technology building or zero-energy building as part of the efforts to reduce the overhead costs. However, the adaption may not be applicable to the old buildings such as the female residency at UniKL BMI. Switching the fluorescent lamps to the LED lamps is considered as an acceptable method, and it has proven to save the energy without doing major renovation to the building itself. Despite of a large sum which is needed to purchase the LED lamps for the first time, the profit of using it is seen to be gained in the following year. In a nutshell, substituting the fluorescent lamps with the LED lamps is recommended as an alternative solution to reduce the energy consumption for UniKL BMI. It benefits and profits the UniKL BMI as a user and promotes better lifestyle since the LED lamps is environmental friendly. Acknowledgements Deepest gratitude to the individuals who have assisted the authors throughout the duration of this study. In particular, Finance and Management Department of UniKL BMI for their assistances such as visits to study-target locations and providing us with relevant reports and photos. We also extend our sincere appreciation to everyone who has directly or indirectly contributed to the project.

References 1. C.W. Gellings, K.E. Parmenter, Demand side management, in Energy Management and Conservation Handbook, 2nd edn., ed. by F. Kreith, D.Y. Goswami (CRC Press, Florida, 2016), pp.387–408 2. P. Kumar, G. Brar, L. Singh, Energy efficiency evaluation in commercial and residential buildings with demand side management: a review. Int. Conf. Power Syst., 1–6 (2019) 3. L. Martirano, E. Habib, G. Parise, G. Greco, M. Cianfrini, L. Parise, F. Massarella, P.D. Frattura, Demand side management in mixed residential/commercial buildings with PV on site generation. Ind. Commer. Power Syst. Technical Conf., 1–7 (2017) 4. J. Zhong, C. Kang, K. Liu, Demand side management in China. IEEE Pow. Ener. Soc. GE (2010). https://doi.org/10.1109/PES.2010.5589964 5. L.P. Moji, K. Kusakana, B.P. Numbi, Demand side management of grid- tied hybrid photovoltaicdiesel-battery energy system for a university engineering building, in Open Innovations Conference, 2018. https://doi.org/10.1109/OI.2018.8535866 6. K. Edirisinghe, R. Abeyweera, N.S. Senanayake, Evaluation of effectiveness of LED lighting in buildings. SLEMA J. 19(2), 8–14 (2016) 7. Energy-saving potential of LED lighting systems. Indoor Built Environ. 22(1), 235–241 (2013). https://doi.org/10.1177/1420326X12470298 8. W.R. Prindle, From shop floor to top floor: best business practices in energy efficiency. Centre for climate and energy solutions (2010). https://www.c2es.org/document/from-shop-floor-totop-floor-best-business-practices-in-energy-efficiency. Accessed 28 July 2022 9. P. Kumar, G. Brar, S. Singh, S. Nikolovski, H.R. Baghaee, Z. Balki´c, Perspectives and intensification of energy efficiency in commercial and residential buildings using strategic auditing and demand side management. Energies 12(23), 4539–4570 (2019)

The Efficiency of GSCM Implementation in the Shipbuilding Industry in Malaysia Nur Alliena Ahmad Jafri, Siti Noor Kamariah Yaacob, Anis Farhani Abdul Ghafar, Ahmad Azmeer Roslee, and Wardiah Mohd Dahalan

Abstract Various important factors that affect business today include the environment. Among the criteria identified in environmental issues are more systematic and efficient in management system. All sectors play an important role in maintaining green environmental activities that are always clean, including the Malaysian shipbuilding sector. The aim of this study is to investigate more closely the effectiveness of drivers for the application of green supply chains in Malaysia (GSCM) in the shipbuilding industry. The methods used are online surveys and questionnaires. The collected data were then processed and analyzed using Statistical Package for the Social Sciences (SPSS). From the research conducted, it was found that green initiatives and regulations have a semi-significant relationship with the five dimensions of maritime green supply chain management (MGSCM). This research provides to the maritime transport information by filling up a gap with respect to research evidence based on a survey of MGSCM hypothetical models. N. A. Ahmad Jafri Student Development Section, Universiti Kuala Lumpur, Malaysian Institute of Marine Engineering Technology, Lumut, Perak, Malaysia e-mail: [email protected] S. N. K. Yaacob Technoputra Section, Universiti Kuala Lumpur, Malaysian Institute of Marine Engineering Technology, 32200 Lumut, Perak, Malaysia e-mail: [email protected] A. F. Abdul Ghafar Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Malacca, Malaysia e-mail: [email protected] A. A. Roslee Marine Engineering Section, Universiti Kuala Lumpur, Malaysian Institute of Marine Engineering Technology, 32200 Lumut, Perak, Malaysia e-mail: [email protected] W. Mohd Dahalan (B) Marine Electrical and Engineering Section, Universiti Kuala Lumpur, Malaysian Institute of Marine Engineering Technology, Lumut, Perak, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_4

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Keywords Shipbuilding · Supply chain · GSCM · MGSCM

1 Introduction This study is to know the drivers’ effect of implementation and interpret the efficiency of maritime green supply chain management (GSCM) in shipbuilding industry in Malaysia. The food supply chain sector can be improved through the power of certain institutions by knowing who and how these green practices are practiced. Based on this reasoning, the institutional theory should be evaluated as recognizing the main drivers in the use of green practices. Realizing the main drivers is an important factor to empower the maritime sector to obtain international sustainability norms [1], while the understanding in guiding maritime organizations in carrying out the implementation of environmental protection assessment in the long term is also the most important factor. To strengthen the field of research in the maritime supply chain at the global level, the empirical evidence obtained from this study is very important to show how the implementation of GSCM has been practiced in Malaysia. To establish the GSCM conceptual construct, empirically based research on maritime supply chains is needed. From a maritime point of view, the word green refers to all non-commercial sailing activities as well as environmentally friendly commercial sailing that aims to reduce marine pollution and negative effects on the environment. The aim of this research is to provide a clear understanding and enlightenment regarding the drivers and motivators that influence the involvement or participation of suppliers with GSCM initiatives in shipbuilding. A very important factor necessary to know is the efficient and fast drivers in the implementation of GSCM initiatives and their relative importance. A company needs to comply with environmental practices for competitive reasons as well. For individual firms, the factor of self-adjustment with social and market forces is determined by a well-planned strategy. For a company, it is very important to include their suppliers in a green supply chain initiative to create their sourcing strategy while paying close attention to the greening policy of their suppliers [2]. The main issue faced by GSCM is the lack of facilities provided by the management. A written certificate of compliance with all environmental matters will be provided to all customers such as shipbuilders or car manufacturers [3]. From the statement of the rules of International Maritime Organization (IMO), shipbuilding that will be built can immediately reduce the rate of greenhouse gas (GHG) emissions by 18% and further decrease by 22% by 2021 and is expected to increase the reduction by 35% by 2026. Meanwhile in the shipbuilding industry, they require suppliers to participate in green activities, and implement active and productive environmental management to upgrade the environmental performance efficiency of the entire chain [4]. The main factor identified is the problem faced by ship owners in carrying out and following GSCM to the shipbuilding industry according to IMO

The Efficiency of GSCM Implementation in the Shipbuilding Industry …

27

regulations. According to Moshiul et al. [5], distribution of bank loans to corporations has proposed to start green technology. Malaysia is currently promoting green technology financing schemes to minimize emissions, marine pollution, intrusive species, and other passive environmental effects. The purpose of this research is to investigate the implementation of GSCM in the shipbuilding industry in Malaysia. The objective of the study is to examine the driving effects and interpret the efficiency of GSCM implementation in the shipbuilding industry in Malaysia.

2 Analysis of the Previous Works 2.1 Green Supply Chain Management The main job description of GSCM in the literature consists of green purchasing to an integrated green supply chain from suppliers to manufacturers and then to customers and reverse logistics [6]. GSCM also incorporates elements of traditional supply chain management, which incorporate environmental criteria or concerns into organizational purchasing decisions and long-term relationships with suppliers. This enables a systematic combination of cycles such as supplier determination and material purchase, item plan, item assembly and collection, distribution, and end of life of the board. According to Aziz et al. [7], greening the production network is the way toward joining ecological measures and worries into authoritative buying choices and long-haul associations with providers.

2.2 GSCM Within the Shipbuilding Industry Sector The shipbuilding enterprise sector is such as designing, building, converting, and upgrading ships and marine equipment manufacturing. In other words, ‘ship’ means various types of ships such as high seas, cruise ships, passenger ships, fishing ships, and ships used by government agencies, while ‘marine equipment’ means parts and components assembled and integrated to form a ship’s system [8]. Shipbuilding organizations are usually associated with many project workers working around the world, which prevent the precise and executive examination of ecological pollution that may be caused in the shipbuilding cycle, as well as looking at the naturally hostile work cycle and the use of pollutants throughout the supply chain network [9].

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2.3 IMO Convention The IMO is an international maritime organization that is active in providing guidelines and regulations in shipbuilding. The 59th Marine Environment Protection Committee (MEPC) General Assembly in 2009 agreed on GHG regulations and revised Marine Pollution (MARPOL) Annex VI to reduce carbon dioxide (CO2 ) emissions from ships by 2030 at the 2009 MEPC General Assembly 62 in August 2013. The IMO has issued guidelines that control the maximum discharge of hazardous particles to ships that have been detained. With this regulation, according to MARPOL, the amount of greenhouse gas emissions from ships can be significantly reduced. These regulations are mandatory technical and operational energy efficiency measures to realize the goals of GCSM.

3 Methodology of the Research This research involves two categories of data collection which are classified as the primary and secondary data. Questionnaire survey is used as the tool in collecting the primary data. The survey is done among the shipbuilding owners. The collected data will be transformed into statistical information and later give the result of the research. Primary data • Questionnaire survey. Secondary data • Journals, articles, books, news, websites, and other reliable resources. The method for this research is to use an online survey to collect data. In this study, respondents were sampled in the MMHE sector using suppliers and supply chains that are the largest shipbuilding companies in Malaysia. This sector includes companies active in maritime shipbuilding which consists of repair and construction of large and small yachts, maritime supplier construction, repair maintenance, small ship construction, and large yacht building. The questionnaire is on the web for fourteen days, which is seen as a satisfactory time interval for overview cooperation. Contact details of 45 suppliers were collected to ensure a successful response. In total, 35 responses were collected which give a response rate of 77.7% as shown in Table 1.

The Efficiency of GSCM Implementation in the Shipbuilding Industry … Table 1 Responses’ overview

29

Respondents

Percent

Male

25

71.4

Female

10

28.6

Gender

Number of employees 0–49

16

45.71

50–99

8

22.86

100–199

6

17.14

200–499

5

14.29

Years of working experience 0–5

20

44.44

5–10

18

40.00

10–15

7

15.56

4 Analysis of the Results 4.1 Response Rates To evaluate the idea of the assessment model, latent model, and covered model, composite reliability, one-dimensionality, and construct validity were used. Reliability refers to the internal stability of the items used to measure the latent construct. It is best estimated by the Cronbach’s alpha. Table 2 shows the alpha coefficient that has a value greater than 0.6. This indicates that the items are highly internally consistent. Table 2 Reliability analysis of each construct Construct

Items

Cronbach’s alpha

Competitive advantage (1)

6

0.84

Customer requirements (2)

4

0.8

GSCM participation (3)

5

0.91

Regulations and governmental involvement (4)

5

0.86

Social responsibility and stakeholders (5)

5

0.95

Supplier readiness (6)

4

0.89

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N. A. Ahmad Jafri et al.

Table 3 Matrix of construct correlations (1)

(2)

(3)

(4)

(5)

(6)

Competitive advantage (1)

0.78

Customer requirements (2)

0.50

0.79

GSCN participation (3)

0.42

0.38

0.86

Regulations and governmental involvement (4)

0.69

0.35

0.38

0.80

Social responsibility and stakeholders (5)

0.59

0.48

0.26

0.58

0.9

Supplier readiness (6)

0.76

0,42

0,33

0,73

0,70

0,86

Ave

0.62

0.62

0.74

0.64

0.81

0.75

Composite reliability

0.89

0.87

0.93

0.9

0.96

0.92

4.2 Reliability Analysis From the data analysis carried out, the supplier acts as a dependent variable, while competitive advantage, customer needs, GSCM participants, sociability, stakeholders are estimated as independent variables. The correlation coefficient is at least − 1 and the largest value is 1. If 0, then there is no correlation at all, while a correlation of 1 means perfect correlation. This means that if it is closer to 1 or − 1, the relationship between two variables is strong. Indeed, this can be a simple guide, that a correlation number above 0.5 indicates a strong correlation and below 0.5 indicates a weak correlation. Based on Table 3, stakeholders have the highest P value of 0.9 and this is close to 1. One of the objectives of this research is to study the drivers’ effect of implementation GSCM and to interpret efficiency GSCM in the shipbuilding industry in Malaysia. Using the Pearson correlation coefficient method, analysis of 45 respondents reveals that there was an affirmative between stakeholder and GSCM. The consequence of correlation coefficient is 0.9 for the stakeholder while for supplier readiness and participation is 0.86 in conclusion for the contribution 0.8. All the outcomes show that the relationship between the competitive advantage and customer requirement is moderate. But, the highest relationship is between stakeholder and GSCM participation. A hypothesis has stated with the H null and H alternatives: H0: There are no significant regulations and governmental involvement. H1: There are significant stakeholder, regulations and governmental involvement, and customer requirements (claim).

5 Conclusion Even though the significance of GSCM is progressively being perceived by numerous endeavors, there still is by all accounts an absence of inspiration for firms to partake

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in these drives. Based on the current research work, it is very striking that some of the current literature highlights some researchers who may affect the choice to participate in the GSCM study, but few of them approve these researchers to undergo training. To clarify this issue, the study identified five main factors based on the existing literature that has been produced. A through strategy was used to approve the scale for development related to each of the six variables. The results from the study show that there are strong support, government regulation, and involvement as well as customer needs. In general, the following can be concluded: This study reflects the importance of various business areas, ethnicities, and items included. Results found for regulatory and government contributions and customer needs are varied in non-maritime studies [10]. This can be explained by (1) contrasts in area and industry type, (2) contrasts in item life expectancy, (3) contrasts in direct effect on air quality, and (4) contrasts in degrees of pressing factor and inspiration between enterprises.

References 1. M.F. Jasmi, Y. Fernando, Drivers of maritime green supply chain management. Sustain. Cities Soc., 366–383 (2018). https://doi.org/10.1016/j.scs.2018.09.001 2. T. Lee, H. Nam, A study on green shipping in major countries: in the view of shipyards, shipping companies, ports, and policies. Asian J. Shipp. Logist. 33(4), 253–262 (2017). https://doi.org/ 10.1016/j.ajsl.2017.12.009 3. T. Muka, D. Imo, Jaspers et al., The global impact of non-communicable diseases on healthcare spending and national income: a systematic review. Eur. J. Epidemiol. 30(4), 251–277 (2015) 4. M.C. Caniëls, E. Cleophas, J. Semeijn, Implementing green supply chain practices: an empirical investigation in the shipbuilding industry. Marit. Policy Manag. 43(8), 1005–1020 (2016). https://doi.org/10.1080/03088839.2016.1182654 5. A.M. Moshiul, R. Mohammad et al., The evolution of green shipping practices. TEM J. 10(3), 1112–1121 (2021) 6. G. Büyüközkan, G. Çifçi, Evaluation of the green supply chain management practices: a fuzzy ANP approach. Prod. Plan. Control 23(6), 405–418 (2012) 7. T.N. Aziz, H.S. Jaafar, R.M. Tajuddin, Green supply chain: awareness of logistics industry in Malaysia. Procedia Soc. Behav. Sci. 219, 121–125 (2016). https://doi.org/10.1016/j.sbspro. 2016.04.052 8. K.W. Green, P.J. Zelbst, J. Meacham et al., Green supply chain management practices: impact on performance. Supply Chain Manage.: Int. J. Res. 17(3), 290–305 (2012). https://doi.org/10. 1108/13598541211227126 9. M.C. Caniëls, E. Cleophas, J. Semeijn, Implementing green supply chain practices: an empirical investigation in the shipbuilding industry. Marit. Policy Manag 43(8), 1005–1020 (2016) 10. G.M. Ugarte, J.S. Golden, K.J. Dooley, Lean versus green: the impact of lean logistics on greenhouse gas emissions in consumer goods supply chains. Marit. Policy Manag. 22(2), 98–109 (2016)

Women and Technology: Enhancing Gender Equality in the Logistics and Transport Sector Nor Aida Abdul Rahman, Zawiah Abdul Majid, and Nurhayati Mohd Nur

Abstract The aim of this chapter is three fold, to shed light on the role of technology in enhancing women capability and gender equality, as well as to highlight key barriers of technology application among women in the logistics and transport sector. The third aim of this chapter is to provide a basis for future scholars to explore on technology and women in the field of logistics and transport. This study is an abductive approach where the researcher uses previous published work to elaborate on the issue of women and technology in enhancing gender equality in logistics and transport context. Keywords Women · Technology · Aviation · Logistics and transport · Emerging economies

1 Introduction Across the globe, women’s aptitude is always recognized as a potential value workforce that has a certain value which will drive organizational success in any sector. Women and men at the workplace always have different capabilities and different expectations. Nevertheless, they need each other. Women who are talented in the field and have high achievements will lead to better mobility of women in the future. As reported in the World Economic Forum [1], empowering women is substantial due to N. A. A. Rahman (B) Aviation Management, Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Persiaran A, Off Jalan Lapangan Terbang Subang, 47200 Subang, Selangor, Malaysia e-mail: [email protected] Z. A. Majid · N. M. Nur Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Lot 2891 Jalan Jenderam Hulu, 43800 Dengkil, Selangor, Malaysia e-mail: [email protected] N. M. Nur e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_5

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the fact that it leads to closing gender gaps in labor force of any industry in any country worldwide. Developing women’s talents and skills is associated with positive results such as better education and health, higher international competitiveness and help to boost country development and economic growth. In fact, developing and broadening the talent, technology skills, communication skills, experience, and knowledge of women workers in any industry are among the primary goal of the United Nation (SDG 5). As published in United Nation Women [2], every parties need to play their role to support women and accelerate their talent to achieve gender equality by the year 2030. It is undeniable that women involvement in many transportation sectors such as aviation, maritime, road and logistics are underrepresented if compared to men. Proper planning and bold action by all stakeholders involved are critical to support women development in every industry in every country. Proper training and knowledge need to be equipped by women to increase their social, cognitive, as well as technical skills. As stressed by earlier scholars, more women in the field of science and technology (STEM) are critically needed to increase diversity of work ideas at the workplace [3]. This is also supported by other women association in Asia Pacific Economic Cooperation Countries (APEC), as well as Women National Policy. In this modern era, many organizations have realized that women can perform better than man including at managerial level. As such, investing in women capacity building to develop sustainable woman leaders is considered as a great stimulus to economic growth as women are known to be more productive and hardworking compared to men [4]. In the logistics and transport sector, women participation in this industry is hindered by low expectation, limited access to critical skills, inadequate advancement opportunities and unequal policy structures, which results in gradual career growth [5]. Accordingly, the logistics sector requires more women, and the industry is looking for more women to work in the field [3]. In order to do that, four key proposals are recommended to achieve gender equality in the field of transport. There are clear targets and directions, open pathways with technology, to target women with purpose, as well as create a culture for growth. Table 1 sheds lights on the four areas to focus in getting more women to work in the logistics and transport. On the other hand, another preliminary study in Asia confirms the difficulty of female graduates to enter aviation field is because of low skills, low technology advancement and talent [6]. As reported, since the numbers of female registration in aviation field is low, therefore, developing and broadening the skills, talent, experience and knowledge among the women workers and graduates is crucial. Recognizing this critical issue and being the priority focus of the United Nation and many women agencies worldwide including APEC as depicted in the APEC Women in Transport (WIT) framework, this study aims to highlight the importance of technology knowledge in enhancing women skills in the field of logistics and transport to improve gender equality in the field. With that, below are the research objectives that are developed in this study: i.

