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Artificial intelligence and relocation of production activities: An empirical cross-national study

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  • Kinkel, Steffen
  • Capestro, Mauro
  • Di Maria, Eleonora
  • Bettiol, Marco

Abstract

Artificial intelligence (AI) is considered the next strategic technological imperative as it allows firms to manage complex tasks and to solve problems in many industries. In the manufacturing context, the use of AI is affecting the configuration of production processes with possible effects on the location of production activities. Despite the increasing relevance of this technology, there is a lack of empirical evidence that assesses the linkage with the firm's production relocation strategies. To fill this gap, this study aims at exploring the relationship between the use of AI and companies' offshoring and backshoring decisions, taking into account the moderating role of digital competences and the intended internationalisation strategies. Based on a cross-national survey with answers from 676 manufacturing companies from 16 industrialized countries, a hierarchical regression analysis was deployed that shows a positive effect of AI on companies' offshoring and backshoring decisions. Moreover, the results show that digital competences and international ambidexterity (simultaneous expansion of business and supply chain activities in domestic and foreign locations) only have a moderation effect on the relationship between AI and backshoring. International concentration (locating business activities in only a few local or global locations) does not moderate the relationship between AI and production relocation strategies (offshoring or backshoring). To advance the theoretical debate on the use of AI and its impact on production relocation strategies, three research propositions are proposed. Finally, some practical implications and the study's limitations are highlighted.

Suggested Citation

  • Kinkel, Steffen & Capestro, Mauro & Di Maria, Eleonora & Bettiol, Marco, 2023. "Artificial intelligence and relocation of production activities: An empirical cross-national study," International Journal of Production Economics, Elsevier, vol. 261(C).
    • Handle: RePEc:eee:proeco:v:261:y:2023:i:c:s0925527323001226
    DOI: 10.1016/j.ijpe.2023.108890
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