Perceived Impediments and Anticipated Solutions to HR (Human Resource) Towards Implementing Industry 4.0 in SMEs: : Impediments and Anticipated Solutions to HR
Pages 1 - 26
Abstract
The study aims to evaluate perceived impediments and anticipated solutions to HR while implementing Industry 4.0 initiatives in SMEs. A group of 10 decision-makers from these SMEs was tasked with assigning ratings to a variety of parameters. To create the model for 10 perceived impediments and five anticipated solutions and subsequently rank them, the TOPSIS technique is employed. According to the data analysis, job reductions, unemployment, and job uncertainty have emerged as the top three significant hurdles, while challenges to trainers, replacement of humans, and training costs have been recognized as the bottom three. Smart HR 4.0 and AI & Data Analytics are the top and lowest-ranked solutions respectively. HR in I4.0 in SMEs parameters have been graded based on their contributing attributes. However, it is also true that there are several impediments associated with the implementation of Industry 4.0. These impediments become more challenging in the context of SMEs.
References
[1]
Adolph, S., Tisch, M., & Metternich, J. (2014). Challenges and approaches to competency development for future production. Journal of International Scientific Publications–Educational Alternatives, 12(1), 1001–1010.
[2]
Agarwal, V., Mathiyazhagan, K., Malhotra, S. and Saikouk, T. (2022), "Analysis of challenges in sustainable human resource management due to disruptions by Industry 4.0: an emerging economy perspective", International Journal of Manpower, Vol. 43 No. 2, pp. 513-541. https://doi.org/10.1108/IJM-03-2021-0192
[3]
Agostini, L., & Nosella, A. (2019). The adoption of Industry 4.0 technologies in SMEs: Results of an international study. Management Decision, 58(4), 625–643.
[4]
Ahammad, M. F., Glaister, K. W., & Gomes, E. (2020). Strategic agility and human resource management. Human Resource Management Review, 30(1), 100700.
[5]
Anshari, M., Almunawar, M. N., & Razzaq, A. (2021). Developing talents vis-à-vis fourth industrial revolution. International Journal of Asian Business and Information Management, 12(4), 20–32.
[6]
Bag, S., Telukdarie, A., Pretorius, J. H. C., & Gupta, S. (2018). Industry 4.0 and supply chain sustainability: Framework and future research directions. Benchmarking, 28(5), 1410–1450.
[7]
Bag, S., Wood, L. C., Mangla, S. K., & Luthra, S. (2020a). Procurement 4.0 and its implications on business process performance in a circular economy. Resources, Conservation and Recycling, 152, 104502.
[8]
Bag, S., Yadav, G., Dhamija, P., & Kataria, K. K. (2021). Key resources for Industry 4.0 adoption and its effect on sustainable production and circular economy: An empirical study. Journal of Cleaner Production, 281, 125233.
[9]
Bag, S., Yadav, G., Wood, L. C., Dhamija, P., & Joshi, S. (2020b). Industry 4.0 and the circular economy: Resource melioration in logistics. Resources Policy, 68, 101776.
[10]
Bai, C., Dallasega, P., Orzes, G., & Sarkis, J. (2020). Industry 4.0 technologies assessment: A sustainability perspective. International Journal of Production Economics, 229, 107776.
[11]
Bauer, W., Schlund, S., Hornung, T., & Schuler, S. (2018). Digitalization of industrial value chains-a review and evaluation of existing use cases of Industry 4.0 in Germany. LogForum, 14(3), 331–340.
[12]
Bulgurcu, B. K. (2012). Application of TOPSIS technique for financial performance evaluation of technology firms in Istanbul stock exchange market. Procedia: Social and Behavioral Sciences, 62, 1033–1040.
[13]
Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1–9.
[14]
Chen, Y., Han, Z., Cao, K., Zheng, X., & Xu, X. (2020). Manufacturing upgrading in Industry 4.0 era. Systems Research and Behavioral Science, 37(4), 766–771.