To explore the types of recent technology for women in logistics and transport in enhancing their skills and work talent.

Women and Technology: Enhancing Gender Equality in the Logistics …

35

Table 1 Areas to focus in getting more women in logistics and transport sector No.

Areas to focus

Description

1

Setting clear target and direction

Company leaders and management level must set the target to achieve gender equality in every activity in the organization and in every strategic direction that they planned

2

Open pathway with technology

To increase technology skills of their staff with recent technology developments such as artificial intelligence (AI) technology, robotic, big data analytics, Internet of things (IOT) and many more

3

Target women with purpose

Target women involvement in any business process and activities

4

Create culture for growth

Organization needs to create visible and harmonize culture to support women development in the company, as well as possible avenues for women promotion and leadership role.

ii. To identify the key barriers of technology that women workers are experiencing in the sector of logistics and transport. iii. To propose future research avenues for future scholars in the field of women in logistics and transport. The structure of this chapter starts with the research background highlighting the importance of women in logistics and transport, followed by the key issue of gender inequality in the field of transport. The next section will briefly discuss the type of technology advancement and technology skills in the field of logistics and transport that women should explore and master, followed by the key carriers or challenges that women are experiencing with regards to technology application from logistics and transport perspective. Then, the authors will also recommend areas for future research for future scholars in the women and logistics field.

2 A Review on Technology in Logistics and Transport Technology refers to the application of scientific knowledge in a specific field and allows the user of technology to brush up their skills, knowledge, method and process used in any operation involved. In the logistics and transport sector, the emergence of new technologies or also called as smart technologies are significant especially those connected to data science technology or artificial intelligence (AI) technology [7]. Machine learning, big data, blockchain and Internet of things are among the most essential technology for logistics and transport players as it allows the process or object to become autonomous. As highlighted by a recent study, among the frontiers technology in the field of logistics are artificial intelligence, machine learning, Internet of things, big data and

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Artificial Intelligence (AI technology)

Internet of Things (IoT technology)

Big Data and Analytics (BDA)

Blockchain Technology (BT)

Machine Learning (ML technology)

Fig. 1 Type of technology for women empowering in logistics and transport to enhance gender inequality

block chain technology [7]. Similarly, in the transportation sector such as aviation, maritime and road transport, these kinds of technology are also popular in the field to improve its operation and performance. For instance, AI is also useful to show the absence of the governance, as well as data quality [8]. Similarly, Tarafdar et al. [9] and Yang et al. [10] also debate the potential of technology in delivering business value in all sectors including logistics and transport. As such, equipping women with knowledge and brushing up women technology skills in these areas are significant to allow them to achieve a certain level of high achievement at the workplace, and also at the higher level as a leader. Figure 1 illustrates the type of frontiers technology that would be useful in logistics and transport especially for women training capacity to improve gender equality in logistics and transport sector. In previous studies, it was highlighted that the role of women in the logistics and transport sector has been improved in the last five decades. During the 1970s, there were almost zero women leaders in the top management position in many industries [11]. After five decades, the number of women leaders in many industries is starting to rise [12]. From the logistics and transport perspective, women involvement in this service sector is very low as the industry is dominated by male worker or gents. It is very challenging for women to climb their career ladder in this logistics and transport field without appropriate experience, skills, knowledge and capability. Previous research has explained that one of the key reasons is because of the limited or scarce resources especially in terms of personnel development such as training and capacity building [13–15]. Therefore, it is vital for every woman in the logistics and transport to be exposed with recent development of technology. As highlighted above, there are few types of technology that could advance women opportunity to grow further in this logistics and transport sector. AI technology is one of the popular technologies in transport for instance in the aviation sector. Women

Women and Technology: Enhancing Gender Equality in the Logistics …

37

who work in maintenance, repair and overhaul (MRO) organization for example could help to expedite the process of recognizing the aircraft to do maintenance check or repair. Similarly to block chain technology in MRO, the original document of any document from the supplier can be controlled and monitored to avoid fraud. Women with this kind of technology knowledge will create respect among the workers especially male. Interestingly, technology knowledge will enhance capability, capacity and also expertise of the women in the air transport field. From other context such as logistics, the blockchain technology also starts gaining popularity in avoiding documentation fraud [16]. Knowledge about this type of technology will help women to actively work in every aspect in the field without any limitation. Women can work together with men for every task assigned and eventually will increase gender equality in logistics and transport. Another example highlighted in Fig. 1 is big data and analytics. Women equipped with this technology knowledge are able to help their organization on analyzing the market trend and forecast. For instance, women who work with the airlines organizations would be able to use data that they extract and analyze the data to see the passenger traveling trends. The findings from the analysis will be very useful for planning and decision making. Big data knowledge helps women employees in boosting their confidence and gaining leadership skills in thriving the future market. What has been explained above is absolutely agreeable. However, every new technology application may have their pros and cons. At the same time, regulations in specific sectors with regard to technology application is also one of the main issues. The next subsection will elaborate further on key barriers of technology application among women from the logistics and transport perspectives

3 Key Barriers of Technology Application Among Women in Logistics and Transport It was reported that communication challenges are one of the key challenges for technology user. Communication with mentors regarding technology application may lead to social isolation. Women need to be trained to reach a certain level to be equal with what men have at the workplace. With technology, it helps women to grow further in the organization. However, working with technology may lead to working isolation and in turn will have affects in terms of physical communication, language communication, as well as emotional communication. Another barrier or challenge for women in applying technologies in logistics and transport is cost or price of technology. It was reported that technology is always associated with high price. Sending women workers for training to enhance their technology skills and working capability will involve dollars and cents. If the organization has limitation on the training budget for their women staff, women would not have a chance to join any technology training.

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In relation to this factor, one more important barrier for women is the selection process in their organization for training. As stressed earlier by Burke and Nelson [17], any organization in any sector including logistics and transport does not prefer to send women staff as they assume women lack capability when compared to men for general management skills and specific skills. This will definitely limit women participation in any technology related training. Another barrier for women in technology application is the lack of empowerment in the industry. In logistics and transport industry, it is recognized that this industry is always largely dominated by men or male worker. As highlighted by Mavin et al. [14], the reason males are always being given priority compared to women is because of the patriarchal system. Meaning that, men or male workers are always highly valued compared to women workers. Therefore, with regard to women technology empowerment, men are always being given a priority compared to women. In other word, it is already in organizational culture that women are lower than men. This assumption or culture in logistics and transport sector needs to be improved. An earlier work highlighted that in some cases, women become demotivated to shine at the workplace due to the fact that they do not have internal motivation. It was found that women are becoming passive or demotivated because of the challenges they face along their career path [18].

4 Conclusion and Future Research The recent wave of technology has brought some limitation and contribution which opens up new opportunities for scholars to further study on technology development and its impact in the logistics and transport perspectives. This study also sets the direction of future researchers. While this paper conceptualizes and offers insights into the role of technology in overcoming women challenges in the field of logistics and transport, future scholars could also explore how these technologies can practice overcoming aviation related challenges. This is also supported by previous scholars [19]. In fact, Rahman et al. [20] also called for more research in the field of logistics and humanitarian technology whereby women could also be involved. Moreover, future research is encouraged to look more specifically into the types of data, infrastructure requirements and how the connectedness of industry 4.0 (IR4.0) technologies can be utilized to support decision making and planning across the aviation spectrums of airline, ground handler, caterer, airport and MROs. Acknowledgement This study is supported by Universiti Kuala Lumpur and Ministry of Higher Education, Malaysia (FRGS grant).

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References 1. World Economic Forum, Women’s economic empowerment is the smart thing to do. What’s stopping us? (2017). https://www.weforum.org/agenda/2017/01/womens-economic-empowe rment-is-the-smart-and-right-thing-to-do-whats-stopping-us/. Accessed 25 July 2022 2. United Nation Women, Are we on track to achieve gender equality by 2030? (2022) https://data. unwomen.org/features/are-we-track-achieve-gender-equality-2030. Accessed 26 July 2022 3. S. Banks, Logistics needs more women. Logistics Management (2022). https://www.logistics mgmt.com/article/logistics_needs_more_women. Accessed 27 July 2022 4. N.A.A. Rahman, Women in logistics and transport: concept, capacity, conceptual model and commendation. Test Eng. Manag. 81, 5799–5833 (2019) 5. APEC, APEC women in transportation data framework and best practices report, Nathan Associates (2017). https://www.nathaninc.com/wp-content/uploads/2015/12/2017APEC-WiT-Best-Practices-Compendium-Update.pdf. Accessed 10 Nov 2019 6. R. Shalal, Aviation industry urged to hire more women as staff shortages loom (2018). https://www.reuters.com/article/us-britain-airshow-gender-idUSKBN1K9293. Accessed 28 July 2022 7. S.H. Chung, Applications of smart technologies in logistics and transport: a review. Transp. Res. E: Logist. Transp. Rev. 153, 102455 (2021) 8. N.P. Rana, S. Chatterjee, Y.K. Dwivedi, S. Akter, Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. Eur. J. Inf. Syst., 1–24 (2021) 9. M. Tarafdar, C.M. Beath, J.W. Ross, Using AI to enhance business operations. MIT Sloan. Manag. Rev. 60, 37–44 (2019) 10. G. Yang, G. Ji, K.H. Tan, Impact of artificial intelligence adoption on online returns policies. Ann. Oper. Res. 308, 1–24 (2020) 11. C.E. Helfat, M.A. Campo-Rembado, Integrative capabilities, vertical integration, and innovation over successive technology lifecycles. Organ. Sci. 27, 249–264 (2016) 12. D. Elmuti, H. Jia, H. Davis, Challenges women face in leadership positions and organizational effectiveness: an investigation. Educ. Leadersh. 8, 67–87 (2009) 13. M.I. de Sánchez, Women in architecture: the Spanish case. Urban Res. Pract. 3, 203–218 (2010) 14. S. Mavin, G. Grandy, J. Williams, Experiences women elite leaders doing gender: intra-gender micro-violence between women. Br. J. Manag. 25, 439–455 (2014) 15. C. Peus, S. Braun, K. Knipfer, On becoming a leader in Asia and America: empirical evidence from women managers. Leadersh. Q. 26, 55–67 (2015) 16. C.W. Lin, T. Chen, 3D printing technologies for enhancing the sustainability of an aircraft manufacturing or MRO company—a multi-expert partial consensus-FAHP analysis. Int. J. Adv. Manuf. Technol. 105, 4171–4180 (2019) 17. R. Burke, D. Nelson, Women executives: health, stress, and success. AOM. 14, 107–121 (2000) 18. Emory, Is this the year “equal pay for equal work” is addressed? (2008). http://knowledge. emory.edularticle.cfm?articleid=1175. Accessed 29 July 2022 19. S.F. Wamba, A. Gunasekaran, T. Papadopoulos, E. Ngai, Big Data analytics in logistics and supply chain management. Int. J. Logist. Manag. 29(2), 478–484 (2018) 20. N.A.A. Rahman, A. Ahmi, L. Jraisat, A. Upadhyay, Examining the trend of humanitarian supply chain studies: pre, during and post COVID-19 pandemic. J. Humanit. Logist. Supply Chain Manag., 1–24 (2022)

The Prevalence of Work-Related Musculoskeletal Disorders and Work Productivity of Aviation Maintenance Personnel Nur Nabilah Mohd Yusof, Nurhayati Mohd Nur, and Eida Nadirah Roslin

Abstract This paper aims to investigate the prevalence of work-related musculoskeletal disorders (WMSDs) and the work productivity of aviation maintenance personnel. In this study, a set of questionnaires were distributed to aircraft maintenance personnel in the selected maintenance organization. In total, 197 respondents participated in this study. The results showed that 97.9% of the respondents experienced WMSDs symptoms on at least one part of their body. The highest prevalence of WMSDs for the past 12 months is at lower back with percentage of 67.0% (n = 132), followed by neck 61.4% (n = 121), shoulder 55.8% (n = 110), upper back 45.7% (n = 90), knees 34.5% (n = 68), wrist 29.9% (n = 59), and ankle 28.9% (n = 57). The results also showed that 77.6% (n = 153) of the respondents agreed that body pain or discomfort reduced work productivity. The findings also revealed that the respondents experienced absenteeism (88.32%, n = 174) and presenteeism (98.85%, n = 195) due to body pain or discomfort. It can be concluded that aircraft maintenance personnel experience body pain and discomfort which leads to the risk of contracting WMSDs and reduced work productivity. The findings of this study provide knowledge to the aviation industry to evaluate the existing tasks and workstations to mitigate the risk of WMSDs that could improve the safety and health of the maintenance personnel while simultaneously optimizing work productivity. Keywords Work-related musculoskeletal disorders (WMSDs) · Work productivity · Aviation · Maintenance N. N. M. Yusof · N. M. Nur (B) Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Jalan Jenderam Hulu, 43800 Dengkil, Selangor, Malaysia e-mail: [email protected] N. N. M. Yusof e-mail: [email protected] E. N. Roslin Universiti Kuala Lumpur, Malaysia France Institute, Section 14, Jalan Damai, Seksyen 14, 43650 Bandar Baru Bangi, Selangor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_6

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1 Introduction Aviation maintenance needs to be performed properly to ensure every plane leaving the ground is reliable, safe, airworthy, and at the lowest possible cost. Maintaining fleets properly is vital for aviation to remain one of the safest transportation ways [1]. The maintenance of aircraft involves the activity of maintenance, repair, and overhaul (MRO). The task must be performed by the approved maintenance organization (AMO) which is responsible to appoint the licensed personnel that fulfilled the Civil Aviation Authority Malaysia (CAAM) requirement to operate any maintenance activities of the aircraft. According to the International Civil Aviation Organization (ICAO) approved documentation, aircraft maintenance personnel referred to engineers, technicians also non-destructive test technicians. Generally, in the aviation industry, there are two major maintenance types which are called scheduled and non-scheduled maintenance. Scheduled maintenance is performed at predefined ages of the system to reduce the probability of failure of the system. Meanwhile, maintenance that is performed to restore a system to functioning after it has already failed is referred to as unscheduled preventive maintenance in which the monitored “condition” of the system triggers the maintenance action [2]. Another type of aviation maintenance is layover maintenance which needs to be performed online at the gate or at a connecting airport. These maintenance activities must be planned perfectly to fit in the overall schedule of aircraft that come and go at the gates. Otherwise, delays may occur, thus incurring additional operating costs subsequently. Layover maintenance consists of two parts: short-term layover maintenance and regular checks. Since both parts have other features and concerns, their planning is separated. Short-term layover maintenance includes, in addition to a pre-flight check, a transit, and a daily check [3]. The maintenance activities are challenging but crucial, especially for the engine of an airplane. The engine is complex, subject to wear and failure, safety–critical, and expensive. Therefore, optimization of policy for maintenance and maintenance scheduling of engines, which arbitrates the balance between cost and safety, is a considerable problem. Therefore, it is undeniable that quality time management is imperative in the aviation industry. Time plays an important role to ensure fleets are airworthiness and in safe condition in good time; otherwise, airlines tend to be less profitable. Consequently, this situation would drive the urge of maintenance personnel to constantly perform manual handling tasks such as inspection, repair, removal, and installation in a restricted time with a load of tasks per shift [4]. Performing manual handling tasks could expose maintenance personnel to workrelated physical risk factors that lead to physical fatigue and the risk of contracting WMSDs. WMSDs are usually caused by awkward working posture [5], repetitive tasks [6], and heavy lifting [7]. As WMSDs are alarming in various industries and by looking at the structure of the aircraft itself which is gigantic (high reach space) and have confined spaces mostly require the maintenance personnel to perform tasks in an uncomfortable condition where body parts sometimes need to be bent, squeezed, twisted, and prolonged sitting or standing as well. A study has been conducted among

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maintenance personnel to perform aircraft structure repair on aircraft where drilling and riveting are the main tasks that need to be completed. The study revealed that the maintenance personnel was involved in an awkward posture and ergonomics modification must be implemented for the task [8]. The work environment also influenced the existence of work in an awkward posture such as carrying heavy items and also the height of some components that may cause the personnel to work in the overhead position. For example, a task involving confined space such as cleaning the fuel tank that requires the maintenance personnel to twist, squeeze, and bend while working. In addition, the line maintenance team also experienced difficulties to carry components to be installed in the aircraft. Other than that, repetitive movement and load lifting activities among maintenance personnel should be another risk factor that is considered high in the aviation industry. Recent studies also revealed the relationship between multi-various WMSDs risk factors [7, 9]. The work-related physical risk factors could affect work productivity at work in terms of the number of tasks completed over time or completion time to perform a certain number of tasks given [10]. However, there is a lack of studies that discuss the WMSDs and work productivity of aviation maintenance personnel which motivates this study.

