IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v196y2023ics0040162523005322.html
   My bibliography  Save this article

Implementing Industry 4.0 technologies: Future roles in purchasing and supply management

Author

Listed:
  • Delke, Vincent
  • Schiele, Holger
  • Buchholz, Wolfgang
  • Kelly, Stephen

Abstract

Technological advancements associated with Industry 4.0 drive a paradigm shift with economic and social consequences where digitalization, robotization, and other emerging technologies reshape the interconnection between organizations. Critical areas that need to adapt to the change are inter-organizational buyer-supplier relationships managed by Purchasing and Supply Management (PSM) professionals. That is, their future responsibilities and skills are likely to change. Introducing the concept of specialized roles to summarize needed competencies, this research conducted a real-time Delphi study using an internet-based platform involving 47 procurement experts. As a result, the roles of the Data Analyst, Master Data Manager, Process Automation Manager, Supplier Onboarding Manager, System Innovation Scout, and Legislation Specialist were identified as essential Industry 4.0 PSM roles. For these roles, the probability of their occurrence, industry impact, desirability, and level of industry adoption are assessed. Based on emerging technologies in PSM and adopting a human-centered perspective, this research shows the need to focus on talent development to enable a technology-driven revolution. Thus, the contributions lay in the literature on Industry 4.0 and the PSM skills and capabilities domain, highlighting the required roles for Smart Working and effective Smart Supply Chains management as parts of the digital transformation journey.