[15]
Cimini, C., Boffelli, A., Lagorio, A., Kalchschmidt, M., & Pinto, R. (2020). How do Industry 4.0 technologies influence organisational change? An empirical analysis of Italian SMEs. Journal of Manufacturing Technology Management, 32(3), 695–721.
[16]
Coupe, T. (2019). Automation, job characteristics and job insecurity. International Journal of Manpower, 40(7), 1288–1304.
[17]
Cugno, M., Castagnoli, R., & Büchi, G. (2021). Openness to Industry 4.0 and performance: The impact of barriers and incentives. Technological Forecasting and Social Change, 168, 120756.
[18]
Dafflon, B., Moalla, N., & Ouzrout, Y. (2021). The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: A literature review. International Journal of Advanced Manufacturing Technology, 113(7-8), 2395–2412.
[19]
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383–394.
[20]
Do, T. N., Kumar, V., & Do, H. M. (2020). Prioritize the key factors of Vietnamese coffee industries for sustainability . International Journal of Productivity and Performance Management, 69(6), 1153–1176.
[21]
Ghobakhloo, M. (2018). The future of manufacturing industry: A strategic roadmap toward Industry 4.0. Journal of Manufacturing Technology Management, 29(6), 910–936.
[22]
Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869.
[23]
Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0. (pp. 195-215). Apress.
[24]
Grube, D., Malik, A. A., & Bilberg, A. (2019). SMEs can touch Industry 4.0 in the smart learning factory. Procedia Manufacturing, 31, 219–224.
[25]
Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358–390.
[26]
HermannM.PentekT.OttoB. (2016). Design principles for Industrie 4.0 scenarios. Proceedings of the Forty-Ninth Hawaii International Conference on System Sciences, 3928-3937. 10.1109/HICSS.2016.488
[27]
Hofmann, E., & Rüsch, M. (2017). Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry, 89, 23–34.
[28]
Horvath, D., & Szabo, R. Z. (2019). Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological Forecasting and Social Change, 146, 119–132.
[29]
Hwang, C. L., Lai, Y. J., & Liu, T. Y. (1993). A new approach for multiple objective decision making. Computers & Operations Research, 20(8), 889–899.
[30]
Hwang, C. L., & Yoon, K. (1981). Methods for Multiple Attribute Decision Making. In Multiple Attributes Decision Making (pp. 58–191). Springer.
[31]
Ivanov, D., Tang, C. S., Dolgui, A., Battini, D., & Das, A. (2021). Researchers’ perspectives on Industry 4.0: Multi-disciplinary analysis and opportunities for operations management. International Journal of Production Research, 59(7), 2055–2078.
[32]
Kagermann, H., Lukas, W. D., & Wahlster, W. (2011). Industrie 4.0: Mit dem Internet der Dinge auf dem Weg zur 4. industriellen Revolution. VDI nachrichten, 13(1), 2-3.
[33]
Kamble, S. S., Gunasekaran, A., & Sharma, R. (2018). Analysis of the driving and dependence power of barriers to adopt Industry 4.0 in Indian manufacturing industry. Computers in Industry, 101, 107–119.
[34]
Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, B. H., & Noh, S. D. (2016). Smart manufacturing: Past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(1), 111–128.
[35]
Karadayi-Usta, S. (2019). An interpretive structural analysis for Industry 4.0 adoption challenges. IEEE Transactions on Engineering Management, 67(3), 973–978.
[36]
Khanzode, A. G., Sarma, P. R., Mangla, S. K., & Yuan, H. (2021). Modeling the Industry 4.0 adoption for sustainable production in micro, small & medium enterprises. Journal of Cleaner Production, 279, 123489.
[37]
Kiel, D., Müller, J. M., Arnold, C., & Voigt, K. I. (2017). Sustainable industrial value creation: Benefits and challenges of Industry 4.0. International Journal of Innovation Management, 21(8), 1–34.