2 Methodology 2.1 Industrial Survey In the industrial survey, a set of questionnaires were distributed to aircraft maintenance personnel in the selected maintenance organization. The survey questionnaires are divided into four sections: A, B, C, and D. Section A is specifically for attaining demographic information, whereas section B and section C focuses on work productivity, and section D is related to WMSDs risks, adapted from the Nordic Musculoskeletal Questionnaire (NMQ). The industrial survey targets respondents in the range of 150–200 [11, 12]. The minimum sample size required was also calculated through the sample size calculator software (Raosoft.com), at a 95% confidence level [13]. The calculation result suggested a minimum of 169 responses were required to satisfy the survey results.

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3 Results and Discussion 3.1 Reliability Test A reliability test had been performed on the questionnaires used in this study. The value of Cronbach’s alpha is 0.805. The result indicated that items in the questionnaires are interrelated with high-reliability value [14].

3.2 Demographic Data In total 197 respondents participated in this survey. All respondents were declared healthy and did not experience any accidents for the past 7 days to ensure the results are not affected by other external factors. Most of the respondents are males who contributed about 83.2% (n = 164) meanwhile female respondents only comprised about 16.8% (n = 33). Fewer females are involved in this maintenance area because of several factors. For example, to concise the gender issue in the aviation maintenance field, a study has been conducted among women in the American population, where the results show the main factors that make women less interested in the aviation maintenance field are physical limitations, social environment, and safety environment [15]. Regarding the WMSDs issue, gender contributes as one of the risk factors that may indicate either the ease of experiencing body discomfort or vice versa [16, 17]. However, the gender factor is not the factor investigated in this study, as this work focuses only on musculoskeletal disorders and physical risk factors at the workstation. In terms of age, the highest population in this survey comes from aviation maintenance personnel aged between 19 and 25 years, which represents a percentage of 51.27% (n = 101). The second highest was aged from 26 to 35 years old, contributing to about 38.1% (n = 75). Meanwhile, only 8.6% (n = 17) and 2.03% (n = 4) of the respondents are from the age range of 36 to 45 years old and more than 45 years old, respectively. Other than that, this survey identified the position of respondents. Most of the respondents that answered the survey are technicians 57.87% (n = 114), followed by Licensed Aircraft Engineers (LAE) who contributed 24.37% (n = 48) to this industrial survey, and 17.77% (n = 35) are from non-destructive testing inspectors. All respondents have been identified to be working directly with aircraft aviation maintenance. The industrial survey also focused on the section where the respondents were involved in their working experience. This is because the types of maintenance may have varied based on workload, daily routine, and risk factors that contributed to WMSDs symptoms and affected work productivity. The majority of the respondents are involved in the base maintenance section, 97 respondents (49.24%). Differing from line maintenance, only 82 respondents (41.62%) work in the abovementioned section, and the least number of respondents is from component maintenance, contributing to only 9.14% (n = 18).

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Based on these results, data trends from this survey showed that base maintenance personnel can be more prone to risk factors due to the heavier task performed and complicated tasks given in practice, mainly heavy checks, such as C and D checks. During those checks, major and minor aircraft systems are evaluated together with complex and time-consuming tasks such as corrosion prevention, structural work, replacement of major components, and interior refurbishment, compared to line maintenance or so-called routine maintenance [1]. The period of working experience can be one of the factors that lead to WMSDs symptoms, previous studies found that the increase in WMSDs symptoms is concurrent with several working years [18]. Based on the results, the majority of the respondents (40.1%, n = 79) have been working as a maintenance personnel for 1 to 5 years. Meanwhile, only 18.27% (n = 36) of the respondents have working experience for more than 10 years, and 19.29% (n = 38) have been derived for respondents that have been working for 6 to 10 years (16%). For respondents with working experience of less than 1 year, this contributed to about 22.34% (n = 44). The data distribution of working experience is via normal distribution, where the highest population is from those working for 1 to 5 years. Most respondents have working experience of between 1 and 5 years; this is where the entry-level population comes from. This is relatable with the results where the technician is the majority population that was discussed earlier. This is because in the aviation field, normally, the personnel can be a technician before they obtain the Licensed Aircraft Engineer (LAE) position, in which the training for such position would take from 3 to 5 years. From this fact, the results show synchronization between both working experience and position. Occasionally, the number of years is considered long enough if the working environment is surrounded by work-related physical risk factors and the risk of WMSDs. This is supported by a series of studies that stated WMSDs are not only associated with the number of working years, but also with a series of prolonged hours that can lead to serious musculoskeletal injuries due to frequent exposure to related risk factors. Thus, indirectly, results from years of working in this study are considered significant, where the degree of severity of WMSDs symptoms can be measured. The type of maintenance services can be traced from the survey, as it is significant data to ensure which part of maintenance is more prone to contracting WMSDs risk. These results correspond to the types of maintenance tasks performed. For those working in line maintenance, aviation maintenance personnel normally deal with maintenance in the hangar without taking a long time to perform maintenance works. This is different for those working with heavy or base maintenance, in which the tasks involved are more difficult and include heavy-duty such as engine maintenance. For component maintenance, the personnel normally work in a specific shop, where the task becomes more precise only for certain components. In this study, the maintenance service that respondents dealt with is selected as one of the factors that are relevant to the risk factors of WMSDs. Hence, from the industrial survey, the majority of the maintenance personnel work with airframes (38.58%), followed by avionics (26.9%), and engines (18.8%). Only a few of them (15.74%) are involved in others maintenance services such as non-destructive inspection.

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3.3 The Prevalence of WMSDs The results of the industrial survey showed that 97.9% of the respondents have WMSDs symptoms on at least one part of their body. By referring to Fig. 1, for the past 12 months, respondents have had discomfort in their lower back, showing the highest prevalence of WMSDs symptoms with a percentage of 67% (n = 132). The second highest body part that is exposed to WMSDs is the neck with 61.4% (n = 121), followed by the shoulder at 55.8% (n = 110). Consequently, the prevalence of WMSDs symptom in the upper back shows a percentage of about 45.7% (n = 90). Respondents with knee troubles are also notably seen, with a contribution of a percentage of 34.5% (n = 68). Then, the respondents who have wrist and ankle troubles are also considered to have a high percentage at 29.9% (n = 59) and 28.9% (n = 57), respectively. Meanwhile, respondents who reported having less trouble at the elbow show the lowest percentage compared to other body parts, which is 13.2% (n = 26). Further to the above, 20.3% of respondents (n = 40) also reported experiencing discomfort at the hips during the past 12 months. For body discomfort experienced by the respondents over the past seven days, the most prevalence of WMSDs was observed in the lower back, 25.38% (n = 50), followed by the second-highest of WMSDs prevalence faced by respondents which are shoulders 20.81% (n = 41), then followed by respondents who faced discomfort in the neck 17.25% (n = 34). By slightly different percentage values, the upper back 14.21% (n = 28) and wrists 12.69% (n = 25) are other body parts that respondents reported having trouble with for the past seven days. Both knees and ankles share the same percentage at 9.14% (n = 18) of the total number of respondents. On the other hand, only 4.07% (n = 8) suffered discomfort at the elbow in the past seven days. The results are shown in Fig. 2. 180 160 140 120 100 80 60 40 20 0

157 121 76

138 110

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Fig. 1 Prevalence of WMSDs for the past 12 months

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Fig. 2 Prevalence of WMSDs for the past 7 days

3.4 Work Productivity Further investigation had been done to identify the effect of body discomfort on work productivity. The results found that 77.6% (n = 151) of the respondents agreed that body discomfort affects their work productivity. Work productivity is portrayed in terms of absenteeism and presenteeism. When respondents still go to work but do not perform fully at work, it is called presenteeism. 98.85% (n = 194) of the respondents had missed working hours due to body discomfort for the past seven days. It can be claimed that almost all respondents have missed work for at least an hour due to body discomfort. On the other hand, when respondents tend to get away from the workplace or take leave, this situation is called absenteeism. This study found that the absenteeism percentage is high, where almost 88.32% (n = 172) of the respondents were away from work due to body discomfort.

3.5 The Effects of WMSDs on Work Productivity This study aims to investigate the prevalence of WMSDs and its effects on the work productivity of aviation maintenance personnel. As presented in the earlier section, aircraft maintenance personnel experienced body pain or discomfort in at least one part of their body. It is important to maintain a good posture while performing maintenance tasks, especially when one is exposed to various manual material handling such as that in maintenance line, workshop, component shop, and hangar. Maintenance activities are sometimes performed in confined work areas, which resulted in body pain or discomfort. The body pain and discomfort disturbed the work progress of the maintenance personnel.

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Apart from that some of the maintenance activities are performed in a small area. The small area in the aviation section, such as the aircraft tank, will lead to body discomfort and pain whereby the maintenance personnel needs to squeeze of their body to fit into the aforementioned working area. Maintenance activities are also involved in frequent carrying or lifting of heavy or overload items. The total load or how frequently the personnel deal with the heavy item may affect the degree of discomfort that leads to physical fatigue and WMSDs symptoms. The work-related physical risk factors in maintenance activities include heavy lifting, repetitive motion, and awkward posture. The pain in any body parts would force maintenance personnel to take a longer time to accomplish their work. Maximizing work productivity is critical in the aviation industry, especially in the maintenance section. As aviation maintenance constantly deals with time and cost, the personnel are willing to work extra hours to finish their task or routine. The activities recorded in the task card, either in routine maintenance or non-routine maintenance, must be completed as planned by the airlines. Due to long working hours of the conventional 8 h, as well as overtime, respondents often experienced physical fatigue and discomfort in any part of their body. When the maintenance personnel experience body pain or discomfort, they tend to take a short break while working which caused missed working hours to increase. This kind of situation is called presenteeism, whereby the personnel present at work with less performance or not at full capacity at work. The persistent and ongoing health-related issues among personnel in an organization reduced work productivity and will increase the operation cost [19]. The survey results showed that more than 98% of respondents tend to miss working hours (at least 1 h) whenever feeling pain in any part of their body during work. The result indicated that as the personnel feel disturbed and disrupted due to body discomfort, the situation gives an impact on the work completion time which leads to a reduction in work productivity. Instead of missing working hours, the respondents decided to take medical leave due to body pain. This kind of situation is related to absenteeism. The survey reported about 88% of respondents were involved in absenteeism which caused a loss of work productivity. Due to the critical need of completing work on time and less absenteeism in the aviation maintenance area, it is important to implement the ideal ergonomics workstation to reduce the WMSDs physical risk factors which help in increasing the personnel’s work productivity. It is important to take a short break during work to ensure the posture or repetitive work done is not prolonged. Apart from that, ergonomics and safety training in the industry has now become imperative to provide knowledge among maintenance personnel so that implementation of the safe method when performing tasks can be done. Indirectly, accidents and injuries especially when dealing with physical risk factors of WMSDs can be reduced and improve work productivity.

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4 Conclusion Aircraft maintenance personnel experienced body pain and discomfort, with the most pain or discomfort discovered in the lower back, followed by the neck and shoulder. The body discomforts among aviation maintenance personnel were extremely caused by the exposure to heavy lifting, awkward posture, and repetitive motion. These work-related physical risk factors caused physical fatigue which leads to the risk of contracting WMSDs. The WMSDs risks are found to reduce work productivity due to absenteeism and presenteeism. The findings of this study provide knowledge to the aviation industry to evaluate the existing tasks and workstations to mitigate the risk of WMSDs that could improve the safety and health of the maintenance personnel while simultaneously optimizing work productivity. Acknowledgements This paper is a part of the research which is financially supported by the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme (FRGS/1/2018/TK03/UNIKL/02/3).

References 1. J.V. Bergh, P.D. Bruecker, J. Belien et al., Aircraft maintenance operations: state of the art. Hubrussel Research Paper, Brussel (2013) 2. D.R. Vieira, P.L. Loures, Maintenance, repair, and overhaul (MRO) fundamentals and strategies: an aeronautical industry overview. Int. J. Comput. Appl. 135(12), 21–29 (2016) 3. D. Boyd, A. Stolzer, Causes and trends in maintenance-related accidents in FAA-certified single-engine piston aircraft. J. Aviat. Technol. Eng. 5(1), 17 (2015) 4. M. Sheikhalishahi, L. Pintelon, A. Azadeh, Human factors in maintenance: a review. J. Qual. Maint. Eng. 22, 218–237 (2016) 5. E. Houshyar, I.J. Kim, Understanding musculoskeletal disorders among Iranian apple harvesting laborers: ergonomic and stopwatch time studies. Int. J. Ind. Ergon. 67, 32–40 (2018) 6. D.S. Chander, M.P. Cavatorta, An observational method for postural ergonomic risk assessment (PERA). Int. J. Ind. Ergon. 57, 32–41 (2017) 7. S. Bulduk, E. Özgür Bulduk, G. Alpaslan, Job satisfaction among aircraft baggage handlers and their exposure to risk factors for work-related musculoskeletal disorders: a case study. Work 56(2), 301–308 (2017) 8. S.A. Stader, Ergonomic evaluation of aircraft wing recovering tasks in general aviation maintenance. Proc. Human Factors Ergon. Society Ann. Meet. 57(1), 1249–1253 (2013) 9. N. Mohd Nur, M.A.S. Mohamed Salleh, M. Minhat et al., Load lifting and the risk of workrelated musculoskeletal disorders among cabin crews. IOP Conf. Ser.: Mater. Sci. Eng. 370, 1–9 (2018) 10. D. Beaton, C. Bombardier, R. Escorpizo et al., Measuring worker productivity: frameworks and measures. J. Rheumatol. 36(9), 2100–2109 (2009) 11. P.K. Hanumegowda, S. Gnanasekaran, S. Subramaniam et al., Occupational physical risk factors and prevalence of musculoskeletal disorders among the traditional lacquerware toy makers of South India. Work 70, 405–418 (2021) 12. M.A. Memon, H. Ting, J.H. Cheah et al., Sample size for survey research: review and recommendations. J. App. Struct. Equ. Modeling 4(2), 2590–4221 (2020)

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13. S.N. Ahmat, M.R. Muda, C.F. Neoh, Self-esteem level and its relationship to academic performance among undergraduate pharmacy students in a Malaysian public university. Indian J. Pharm. Educ. 52(2), 197–201 (2018) 14. J. Pallant, SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS (Routledge, London, 2020) 15. P.J. Clark, J.M. Newcomer, A.M. Jones, Overcoming gender barriers in aircraft maintenance: Women’s perceptions in the United States. Coll. Aviat. Rev. 33(2), 66–84 (2015) 16. K.H. Choi, J.K. Kim, H.H. Shim et al., Gender-based differences in actual thumb force exertions at various target force levels. Appl. Sci. 10(1), 1–9 (2020) 17. P. Madeleine, S. Vangsgaard, J.H. Andersen et al., Computer work and self-reported variables on anthropometrics, computer usage, work ability, productivity, pain, and physical activity. BMC Musculoskelet. Disord 14, 226 (2013) 18. M.Z. Alnaser, A.M. Almaqsied, S.A. Alshatti, Risk factors for work-related musculoskeletal disorders of dentists in Kuwait and the impact on health and economic status. Work 68(1), 213–221 (2021) 19. J. Chen, J. Qiu, C. Ahn, Construction worker’s awkward posture recognition through supervised motion tensor decomposition. Autom. Constr. 77, 67–81 (2017)

Stress Factors and the Impacts of COVID-19 Pandemic: A Review on the Aviation Industry Noor Ikma Syazwana Paisan and Rita Zaharah Wan-Chik

Abstract This study outlines the stress factors and the impact of the COVID-19 pandemic on the stress variables among aviation workers, which includes airline employees, flight crews, pilots, maintenance crews, air traffic controllers, airport or ground workers, engineers, training personnel, and other aviation-related personnel. A review was done on 37 research papers using systematic literature review (SLR) and discovered nine stress factors among aviation workers which are working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and the COVID-19 itself. The findings of this study could provide insights to employers in the aviation industry for mitigation actions that could help to successfully reduce and eliminate stress factors in the workplace. Keywords Stress factors · COVID-19 · Aviation · SLR

