Backshoring and improved key manufacturing resources in firms’ home location

Abstract

This research explores the influence on manufacturing backshoring of improved key manufacturing resources in the home location of firms. Analysis of recent cases of backshoring in the European manufacturing industry shows that the production processes of firms that have backshored to their home location offer greater optimisation in terms of workforce, are more production assets intensive and have a higher technological level than when they offshored. The results highlight the relevance of internal factors in manufacturing backshoring analysis. This is of special interest from a production systems perspective because it is these internal factors that managers can control and therefore gain decision-making power regarding the location of manufacturing activities. This study also contributes to the debate on how innovations and improvements in manufacturing processes could increase industrial production and employment in advanced economies.

Keywords:

• Backshoring
• reshoring
• manufacturing location
• European manufacturing industry

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The European Foundation for the improvement of living and working conditions (Eurofound) was established by Council Regulation (EEC) No 1365/75 to contribute to the planning and establishment of better living and working conditions through activities designed to increase and disseminate knowledge.

2 Although the databases have been created by the same team using the same methodology and a common format that allows events in both to be related, and our criteria for profiling the samples have been the same for both databases (time period and number of affected workers), using distinct databases could be a source of uncertainty for the reliability of the results. In our case, this uncertainty stems from 4 of the 61 cases of backshoring held in the European Reshoring Monitor, which does not contain information on the year of prior offshoring, but which the European Restructuring Monitor presents as offshoring processes in different years for the 2007–2018 period analysed. So that this does not affect the reliability of results, we have selected as the year for prior offshoring for these 4 cases that in which the values for the analysed variables –process optimisation, capital intensity and technological level- were greatest. This guarantees that if a different year were used for these 4 cases, the variable values would favour the results already obtained that confirm the hypothesis proposed in our research.

3 Further research avenues include the need to differentiate between strategic backshoring and reaction to failure (Müller, Dotzauer, and Voigt 2017). In this respect, Bals, Kirchoff, and Foerstl (2016) suggested analysing cases of mistake correction separately.

4 The databases (see appendix) contain the dates when implementation was announced, started and finished for both the backshoring and its prior offshoring processes. The times used in our research to gather the data and calculate the formulas are those referring to the year immediately before the implementation of each process. That way we guarantee that the values of the variables are not partially affected by the process implementation and thus give a real view of the situation prior to starting the backshoring and offshoring processes.

5 This process was carried out in order to compare variables that have scales or units with different measurements (Milligan and Cooper 1988), as in our case. This standardisation aims to enable a comparison of the influence of each independent variable according to the values for the regression coefficients obtained for each of these variables (Lampón, Cabanelas, and Carballo 2017). In our case, the standardised variable z is calculated for each variable x, as z = (x – m)/ s. Where m is the arithmetical mean and s the standard deviation of variable x.