Economics at your fingertips  

The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0

Giovanna Culot, Guido Orzes, Marco Sartor and Guido Nassimbeni

Technological Forecasting and Social Change, 2020, vol. 157, issue C

Abstract: Industry 4.0 is expected to impart profound changes to the configuration of manufacturing companies with regards to what their value proposition will be and how their production network, supplier base and customer interfaces will develop. The literature on the topic is still fragmented; the features of the emerging paradigm appear to be a contested territory among different academic disciplines. This study assumes a value chain perspective to analyze the evolutionary trajectories of manufacturing companies. We developed a Delphi-based scenario analysis involving 76 experts from academia and practice. The results highlight the most common expectations as well as controversial issues in terms of emerging business models, size, barriers to entry, vertical integration, rent distribution, and geographical location of activities. Eight scenarios provide a concise outlook on the range of possible futures. These scenarios are based on four main drivers which stem from the experts’ comments: demand characteristics, transparency of data among value chain participants, maturity of additive manufacturing and advanced robotics, and penetration of smart products. Researchers can derive from our study a series of hypotheses and opportunities for future research on Industry 4.0. Managers and policymakers can leverage the scenarios in long-term strategic planning.

Keywords: Industry 4.0; Value chain; Scenario planning; Delphi study; Customization; Servitization (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.techfore.2020.120092

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2020-10-10
Handle: RePEc:eee:tefoso:v:157:y:2020:i:c:s0040162520309185