1 Introduction The terms “work stress” and “job challenge,” which refer to two distinct ideas, are frequently interchanged, but they are actually not interchangeable. Challenge motivates people to learn new skills and master the jobs by stimulating individuals, both mentally and physically. People often feel relaxed and satisfied after completing a challenge. As a result, the challenge is an important component of a healthy and productive work environment, whereas stress contributes more adverse effects than good effects. When people say that a little bit of stress is good for you, they are N. I. S. Paisan Aviation Management Program, Universiti Kuala Lumpur Malaysian Institute of Aviation Technology, Selangor, Malaysia e-mail: [email protected] R. Z. Wan-Chik (B) Technical Foundation/Aviation Management Section, Universiti Kuala Lumpur, Malaysian Institute of Aviation Technology, Selangor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_7

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in fact pointing to the challenge of working and not the job stress. In workplaces, since modern businesses operate in a rapidly changing environment, employees are confronted with a variety of mental, emotional, and behavioral issues that cause them stress [1]. Stress that arises from work can be a silent killer since it promotes emotional and mental disorders such as irritation, depression, and anxiety [2]. Authors of [3] described stress as the sensation of being overburdened and therefore unable to manage with emotional or mental strain. Stress factors can come from work, environment, socioeconomy factors like poverty and low income, self-desire, social relationships such as interpersonal and intrapersonal relationships, and stress can also come from home [4]. This stress in workplaces is known as work-related stress (WRS), and it will not only impact the well-being of an individual, but also their job performance. Time constraints and role uncertainty have a major and detrimental impact on the performance of the employee [5]. WRS is defined by the World Health Organization (WHO) as a person’s reaction when confronted with job expectations and burdens that are not matched to their knowledge and talents and that test their capability to handle the pressure [6]. Job stress is also associated with the emotional response that arises when job criteria do not meet the worker’s talents, resources, or needs. Occupational stress may lead to health issues and even body injury [7]. Indirect stress effects are those that arise because of psychological variables linked with task load demands [8]. Stress and job performance relate to one and another especially for WRS as it happens in the workplace. There is a thin line between these two, and they can sometimes be indistinguishable. The general responsibility of an employer is to ensure a healthy and safe working environment and to protect the welfare of employees. Providing a safe and healthy workplace includes ensuring that the characteristics stated above have no adverse impacts on the workers [6]. Air transportation players like flying crews and air traffic controllers require some of the strictest medical and mental requirements for work. Parts of the job requirements for license holder, pilots, and cabin crew are that they must not have any history of “psychiatric disease or disability, condition or disorder, acute or chronic, congenital or acquired” [9]. Apart from the requirements, there are also incidents and accidents that were impacting organizations in terms of loss or reduction of resources: people, money, and assets. It has been reported that airline pilots are listed as the third most stressful jobs in 2019 [10]. High job performance is demanded of pilots as flying an airplane with potentially hundreds of lives on board is one of their primary responsibilities. In Stockholm, Sweden, in 2007, a Cathay Pacific 747F scheduled to fly from Stockholm to Dubai started taxiing before it was given the all-clear, hit a tow truck, and continued taxiing for an additional 150 m. Fortunately, no one was killed or hurt; the tow crew’s shock was the only casualty. Due to stress, fatigue, and inadequate checklists for the pilots, which also limited their ability to focus, this occurred [11]. However, in another case, 51 people were killed in a plane crash at Kathmandu’s Tribhuvan International Airport [12], where the pilot of the US-Bangla plane was suspected of trying to lie to the control tower during the landing process and was found smoking continuously inside the cockpit throughout the hour-long flight from Dhaka to Kathmandu. Upon investigation, the captain was discovered to be extremely stressed and anxious where he made a string of erroneous judgments that led to the crash of flight BS211. This demonstrates that even

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while there are rules that the aviation players must follow, they are insufficient if the primary cause—namely stress factors or stressors—are not removed in the first place. This can result in fatalities, injuries, and loss of resources. This study is interested in examining stress factors for pilots and other aviation sector personnel based on recent literature, especially those published within the last ten years. Additionally, to look into how the COVID-19 epidemic (which was initially a pandemic) has affected the stress variables in the aviation sector.

2 Methodology This study employs the systematic literature review (SLR) to investigate stress factors among aviation workers. The method involves identifying and summarizing relevant studies that used coordinated, thorough, and repeatable review throughout the project’s life cycle [13]. Keyword search for publications to be analyzed for this study includes “stress” + “aviation” + “air transportation” + “COVID-19” + “workers” and the years chosen were between 2011 and 2021 as to narrow down for studies in the past ten years. After removing duplicates and irrelevant studies, the total number of publications chosen to be analyzed for this study was 37. The literature is then examined by methodically categorizing and documenting the characteristics of textual, visual, or auditory information. The discovered emerging themes of stress factors are then classified and subcategorized into various groups. Categorization occurred early in the review process by generating preliminary categories by explaining where and how patterns occur. This results in data extraction, which occurs after re-reducing data into labels to create groups for more efficient analysis. The possible categories were key terms emphasized in the concept of this study to address the issue at hand, which is stress factors. The categories were then combined to form main themes that accurately identify the data in terms of concepts or topics. It is critical to specify exactly what the themes represent when creating them, even if the themes do not appear to suit the result. Finally, the themes were supported by facts and a broad theoretical viewpoint.

3 Results and Discussion From the literature, there were nine main stress factors discovered within the aviation industry which could be categorized to: working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and COVID-19 pandemic. Working hours. Under the working hours, there were two emerging subcategories discovered to be the stress factors: unusual working hours and long working hours. Unusual working hours may occasionally be caused by the nature of the tasks being performed [14–17], whereas long work hours are typically the result of overtime

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and additional hours [18–22]. Given the time required to complete a task, it is not uncommon for flight crews to work quite different hours from those working at airport offices [23]. Long working hours restricted their opportunities for rest, which is generally coupled with the load of on-call duty for pilots and flight crews [24, 25]. The COVID-19 pandemic has only made matters worse, particularly for airline employees and pilots who now work irregular shifts instead of the typical ones [16, 21, 22]. Workloads. As in most organizations, all workers have responsibilities that have been assigned to them by their managers, but having too many responsibilities, also known as workloads, can cause workers to become stressed [16, 19, 25–29]. This is due to the fact that as workloads increased, so did the pressure [30]. According to some reports, the quality and heavy workload of activities, as well as the stringent workload breaks restrictions, were contributing factors in the stress experienced by aviation maintenance crews [15, 17]. Additionally, COVID-19 had also changed the workload and introduced to the aviation workers new workflows and work processes [25]. Flight crews, on the other hand, experience stress as a result of the time constraints and work intensity during COVID-19, which also causes fatigue [24]. Furthermore, pilots have been impacted by the pandemic, with an increase in workload during the crisis, intensive cargo operations, emergency operations, additional workflows, and work processes [21]. Internal factors. For internal factors, it can be divided into personal stressors, WRS, and social support. Personal stressors are any negative internal or psychological feelings a person may experience [31–33]. Sleep quality, circadian rhythms, sleep duration, socioeconomic factors, commuting, family life, and even social life are all possible personal traits that may become stressors for maintenance crews [15]. Adding to the list of personal issues is home worries, physical discomfort, being unwell, alcohol abuse, nicotine abuse, and prescription drugs abuse which may all be stressors [34]. Additionally, life pressures which are typically psychological in nature, include problems with money, relationships, and emotions are found to be stressors for cabin crews [35]. Furthermore, domestic issues such as divorce, death of a family member, financial difficulties, moving homes, and changes in lifestyle may also have an effect on the employees personally, particularly flight crews. Other issues such as work aggravation and dissatisfaction, mood difficulties and depression, poor judgment, and an inability to concentrate, are found to be stressors for aviation maintenance workers [14, 17]. For aviation maintenance employees, stress can be brought on by boredom, weariness, lack of sleep owing to having too much to do in too little time, shift changes, and jet lag [34]. Additionally, performance pressure and an uneven work-life schedule contribute to WRS among airline employees [16]. WRS was identified as a source of stress for pilots [32, 36], and stress level can also be increased by lack of social support from those around them [16, 29]. When coping with the COVID-19 pandemic, stress can be exacerbated by a person’s personal stressors as well as by problems or events that occur outside of the workplace, such as family troubles, health problems, or financial difficulties [31]. Ergonomic issues. The workplace environment has a role in stress among aviation workers as a result of hazardous working circumstances [17, 29]. The cramped

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quarters of the cockpit and the unnatural workplace of being five miles up in the air were noted drawbacks for pilots [36]. Maintenance crew’s stress levels were found to be increased by physical elements such heat, noise, and vibration [34, 37]. High air traffic density, significant flying mishaps, and physical workplace pressures caused flight crews to feel stressed [23, 38]. Moreover, ergonomic issues occurred as a result of inadequate workplace safety [16, 39]. The threat of COVID-19 adds stress to the pilots’ already high levels of heat and humidity, noise, vibration, and low oxygen levels [40]. Job uncertainty. Job insecurity and concerns are two emerging subcategories of job uncertainty. Several studies have identified job insecurities as stressors for pilots, flight crews, airport workers, and airline crews [15, 16, 19, 32, 35]. Aviation workers in general are concerned about the country’s future and technological uncertainties [41, 42] with air traffic controllers particularly are concerned about their employment prospects [29] and airport workers frequently express concerns about the future or their slow career advancement [1]. Authors of [15] support the country’s future as well, citing economic pressure among maintenance workers as a stressor. Any emergencies, unusual situations, or unfavorable working conditions can also cause stress in flight crews [23]. Meanwhile, with mostly all passenger flights being grounded due to the COVID-19 pandemic, 66 percent of flight attendants either feared or were concerned about losing their jobs [43]. Losing a job as a result of COVID-19 was also mentioned as a source of stress for other aviation personnel, including pilots and training personnel [24, 25, 44–46]. Other aviation workers are stressed because they are concerned about the future of their country if the pandemic continues [42]. Job demands. Performance pressure and job satisfaction are two examples of employer demands which are stressors for air traffic controllers [29, 30]. Demanding job makes the airport and ground staff unhappy [1]. Flight crews, on the other hand, are stressed when they must adapt to the situation [23] and expected to be versatile, flexible, and to be available when duty calls [5]. While task demands differ for each task assigned to workers, aviation workers in general, maintenance workers, and flight crews all report that task demands were a source of stress for them [14, 20, 41]. Furthermore, when COVID-19 hits, employer demands and expectations rise, causing airline workers to feel stressed even though the demands are within the scope of their job [47]. Flight crews, on the other hand, experience stress as a result of the psychological and physical demands of flight, as well as the need for on-call duties before and during the COVID-19 pandemic [24]. Organizational issues. The organizational issues can be divided into two: superior’s support and staff management. Aviation workers, engineers, air traffic controllers, and pilots reported for being stressed due to a lack of managerial support from their superiors, supervisors, flight operations, and management [28, 36, 48]. Due to a lack of staff management, there are issues with role ambiguity and role conflict, which cause engineers, airport or ground workers, air traffic controllers, and aviation workers in general to feel tense [17, 19, 30]. This could be because of a disjointed organizational structure [1] or poor organizational climate [16]. Pilots may have different goals and values than management, and they felt that there is a

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lack of management engagement with pilots [36]. Different leadership styles, interpersonal relationships, organizational factors, and organizational structure can all cause stress in aviation workers [41]. Organizational factors also emerge during the COVID-19 pandemic, with engineering workers expressing stress due to a lack of support from superiors and role ambiguity or conflict [48]. Team conflict. Negative interpersonal interactions can also be difficult and become a stress factor [30] and conflicts among employees at work could also be to blame [1]. Conflict at work was found to be a stressor for air traffic controllers and hierarchy pressure for the maintenance crew [15, 29]. Tension may also result from the hierarchy when coworkers cannot provide help [14]. Pilots feel stressed out as a result of the changes in team attitude and cooperation [21]. It was reported that because of a lack of coworker support, aviation professionals are stressed when COVID-19 spreads around the world [48], and the pressure from team dynamics in aviation workers during the pandemic can cause distress [25]. COVID-19 pandemic. The recent COVID-19 pandemic itself has been reported by several studies to be a stress factor for aviation workers in general and airline employees [25, 42, 47]. This is due to the pandemic’s infection fears, frustration, boredom, insufficient home supplies, fear of personally contracting the virus, fear for a family member’s health, potential ongoing medical problems, need to maintain social isolation, difficulty maintaining a positive atmosphere with close family and others in society, and even dread of coming into contact with COVID-19 patients. Aviation workers in general experience stress as a result of monetary loss, financial concerns as a result of a furlough or job loss, inability to pay rent or the home loan, potential eviction due to unpaid rent/loan, and insufficient money for food for the family during COVID-19 [42]. Others are distressed as a result of the increased financial burden [25]. Pilots experience stress as a result of financial concerns and income loss [40]. Moreover, staying at home for an extended period of time due to isolation, also known as home quarantine, was one of the stress factors brought on by COVID-19 for pilots and aviation workers [21, 25, 42, 45].

4 Conclusion To summarize, there are nine stress factors among aviation workers found from reviewing 37 publications. The stress factors are working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and COVID-19. The findings of this study could provide insights to employers in the aviation industry for mitigation actions that could help to successfully reduce and eliminate stress factors in the workplace to produce good job performance.

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Development of a Pocket Alarm Security System Nur Amirah Sabrina Luqman, Izanoordina Ahmad, Zuhanis Mansor, and Siti Marwangi Maharum

Abstract Technologies have evolved and simplified many people’s lives in the twenty-first century. However, the number of problems and cases of domestic violence reported continues to rise. As a result, it has become a source of anxiety for many people as they go about their daily lives. This prototype focuses on the construction of a technology that is connected to apps in terms of security. This project allows users to broadcast their current position to a pre-added contact in an app with a single button press. A few more features have been incorporated to assure the device’s effectiveness, and the design is intended to be portable. The main microcontroller in this project is the NodeMCU. The system use to alert is by using the application of Blynk. Hopefully, by using this device with an accuracy of 98%, the user could be able to feel more secure while going through their regular routines and the domestic crimes could be prevented. Keywords Domestic crimes · NodeMCU · Blynk · Pre-add contact · Internet of things

N. A. S. Luqman · I. Ahmad (B) · Z. Mansor · S. M. Maharum Universiti Kuala Lumpur British Malaysian Institute, Batu 8, Jalan Sungai Pusu, 53100 Gombak, Selangor, Malaysia e-mail: [email protected] N. A. S. Luqman e-mail: [email protected] Z. Mansor e-mail: [email protected] S. M. Maharum e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_8

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1 Introduction Domestic crime rates have fluctuated during the past ten years in Malaysia [1], according to reported cases. Throughout the advancement of the technology era, this issue will undoubtedly get more serious. Hopefully, our research will aid in stopping these crimes from happening. A compact, useful device that, with a single click, notifies the pre-set contacts in the apps. The user’s current GPS location will be broadcasted throughout the app. The user of this equipment should feel secure while going about their daily business. Violent crimes in Malaysia are classified as murder, rape, robbery, and other crimes that involve injury due to the country’s high domestic crime rates, as opposed to property crimes, which include car theft, home invasions, and so forth. Previous works that have hardware and functionality similarities are analyzed and discussed. Hence, the design of the project is capable of overcoming any faults in previous projects. The purpose of designing and developing “Suraksha,” a women’s safety gadget, was to provide a product with a wide range of capabilities [2]. The main tactic is to intimidate victims into giving police both their current location and a distress signal message. Devices are activated through the use of switches, shock sensors, and voice. The device is locked when not in use to stop unauthorized signals from being sent. When a distress signal is transmitted to the registered mobile number, it uses a GSM module to send the location to the authorities. The goal of the project [3] is to develop an intelligent, smart security system for women. All across the world, women experience a lot of unethical physical harassment. This project is a suggestion made to address such an issue. Two items make up this project: a wristband and eyeglasses. The device has a pressure switch that serves as an input and resembles a bracelet. The result is made known when it is triggered. This project introduces screaming alarms and tear gas with the goal of adding self-defense features, and they send location and messages to emergency contacts as well as enabling the culprit to be seen in real-time video. The spectacles come with tear gas and a webcam for live streaming footage. The project’s process flow is completed by the use of a pressure switch, a Raspberry Pi 2, a GSM modem, a GPS receiver, a screaming alarm, tear gas, and live streaming video. The development of a smart device that can help women in emergency situations is discussed in the publication of the smart shield for women safety [4]. The system is a wearable smart gadget that has a jacket-like appearance. The device has a number of modules, including GPS, GSM, a camera, a buzzer, and a shock mechanism circuit. The system’s primary objective is to give women a trustworthy security system. The system also makes use of a number of other sensors. The prototype jacket is a model with the GPS REB-4216, GSM SIM300, SMD LED module, and buzzer controlled by the Atmega8A microcontroller. The LCD displays the latitude and longitude information that was sent through NMEA. When the switch is depressed, the emergency contacts receive a GSM message with the position displayed on Google Maps.

