Artificial Intelligence and Backshoring Strategies: A German-Italian Comparison

Artificial Intelligence and Backshoring Strategies: A German-Italian Comparison

Steffen Kinkel (Karlsruhe University of Applied Sciences, Germany), Mauro Capestro (University of Padova, Italy) and Eleonora Di Maria (University of Padova, Italy)
DOI: 10.4018/978-1-7998-5077-9.ch013

Abstract

The Industry 4.0 technologies, such as artificial intelligence (AI), are transforming the manufacturing processes and affecting the location of manufacturing activities across countries, with a potentially positive impact on the backshoring of production processes. The chapter aims at providing empirical evidence on the relationship between AI and relocation, exploring how AI is related to both the offshoring and backshoring strategies, using data from an international sample of 124 German and Italian manufacturing companies. Following the investigation of AI use by German and Italian manufacturing companies, the study analyses the differences in some strategic factors and the offshoring and backshoring decisions between German and Italian companies, AI users and non-users, and between the German and Italian AI users. Results show that the most important differences concern AI users and non-users and indicate a higher value of AI use for backshoring rather than offshoring strategies. The findings enable the derivation of both theoretical and managerial contributions.
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Introduction

In the last decades, acting globally has become a strategic choice not only for multinational companies, but also for small and medium-sized Enterprises (SMEs) that are getting more involved in the global arena (Ancarani, Di Mauro, Fratocchi, Orzes, & Sartor, 2015; Gray, Esenduran, Rungtusanatham, & Skowronski, 2017). In addition to the entry in new markets, SMEs have also started to offshore the production processes abroad, especially in the low-cost countries to benefit of lower labor costs (MacCarthy & Atthirawong, 2003). However, other studies show that cost-driven offshoring decisions are not always based on solid reflections (Kinkel, Lay, & Maloca, 2007). Despite the key role of production offshoring, in these last years also backshoring has received growing attention in the academic literature as well as by policy-makers (Di Mauro, Fratocchi, Orzes, & Sartor, 2018; Kinkel, 2012; Stentoft, Olhager, Heikkilä, & Thoms, 2016b). Research studies link these strategies to the lack of quality and flexibility of low-cost countries, a narrowing gap in labor costs and too high co-ordination and transportation costs (Ancarani & Di Mauro, 2018).

In addition to these important factors, another key driver of the relocation strategies is coming at the centre of the attention of firms: the new technologies connected to the Industry 4.0 paradigm. Such new technologies – from 3D printing to automation – are enabling firms to re-organize the manufacturing processes as well as the relationships along value chain (Agostini & Filippini, 2019). On the one hand, the use of the Industry 4.0 technologies leads to technological and organizational ownership advantages that enable companies to exploit them in all attractive markets, stimulating FDI and thus offshoring activities. On the other hand, the new technologies may have a positive effect also on the backshoring strategies as they allow firm exploiting the potential of home-based resources and of higher productivity and flexibility (Ancarani, Di Mauro, & Mascali, 2019; Dachs, Kinkel, & Jäger, 2019a). As far as the international strategies are concerned, new research is pointing to the potential transformation that Industry 4.0 technologies can have on the reshoring and backshoring strategies because of the positive impact they have on quality, productivity and flexibility (Alcácer, Cantwell, & Piscitello, 2016). The new technologies opportunities in terms of backshore are strategically essential for the developed manufacturing countries, such as Germany and Italy that in the past have offshored a large part of their production activities (Bortolini, Ferrari, Gamberi, Pilati, & Faccio, 2017; Kinkel, 2014).

Key Terms in this Chapter

Industry 4.0 Paradigm: Integration of manufacturing operations systems and information technologies to create the so-called Cyber-Physical Systems that enables companies to have flexible manufacturing processes and to analyze large amounts of data in real time, improving strategic and operational decision-making.

Digital Strategy: The company strategic plan that focus on the use of digital resources, such as technologies, digital skills, and capabilities to achieve one or more business goals and to improve business performance.

Cross-Country Analysis: The comparison of some specific units of analysis (in this case companies) across, at least, two countries. It aims to capture differences and similarities respect to the variables analyzed.

Backshoring: The decision to relocate manufacturing activities, previously moved abroad, back to the home country of the parent company.

Offshoring: Relocation of production and other value chain activities to a foreign location. These strategies required production and manufacturing processes to be sliced up into smaller segments and to be coordinated by the lead firm.

Artificial Intelligence: A system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.

Manufacturing Industries: The branch of manufacture and trade based on the fabrication, processing, and/or preparation of products from raw materials and commodities.

Competitive Factors: Company’s features or benefits considered keys or essentials for the creation and sustaining of the company’s competitive advantage and position in an industry or market. They could be related to the company’s production and other business processes, to the products and/or to the services offered to the markets.

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