Relocation of second degree: Moving towards a new place or returning home?

A hybrid fuzzy-AHP-TOPSIS model for evaluation of manufacturing relocation decisions

Manufacturing relocation decisions are complex because they involve combinations of location modes like offshoring or reshoring, and governance modes like insourcing or outsourcing. Furthermore, the uncertainty involved in the decision-making process makes it challenging to reach a right-shoring decision. This study presents a hybrid fuzzy-AHP-TOPSIS model to support generic relocation decisions. Industry experts were involved in a pairwise comparison of the competitive priorities’ decision criteria. A meta-synthesis of empirical studies is used to generate theoretical relocation scenarios. The presented hybrid model is used to rank the relocation scenarios in order to identify the most pertinent alternative. The resiliency of the solution is presented through a sensitivity analysis. The results indicate that the proposed hybrid model can simultaneously handle all the main relocation options involving governance modes. Based on the input data in this study, the competitive priorities criteria quality, time and cost are shown to have a strong impact, whereas the sustainability criterion has a weak impact on the choice of relocation option. The research presented in this paper contributes to the research field of manufacturing relocation by demonstrating the suitability of the hybrid fuzzy-AHP-TOPSIS model for relocation decisions and the resilience of the results. Furthermore, the research contributes to practice by providing managers with a generic relocation decision-support model that is capable of simultaneously handling and evaluating various relocation alternatives.

Antecedents and enablers of supply chain reconfigurability and their effects on performance

The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as the COVID-19 pandemic, demand uncertainty, and new technologies. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability, and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using "Matrice d'Impacts Croisés, Multiplication Appliquée à un Classement" (MICMAC) analysis. This article provides a better understanding of the six characteristics previously mentioned to improve the reconfigurability of supply chains by considering the interactions between their factors. Thus, this analysis helps managers to understand the characteristics that influence the change of the supply chain structure and those that enable changing the supply chain functions in order to optimize the supply chain reconfiguration process.

Covid-19 attacks the body of purchasing and supply management: A medical check of the immune system

Much like the immune system of the body, the ‘immune system’ of purchasing and supply management (PSM) is also affected by the Covid-19 virus. Medicine must hinder the spread of the virus and outbreak of disease, just as PSM must prevent risk events and handle supply disruptions. The existing debate on supply resilience and robustness can be demonstrated using this medical analogy. The purpose of this article was to perform a medical check of the ‘PSM immune system’ to identify lessons and research gaps when confronted with a low-frequency-high-impact event such as the pandemic. As a provocative note, this article identifies research gaps in elements of the immune system of PSM (e.g., helper cells – consultancy support or memory cells – feedback loops). The results call for a more holistic debate on the immune system of PSM. Two approaches for research on ‘conventional’ or ‘alternative’ risk management schools of thought are presented as a basis for future discourse on how to improve the PSM immune system.

Doing the right thing or doing things right: what is better for a successful manufacturing reshoring?

The article concerns the revision of earlier decisions to offshore production activities (so called “relocation of second degree”); more specifically it is focused on the “reshoring” (also referred as “relocation to the home country”, “back-reshoring” or “back-shoring”). The research aims are to investigate what types of mistakes occur along the decision-making and implementation process and how they affect the outcome, in terms of success or failure, of a relocation strategy. A multiple case study involving four companies in the fashion industry from Portugal and Italy was conducted. The cross-case analysis allowed to differentiate decision-making mistakes from implementation ones and to assess differences and similarities among the cases in terms of content of the relocation, drivers and outcomes. The research contributes to previous literature on reshoring by bringing evidence of different types of mistakes to be considered, thus requiring further conceptualization of the reshoring process. Managers and entrepreneurs should consider the importance of doing the things right also during the implementation, too often underestimated. The present article is the first one in the reshoring literature bringing evidence of cases of failure in the relocation decisions and discriminating among different kinds of mistakes.

Back-shoring vs near-shoring: a comparative exploratory study in the footwear industry

After decades of off-shoring strategies, companies are often critically re-evaluating their earlier location decisions; in doing so, sometimes they implement the so-called relocation of second degree. Among them, back-shoring (i.e., relocation to the home country) and near-shoring (relocation to the home region) are two of the alternatives attracting growing interest from scholars. This paper aims to shed new light on the variables influencing the choice made between these two alternatives. As requested in the extant literature, a contingency approach is adopted, focusing attention on the footwear industry. Given the exploratory nature of the paper, evidence from 41 back-shoring and near-shoring strategies are analysed, comparing data from Spanish and Italian companies. Collected data are adapted to test hypotheses concerning three sets of variables: firms’ characteristics, motivations for the second degree relocation and its barriers. Collected data show that firm’s size directly influences the chosen alternative since larger companies prefer to near-shore instead of back-shore. When considering motivations, while the “made in” effect does not influence the firm’s choice, availability of skilled contractors and/or government aids induces companies to relocate to the home country instead of the home region. Finally, companies fearing encountering barriers, in terms of skilled contractors’ availability and/or (re-)development of internal manufacturing competences, will prefer the back-shoring rather than the near-shoring option. The study is focused on two countries (Spain and Italy) where the manufacturing sector (and the footwear industry within it) is still relevant to the local economy. Findings cannot be generalized to countries/industries where the local industry has been totally dismantled, without a previous in-depth analysis. The findings obtained offer managers useful insights on the elements that should be carefully evaluated when considering back- and near-shore alternatives. Additionally, valuable insights are provided for policy makers that plan to design industrial policies supporting back-reshoring policy initiatives. To the best of our knowledge, this is the first paper in the extant literature addressing variables influencing the choice between back- and near-shoring alternatives.