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The goal of smart gadget for women safety utilizing the Internet of things (IoT) is to create a low-cost safety tool that, in dire circumstances, might well save a woman’s life [5]. The proposed system combines cutting-edge IoT technologies with hardware innovations like the Raspberry Pi and NodeMCU to provide an end-to-end security solution for women’s safety. The system is divided into two components. When there is a suspected motion in front of the camera, the first portion ensures that the device takes a picture of the offender; the devices take the offender’s picture and send it as an attachment to the relevant e-mail address together with the victim’s location. The second section is dedicated to self-defense. When the attacker is closer, the LED flash on the smart pendant beams on the offender’s eyes to obscure their vision while also sending an alert call to family members and friends via the cloud. Design and implementation of a system for women’s safety concept and implementation of the “smart band” were detailed based on the IoT technology [6]. The device comes with a trigger, an ATmega2560 microcontroller, a GSM module (SIM900), a GPS module (neo-6 M), an IoT module (ESP-12), a neurostimulator, a buzzer, and vibrating sensors. In this experiment, a participant must keep the device’s trigger turned on when she senses danger. When the gadget is turned on, the global positioning system (GPS) is used to determine the current location, and GSM is used to send an emergency message to the registered mobile number and a nearby police station (Global System for Mobile Communication). The homepage is refreshed, and the position is continuously tracked by the IoT module. In emergency situations, the buzzer will serve as an alarm to notify onlookers, letting them know that someone is in difficulty, and the vibrating sensor will transmit the last position if the device malfunctions. The neurostimulator will deliver a non-lethal electric shock to identify the attacker. Therefore, this project is to create a prototype that will help to reduce the risk of domestic crimes in Malaysia. The first and foremost objective of this project is to design a system for a pocket alarm system that is compact with the integration of the IoT. The second objective of this project is to develop a prototype of a pocket alarm system that will allow users to pre-add emergency contacts. The last objective of this project is to test and evaluate the pocket alarm system to determine whether it can easily be used by users in an emergency situation.

2 Methodology The project involves three main experiments and described as follows: Experiment 1 involves designing a system that is compact with the integration of application. Experiment 2 involves developing a prototype that will allow users to connect with GPS and Blynk when the device is triggered. Experiment 3 involves identifying and measuring the location accuracy by comparing both the real location from the mobile phone GPS location coordinate

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Fig. 1 Block diagram of pocket alarm security system

and the prototype GPS location coordinate. Determining the GPS signal’s stability in this experiment, the prototype is being carried to places such as underground, rooftops, and indoors and outdoors too. Figure 1 shows the operating system of the pocket alarm system. The two-push button is separated into two inputs, whereas the battery acts as the source for the microcontroller. GPS is one of the button outputs, followed by a buzzer and led as another output. All the systems are processed through the microcontroller NodeMCU. When the system is at its initial state, all inputs will be turned off as shown in Fig. 2. Once the source is turned on, the microprocessor will read the data. The microprocessor will then read the inputs from pushbuttons 1 and 2. If pushbutton 1 s input is high or if it has been pressed, the GPS module will be triggered by the microprocessor, and the GPS module will initiate and send the location data to the cloud. Furthermore, if the second pushbutton is pressed, the buzzer and the super bright LED will be activated by the microcontroller. Lastly, if the microprocessor reads the input for the push button to be low, the system will end.

3 Results and Discussion Autodesk Fusion 360 was used to design the prototype casing. The design is compact, which is easy to hold in hand, comfortable, and practical. Based on offline surveys from students around the campus, they agree that the device prototype can easily be distinguished as a keychain rather than a safety device. They also commented that

Development of a Pocket Alarm Security System Fig. 2 Flowchart of pocket alarm security system

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the device is light weight, which makes it a bonus point toward the compactness of the prototype design as shown in Fig. 3. Based on the following Fig. 4a, the interface used is Blynk. Inside the Blynk interface, latitude and longitude coordinates are displayed with the actual location in the maps. When the button v6 is pressed, it will send a signal (email) to the pre-added contact shown in Fig. 4b. Figure 4c is the e-mail example of the notification received in email. Based on Fig. 5a, which shows the system when the button is pressed, GPS is turned on. The latitude and longitude of the device’s location are displayed. However,

Fig. 3 Prototype of pocket alarm security system

Fig. 4 Blynk interface of the system

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Fig. 5 Location of user using pocket alarm security system

Fig. 6 Reading of GPS accuracy percentage × number of attempts

based on Fig. 5b, the location is not 100% accurate. Few more experiments on accuracy have been conducted to detect and calculate the accuracy of the GPS module of the prototype. The result of this experiment is that the accuracy of the GPS signal is between 95 and 98%, as shown in Fig. 6.

4 Conclusion The pocket alarm system has achieved the objectives based on the results from these three experiments with good accuracy. Some of the features are effective in ensuring the system’s users’ safety. There are numerous features that need to be added to

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the system after conducting the project to make it competitive and appealing in the market. Firstly, based on objective 1, the system was designed with the integration of Blynk. Linking the hardware devices to the cloud using the application of Blynk has been a success. Secondly, based on the second objective, the prototype has gone through some minor changes throughout the process to ensure the most efficient and stable system. Lastly, objective 3 was successfully achieved by testing and evaluating the prototype to detect any casualties. As a conclusion, this project was a success. With an accuracy of 98% achieved, however, further improvement in design is needed to ensure that the system can be used widely even in discrete or high signal traffic areas. Acknowledgements The author would like to thank you Universiti Kuala Lumpur BMI and R4R/IERL Research Cluster for the provision of laboratory facilities and financial support.

References 1. M.U. Mahidin, Crime Statistics Publication. DOSM (2021). https://www.dosm.gov.my/v1/ index.php?r=column/cthemeByCat&cat=455&bul_id=eHE0eGZWSmNROG1BbHR2TzFv ZzZxQT09&menu_id=U3VPMldoYUxzVzFaYmNkWXZteGduZz09. Accessed 25 Nov 2021 2. N. Bhardwaj, N. Aggarwal, Design and development of “Suraksha”—a women safety device. IJICT 4, 787–792 (2014) 3. G.P. Miriyala, P. Sunil, R.S. Yadlapalli et al., Smart intelligent security system for women. IJECET 7, 41–46 (2016) 4. R. Akshay, N.K. Sachin, K.R. Prasanna, M.N. Chithra et al., Women safety jacket with smart safety protocol and screaming sensor a smart jacket for womens safety. IJERT 8, 1–3 (2020) 5. M. Zikriya, M.G. Parmeshwar, S.R. Math et al., Smart gadget for women safety using IoT. IJERT 6, 1–5 (2017) 6. B. Sathyasri, U.J. Vidhya, G.V.K.J. Sree et al., Design and implementation of women safety system based on Iot technology. IJRTE 7, 177–181 (2019)

Women’s Behavior Toward the Supply Chain Roles in Malaysia Nur Khaleda Ayunni Azlin, Hairul Rizad Md Sapry, Jimisiah Jaafar, Jamilahtun Md Ghazali, and Abd Rahman Ahmad

Abstract Nowadays, the role of women in the supply chain is undoubtedly critical in most sectors, with an average of 41% of the supply chain workforce in 2021 being women. Although the significant contributions of women to the supply chain function, there is still a lack of understanding of women’s behavior toward the role in supply chain management (SCM), a male-dominated field that is the subject interest of the study. The study has used the groundwork of theory planned behavior (TPB) to facilitate the investigation and the development of a hypothesis. In doing so, the research has collected feedback from 102 respondents for the structural equation modeling analysis using SmartPLS 3.0. The data was then verified and analyzed against five hypotheses that statistically support the path of the relationship. The results indicated that all developed exogenous constructs in the TPB framework statistically influence the endogenous construct (behavior interest) of the women toward the role in SCM. This study contributes new insight to understand the women’s behavior toward the SCM role, which is still lacking in the SCM field. Keywords Supply chain management · Theory planned behavior (TPB) · Women’s role N. K. A. Azlin · H. R. M. Sapry (B) · J. Jaafar · J. M. Ghazali Industrial Logistics, Universiti Kuala Lumpur Malaysian Institute of Industrial Technology, 81750 Masai, Johor, Malaysia e-mail: [email protected] N. K. A. Azlin e-mail: [email protected] J. Jaafar e-mail: [email protected] J. M. Ghazali e-mail: [email protected] A. R. Ahmad Faculty of Information Technology and Management, Universiti Tun Hussein Onn, 86400 Parit Raja, Johor, Malaysia e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_9

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1 Introduction This research is appropriate and critical as a reference to understand women’s perceptions of the appropriateness of their roles in the supply chain field. Accordingly, this research uses the theory of planned behavior (TPB) framework, which offers a valuable theoretical framework to analyze women’s behavior toward the appropriateness of their role in the supply chain in Malaysia. The TPB framework has a strong theoretical and empirical basis and has the potential to be used across all areas of research. The proposed model of theory planned behavior (TPB) is shown in Fig. 1.

2 Methodology Items for each construct were selected and developed through an extensive review of previous studies that serve as a guide in the instrument development. A five-point Likert scale, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5), was selected as a measurement for the instrument. Five items are developed and used to measure the attitude of the women, subjective norm, perceived behavior, intention of women,

Fig. 1 Model of women’s behavior adopted from theory planned behavior (TPB)

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and interest of women in supply chain roles. In addition, demographic information such as age, income, education, and position are also collected to understand the trend of the respondent. This study used a SmartPLS 3.0 for structural equation modeling (SEM) to study the relationship path. An online questionnaire using the Google Forms platform was developed and disseminated to the targeted respondents through social media and managed to obtain a total of 102 questionnaires for the final analysis.

3 Results and Discussion In the measurement model, the assessment is to determine the indicator reliability, internal consistency reliability, convergent validity, and discriminant validity which are critical in measurement model analysis, as presented in Table 1. The external loading value of 0.70 indicates a sufficient level of reliability, similar to the Cronbach’s alpha (CA) value. However, the CA value is a less accurate measure of reliability than the composite reliability value, where each item is measured based on the loading of the construct indicator. Meanwhile, the average variance extracted (AVE) is above the threshold value of 0.5 suggested by Sarstedt et al. [1]. For the variance inflation factor (VIF), all constructs achieved a moderately correlated VIF value between the 1 and 4 range, and multicollinearity is not a serious issue if the value of VIF is below 5 [2]. As for the composite reliability (CR), all constructs achieved a higher CR value between 0.7 and 0.90 ranges which are ‘Satisfactory to Good’ [2]. The results show that the construct of attitude, subjective norm, perceived behavior, intention, and interest are statistically significant at p < 0.05. In addition, the application of the [3] criterion of discriminant validity shows that the AVE value for each latent variable is higher than other correlations between latent variables, and this supports the reliability and convergent validity required in SEM analysis. The next step is the structural model assessment (internal model), which evaluates the effect of the hypothesized relationship to the interest of women in SCM. The result of bootstrapping indicates that all five hypotheses were supported, as presented in Table 2. The R-squared (R2 ) value of 0.623 indicates that the three constructs (attitude, subjective norm, perceived behavior control) all together explained about 62.3% of the variance in influencing women’s intention toward their interest in the SCM role, and the R2 value of 0.662 for the interest indicates that 66% of the variance in women’s interest in the role in SCM is predicted by two constructs (intention and perceived behavior). The blindfolding technique is a systematic pattern of data point elimination and prediction of relevance Q2 in the structural model. It measures whether a model has predictive relevance or not (> 0 is good). A Q2 value larger than zero, indicates that the PLS path model has predictive relevance for its construct, as suggested by Sarstedt et al. [1].

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Table 1 Construct validity, dimensionality, reliability, and item Construct

Item

Loading

VIF

AVE

CR

CA

Attitude

CI

0.865

2.764

0.758

0.940

0.920

C2

0.819

2.268

C3

0.878

3.199

C4

0.912

4.634

C5

0.876

3.369

C6

0.823

3.487

0.834

0.942

0.95

C7

0.944

4.165

C8

0.937

4.686

C9

0.957

4.294

C10

0.881

2.611

C11

0.868

4.059

0.828

0.949

0.952

C12

0.911

4.115

C13

0.901

3.793

C14

0.950

2.929

C15

0.934

3.123

C16

0.905

2.898

0.799

0.942

0.94

C17

0.921

4.784

C18

0.89

4.620

C19

0.862

4.429

C20

0.891

4.212

C21

0.840

2.483

0.792

0.950

0.939

C22

0.888

3.303

C23

0.874

3.323

C24

0.926

3.395

C25

0.92

3.876

Interest

Intention

Perceived behavioral control

Subjective norm

Table 2 Structure relationship and hypotheses testing results Hypothesis

Path

H1

Attitude → Intention

H2

Subjective norm → Intention

H3

Path coefficient

T Statistics

P-values

Decision

0.426

3.017

0.030

Supported

1.701

7.446

0.000

Supported

Perceived behavior → Intention

-0.877

3.651

0.000

Supported

H4

Perceived behavior → Interest

0.687

6.494

0.000

Supported

H5

Intention → Interest

0.432

2.527

0.012

Supported

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Table 3 Result of moderator effect Paths Attitude → Intention → Interest Perceived behavior → Intention → Interest Subjective norm → Intention → Interest

Patch coefficient

P-values

Mediating effects

1.084

0.000

Partial mediation

−1.024

0.005

Partial mediation

1.064

0.001

Partial mediation

Further, the R-square values of 0.020, 0.150, and 0.350 indicated the predictor variable’s low, medium, or large effect in the structural model. For the endogenous construct of women’s desire for the role of SCM, the exogenous construct of attitude, behavioral perception, and the subjective norm have a lower effect on the model because the f 2 value is below 0.02. For the endogenous construct of women’s interest in SCM roles, the intention construct also has a lower effect because its f 2 value is 0.063, but the behavior construct has a value of 0.806, which is a strong effect. This study also tested the effect of women’s intentions as a mediator between the independent variables (attitudes, subjective norms, and perceived behavioral control) and the dependent variable (women’s behavioral interest). According to Sarstedt et al. [1], the effect size of the model can be partial mediation effect, full mediation effect, and no mediation effect. Based on criteria by Sarstedt et al. [1], a partial mediation effect occurred in this study, as presented in Table 3.

4 Conclusion The main objective of this research is to understand the determinants that influence women’s behavior to accept a role in the field of SCM by using the basis of the theory of planned behavior (TPB). The results of this study show that women’s intentions are mediating their evaluation (attitude), belief about whether most people approve or disapprove of their behavior (subjective norm), and a perception of the ease or difficulty of performing the behavior (perceived behavior control) toward the role in SCM, while the perceived behavior control also can directly influence their interest in SCM, which is in line with previous studies Song et al. [4], Badgaiyan and Verma [5], and Bellini and Aiolfi [6]. The more intentions and highly regarded role of SCM will lead to a higher level of interested among women. This study also confirms the applicability of exogenous constructs of the theory of planned behavior (TPB) (attitudes, subjective norms, and perceived behavior) that indirectly influence women’s interest in SCM roles. Acknowledgements We would like to extend our sincerest gratitude to all the respondents who took part in this research.

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References 1. M. Sarstedt, C.M. Ringle, J.F. Hair, Partial least squares structural equation modeling. in Handbook of Market Research (Chapter, 15) (Springer, 2021) 2. J.F. Hair, G.T.M. Hult, C.M. Ringle et al., A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd edn. (Sage Publications Inc., Thousand Oaks, CA, 2017) 3. C. Fornell, D.F. Larcker, Evaluating structural equation models with unobservable variables and measurement error. J. Market. 18(1), 39–50 (1981) 4. H.G. Song, N. Chung, C. Koo, Consumers’ impulsive buying behavior of restaurant products in social commerce. Int. J. Contemp. Hosp. Manage. 29(2), 709–731 (2017) 5. A.J. Badgaiyan, A. Verma, Does urge to buy impulsively differ from impulsive buying behavior? Assessing the impact of situational factors. J. Retail. Consum. Serv. 22, 145–215 (2015) 6. S. Bellini, S. Aiolfi, Impulse buying behavior: the mobile revolution. Int. J. Retail. Distrib. Manage. 48(1), 1–17 (2020)

Measuring the Awareness on Safety Management and Behavior: A Case Study in a Service-Based Company in East Coast Malaysia Nur Aila Syafira Norzeri, Sallaudin Hassan, Jimisiah Jaafar, Mohd Farid Shamsudin, and Waqia Begum Fokeena Abstract Safety is always considered as a major concern by all organizations. Thus, activities related to awareness on safety have been implemented to inculcate employee’s involvement and commitment toward safety. Based on recent trends, the number of cases related to worker’s accidents at workplaces are still occurring. Past research revealed that working conditions can be improved if the organization is enhancing practices in safety management. The purpose of this study is to measure the level of safety management and behavior at workplaces. This is quantitative research whereby a survey questionnaire was used among employees from several service-based companies. The Statistical Package for Social Sciences (SPSS) version 21 has been used for data analysis. Mean analysis was conducted to calculate the level of safety from the aspect of commitment, training, involvement, communication, feedback, rules, and procedures. The result showed that the level of safety management and behavior is considered as high. The main reason is due to extensive training and activities related to safety by the organization. The results from this research can be used for future research related to safety at workplaces. N. A. S. Norzeri · S. Hassan (B) · J. Jaafar Quality Engineering Research Cluster (QEREC), Quality Engineering, Universiti Kuala Lumpur, Malaysian Institute of Industrial Technology (MITEC), Persiaran Sinaran Ilmu, 81750, Bandar Seri Alam, Masai, Johor Bahru, Malaysia e-mail: [email protected] N. A. S. Norzeri e-mail: [email protected] J. Jaafar e-mail: [email protected] M. F. Shamsudin Universiti Kuala Lumpur, Business School (UBIS), Jalan Persiaran Gurney, 54000 Kuala Lumpur, Malaysia e-mail: [email protected] W. B. Fokeena Eduxplora Limited, 47 Dr. Hassen Sakir Street, Port Louis, Mauritius e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_10

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Keywords Safety · Safety management practices · Behavior

1 Introduction Past research indicated that the equipment and physical environment in the workplace were responsible for the rate of injuries at the company [1]. In the meantime, other concerns are attributed to workers’ dangerous actions and employee contact with the organization’s processes [2]. In addition, occupational accident or workplace injury often typically happens as a result of the hazardous conduct of the employee, the organizational factor, and the rising risk related to safety. ISO 45001 which is related to safety and health management therefore guides for safeguarding safety, health, and well-being among all workers and shielding others from threats of safety in relation to the activities of people at work [3]. To succeed in business, a company must consider safety and health at the workplace. Good practices in safety and health will enhance employee’s motivation and productivity. The attendance rate will be increased and thus ensure excellence in business operation, reduce cost of sick pay and part time worker’s cost. It also improved attitude and behavior of employees, and thus, it will help to reduce potential accident at the workplace [4]. Another positive impact is that it will improve the image of the organization and help to increase the reputation in the industry. Regardless of any industry, concern on safety and health is very important since it will influence the work quality and productivity. According to Lamm et al. [5], having good practices in safety at the workplace is very crucial and directly influences the quality of work and productivity as well. This will eventually increase the profit for the company. One of the approaches to achieve it is through having a good awareness on safety management and behavior. Past records indicated that accidents at workplaces happened due to poor behavior on safety. Apart from that, it was also identified several contribution factors like deviation from safety policies, procedures, and poor documentation system. Research by Neal and Griffin [6] revealed that safety behavior can be categorized in two which is compliance and involvement in safety. Lack of information related to safety procedures will influence the number of accidents at the workplace. Thus, safety management practices need to be established systematically and effectively so that all employees are aware on the requirements. Therefore, the way operation is running is in safe condition. It will also help to contribute in conducive are of work, enhance discipline and consistently aware on safety to avoid accidents at workplaces [7]. Based on the above scenario, below are the objectives of this research: (i) To investigate safety management practices from the perspective of employees. (ii) To investigate safety behavior among workers at the company. It is expected that the result of this research can be a valuable input to the organization related to safety management practices at the workplaces. The information also

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can be deployed for the development of safety programs in organizations. Several suggestions are provided to enhance the acceptance of employees toward safety programs.

