Industry 4.0 concepts within the Czech SME manufacturing sector: an empirical assessment of critical success factors
The paper analysed factors that has the most impact in influencing the achievement of a sustainable process management model in the implementation of Industry 4.0 concepts within the Czech SME manufacturing sector. Several factors were identified and their interactions with digital technologies within the production environments was analysed. These factors, from an organisational perspective were identified as critical to success in the quest to achieve Industry 4.0 compliance and digital transformation of the manufacturing operations of companies. They include: strategy, organisational fit, competitiveness, operations and human resources. A mixed methods approach was adopted for the research. It involved both the qualitative and quantitative methodological approaches. The qualitative aspect involved an extensive systematic review of relevant literature which was useful in developing the conceptual framework and identifying the relevant factors that enable the implementation of an efficient Industry 4.0 process management model in SMEs; the quantitative aspect involved the use of a survey questionnaire to collect data which was analysed using confirmatory factor analysis statistical approach to test the measures of the constructs in the proposed conceptual framework. The result from the statistical analysis shows the factors that in the conceptual model that were supported as being relevant in achieving an efficient process management model for successful implementation of Industry 4.0 concepts in Czech manufacturing SMEs. The research limitation is based on the fact that the SMEs covered in the quantitative aspect of the research are restricted to a particular geographical location – Czech Republic. It would be interesting to have similar studies conducted in other geographies for a comparative perspective. It contributes to the scientific and practical discourse on Industry 4.0 process management model implementation in SMEs by investigating the phenomenon through the production of credible scientific evidence.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Baena, F., Guarin, A., Mora, J., Sauza, J., & Retat, S. (2017). Learning factory: the path to Industry 4.0. Procedia Manufacturing, 9, 73–80. https://doi.org/10.1016/j.promfg.2017.04.022
Chromjakova, F. (2017). Process stabilization-key assumption for implementation of Industry 4.0 concept in industrial company. Journal of Systems Integration.
Dassisti, M., Giovannini, A., Merla, P., Chimienti, M., & Panetto, H. (2018). An approach to support Industry 4.0 adoption in SMEs using a core-metamodel An approach to support Industry 4.0 adoption in SMEs: a core-metamodel and applications. In Annual Reviews in control. Elsevier. https://doi.org/10.1016/j.arcontrol.2018.11.001
De Carolis, A., Macchi, M., Negri, E., & Terzi, S. (2017). A maturity model for assessing the digital readiness of manufacturing companies. In H. Lödding, R. Riedel, K.-D. Thoben, G. von Cieminski, & D. Kiritsis (Eds.), Advances in production management systems. The path to intelligent, collaborative and sustainable manufacturing (pp. 13–20). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-66923-6_2
Dilberoglu, U. M., Gharehpapagh, B., Yaman, U., & Dolen, M. (2017). The role of additive manufacturing in the era of Industry 4.0. Procedia Manufacturing, 11, 545–554. https://doi.org/10.1016/j.promfg.2017.07.148
DIN. (2016). German standardization roadmap: Industry 4.0. German Standarization Roadmap Industry 4.0 Version 2, 77. http://www.din.de/blob/65354/f5252239daa596d8c4d1f24b40e4486d/roadmap-i4-0-e-data.pdf
Faller, C., & Feldmúller, D. (2015). Industry 4.0 learning factory for regional SMEs. In Procedia CIRP, 32, 88–91. https://doi.org/10.1016/j.procir.2015.02.117
Fettig, K., Gačić, T., Köskal, A., Kühn, A., & Stuber, F. (2018). Impact of Industry 4.0 on organizational structures. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1–8). https://doi.org/10.1109/ICE.2018.8436284
Ford, M. (2015). Industry 4.0: Who benefits? SMT: Surface Mount Technology, 30(7), 52–55.