[38]
Kumar, S., Suhaib, M., & Asjad, M. (2021). Narrowing the barriers to Industry 4.0 practices through PCA-Fuzzy AHP-K means. Journal of Advances in Management Research, 18(2), 200–226.
[39]
Kumar, V., Verma, P., Jha, A., Lai, K. K., & Do, H. M. (2020). Dynamics of a medium value consumer apparel supply chain key parameters. International Journal of Productivity and Performance Management. Advance online publication.
[40]
Kurt, R. (2019). Industry 4.0 in terms of industrial relations and its impacts on labour life. Procedia Computer Science, 158, 590–601.
[41]
Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239–242.
[42]
Lee, J., Davari, H., Singh, J., & Pandhare, V. (2018). Industrial Artificial Intelligence for Industry 4.0-based manufacturing systems. Manufacturing Letters, 18, 20–23.
[43]
Leng, J., Ruan, G., Song, Y., Liu, Q., Fu, Y., Ding, K., & Chen, X. (2021). A loosely-coupled deep reinforcement learning approach for order acceptance decision of mass-individualized printed circuit board manufacturing in Industry 4.0. Journal of Cleaner Production, 280, 124405.
[44]
Lim, C. H., Lim, S., How, B. S., Ng, W. P. Q., Ngan, S. L., Leong, W. D., & Lam, H. L. (2021). A review of Industry 4.0 revolution potential in a sustainable and renewable palm oil industry: HAZOP approach. Renewable & Sustainable Energy Reviews, 135, 110223.
[45]
Luthra, S., & Mangla, S. K. (2018a). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168–179.
[46]
Luthra, S., & Mangla, S. K. (2018b). When strategies matter: Adoption of sustainable supply chain management practices in an emerging economy’s context. Resources, Conservation and Recycling, 138, 194–206.
[47]
Machado, C. G., Winroth, M., Carlsson, D., Almström, P., Centerholt, V., & Hallin, M. (2019). Industry 4.0 readiness in manufacturing companies: Challenges and enablers towards increased digitalization. Procedia CIRP, 81, 1113–1118.
[48]
Mangla, S. K., Govindan, K., & Luthra, S. (2016). Critical success factors for reverse logistics in Indian industries: A structural model. Journal of Cleaner Production, 129, 608–621.
[49]
Margherita, E. G., & Braccini, A. M. (2021). Managing Industry 4.0 automation for fair ethical business development: A single case study. Technological Forecasting and Social Change, 172, 121048.
[50]
Masood, T., & Sonntag, P. (2020). Industry 4.0: Adoption challenges and benefits for SMEs. Computers in Industry, 121, 103261.
[51]
Mittal, S., Khan, M. A., Romero, D., & Wuest, T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems, 49, 194–214.
[52]
Moktadir, M. A., Ali, S. M., Kusi-Sarpong, S., & Shaikh, M. A. A. (2018). Assessing challenges for implementing Industry 4.0: Implications for process safety and environmental protection. Process Safety and Environmental Protection, 117, 730–741.
[53]
Möller, D. P. (2016). Digital manufacturing/Industry 4.0. In Guide to Computing Fundamentals in Cyber-Physical Systems (pp. 307–375). Springer.
[54]
Muller, J. M., Buliga, O., & Voigt, K. I. (2018). Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0. Technological Forecasting and Social Change, 132, 2–17.
[55]
Nam, T. (2019). Technology usage, expected job sustainability, and perceived job insecurity. Technological Forecasting and Social Change, 138, 155–165.
[56]
Nardo, M., Forino, D., & Murino, T. (2020). The evolution of man–machine interaction: The role of human in Industry 4.0 paradigm. Production & Manufacturing Research, 8(1), 20–34.
[57]
Pathak, D. K., Verma, A., & Kumar, V. (2020). Performance variable of GSCM for sustainability in Indian Automobile Organizations using TOPSIS Method. Business Strategy and Development, 3(4), 590–602.
