Abstract
With the diffusion of Industry 4.0, manufacturing firms can decentralize their operational decisions and enable real-time data-driven decision-making. Using a socio-technical approach and the manufacturing shop-floor as a unit of analysis, this article studies the changes induced by digitalization on operational decision-making, organizational structures, and individual competencies. A cross-country multiple case study conducted in the automotive sector suggests three main areas on which firms have to focus: decentralized data-driven decision-making, front-line managers’ upskilling, and production workers’ involvement. The successful implementation of digitalization and the actual decentralization of decision-making depend on individual factors related to the competencies of front-line managers, who acquire a central role in this skill-biased technological and organizational change.
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References
Agostini, L., Filippini, R.: Organizational and managerial challenges in the path toward Industry 4.0. Eur. J. Innov. Manag. 22(3), 406–421 (2019)
Almada-Lobo, F.: The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES). J. Innov. Manag. 3(4), 16–21 (2015)
Appio, F.P., Frattini, F., Petruzzelli, A.M., Neirotti, P.: Digital transformation and innovation management: a synthesis of existing research and an agenda for future studies. J. Prod. Innov. Manag. 38(1), 4–20 (2021)
Bostrom, R.P., Heinen, J.S.: MIS problems and failures: a socio-technical perspective Part I: the causes. MIS Quart. 1(3), 17 (1977)
Cagliano, R., Canterino, F., Longoni, A., Bartezzaghi, E.: The interplay between smart manufacturing technologies and work organization. Int. J. Oper. Prod. Manag. 39(6/7/8), 913–934 (2019)
Colombari, R., Neirotti, P.: Closing the middle-skills gap widened by digitalization: how technical universities can contribute through Challenge-Based Learning. Stud. Higher Educ. 1–16 (2021)
Colombari, R., et al.: The interplay between data-driven decision-making and digitalization: a firm-level survey of the Italian and U.S. automotive industries. Int. J. of Prod. Economics 255, 108718 (2023)
Creswell, J.W., Poth, C.N.: Qualitative Inquiry & Research Design: Choosing Among Five Approaches, 4th edn. Sage, Los Angeles (2018)
Culot, G., Nassimbeni, G., Orzes, G., Sartor, M.: Behind the definition of Industry 4.0: analysis and open questions. Int. J. Prod. Econ. 226, 107617 (2020)
Gioia, D.A., Corley, K.G., Hamilton, A.L.: Seeking qualitative rigor in inductive research. Organ. Res. Methods 16(1), 15–31 (2013)
Gupta, V., Acharya, P., Patwardhan, M.: A strategic and operational approach to assess the lean performance in radial tyre manufacturing in India. Int. J. Product. Perform. Manag. 62(6), 634–651 (2013)
King, N.: Using templates in the thematic analysis of text. In: Cassels, C., Symon, G. (eds.) Essential Guide to Qualitative Methods in Organizational Research, pp. 256–270. Sage, London (2004)
Lavalle, S., Lesser, E., Shockley, R., Hopkins, M., Kruschwitz, N.: Big data, analytics and the path from insights to value. MIT Sloan Manag. Rev. 52(5), 21–32 (2011)
Mavrikios, D., Papakostas, N., Mourtzis, D., Chryssolouris, G.: On industrial learning and training for the factories of the future: a conceptual, cognitive and technology framework. J. Intell. Manuf. 24(3), 473–485 (2013)
Parker, S.K., Grote, G.: Automation, algorithms, and beyond: why work design matters more than ever in a digital world. Appl. Psychol. 71(4), 1171–1204 (2020)
Piva, M., Santarelli, E., Vivarelli, M.: The skill bias effect of technological and organisational change: evidence and policy implications. Res. Policy 34(2), 141–157 (2005)
Sung, T.K.: Industry 4.0: a Korea perspective. Technol. Forecast. Soc. Chang. 132, 40–45 (2018)
Trist, E.L., Bamforth, K.W.: Some social and psychological consequences of the longwall method of coal-getting. Hum. Rel. 4(1), 3–38 (1951)
Veile, J.W., Kiel, D., Müller, J.M., Voigt, K.I.: Lessons learned from Industry 4.0 implementation in the German manufacturing industry. J. Manuf. Technol. Manag. 31(5), 977–997 (2020)
Wilkesmann, M., Wilkesmann, U.: Industry 4.0–organizing routines or innovations? VINE J. Inf. Knowl. Manag. Syst. 48(2), 238–254 (2018)
Yin, R.K.: Case Study Research: Design and Methods. Sage Publications, Thousand Oaks, Calif (2003)
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Colombari, R., Berbegal Mirabent, J., Neirotti, P. (2024). The Impact of Digitalization on Production Management Practices: A Multiple Case Study. In: Bautista-Valhondo, J., Mateo-Doll, M., Lusa, A., Pastor-Moreno, R. (eds) Proceedings of the 17th International Conference on Industrial Engineering and Industrial Management (ICIEIM) – XXVII Congreso de Ingeniería de Organización (CIO2023). CIO 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-031-57996-7_44
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