2 Literature Review 2.1 Safety Management The scope of safety management is wide. It is closely related to documented information such as establishment of policies, procedure, and operation manual. It is also connected with programs to ensure safety to the employees in the organization. In addition, safety management practices are also considered as a method to identify and address hazards at workplaces which can cause accidents [8].

2.1.1

Involvement of Employees

Based on a study by Cox and Cheyne [9], involvement of workers in safety is very important. And, organization has required to take action to engage workers with safety programs. It is a behavior-oriented approach whereby workers are involved in the flow of communication and decisions related to safety in the organization. This approach will allow workers to provide suggestions to the management. In fact, workers can also be involved in safety committees since they are experienced at workplaces. Getting workers involved in safety programs and decision-making related to safety will increase their engagement with the management and enhance their motivation to implement safety at the workplace.

2.1.2

Training Related to Safety

Training on safety is critical. It is considered as the primary factor to ensure that the organization can successfully execute a safety program. Based on training by a certified person, the employee will have better knowledge on improving aspects related to safety at the workplace. According to Vredenburgh [10], effective training will be able to provide significant effect on the employee behavior at workplace. They are more alert on potential cause of accident, unsafe condition, and unsafe act. In addition, the employees are also more concerned of procedures and policies related to safety.

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Management Commitment

A study by Zohar [11] revealed that the management commitment is another important component in determining the direction of a company in many aspects inclusive safety. The implementation of safety also is influenced by top management policies. A company needs to develop a good perception of employees on a safety development and implementation. The management is required to establish safety committee when necessary. The committee will plan and execute the activities and requirements related to safety. The committee is responsible to develop the quality policy, safety objective and to conduct risk assessment. The committee also will arrange for internal audit to be conducted as to ensure all requirements are fulfilled. The external audit by appointed parties or government agencies will also help to ensure the implementation of safety and health in accordance to the procedure. Findings from the audit can be sources for continuous improvement. The result of audit will be reviewed by the top management in management review meetings. During the management review meetings, the entire activities related to safety and health will be reviewed. Necessary action will be taken for improvement.

2.1.4

Safety Rules and Procedures

Organizations with established safety committees will have a better way to manage the rules and regulation. This is added by the commitment by the top management. The documentation is required to be established properly and in accordance to documented information requirements. The procedures are important to be properly established as main reference for the purpose of training to the employee. In addition, the procedures also will be referred and guidance for employee in daily work. The enforcement by the safety committee through audit and inspection is important to ensure procedures are followed by the employee. The safety committee needs to remind employees on the implication of disobey to the safety procedures. A study by Mearns et al. [12] revealed that there is a significant relationship between safety procedures and the level of accidents at workplace statistics.

2.1.5

Safety Communication and Feedback

Two-way communication between management and workers on safety is very crucial. The communication from the top management and safety committee must be precise but easy to be understood by the workers. A suitable medium of communication is required to be established by the company to ensure effective delivery of message or information to the workers. In certain organization, there are foreign workers who may not clearly understand the local language. Therefore, most of companies established procedures or working instructions in multiple languages. Another important aspect is that the company should encourage and enforce a bottom-to-top communication channel. This will allow low-level workers to communicate and provide

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suggestions to management. This can be done though several means such as online surveys and interviews. According to Cohen and Cleveland [13], communication and feedback will help to improve the organization to implement safety and health.

2.2 Safety Behavior Safety behavior is referred to the way the management and workers act to the safety and health requirements. It can also be reflected by the way employee responds to the safety and health campaign and training. In this context, the role of low-level management such as supervisors or team leaders is critical since they are the one who directly communicate and monitor daily work by the workers. The most important aspect is to ensure that everyone performs the work in safe condition and safe act. Poor behavior and less concern on safety will give negative impact such as accident which could be led to injury or death. According to Pidgeon [14], the participation from employees in safety programs helps to motivate the team members to ensure safety at the workplace.

3 Methodology This study was conducted at one private company which is involved in manufacturing, properties, services, and technologies in Malaysia. It has more than 300 employees and has been operating for more than 20 years in the East Coast of Malaysia. This is a quantitative research, whereby the primary data were collected from employees at the company. Overall, 175 questionnaires were distributed among the respondents of this company. The information is collected from ISO 45001:2018 and guidelines related to safety management practices and safety behaviors, as well as the historical reports on the Safety, Health, and Environment (SHE) department of the company. Other secondary data were obtained from official statistics, mass media products, letters, government reports, and web information. In this research, the questionnaires were developed based on adaptations from previous similar studies. The data collection began by establishing a survey form on the employee perception on safety management practices and its correlations toward safety behavior. A pilot test was conducted using 30 sample questionnaires. A total of 175 questionnaires were distributed among the respondents of this company for the final survey. The sampling was based on the convenience sampling method. The questionnaire was divided into three main sections. Part 1 in the questionnaire contained the demographic characteristics of the respondents. Part 2 in the questionnaire focused on the safety management practices. In this research, five different instruments according to the different aspects of workers’ involvement, safety training, management commitment, communication and feedback systems,

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and rules and safety procedures were used. Part 3 in the questionnaire used two main dimensions which were safety compliance and safety participation.

4 Results and Discussion Data analysis was conducted on 159 correctly filled questionnaires after data cleaning and checking for outliers. SPSS version 21 was used for data entry and data analysis. Research Question 1: What is the level of safety management practices among workers? Descriptive analysis was employed to obtain for the result for first objective. Results for descriptive analysis are depicted in Table 1. It consisted of five aspects in safety management practices. The mean value for five dimensions in safety management practices ranged from 4.273 to 4.372, refer to Table 1. The result indicated that the safety management practices in this company have a mean value of 4.312, which indicates a very high level of data consistency. It can firstly be due to the fact that the company has been in the industry quite sometime. The company also has more experiences and skilled workers. The high mean value for safety management practices is further proven by the certification of ISO 9001:2015, ISO 14001:2015, ISO 45001:2018, and other quality accreditations possessed by the company. Workers’ involvement in this study also showed a very high mean value of 4.354. As mentioned, the majority of the workers of this company are experienced, and therefore, their safety and health skills have also developed and improved over the years. Thus, safety rules’ and procedures’ feedback also gave a mean value of 4.312 which is also relatively high, as can be explained by the high commitment of the company by its possession of the ISO9001:2015 certification which includes efforts in good perception and understanding by the staff of the company. As for the lowest mean value which is management commitment, the value of mean is still considered very high (4.273). This result indicates that the respondent believed that there is very good commitment from the top management. Management commitment with regard to safety influences the safety behavior of an employee and protects the employees from accidents at workplace.

Table 1 Dimensions in safety management practices—mean and std. deviation statistics Dimension

N

Mean

Std. deviation

Management commitment

159

4.273

0.909

Safety training

159

4.372

0.947

Worker’s involvement

159

4.354

0.832

Safety communication and feedback

159

4.283

0.837

Safety rules and procedure

159

4.312

0.876

Measuring the Awareness on Safety Management and Behavior: A Case … Table 2 Safety behavior—mean and std. deviation statistics

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Dimension

N

Mean

Std. deviation

Safety compliance

159

4.291

0.873

Safety participation

159

4.342

0.865

Research Question 2: What is the level of safety behavior among workers? Based on the mean value of safety behavior, most of the respondents showed that they have a high possibility to practice their work in a safe manner using the required equipment, follow the exact safety rules and procedures, ensure the maximum levels of safety and abiding to the correct work procedures. Based on Table 2, safety compliance showed a lower mean value (4.291) compared to the safety participation. Nevertheless, the value of 4.291 is considered as high. Thus, most of the respondents show the agreement that they have high possibility to practice their work in a safe manner, using the necessary tools, follow the correct safety rules and procedures. This will help to make sure the highest levels of safety and does not deviate from the correct work procedures. In addition, safety participation produced a mean value of 4.342 which shows the highest value among the two safety behavior dimensions. Based on this result, it can be summarized that the respondents have very good voluntary behavior toward applying safety at the workplace. It may be caused by the good awareness of the respondent on safety which eventually impacts their behavior at the workplace. Based on the outcomes of this research, several recommendations have been proposed. Basically, employees have a commitment to protect their own health and the health of their co-workers. A healthy atmosphere and safe behavior are important elements that employers must ensure within the organizations. Staff and managers must be trained to keep a health and safety mindset in order to enhance and secure a stable work environment. Such a mindset does not always go hand in hand with the learning of expertise or experience in the application of machinery. Most people will learn to drive a car, for example, in a very short amount of time; however, a mature attitude is needed [15]. Employees should be encouraged to act in ways that are unusually or extremely safe as part of a successful safety incentive model. The rewarded activity should reduce the risk of injury and increase occupational safety. Rather than concentrating on the result, rewards focused on observable safety actions and attitudes can inspire and improve safety efficiency. Money can be an effective motivator, but incentives do not have to be monetary to be effective. This research provides some insights and guidelines for the employees in the organization to be more responsible toward safety. In addition, it provides the reference for safety management practices and safety behavior in the organization. The top management through safety committees has a very significant role in ensuring safety management practices which eventually will impact the awareness, behavior, and productivity of the organization.

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5 Conclusion This research focused on measuring the level of safety management practice and safety behavior. It is highly recommended that the organization increases their commitment and safety communication between the management team and the workers. Overall, this research revealed that the safety behavior of people in an organization depends on management practices. Future research can expand the scope of the study to more organizations across different industries. The level of analysis can be further extended to look at the relationship between safety management practices and safety behavior. Acknowledgements Gratitude is expressed to all team members involved in this research project from the proposal stage to the completion. Our appreciation goes to the Centre for Woman Advancement and Leadership (CWAL) for its support and for taking the initiative to publish this book chapter.

References 1. A.G. Vredenburgh, Organizational safety: which management practices are most effective in reducing employee injury rate. J. Safety Res. 33(2), 259–276 (2002) 2. B. Wilpert, Industrial/organizational psychology and ergonomics toward more comprehensive work sciences, in Proceedings of the 12th Triennial Congress of the International Ergonomics Association, vol. 1 (1994), pp. 37–40 3. G. Dessler, Human Resource Management, 12th edn. (Upper Saddle River, NJ, Pearson/Prentice Hall, 2011) 4. M.N. Vinodkumar, M. Bhasi, Safety management practices and safety behaviour: assessing the mediating role of safety knowledge and motivation. Accid. Anal. Prev. 42(6), 2082–2093 (2010) 5. F. Lamm, C. Massey, M. Perry, Is there a link between workplace health and safety and firm performance and productivity? Empl. Relat. 32(1), 75–90 (2006) 6. A. Neal, M.A. Griffin, Perceptions of safety at work: developing a model to link organizational safety climate and individual behavior, in 12th Annual Conference of the Society for Industrial and Organizational Psychology (St. Louis, MO, 1997) 7. M. Cooper, D. Cotton, Safety training-a special case? J. Eur. Ind. Train. 24(9), 481–490 (2000) 8. A. Labodová, Implementing integrated management systems using a risk analysis based approach. J. Clean. Prod. 12(6), 571–580 (2004) 9. S.J. Cox, A.J.T. Cheyne, Assessing safety culture in offshore environments. Saf. Sci. 34(1), 111–129 (2000) 10. A.G. Vredenburgh, Organizational safety: which management practices are most effective in reducing employee injury rates? J. Safety Res. 33(2), 259–276 (2002) 11. D. Zohar, Safety climate in industrial organizations: theoretical and applied implications. J. Appl. Psychol. 65(1), 96–102 (1980) 12. K. Mearns, S.M. Whitaker, R. Flin, Safety climate, safety management practice and safety performance in offshore environments. Saf. Sci. 41(8), 641–680 (2003)

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13. H.H. Cohen, R.J. Cleveland, Safety program practices in record-holding plants. Prof. Saf. 28(3), 26–33 (1983) 14. N. Pidgeon, Safety culture: key theoretical issues. Work and stress. Int. J. Healthc. 12(3), 202–216 (1998) 15. P.E. Hagan, J.F. Montgomery, J.T. O’Reilly, Accident Prevention Manual for Business and Industry, 12th ed. (NSC, Illinois, USA, 2001)

Deep CNN-Based Facial Recognition for a Person Identification System Using the Inception Model Isaiah Chong Kai Ean, Mohd Fadzil Abu Hassan, Yusman Yusof, and Nur Zulaikhah Nadzri

Abstract Reliable person identification is a primary factor and administered in the initial stages for safety measures. One of the contactless person identifications for tracing techniques is using an image-based face identification system. In this project, an algorithm of machine vision-based person identification using the Inception V3 is proposed, and the performance of the model is analyzed to gain the desired results for contactless person identification. A collection of facial image datasets had been created and each of the seven subjects was contributing 600 facial images; thus, 4200 images in total were stored in the database. The dataset is physically available at https://bit.ly/3jVhApz. A well-known Haar Cascade Classifier was used to capture and extract the facial region from the raw images. Data augmentation is carried out to increase the variation of the facial features within the training dataset by manipulating images with transformations such as horizontal flipping, random cropping, zooming, and color space augmentations. Thus, minimizing the distance between the training set and validation set, and the dataset was split using the Holdout method. This project has produced a good performance of face recognition system using the Inception V3 model with validation and testing accuracy rates of 99.7% and 99.4%, respectively. From the result, it shows that the model is able to give good performance in identifying a set of persons by using facial features in an image. Keywords Data augmentation · Face recognition · Facial dataset · Inception V3

I. C. K. Ean · M. F. Abu Hassan (B) · Y. Yusof · N. Z. Nadzri UniKL Robotics and Industrial Automation Center (URIAC), Universiti Kuala Lumpur Malaysia France Institute, Section 14 Jln. Teras Jernang, 43650 Bangi, Selangor, Malaysia e-mail: [email protected] I. C. K. Ean e-mail: [email protected] Y. Yusof e-mail: [email protected] N. Z. Nadzri e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_11

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1 Introduction Face recognition is an area of investigation which is extensively studied. It encompasses computer vision, image processing, and pattern recognition. Many types of applications can be used for this research such as identity verification, video surveillance, lip tracking, gender classification, and extraction of facial expression. While techniques for face recognition are well established, the development of automatic detection and face recognition systems is still very challenging. It is hard to reliably locate the face and its attributes since there are many differences in shape, structure, and texture of the human face. Face detection can also be a daunting task as many factors will affect the performance such as pose orientation and position, facial expressions, lighting conditions, different skin tones, facial accessories, and any scars or marks on faces. The complex nonlinear facial appearance variations are inevitable limitations in a face recognition system [1]. Thus, face recognition systems have frequently been reported to have inconsistent performance or failures with numerous false alarms in real-world applications. Deep convolutional neural networks (CNNs)-based techniques have dominated the object recognition application. They showed significant performance improvements under image quality degradation. Surprisingly, it showed strong invariance features set to the face pose, lighting, expression changes, smile, roar, color eye, etc., which may represent the facial identity with unprecedented stability. In this paper, the Inception V3 model was selected and trained using a large number of facial datasets to perform face recognition for seven subjects. The rest of this paper is organized as follows: Sect. 2 describes the various views and works from previous research, while Sect. 3 describes the proposed methodology for the development of the face recognition system in detail. Results and discussion are presented in Sect. 4. Finally, Sect. 5 presents the conclusion and future work of this paper.

2 Related Works 2.1 Machine Learning The conventional machine learning and deep learning are artificial intelligence (AI) subfields. The conventional machine learning techniques are limited in their ability to analyze data in its original form, whereas deep learning is a sophisticated machine learning approach that enables computers to automatically extract, analyze, and comprehend relevant information from raw data [2]. Some of the most common conventional machine learning algorithms such as Support Vector Machine, Logistic Regression, and Naïve Bayes promising good

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performance result in classifying tourist attraction images by using various conventional classifiers were shown in Sujaini [3]. Whereas the recent trending investigation domains in the field of AI, deep learning such as convolutional neural network (CNN) provide tremendous result in image and video features-based classification. CNN permits the multiple layers models for computation to learn representations of data by processing them in their original form which is not possible in conventional machine learning. For instance, the CNN-AlexNet model was trained to recognize actions and showed a good performance in detecting fall events [4].