Ganzarain, J., & Errasti, N. (2016a). Three stage maturity model in SME’s towards industry 4.0. Journal of Industrial Engineering and Management, 9(5), 1119–1128. https://doi.org/10.3926/jiem.2073
Ganzarain, J., & Errasti, N. (2016b). Three stage maturity model in SME’s towards Industry 4.0. Journal of Industrial Engineering and Management, 9(5), 1119–1128. https://doi.org/10.3926/jiem.2073
Gilchrist, A. (2016). Introducing Industry 4.0. In Industry 4.0 (pp. 195–215). https://doi.org/10.1007/978-1-4842-2047-4_13
Ginevičius, R., & Ostapenko, A. (2015). A quantitative evaluation of the company environment for the formation of its effective expansion strategy. Intelektine Ekonomika, 9(2). https://search.proquest.com/docview/1992363358?accountid=15518
Gubán, M., & Kovács, G. (2017). Industry 4.0 conception. Acta Technica Corviniensis – Bulletin of Engineering, 10(1), 111–114. https://search.proquest.com/docview/1869485942?accountid=15518
Harrington, D. (2008). Use of confirmatory factor analysis with multiple groups. Confirmatory Factor Analysis. Oxford Scholarship Online. https://doi.org/10.1093/acprof:oso/9780195339888.003.0005
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. https://doi.org/10.1016/j.compind.2017.04.002
Joreskog, K. G., & Sorbom, D. (2006). Recent developments in structural equation modeling. Journal of Marketing Research, 19(4), 404–416. https://doi.org/10.2307/3151714
Kopp, J., & Basl, J. (2017). Study of the readiness of Czech companies to the industry 4.0. Journal of Systems Integration, (3).
Lee, J., Bagheri, B., & Kao, H. A. (2015). A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23. https://doi.org/10.1016/j.mfglet.2014.12.001
Lee, J., Kao, H. A., & Yang, S. (2014). Service innovation and smart analytics for Industry 4.0 and big data environment. In Procedia CIRP, 16, 3–8. https://doi.org/10.1016/j.procir.2014.02.001
Li, L. (2017). China’s manufacturing locus in 2025: With a comparison of “Made-in-China 2025” and “Industry 4.0”. Technological Forecasting and Social Change, 135 (October 2018), 66–74. https://doi.org/10.1016/j.techfore.2017.05.028
Long, F., Zeiler, P., & Bertsche, B. (2016). Modelling the production systems in industry 4.0 and their availability with high-level Petri nets. IFAC-PapersOnLine, 49(12), 145–150. https://doi.org/10.1016/j.ifacol.2016.07.565
Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1–10. https://doi.org/10.1016/j.jii.2017.04.005
Meissner, H., Ilsen, R., & Aurich, J. C. (2017). ScienceDirect Analysis of control architectures in the context of Industry 4.0. Procedia CIRP, 62, 165–169. https://doi.org/10.1016/j.procir.2016.06.113
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. https://doi.org/10.1016/j.jmsy.2018.10.005
Morteza, G. (2019, January 1). Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing. F. Masood (Ed.). Journal of Manufacturing Technology Management, 31(1), 1–30. https://doi.org/10.1108/JMTM-11-2018-0417
Mrugalska, B., & Wyrwicka, M. K. (2017). Towards lean production in industry 4.0. In Procedia Engineering, 182, 466–473. https://doi.org/10.1016/j.proeng.2017.03.135
Müller, J. M., Buliga, O., & Voigt, K.-I. (2017). Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0. Technological Forecasting and Social Change, 132 (July 2018), 2–17. https://doi.org/10.1016/j.techfore.2017.12.019
Müller, 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. https://doi.org/10.1016/j.techfore.2017.12.019
Oesterreich, T. D., & Teuteberg, F. (2016). Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry. Computers in Industry, 83 (December 2016), 121–139. https://doi.org/10.1016/j.compind.2016.09.006
Oreoluwa, R. (2011). Small and medium scale enterprises and economic growth in Nigeria: An assessment of financing options. Pakistan Journal of Business and Economic Review, 2(1).
Petrasch, R., & Hentschke, R. (2016). Process modeling for industry 4.0 applications: Towards an industry 4.0 process modeling language and method. In 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016. Khon Kaen, Thailand. https://doi.org/10.1109/JCSSE.2016.7748885
Pfohl, H.-C., Yahsi, B., & Kuznaz, T. (2015). The impact of Industry 4.0 on the supply chain. Proceedings of the Hamburg International Conference of Logistic (HICL)-20, (August), 32–58.