[58]
Pirola, F., Cimini, C., & Pinto, R. (2019). Digital readiness assessment of Italian SMEs: A case-study research. Journal of Manufacturing Technology Management, 31(5), 1045–1083.
[59]
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. 14516251.
[60]
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. 21838546.
[61]
Popkova, E. G., & Zmiyak, K. V. (2019). Priorities of training of digital personnel for Industry 4.0: Social competencies vs technical competencies. On the Horizon, 27(3/4), 138–144. Advance online publication.
[62]
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A. B. L., & Rajak, S. (2020). Barriers to the adoption of Industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, 107546.
[63]
Rana, G., & Sharma, R. (2019). Emerging human resource management practices in Industry 4.0. Strategic HR Review, 18(4), 176–181.
[64]
Rauch, E., Matt, D. T., Brown, C. A., Towner, W., Vickery, A., & Santiteerakul, S. (2018). Transfer of Industry 4.0 to small and medium sized enterprises. Advances in Transdisciplinary Engineering, 7, 63–71.
[65]
Roblek, V., Meško, M., & Krapež, A. (2016). A complex view of industry 4.0. Sage open, 6(2), 1-11.
[66]
Rombaut, E., & Guerry, M. A. (2020). The effectiveness of employee retention through an uplift modeling approach. International Journal of Manpower, 41(8), 1199–1220.
[67]
Sari, R. P., & Santoso, D. T. (2020). Readiness Factor Identification on Kabupaten Karawang SMEs towards Industry 4.0 Era. Jurnal Teknik Industri, 22(1), 65–74.
[68]
Sarı, T., Güleş, H. K., & Yiğitol, B. (2020). Awareness and readiness of Industry 4.0: The case of Turkish manufacturing industry. Advances in Production Engineering & Management, 15(1), 57–68.
[69]
Scremin, L., Armellini, F., Brun, A., Solar-Pelletier, L., & Beaudry, C. (2021). Towards a framework for assessing the maturity of manufacturing companies in Industry 4.0 adoption. In Research Anthology on Cross-Industry Challenges of Industry 4.0 (pp. 895–925). IGI Global.
[70]
Segal, M. (2018). How automation is changing work. Nature, 563(7733), S132–S135. 30487630.
[71]
Sharma, N. K., Kumar, V., Verma, P., & Luthra, S. (2021). Sustainable reverse logistics practices and performance evaluation with fuzzy TOPSIS: A study on Indian retailers. Cleaner Logistics and Supply Chain, 1, 1-18.
[72]
Sharma, N.K. & Singh, G.S. (2017). A Study on Indian Logistics Network and Its Impact on Economic Growth. IUP Journal of Supply Chain Management, 14(4), 38-60.
[73]
Singh, R. K., Gupta, A., Kumar, A., & Khan, T. A. (2016). Ranking of barriers for effective maintenance by using TOPSIS approach. Journal of Quality in Maintenance Engineering, 22(1), 18–34.
[74]
Singh, R. K., & Kumar, R. (2020). Strategic issues in supply chain management of Indian SMEs due to globalization: An empirical study. Benchmarking, 27(3), 913–932.
[75]
Sivathanu, B., & Pillai, R. (2018). Smart HR 4.0–how Industry 4.0 is disrupting HR. Human Resource Management International Digest, 26(4), 7–11.
[76]
Sriram, R. M., & Vinodh, S. (2021). Analysis of readiness factors for Industry 4.0 implementation in SMEs using COPRAS. International Journal of Quality & Reliability Management, 38(5), 1178–1192.
[77]
Stentoft, J., Adsbøll Wickstrøm, K., Philipsen, K., & Haug, A. (2020). Drivers and barriers for Industry 4.0 readiness and practice: Empirical evidence from small and medium-sized manufacturers. Production Planning and Control, 32(10), 811–828.