2.2 Face Detection To begin describing the details of the Haar Cascade Classifier, the source of the face detector algorithm must first be explained. OpenCV was started to accelerate research in computer vision and its commercial applications. The OpenCV library contains multiple functions such as face detection, face recognition, face tracking, and a variety of artificial intelligence methods which are readily usable [5]. The Haar Cascade Classifier was invented by Viola and Jones [6]. This method is an adaptive machine learning approach that involves a cascade function that is trained with images. During training, many images with faces and without faces are used to train the classifier. A set of features is extracted from the faces, and these attributes will be used to detect faces in other images.

2.3 Face Recognition The face recognition working principle mainly consists of two tasks which are feature extraction and feature classification. Feature extraction involves the extraction of distinctive features through the reduction of noise found in the original data. Meanwhile, feature classification implements a classifier to recognize the extracted features. Both tasks practically form the process of face recognition. Inception V3 is one of the widely used and high-performance image recognition models. The model represents the result of numerous ideas based on the primary study [7] explored over time by many scholars as state-of-the-art CNN models [8– 10]. According to Madhu Latha and Krishnam Raju [11], the Inception V3 model comes from the TensorFlow platform. It is an updated version of the Inception V1 and Inception V2 models. The model was trained on the ImageNet dataset which was able to distinguish between 1000 classes over 1.2 million images and even achieved high accuracy. The Inception V3 model uses a deep neural network architecture and Inception modules. The Inception module implemented in the Inception V3 model allows more efficient computation by taking multiple sizes of kernels together to operate at the same level rather than stacking them sequentially.

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A comparison study done by Klemen Grm, four deep learning models were used which were the AlexNet, VGG-Face, GoogLeNet, and SqueezeNet [12]. In this study, the models were tested on various image quality covariates such as blur, compression, and noise. The models are performing in ranges of 73–83% verification accuracy at the lowest JPG compression quality. For the noise test, all models performed at 50% verification accuracy at the maximum noise. This study shows the weakness of deep learning models toward image blur, compression quality, and noise which are some factors that can be found in video face recognition. An end-to-end pipeline strategy was proposed by Melinte and Vladareanu [8] that employs two optimized CNN models. The selected models are for face recognition and facial expression recognition. For expression recognition, the transfer learning, and fine-tuning parameters from VGG, the Inception V3 and ResNet have been used. ResNet obtained the highest training accuracy, followed by VGG and Inception V3 with 90.14%, 87%, and 81%, respectively. This differs from the study in AlBdairi et al. [13], where they proposed the Inception V3 model for recognizing people’s ethnicities based on their facial features.

3 Material and Methods The project is carried out in multiple stages to achieve face recognition using Inception V3. The first stage is developing a dataset for the face recognition model. The dataset comprises face images to train and test the model. The second stage involves the reconstruction of the face recognition model using the pre-trained Inception V3 model. Figure 1 shows the flow process of the face recognition model.

3.1 Facial Dataset Collection The data acquisition is captured by using a hand-held digital camera (smartphone camera). The images of the face were captured from a few different angles to capture various facial features’ variation. The distance between the subject and the stationary camera is within 1–5 m. Therefore, three angles (0°, 45°, and −45°) were set from the stationary camera to the subjects. There are angle views from the front, the left side of the face, and the right side of the face, respectively. In addition, various subject face angles and facial/environment conditions were considered including the head facing forward/left/right/look up/look down, closed eyes, bare face, wearing hat/hijab, wearing glasses, genre, and illumination. After the raw images of faces have been collected, the Haar Cascade Classifier [6] is reconstructed. The model is used to extract the faces from the collection of raw images and then automatically crop the extracted face images (224 × 224 × 3). Data augmentation is carried out after the face extraction process is completed. According to Shorten, one of the ways to reduce overfitting during the training

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Fig. 1 Face recognition system development flow process

process is by implementing data augmentation on the training dataset [14]. Data augmentation can increase the variation within the training dataset which minimizes the distance between the training set and validation set. For this project, the training dataset undergoes horizontal flipping, shearing, rotation, height shift, and width shift. Figure 2 shows the resultant data augmentation of an image in the training dataset. A well-constructed dataset is vital for the efficiency of the system. According to Koul et al. [15], a dataset must be split into two sets which are the training set and the test set. The training set is used to train a model on how to apply concepts and produce results. The test set is used to determine the effectiveness of the training received by the model. The test set must be excluded from the training set because

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Fig. 2 Image augmentation

the model is familiar with the training set and will produce the expected output. Figure 3 shows the dataset distribution. The total number of face images generated was 4200 images. Seven subjects (staff and students of the Industrial Automation Section, UniKL MFI) were contributing for facial images in the dataset, and each subject has 600 images. The dataset was split into two sets using the Holdout method [16], where 80% of random samples were selected for the training set and 20% for the testing set. The dataset is freely downloadable at https://bit.ly/3jVhApz.

Fig. 3 Dataset distribution

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3.2 Reconstruction of Face Recognition Model The Inception V3 model uses a very deep neural network architecture and inception modules [7]. The number of input channels is limited by adding an extra 1 × 1 convolution before the 3 × 3 and 5 × 5 convolutions. By limiting the input channel, it may reduce the computational cost. The reconstruction of the face recognition model (Inception V3) was done on the Jupyter Notebook. The pre-trained Inception V3 model was trained and tested on the dataset using TensorFlow and Keras machine learning library. The model takes an image and converts it into face embeddings and classifies those embeddings into the correct identities of the person. The Inception V3 model was trained to undergo 30 epochs. Once training is completed, the five best models from different epochs are selected to undergo the testing phase. The models are selected based on their performance and computational cost. Computational cost is measured in terms of time (seconds) taken to train and validate the model. Then, the model was tested using the test dataset. This test will output the model’s performance on the test dataset in terms of accuracy and loss. All five selected models are tested to observe each model’s performance on the test dataset. Once the test is performed, the selected model’s output was visualized in the form of a confusion matrix. The confusion matrix assists in the analysis of false positives and true positives done by the model for evaluating the accuracy performance [16].

4 Result and Discussion 4.1 Training and Validation Analysis The pre-trained Inception V3 model is trained on 4200 face images that belong to seven classes or identities containing six head angle coordinations and three variations of camera view angles. It was trained and validated for 30 epochs. Figure 4 shows the results of the training and validation in terms of accuracy and loss. The time taken for each epoch and total training time were also recorded to measure the overall computational costs taken to train and validate the face recognition model. Based on Fig. 4, the model is underfitting early on as it experiences high training and validation loss in the first three epochs. The training and validation accuracies are also below 80% for the first three epochs. Underfitting is where a model performs very poorly on the training data and is unable to generalize the new data. After epoch 3, it shows no signs of overfitting because the validation errors in terms of the difference between the training accuracy and validation accuracy are not too great apart. In addition, the difference between the training loss and validation loss shows relatively low performance. Overfitting is a situation where a model is unable to generalize well on unseen data. This is judged based on the performance of the

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Fig. 4 Inception V3 performances for face recognition

model on the training and validation datasets. If the difference in performance is high, the model performs very poorly on the validation set as compared to the training set, and overfitting occurs.

4.2 Model Selection For the face recognition model, the best is selected based on the accuracy and computational cost to train the model. The threshold accuracy rate is set to > 95%. Next, the computational cost to train the model is measured in terms of training time. This means that the number of epochs would represent the overall computational cost of training the model. Table 1 shows the best five models which perform well in face recognition with respect to n-epoch. Table 1 The best performance of trained models by epoch Model No.

Epoch

Training accuracy

Validation accuracy

Cumulative training time (s)

1

7

0.9631

0.9628

10,148

2

9

0.9735

0.9732

13,031

3

13

0.9847

0.9896

18,810

4

17

0.9907

0.9896

24,647

5

30

0.9970

0.9940

43,753

Deep CNN-Based Facial Recognition for a Person Identification System … Table 2 The highest performance test result for the best model

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Model No.

Testing accuracy

Testing loss

1

0.9071

0.3137

2

0.9102

0.3029

3

0.9175

0.2930

4

0.9251

0.2751

5

0.9442

0.2551

Based on Table 1, all the chosen model epochs have fit the criteria of achieving an accuracy > 95%. The lowest accuracy was performed by model 1 with 96.31% and 96.28% for training and validation accuracies, respectively, while model 5 in epoch 30 has shown the best accuracy rates with 99.7% training accuracy and 99.4% validation accuracy. It also has the best loss rate which is minimal among the five epochs. It is an obvious choice for the selection of the face recognition model; however, it has a cumulative training time of 43,753 s (≈ 12 h) which shows that training the model to epoch 30 takes up massive computational costs.

4.3 Testing of Face Recognition Model All models underwent testing on the previously separated testing dataset. This test is important to indicate the robustness and the generalization ability of the model toward unseen data. Table 2 shows the five best performance models results. Based on Table 2, model 1 still showed the lowest performance, and the best performance belongs to model 5. Model 5 was capable to achieve 94.42% accuracy with 25.51% loss. Figure 5 shows some samples of successful face detection and identity predictions from various face angles and variations made by model 1 with its confidence level rate. The system is designed to be able to detect the face, notify the identity with confidence level rate and verification status. The breakdown of the system is a bounding box for face detection which is done by the Haar Cascade Classifier. Identity recognition with the confidence level rate is carried out by the Inception V3 algorithm. However, despite successful outcomes when the system carries out its function, some flaws were discovered during running the system.

5 Conclusion The Inception V3 model is expected to carry out face recognition on the detected faces. However, the performance of face recognition can be increased by considering the face detection algorithm to be improved in detecting the face at various angle views and the other possible factors that may affect the particular problem. A robust

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Fig. 5 Sample predictions output from face recognition model

deep learning model for face detection should be considered as the Haar Cascade Classifier was not able to detect faces that were completely tilted sideways. Acknowledgements The authors gratefully acknowledge the group of volunteers from the Industrial Automation Section, UniKL MFI for facial dataset collection. Acknowledgment of support in the grant: Short Term Research Grant (Str19023), UniKL.

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References 1. M. Wang, W. Deng, Deep face recognition: a survey. Neurocomputing 429, 215–244 (2021) 2. N.K. Chauhan, K. Singh, A review on conventional machine learning vs deep learning. Int. Conf. Comput. Power Commun. Technol. (2019). https://doi.org/10.1109/GUCON.2018.867 5097 3. H. Sujaini, Image classification of tourist attractions with K-nearest neighbor, logistic regression, random forest, and support vector machine. Int. J. Adv. Sci. Eng. Inf. Technol. (2020). https://doi.org/10.18517/ijaseit.10.6.9098 4. M.F. Abu Hassan, A. Hussain, M.H. Md. Saad, Y. Yusof, Convolution neural network-based action recognition for fall event detection. Int. J. Adv. Trends Comput. Sci. Eng. (2019). https:// doi.org/10.30534/ijatcse/2019/6881.62019 5. T. Sharanya, P. Sucharith, U. Kasturi, T. Mahesh, Online attendance using facial recognition. Int. J. Eng. Res. Technol. (2020). https://doi.org/10.17577/ijertv9is060163 6. P. Viola, M. Jones, Robust real-time object detection. Int. J. Comput. Vis 57 (2001) 7. C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, Z. Wojna, Rethinking the inception architecture for computer vision. Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. (2016) https://doi.org/10.1109/CVPR.2016.308 8. D.O. Melinte, L. Vladareanu, Facial expressions recognition for human-robot interaction using deep convolutional neural networks with rectified Adam optimizer. Sensors (2020). https://doi. org/10.3390/S20082393 9. A. Ananda, K.H. Ngan, C. Karaba˘g, T. Ter-Sarkisov, E. Alonso, C.C. Reyes-Aldasoro, Classification and visualisation of normal and abnormal radiographs; a comparison between eleven convolutional neural network architectures. Sensors (2021). https://doi.org/10.3390/ S21165381 10. S. Kundu, S. Malakar, Z.W. Geem, Y.Y. Moon, P.K. Singh, R. Sarkar, Hough transform-based angular features for learning-free handwritten keyword spotting. Sensors (2021). https://doi. org/10.3390/S21144648 11. M. Madhu Latha, K. Krishnam Raju, Transfer learning based face recognition using deep learning. Int. J. Recent Technol. Eng. (2019). https://doi.org/10.1109/ICECCE47252.2019. 8940754 12. K. Grm, V. Struc, A. Artiges, M. Caron, H.K. Ekenel, Strengths and weaknesses of deep learning models for face recognition against image degradations. IET Biometrics (2017). https://doi. org/10.1049/iet-bmt.2017.0083 13. A.J.A. AlBdairi, Z. Xiao, M. Alghaili, Identifying ethnics of people through face recognition: a deep CNN approach. Hindawi Sci. Prog. (2020). https://doi.org/10.1155/2020/6385281 14. C. Shorten, T.M. Khoshgoftaar, A survey on image data augmentation for deep learning. J. Big Data (2019). https://doi.org/10.1186/s40537-019-0197-0 15. A. Koul, C. Becchio, A. Cavallo, Cross-validation approaches for replicability in psychology. Front Psychol. (2018). https://doi.org/10.3389/fpsyg.2018.01117 16. M.F. Abu Hassan, A. Hussain, M.H. Md. Saad, Polygonal shape-based features for pose recognition using kernel-SVM. J. Telecommun. Electron. Comput. Eng. 10, 2–6 (2018)

“Hello Dr” Application for Mobile Devices Farahwahida Mohd and Nor Izzatul Elanie Mustafah

Abstract People in this period are constantly looking for a convenient solution to address their health as quickly as possible. Even to stay connected, everyone uses their smartphone. Mobile health care was created to allow people to track and share their health information on the go. Users can become more active and motivated for their health by using mobile health care. It will, however, stimulate improved dialogue with healthcare providers and a better awareness of their overall health. Mobile health technology’s advantages continue to grow and change. With so many people in need of medical care, doctors must make their services accessible and affordable. Due to the epidemic, it is difficult to make an appointment, and there is a long queue to be admitted to a hospital or clinic. Among the many features of the “Hello Dr” app is the ability for both users to earn points and redeem them for future visits to the doctor’s office or other services like home visits and self-diagnoses. Using this mobile healthcare app will help clinicians or doctors to make more informed decisions about their patients. In the modern world, mobile technology enables people to create their future and health goals at any time and from any location. Using the “Hello Dr” app on a smartphone has become the standard for providing better care and health to facilities at the users’ fingertips. Keywords Smart health care · Mobile application · Booking application · Smartphone · Home visit

F. Mohd (B) · N. I. E. Mustafah Universiti Kuala Lumpur Malaysian Institute of Information Technology, Kuala Lumpur, Malaysia e-mail: [email protected] N. I. E. Mustafah e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_12

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1 Introduction These days, consumers are searching for a fast and convenient way to treat their health as soon as possible or to use it on the internet [1]. Because doctors save lives, those in need of medical attention may find that they are not too far away from them. A mobile app that allows patients to schedule appointments with a doctor is a step in the right direction. Once the booking process is simplified, patients will want to make an appointment with the doctors. However, the pandemic coronavirus (COVID-19) poses the greatest global danger in 2020 [2]. Malaysia is one of the countries affected by the pandemic COVID-19; the virus was verified to have arrived in Malaysia in January 2020. It is critical to provide this mobile application to patients in order to treat them. Patients may be afraid to visit a clinic or hospital for treatment since Malaysia is dealing with the pandemic COVID-19. So, if they are sick, our mobile application may make it easier for them to get a consultation. A more efficient alternative is to use an internet mobile application that simplifies living. People utilize electronic transactions to be safer, more secure, and to make their lives easier [3, 4]. Direct paper appointments make it tough to manage patients. Health care has been the most essential public service in emerging countries for the past two decades. Since the pandemic, it has been difficult to obtain an appointment and to obtain a place in a hospital or clinic to be hospitalized [5, 6, 7]. It can link to the pharmacy or clinic for the dispensary because it is an online booking doctor application. The doctor will use this app to order the medication, and a nearby pharmacy or clinic will hold it in reserve. They will deliver through a delivery service such as Lalamove or Grab.

2 Methodology There are numerous software approaches available around the world, each with its own set of benefits and drawbacks. Developing software is a huge undertaking. The process of creating a specialized information system is typically viewed as a way to plan and monitor methods for generating software. System developers will benefit from a methodology of software development that includes a variety of techniques, tools, and documentation aids to help them implement a new information system [8, 9].

2.1 System Development Model Due to the general speed with which it may be implemented, most people prefer rapid application development (RAD) [10]. When compared to other approaches, it can produce high-quality outcomes in a shorter amount of time.

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This process consists of constructing workable software step by step over a variable number of prototyping cycles. Iterative sessions are common. Each iteration session is a chance for the users to provide the full set of functional requirements, not at the beginning of the project. Although RAD has evolved over time, there are four core steps that have remained consistent and may be defined in the “Hello Dr” mobile application. This RAD consists of defining the requirements, prototyping, testing, and refining. RAD distinguishes itself from traditional software development techniques right from the start, with its booking doctor application. This “Hello Dr” mobile app will benefit from a wide range of demand, which will help to provide specific requirements at any stage of the development cycle [11, 4]. This is where the project’s actual development takes place. Making rapid prototypes of various features and functions rather than strictly following predefined specifications is essential for the “Hello Dr” mobile application. After that, the user can decide what they like and do not like about the prototypes. The RAD methodology, in contrast to structured approaches, provides a few stages that specifically include the development team and users to lead to quicker access to the application. RAD’s definition has changed over time. Some fundamental development standards were kept in mind as it is adapted to the changing times.