Phillips, P., & Raby, S. (2017). Small and medium-sized enterprises. In Contemporary Issues in Strategic Management. https://doi.org/10.4324/9781315674827
Porter, M. E., & Kramer, M. R. (2006). Strategy & society: The link between competitive advantage and corporate social responsibility. Harvard Business Review. https://doi.org/10.1108/sd.2007.05623ead.006
Rigdon, E. E., & Hoyle, R. H. (2006). Structural equation modeling: concepts, issues, and applications. Journal of Marketing Research, 34(3), 412–415. https://doi.org/10.2307/3151904
Rodič, B. (2017). Industry 4.0 and the new simulation modelling paradigm. Organizacija, 50(3), 193–207. https://doi.org/10.1515/orga-2017-0017
Sanders, A., Elangeswaran, C., & Wulfsberg, J. (2016). Industry 4.0 implies lean manufacturing: Research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management, 9(3), 811–833. https://doi.org/10.3926/jiem.1940
Schönsleben, P., Fontana, F., & Duchi, A. (2017). What benefits do initiatives such as industry 4.0 offer for production locations in high-wage countries? In Procedia CIRP, 63, 179–183. https://doi.org/10.1016/j.procir.2017.03.356
Schumacher, A., Erol, S., & Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia CIRP, 52, 161–166. https://doi.org/10.1016/j.procir.2016.07.040
Senvar, O., & Akkartal, E. (2018). An overview to industry 4.0. International Journal of Information, Business and Management, 10(4), 50–57. https://search.proquest.com/docview/2110240866?accountid=15518
Sevinç, A., Gür, Ş., & Eren, T. (2018). Analysis of the difficulties of SMEs in industry 4.0 applications by analytical hierarchy process and analytical network process. Processes, 6(12). https://doi.org/10.3390/pr6120264
Shamim, S., Cang, S., Yu, H., & Li, Y. (2016). Management approaches for Industry 4.0: A human resource management perspective. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016. https://doi.org/10.1109/CEC.2016.7748365
Sivathanu, B., & Pillai, R. (2018). Smart HR 4.0 – how industry 4.0 is disrupting HR. Human Resource Management International Digest. https://doi.org/10.1108/HRMID-04-2018-0059
Sung, T. K. (2018). Industry 4.0: A Korea perspective. Technological Forecasting and Social Change, 132, 40–45. https://doi.org/10.1016/j.techfore.2017.11.005
Taiwo, M. A., Ayodeji, A. M., & Yusuf, B. A. (2018). Impact of small and medium enterprises on economic growth and development. American Journal of Business and Management, 1(1), 18–22. https://doi.org/10.11634/21679606170644
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, 7(3). https://doi.org/10.3390/pr7030153
Van Scoter, D. J. (2011). Enterprise system implementation projects: A study of the impact of contextual factors on critical success factors. ProQuest Dissertations and Theses. Oregon State University, Ann Arbor. https://search.proquest.com/docview/919055934?accountid=15518
Vrchota, J., Volek, T., & Novotná, M. (2019). Factors Introducing Industry 4.0 to SMES. Social Sciences, 8(5), 130. https://doi.org/10.3390/socsci8050130
Wagner, T., Herrmann, C., & Thiede, S. (2017). Industry 4.0 Impacts on lean production systems. In Procedia CIRP, 63, 125–131. https://doi.org/10.1016/j.procir.2017.02.041
Wee, D., Kelly, R., Cattel, J., & Breunig, M. (2015). Industry 4.0 – how to navigate digitization of the manufacturing sector. McKinsey & Company, 1–62. https://doi.org/10.1007/s13398-014-0173-7.2
Wiersema, M. F., & Bantel, K. A. (1992). Top management team demography and corporate strategic change. Academy of Management Journal. https://doi.org/10.5465/256474
Wood, P. (2008). Confirmatory factor analysis for applied research. The American Statistician, 62(1). https://doi.org/10.1198/tas.2008.s98
Zhou, K., Liu, T., & Zhou, L. (2016). Industry 4.0: Towards future industrial opportunities and challenges. In 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015 (pp. 2147–2152). https://doi.org/10.1109/FSKD.2015.7382284
Zwikael, O., & Globerson, S. (2006). From critical success factors to critical success processes. International Journal of Production Research, 44(17), 3433. https://doi.org/10.1080/00207540500536921