Suggested Citation

  • Delke, Vincent & Schiele, Holger & Buchholz, Wolfgang & Kelly, Stephen, 2023. "Implementing Industry 4.0 technologies: Future roles in purchasing and supply management," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005322
    DOI: 10.1016/j.techfore.2023.122847
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523005322
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122847?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Winkler, Jens & Kuklinski, Christian Paul Jian-Wei & Moser, Roger, 2015. "Decision making in emerging markets: The Delphi approach's contribution to coping with uncertainty and equivocality," Journal of Business Research, Elsevier, vol. 68(5), pages 1118-1126.
    2. C. Gopinath & Richard C. Hoffman, 1995. "The Relevance of Strategy Research: Practitioner and Academic Viewpoints," Journal of Management Studies, Wiley Blackwell, vol. 32(5), pages 575-594, September.
    3. Toorajipour, Reza & Sohrabpour, Vahid & Nazarpour, Ali & Oghazi, Pejvak & Fischl, Maria, 2021. "Artificial intelligence in supply chain management: A systematic literature review," Journal of Business Research, Elsevier, vol. 122(C), pages 502-517.
    4. Müller, Julian Marius & Buliga, Oana & Voigt, Kai-Ingo, 2018. "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 2-17.
    5. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    6. Vincent Delke & Holger Schiele & Wolfgang Buchholz, 2023. "Differentiating between direct and indirect procurement: roles, skills, and Industry 4.0," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 16(1), pages 1-30.
    7. Meindl, Benjamin & Ayala, Néstor Fabián & Mendonça, Joana & Frank, Alejandro G., 2021. "The four smarts of Industry 4.0: Evolution of ten years of research and future perspectives," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    8. Chiarello, Filippo & Fantoni, Gualtiero & Hogarth, Terence & Giordano, Vito & Baltina, Liga & Spada, Irene, 2021. "Towards ESCO 4.0 – Is the European classification of skills in line with Industry 4.0? A text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    9. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    10. Laurence Viale & Dorsaf Zouari, 2020. "Impact of digitalization on procurement: the case of robotic process automation," Post-Print hal-03695535, HAL.
    11. Pekkanen, Petra & Niemi, Petri & Puolakka, Tiina & Pirttilä, Timo & Huiskonen, Janne, 2020. "Building integration skills in supply chain and operations management study programs," International Journal of Production Economics, Elsevier, vol. 225(C).
    12. Aengenheyster, Stefan & Cuhls, Kerstin & Gerhold, Lars & Heiskanen-Schüttler, Maria & Huck, Jana & Muszynska, Monika, 2017. "Real-Time Delphi in practice — A comparative analysis of existing software-based tools," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 15-27.
    13. Vos, Frederik G.S. & Schiele, Holger & Hüttinger, Lisa, 2016. "Supplier satisfaction: Explanation and out-of-sample prediction," Journal of Business Research, Elsevier, vol. 69(10), pages 4613-4623.
    14. Marco Ardolino & Mario Rapaccini & Nicola Saccani & Paolo Gaiardelli & Giovanni Crespi & Carlo Ruggeri, 2018. "The role of digital technologies for the service transformation of industrial companies," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2116-2132, March.
    15. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    16. Kahle, Júlia Hofmeister & Marcon, Érico & Ghezzi, Antonio & Frank, Alejandro G., 2020. "Smart Products value creation in SMEs innovation ecosystems," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    17. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    18. Rowe, Gene & Wright, George, 1996. "The impact of task characteristics on the performance of structured group forecasting techniques," International Journal of Forecasting, Elsevier, vol. 12(1), pages 73-89, March.
    19. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Frank Werner & Marina Ivanova, 2016. "A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 386-402, January.
    20. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    21. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    22. Li Da Xu & Eric L. Xu & Ling Li, 2018. "Industry 4.0: state of the art and future trends," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 2941-2962, April.
    23. Holger Schiele & Robbert-Jan Torn, 2020. "Cyber-physical systems with autonomous machine-to-machine communication: Industry 4.0 and its particular potential for purchasing and supply management," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 13(4), pages 507-530.
    24. Chang, Shuchih Ernest & Chen, Yi-Chian & Lu, Ming-Fang, 2019. "Supply chain re-engineering using blockchain technology: A case of smart contract based tracking process," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 1-11.
    25. Xu, Liming & Mak, Stephen & Brintrup, Alexandra, 2021. "Will bots take over the supply chain? Revisiting agent-based supply chain automation," International Journal of Production Economics, Elsevier, vol. 241(C).
    26. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    27. Förster, Bernadette & von der Gracht, Heiko, 2014. "Assessing Delphi panel composition for strategic foresight — A comparison of panels based on company-internal and external participants," Technological Forecasting and Social Change, Elsevier, vol. 84(C), pages 215-229.
    28. Frank, Alejandro Germán & Dalenogare, Lucas Santos & Ayala, Néstor Fabián, 2019. "Industry 4.0 technologies: Implementation patterns in manufacturing companies," International Journal of Production Economics, Elsevier, vol. 210(C), pages 15-26.
    29. Kouhizadeh, Mahtab & Saberi, Sara & Sarkis, Joseph, 2021. "Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers," International Journal of Production Economics, Elsevier, vol. 231(C).
    30. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    31. Legenvre, Hervé & Gualandris, Jury, 2018. "Innovation sourcing excellence: Three purchasing capabilities for success," Business Horizons, Elsevier, vol. 61(1), pages 95-106.