3 Results and Discussion An excellent approach to test this mobile application is because if done incorrectly, this mobile application may fail to detect faults that may occur when this “Hello Dr” mobile application runs. For this “Hello Dr” mobile app, the usability testing can be used to determine how easily people can use and understand the user interface. A usability test is a great way to get real-world feedback on your app before releasing it to the public. In order to focus on this mobile application, this strategy provides immediate feedback from the target audience. A pie chart, a bar graph, and short-answer responses were used to display the results of questions in sections A, B, C, and D. Scores were assigned based on the questionnaire’s system usability scale. Doctors at a nearby clinic and social media channels such as the “Warga Serdang and Seri Kembangan” (WSSK) Facebook page were used by the members to communicate with one another. In addition to the questionnaires, participants were sent a link to a Google Form containing the test material, as well as a link to the questionnaires. In each question, a module from the “Hello Dr” smartphone application is used as an answer. During the five days of the application trial, eighteen people completed the Google Form questionnaire. This questionnaire is completed by nine doctors and nine patients. The testers were permitted to install the “Hello Dr” mobile application on their own Android-powered smart devices.

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A total of 33.3% of respondents between the ages of 21 and 30 used this mobile app, while 11.1% of respondents aged 18–20, 35–40, and 41 and older used it. This mobile application includes an area for making recommendations to other users. It reveals that 55.6% suggest this mobile application to others, 38.9% may recommend it to others, and the remainder think that it is not recommended. Half of the respondents gave outstanding answers, while half gave good answers. The majority of respondents believe that it is simple to arrange an appointment with a doctor using this mobile application. This grade ranges from terrible to outstanding. About 33.3% of respondents chose great, while 66.7% chose good. This mobile application is not yet flawless, but it should be. The recommendations and potential enhancements for this “Hello Dr” mobile application are stated below.

4 Conclusion The researchers were successful in developing the “Hello Dr” application for patients and clinicians in the Seri Kembangan area. They can use their smartphone to access this application. If the patient requires therapy, the “Hello Dr” mobile application provides a great platform for consultation. Although medical gadgets and applications unquestionably provide several benefits, some consumers are unaware of the risks and benefits associated with them. It is needed to guarantee that medical applications meet the highest standards of quality and safety, it is critical that they are thoroughly examined, validated, and best practices’ standards are established (Table 1; Figs. 1, 2, 3, 4 and 5).

Table 1 Comparison

Function Booking doctor Home visit Medicine delivery

DOCTOR2U √ √ √

Point and redeem

x

Schedule

x √

History Self-diagnose

x

Notification

x

BOOKDOC √ x x x √ √ x √

Hello Dr √ √ √ √ √ √ √ √

“Hello Dr” Application for Mobile Devices

Fig. 1 Methodology: rapid application development (RAD)

Fig. 2 Age

Fig. 3 Interface for patient and self-diagnose

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Fig. 4 Interface for main page

Fig. 5 Interface for medication treatment

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Acknowledgements We would like to thank the Malaysian Institute of Information Technology, Universiti Kuala Lumpur, and the Final Year Project assessors for their enthusiastic support and constructive criticism of this research work. We would also want to thank the technicians in the MIIT department’s laboratory for their assistance in providing me with the resources needed to execute the software. Finally, we would like to thank our family for their encouragement and support throughout my studies.

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The Fundamentals of Schwann Cell Biology Nurul Husna Abd Razak, Amiza Shahira Zainey, Jalilah Idris, and Muhammad Fauzi Daud

Abstract Schwann cells are ubiquitous in the peripheral nervous system (PNS), forming intimate enwrapments around the axons of the peripheral nerve tissues. Schwann cells exhibit two distinct phenotypes in adult animals: myelinating cells or Remak cells. Myelinating cells form the myelin sheath, facilitating the action potential saltatory conduction. On the other hand, Remak Schwann cells form nonmyelinating interactions with multiple small diameter axons in Remak bundles. Besides establishing and maintaining the neurophysiological functions of axons, Schwann cells are also one of the critical regulators for axonal maintenance and metabolic support, neurodevelopment, and nerve injury response. Schwann cell reprogramming is contingent on the plasticity of Schwann cells, which is important in a wide range of Schwann cell functions, from development to nerve injury and neurodegenerative diseases. Nevertheless, our understanding of the biology of Schwann cell plasticity is still developing. Schwann cell plasticity will become increasingly prominent as a subject area in Schwann cell biology in the following decades as emerging data signify its relevance in developing therapeutic strategies for nerve injury and degenerative neuropathies such as diabetic peripheral neuropathy. Keywords Schwann cell · Myelin · Remak · Schwann cell plasticity · Peripheral nerve

N. H. Abd Razak · A. S. Zainey · J. Idris · M. F. Daud (B) Universiti Kuala Lumpur, Institute of Medical Science Technology, A1-1, Jalan TKS 1, Taman Kajang Sentral, 43000 Kajang, Selangor, Malaysia e-mail: [email protected] N. H. Abd Razak e-mail: [email protected] A. S. Zainey e-mail: [email protected] J. Idris e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 A. Ismail et al. (eds.), Industrial Revolution in Knowledge Management and Technology, SpringerBriefs in Applied Sciences and Technology, https://doi.org/10.1007/978-3-031-29265-1_13

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1 Schwann Cells: The Glial of the Peripheral Nervous System Schwann cells are the primary glia of the peripheral nervous system (PNS); aside from maintaining the structure and function of neurons, they also regulate nutrient uptake to the axons and promote neuronal survival and axonal growth for nerve repair [1]. Schwann cells are ubiquitous in the peripheral nerve tissue, forming intimate enwrapments around neuronal axons [2]. Schwann cells exhibit two cellular phenotypes: myelinating and non-myelinating in the native tissue. Axons with a diameter larger than one μm are enwrapped individually by myelinating Schwann cells forming a multilamellar insulating membrane called the myelin sheath. On the other hand, non-myelinating Schwann cells form the Remak bundle, which is characterized by the association of a single Schwann cell with multiple small axons (< 1 μm diameter) [3, 4]. Schwann cells facilitate saltatory conduction in the neuron by establishing the myelin sheath and the node of Ranvier. The myelin sheath, akin to electrical wire insulation, generates rapid electrical impulses’ transmission along the axonal membrane [5]. The sheath can speed up the electrical impulse in myelinated axons up to 20–100 fold higher than the speed in unmyelinated axons [6]. Schwann cells also provide metabolic maintenance for neurons [7, 8], protect and preserve axonal integrity [9], and mastermind the responses to tissue injury [10]. Moreover, Schwann cells are composed of various receptors that can detect stressors, promoting neuroprotection, regrowth, and remyelination [1].

2 Schwann Cells 2.1 Myelinating Schwann Cells Myelinating Schwann cells form the myelin sheath via the plasma membrane extension, which wraps the axon in discontinuous membranes, interspersed by the nodes of Ranvier. It is responsible for increasing the conduction speed of action potential. The myelin sheath has low capacitance and low electrical resistance across the internode membranes to allow rapid, saltatory movement of nerve impulses [11] which is exclusively found in myelinated axons. The axonal membrane at the nodes of Ranvier is exposed to the extracellular space and enriched with sodium and potassium ion channels [12]. Through this unique process, a high number of myelinated axons with high conduction speed can be compacted into smaller tissue sizes to permit the development of a complex nervous system compared to unmyelinated axons, which require larger tissue sizes. The saltatory conduction significantly improves the metabolic efficiency of neuronal activity as less energy is used to re-establish action potential on the axonal membrane, thus indirectly reducing the metabolic requirements for

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neuronal activity [11]. Thus, myelin increases conduction speed and aids in reducing space and energy for the nerve impulses’ conduction [13]. The myelinating Schwann cells are morphologically and molecularly highly polarized [14]. The myelinating Schwann cells are arranged in domains with distinct membranes that contain a particular polarity of proteins and cytoskeletal elements [15]. It exhibit longitudinal and radial polarity [14–16]. Longitudinally, myelinating Schwann cells are arranged along the axon length into the nodes of Ranvier, paranodes, juxtaparanodes, and internodes. The radial polarity is shown from the axon to the Schwann cell basal lamina. The membrane attached to the axon is the inner membrane surface, termed adaxonal, while the outer (abaxonal) membrane surface is apposed to the Schwann cell basal lamina. In between both membranes, the myelin sheath’s compacted membranes are found [15].

2.2 Remak Schwann Cells Remak Schwann cells are non-myelinating Schwann cells that wrap multiple small diameter axons in Remak bundles [17]. Remak cells perform crucial functions in the development and physiology of the PNS and assist in regeneration after injury [18]. However, Remak Schwann cells are not extensively studied due to the need for electron microscopy to observe these cells and the lack of specific markers to distinguish Remak Schwann cells from immature Schwann cells [18]. The Remak Schwann cells enwrap multiple small diameter axons to form Remak bundles. The maintenance of axonal integrity is closely linked with Schwann cell metabolic support. Thus, even though Remak Schwann cells do not myelinate, the mitochondria of the Schwann cell are crucial for maintaining the axonal integrity [19]. Moreover, Remak bundles are essential in nerve injury and regeneration as almost 50% of Remak Schwann cells reprogram into repair phenotypes and build Bunger bands to assist the regeneration of axons. Interestingly, they can subsequently redifferentiate into myelinating Schwann cells after regeneration [20].

3 The Molecular Mechanism of Schwann Cell Myelination 3.1 Extrinsic Signals The myelination process is governed by complex molecular interactions involving extrinsic signals and intracellular signaling pathways [21]. The axon and extracellular matrix (ECM) exhibit the main extrinsic signals. NRG1, one of the EGF superfamilies, is the critical trigger for myelination [22]. There are six major classes of NRG1, with Types I–III being the most abundant. NRG1 Type III is mainly found on the peripheral axons and binds to and activates the tyrosine kinase erbB family

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to signal the targeted cells [23]. Schwann cells express erbB2/erbB3 heterodimer. Thus, NRG1-erbB2/erbB3 binding triggers myelination [24]. Axons express NRG1III on their membrane or exempted from axons by proteases such as BACE1 and TACE/ADAM17. The larger the axonal diameter, the higher the level of NRG1-III is expressed on the axon membrane, thus promoting the differentiation of immature Schwann cells to myelinating Schwann cells and the formation of myelin [18]. Gpr126, an adhesion G-protein-coupled receptor, is crucial during Schwann cell development by promoting radial sorting [25]. Gpr126 activates the cyclic adenosine monophosphate (cAMP) signaling for myelination to begin in vivo, and it regulates and directly elevates Schwann cell cAMP levels [25, 26]. Gpr126 null Schwann cells cannot express Oct6 or Krox20, being halted in the pro-myelinating stage and unable to produce myelin [27, 28].

3.2 Intracellular Signalings The PI3K/Akt/ mTOR pathways are integral to the Schwann cell development, including proliferation, survival, and myelination. NRG1-III/ErbB2/3 signaling activity phosphorylates 3-phosphoinositide-dependent protein kinase-1, which then converts phosphatidylinositol diphosphate to phosphatidylinositol triphosphate, resulting in the activation of Akt and mTOR [29, 30]. Activation of PLC-γ by NRG1 signaling causes intracellular calcium elevation and phosphatase calcineurin B activation. The elevation of both components dephosphorylates the cytosolic NFAT proteins which later translocate to the nucleus and stimulate NFAT-associated gene transcription [31]. NFATc4, with Sox10, then binds to the myelinating Schwann cell elements (MSE) of Krox20 and is also attached directly to the myelin protein zero promoters to initiate P0 transcription. P0 is a transmembrane protein that is one of the major proteins of the peripheral nerve myelin sheath. MAPK is the primary pathway linked to the pro-myelinating cue of NRG1, and it is critical in initiating Schwann cell differentiation. The involvement of MAPK family proteins, including Erk, P38 MAP kinase, plays a regulatory role in Schwann cell differentiation. Deleting Erk1/2 in developing Schwann cells can halt differentiation and myelination [32]. In line with the study, myelin growth is enhanced when the Erk1/2 pathway is activated [33, 34]. The P38 MAPK signaling pathway promotes the establishment of the pro-myelinating phenotypes during the initial phase of myelination, as when the p38 MAPK is inhibited, it suppresses the myelin formation [35]. cAMP is an intracellular signal that promotes and maintains Schwann cells’ myelinating phenotype. Few in vitro studies of cAMP show that cAMP enhances the strength of NRG1 signals [36, 37], and some studies have demonstrated that cAMP triggers Schwann cells to switch from proliferation to myelination following NRG1III signaling [38]. The expression of pro-myelinating transcription factors, Oct6, is upregulated with the signal from cAMP, and it is also proven to assist NFAT in initiating Krox20 expression. The pro-myelinating transcription factor Oct6 is highly

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expressed in cultured Schwann cells in response to cAMP-mediated signaling [39]. This observation is further corroborated by the presence of cAMP response element binding (CREB) protein in Oct6 [40], which has been shown to regulate Schwann cell differentiation [38].

3.3 Transcription Factors The transcription factors involved in Schwann cell myelination include Oct6, Brn2, and Sox10. Oct6 and Brn2 are crucial in regulating when and how fast the conversion of pro-myelinating Schwann cells into the myelinating phenotype by targeting the Krox20/Egr2 gene [41–43]. During Schwann cell differentiation, Oct6 and Brn2 are upregulated briefly to assist in myelination, while Sox10 is expressed in all phases of Schwann cell lineage [43, 44]. Cis-acting elements found in the Krox20/Egr locus, known as the myelin-associated Schwann cell enhancer or mSCE, act as mediators to promote Krox20/Egr2 expression in Schwann cells [45].

4 Schwann Cell Plasticity It is well established that the peripheral nerve tissue has a relatively superior regenerative capacity than the tissue in the brain and the spinal cord due to the permissive microenvironment in the former [46, 47], which is attributed mainly to its glia Schwann cells. The incredible plasticity of Schwann cells allows them to switch their cellular phenotypes, following injury, from homeostatic maintenance of axon/myelin to promoting tissue regeneration by creating a pro-regenerative microenvironment in injured nerve tissue [48]. In response to injury, myelin and Remak Schwann cells undergo adaptive cellular reprogramming, a radical shift in the differentiation states from mature to pro-regenerative cells, called repair Schwann cells [49]. Repair Schwann cells remove axon and myelin debris through phagocytosis, and they also send signals to recruit and activate macrophages to assist with debris clearance [50]. They also undergo myelinophagy to digest intracellular myelin fragments [51]. Once cleared of the tissue fragments, repair Schwann cells increase neurotrophic factors secretion to promote axonal growth and sustain axotomized neurons [52]. Approximately four weeks after injury, they proliferate, elongate, and reorganize into compact cellular columns, called Bungner bands, generating guiding tracks for regenerating axons [20]. Adaptive reprogramming of Schwann cells has been discussed previously [48, 53]. Reprogramming into repair Schwann cells is characterized by a drastic change in molecular profiles in which the immature Schwann cell molecular markers are upregulated to replace the expression of pro-myelinating and myelin markers. Following injury, Schwann cells elevate or re-express the genes for L1, NCAM, p75NTR, and GFAP, which are commonly activated during development (reviewed in [53, 54]).

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Concomitant downregulation of pro-myelinating and myelin biomarkers such as Krox20, P0, MBP, PMP22, MAG, and periaxin also occurs in the cells, marking for Schwann cell demyelination (reviewed in [53, 54]). Besides the expression of the immature characteristics, several genes are uniquely expressed/upregulated in injury conditions, namely c-Jun, Olig1, and Shh [53]. Notably, the transcription factor c-Jun appears to be the master regulator for reprogramming Schwann cells into proregenerative phenotypes, and it has direct or indirect regulatory links with at least 172 injury-associated genes [55]. Furthermore, repair Schwann cells are characterized by the elevated expression of Notch, Sox2, Id2, Pax-3, Egr1, and Egr2, which are transcription factors that suppress myelination [56]. Repair Schwann cells generate the repair-promoting environment by increasing the secretion of various neurotrophic factors and enhancing surface proteins’ expression, promoting axonal growth and neuronal survival. The pro-regenerative factors include artemin, BDNF, GDNF, NT-3, NGF, VEGF, FGFs, pleiotrophin, N-cadherin, and p75NTR [49, 57]. Furthermore, these cells upregulate cytokine secretion, such as TNF-α, interleukin-1α, and MCP-1. Increased cytokine activity promotes macrophage invasion at the injury site and directly promotes axonal growth. Together with Schwann cells, macrophages facilitate myelin removal through phagocytosis, promoting vascularization of the injury site.

5 Conclusion Schwann cells play an integral part in peripheral nerve functions. They used to be considered inert, playing a passive supporting role to axons; decades of research in Schwann biology have validated the immensely active roles of Schwann cells in coordinating highly complex processes in developing nerve tissue, neurophysiological maintenance, and nerve regeneration. Recent developments in Schwann cell biology have highlighted the significance of Schwann cell plasticity in every aspect of Schwann cells’ life. Unfortunately, the plastic nature of their phenotypes makes them susceptible to pathological disturbances that can lead to neurodegenerative diseases. Furthermore, our understanding of the underlying mechanisms in Schwann cell plasticity remains limited. In the succeeding decades, we will see more studies exploring this question in the quest for therapeutic targets for many neurodegenerative diseases. Acknowledgements We thank the Ministry of Higher Education (MOHE) Malaysia for the financial support (FRGS/1/2019/SKK08/UNIKL/02/3). We also greatly appreciate the financial support from Universiti Kuala Lumpur (UniKL/CoRI/str17089).

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