[78]
Türkeș, M. C., Oncioiu, I., Aslam, H. D., Marin-Pantelescu, A., Topor, D. I., & Căpușneanu, S. (2019). Drivers and barriers in using Industry 4.0: A perspective of SMEs in Romania. Processes (Basel, Switzerland), 7(3), 1–20, 153.
[79]
Valenduc, G., & Vendramin, P. (2016). Work in the digital economy: Sorting the old from the new (Working paper 2016.03). European Trade Union Institute. http:// hdl.handle.net/2078.1/173373
[80]
Verma, P., Kumar, V., Mittal, A., Gupta, P., & Hsu, S. C. (2021). Addressing strategic human resource management practices for TQM: The case of an Indian tire manufacturing company. The TQM Journal.
[81]
Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management, 33(6), 1237-1266.
[82]
Wang, T. C., & Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980–8985.
[83]
Whysall, Z., Owtram, M., & Brittain, S. (2019). The new talent management challenges of Industry 4.0. Journal of Management Development, 38(2), 118–129.
[84]
Wright, S. A., & Schultz, A. E. (2018). The rising tide of artificial intelligence and business automation: Developing an ethical framework. Business Horizons, 61(6), 823–832.
[85]
Yadav, G., Kumar, A., Luthra, S., Garza-Reyes, J. A., Kumar, V., & Batista, L. (2020b). A framework to achieve sustainability in manufacturing organisations of developing economies using Industry 4.0 technologies’ enablers. Computers in Industry, 122, 103280.
[86]
Yadav, G., Luthra, S., Jakhar, S. K., Mangla, S. K., & Rai, D. P. (2020a). A framework to overcome sustainable supply chain challenges through solution measures of Industry 4.0 and circular economy: An automotive case. Journal of Cleaner Production, 254, 120112.
[87]
Yoon, K. (1987). A reconciliation among discrete compromise solutions. The Journal of the Operational Research Society, 38(3), 277–286.
[88]
Yu, F., & Schweisfurth, T. (2020). Industry 4.0 technology implementation in SMEs–A survey in the Danish-German border region. International Journal of Innovation Studies, 4(3), 76–84.
[89]
Yüksel, H. (2020). An empirical evaluation of Industry 4.0 applications of companies in Turkey: The case of a developing country. Technology in Society, 63, 101364.
[90]
Zheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2021). The applications of Industry 4.0 technologies in manufacturing context: A systematic literature review. International Journal of Production Research, 59(6), 1922–1954.
[91]
Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent manufacturing in the context of Industry 4.0: A review. Engineering, 3(5), 616–630.
Index Terms
- Perceived Impediments and Anticipated Solutions to HR (Human Resource) Towards Implementing Industry 4.0 in SMEs: Impediments and Anticipated Solutions to HR
Index terms have been assigned to the content through auto-classification.
Recommendations
Piloting Industry 4.0 in SMEs with RAMI 4.0: an enterprise architecture approach
AbstractReference Architectural Model Industrie 4.0 (RAMI 4.0) is an influential guide to the ongoing digital transformation in industry. However, the adoption of RAMI 4.0 in small and medium-sized enterprises (SMEs) is still emerging. This paper ...
Industry 4.0: Adoption challenges and benefits for SMEs
Highlights- First survey of UK SMEs (n = 271, KMO = 0.701) on adoption of Industry 4.0 technologies (n = 20)
AbstractFuture industrial systems have been popularised in recent years through buzzwords such as Industry 4.0, the Internet of Things (IoT), and Cyber Physical Systems (CPS). Whilst the technologies of Industry 4.0 and likes have many ...
Implementing enterprise resource planning in SMEs: the consultants' perspective
The paper provides examination of the implementation of the enterprise resource planning system (ERP) in small and medium-sized companies (SMEs) in developing countries from the consultants' perspective based on the designed conceptual model. The proposed ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Copyright © 2022.
Publisher
IGI Global
United States
Publication History
Published: 06 October 2022
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Jan 2025