    32. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    33. George Baryannis & Sahar Validi & Samir Dani & Grigoris Antoniou, 2019. "Supply chain risk management and artificial intelligence: state of the art and future research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2179-2202, April.
    34. Andrew Kusiak, 2018. "Smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 508-517, January.
    35. Benzidia, Smaïl & Makaoui, Naouel & Subramanian, Nachiappan, 2021. "Impact of ambidexterity of blockchain technology and social factors on new product development: A supply chain and Industry 4.0 perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    36. Benzidia, Smail & Makaoui, Naouel & Bentahar, Omar, 2021. "The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    37. Juan Manuel Maqueira & José Moyano-Fuentes & Sebastián Bruque, 2019. "Drivers and consequences of an innovative technology assimilation in the supply chain: cloud computing and supply chain integration," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2083-2103, April.
    38. Frank, Alejandro G. & Mendes, Glauco H.S. & Ayala, Néstor F. & Ghezzi, Antonio, 2019. "Servitization and Industry 4.0 convergence in the digital transformation of product firms: A business model innovation perspective," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 341-351.
    39. Han, Hui & Trimi, Silvana, 2022. "Towards a data science platform for improving SME collaboration through Industry 4.0 technologies," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    40. Knight, Louise & Tu, Yi-Hsi & Preston, Jude, 2014. "Integrating skills profiling and purchasing portfolio management: An opportunity for building purchasing capability," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 271-283.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    2. Münch, Christopher & Marx, Emanuel & Benz, Lukas & Hartmann, Evi & Matzner, Martin, 2022. "Capabilities of digital servitization: Evidence from the socio-technical systems theory," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    3. Benitez, Guilherme Brittes & Ghezzi, Antonio & Frank, Alejandro G., 2023. "When technologies become Industry 4.0 platforms: Defining the role of digital technologies through a boundary-spanning perspective," International Journal of Production Economics, Elsevier, vol. 260(C).
    4. Meindl, Benjamin & Ayala, Néstor Fabián & Mendonça, Joana & Frank, Alejandro G., 2021. "The four smarts of Industry 4.0: Evolution of ten years of research and future perspectives," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    5. Kopyto, Matthias & Lechler, Sabrina & von der Gracht, Heiko A. & Hartmann, Evi, 2020. "Potentials of blockchain technology in supply chain management: Long-term judgments of an international expert panel," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    6. Marcon, Érico & Le Dain, Marie-Anne & Frank, Alejandro G., 2022. "Designing business models for Industry 4.0 technologies provision: Changes in business dimensions through digital transformation," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    7. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    8. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Bryde, David J. & Giannakis, Mihalis & Foropon, Cyril & Roubaud, David & Hazen, Benjamin T., 2020. "Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations," International Journal of Production Economics, Elsevier, vol. 226(C).
    9. Rodríguez-Espíndola, Oscar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel & Emrouznejad, Ali, 2022. "Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    10. Cannavacciuolo, Lorella & Ferraro, Giovanna & Ponsiglione, Cristina & Primario, Simonetta & Quinto, Ivana, 2023. "Technological innovation-enabling industry 4.0 paradigm: A systematic literature review," Technovation, Elsevier, vol. 124(C).
    11. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    12. Ricci, Riccardo & Battaglia, Daniele & Neirotti, Paolo, 2021. "External knowledge search, opportunity recognition and industry 4.0 adoption in SMEs," International Journal of Production Economics, Elsevier, vol. 240(C).
    13. Chiarello, Filippo & Fantoni, Gualtiero & Hogarth, Terence & Giordano, Vito & Baltina, Liga & Spada, Irene, 2021. "Towards ESCO 4.0 – Is the European classification of skills in line with Industry 4.0? A text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    14. Shet, Sateesh V. & Pereira, Vijay, 2021. "Proposed managerial competencies for Industry 4.0 – Implications for social sustainability," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    15. Gillani, Fatima & Chatha, Kamran Ali & Sadiq Jajja, Muhammad Shakeel & Farooq, Sami, 2020. "Implementation of digital manufacturing technologies: Antecedents and consequences," International Journal of Production Economics, Elsevier, vol. 229(C).
    16. Gebhardt, Maximilian & Spieske, Alexander & Birkel, Hendrik, 2022. "The future of the circular economy and its effect on supply chain dependencies: Empirical evidence from a Delphi study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    17. Tiberius, Victor & Hirth, Stefanie, 2019. "Impacts of digitization on auditing: A Delphi study for Germany," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 37(C).
    18. Peppel, Marcel & Ringbeck, Jürgen & Spinler, Stefan, 2022. "How will last-mile delivery be shaped in 2040? A Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    19. Pedota, Mattia & Grilli, Luca & Piscitello, Lucia, 2023. "Technology adoption and upskilling in the wake of Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    20. Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro G., 2020. "Industry 4.0 innovation ecosystems: An evolutionary perspective on value cocreation," International Journal of Production Economics, Elsevier, vol. 228(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005322. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.