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In the past decade, firms have become more aware of supply chain disruptions and their impact on the firm. Developing a supply chain resilience organizational culture has been proposed as an effective way to manage supply chain risks. This study intends to explore how the geographical location risks impact the decision to develop a supply chain resilience strategy, in particular, to anticipate the disruption proactively and have a business continuity plan in place. Using a unique database including thousands of manufacturing locations that belong to over 7,000 firms across 102 countries, we test three hypotheses to understand if geographical location risks, frequency of disruptive events, and the region in which a site is located are factors for the likelihood of a firm having a business continuity plan at their locations. The study also seeks to understand if there are regional effects and firm effects affecting the decision to develop resilience. With a particular focus in Latin America and the firms with a manufacturing presence in that region. The main findings of the study are that natural disaster risks do tend to develop a culture of resilience, while macroeconomic risks tend to do the opposite. These results remain stable for firms' effects. The Latin America region shows no observable statistical difference in developing resilience compared to the Asia region. While the Northern America region shows more resilience compared to Asia. We conclude that economic risk is less predictable and harder to develop a plan for than disruptions, such as natural disasters. The findings of this study present an opportunity for governments to develop resilience plans that can make their countries more attractive for investment to multinational firms looking to establish new manufacturing locations around the world.

Using insights from the supply chain resilience perspective and the international business literature, this study aims to investigate the determinants of firms’ decisions to reshore manufacturing under the high levels of uncertainty brought about by the ongoing US–China trade war and COVID-19 pandemic.

The proposed conceptual framework is tested using survey data collected from 702 Taiwanese firms with manufacturing in China. The firms were drawn from a database compiled by Taiwan’s Ministry of Economic Affairs.

The results show that two supply chain factors (tariffs and supply chain completeness) and two non-location-bound factors (labor cost and material cost) are critical determinants of the decision to reshore under uncertainty.

This research elucidates and empirically validates several factors that influence the reshoring decision in uncertain environments. The findings provide valuable theoretical, practical and strategic insights into how firms should manage their value chains in the post-COVID-19 era.

For many years, facilities location problems have attracted a great deal of attention in the literature. As a result, there is now a variety of methods for solving these problems. However, due to the recent interest, little research is found relating to the issues concerning international facilities location problems. Furthermore, in spite of the extensive modelling work done on facilities location, little modelling research exists on location problems. Provides a capacitated multi‐period, 0‐1 mixed integer programming formulation for the international facilities location problem and discusses its applications to an actual company case. This application is carried out to demonstrate not only how the model can be applied in practice but also to show its potential benefits when compared to other methods.

The purpose of this paper is to present recent empirical results concerning offshoring and backshoring of manufacturing from and to Sweden, to increase the understanding of manufacturing relocation in an international context. In particular, extent, geographies, type of production, drivers, and benefits of moving manufacturing in both directions are investigated.

The study is based on survey data from 373 manufacturing plants. The same set of questions is used for both offshoring and backshoring between 2010 and 2015, which allows similarities and differences in decision-making and results between the two relocation directions to be identified.

There are many significant differences between offshoring and backshoring projects. Labour cost is the dominating factor in offshoring, as driver and benefit, while backshoring is related to many drivers and benefits, such as quality, lead-time, flexibility, access to skills and knowledge, access to technology, and proximity to R&D. This is also reflected in the type of production that is relocated; labour-intensive production is offshored and complex production is backshored.

Plants that have both offshored and backshored think and act differently than plants that have only offshored or backshored, which is why it is important to distinguish between these plant types in the context of manufacturing relocations.

The experience of Swedish manufacturing plants reported here can be used as a point of reference for internal manufacturing operations.

The survey design allows a unique comparison between offshoring and backshoring activity. Since Swedish firms in general have been quite active in rearranging their manufacturing footprint and have experience from movements in both directions, it is an appropriate geographical area to study in this context.

The purpose of this paper is to investigate the extent, drivers, and conditions underlying backshoring in the Finnish manufacturing industry, comparing the results to the wider ongoing relocation of production in the international context.

The survey of 229 Finnish manufacturing firms reveals the background, drivers, and patterns of offshoring and backshoring.

Companies that had transferred their production back to Finland were more commonly in industries with relatively higher technology intensity and they were typically larger than the no-movement companies, and with a higher number of plants. They also reported more commonly having a corporate-wide strategy for guiding production location decisions.

Backshoring activity in the small and open economy of Finland seems to be higher compared to earlier studies in larger countries. The findings suggest that there is a transformation in the manufacturing industries with some gradual replacement of labor-intensive and lower technology-intensive industries toward higher technology-intensive industries.

Moving production across national borders is one option in the strategies of firms to stay competitive. Companies must carefully consider the relevance of various decision-making drivers when determining strategies for their production networks.

Manufacturing industries have traditionally been important for employment in the relatively small and open economies of the Nordic countries. From the social perspective, it is important to understand the ongoing transformation and its implications.

There are few empirical studies available of the ongoing backshoring movement, utilizing data from company decision makers instead of macroeconomic factors.

This research aims to provide a new perspective on the evolving linkages between LAs and FSAs in the context of the technology-based manufacturing industry. Firm-level competitive strengths in an international context build upon the combination of (largely) exogenous location advantages (LAs) and endogenous firm-specific advantages (FSAs). The authors focus especially on the decay of LAs over time, which has been observed in many highly developed countries during the past decades. The authors show how the strengthening of FSAs can substitute for decaying LAs, thereby safeguarding against the demise of entire industrial regions.

The authors examine the technology-based manufacturing industry in Belgium, building upon an analysis of survey responses by 66 firms including a subgroup of 26 multinational enterprise (MNE) subsidiaries. The professional association representing this industry in Belgium (Agoria) viewed the firms included in the survey as representative for Belgian technology-based manufacturing in terms of the LAs they presently build upon (or location disadvantages they face) and the internal strengths they command relative to (foreign) rivals. The investigation uncovered the decay of critical LAs in Belgium and in parallel, the rise of ‘compensating’ FSAs of Belgian operations relative to foreign firms, including, especially, MNE sister subsidiaries in other countries. The authors also conducted 23 in-depth interviews with senior level managers (CEOs and senior vice presidents) of technology-based firms, including 10 subsidiaries of foreign-owned MNEs, which validated our analysis of the interplay between LAs and FSAs.

The findings reveal that since inception, Belgian manufacturing operations experienced an overall decay in their critical LAs by 23% on average. Despite this, several Belgian subsidiaries of foreign MNEs consider themselves as commanding a resource-base superior to that of the next-best-in-class subsidiaries. Furthermore, when assessing the dynamic interplay between LAs and FSAs, there is some evidence that the decay of LAs fueled the quest for – and firm-level journey toward – stronger FSAs.

The originality of this study is the alternative perspective to the conventionally assumed “positive-positive” relationship between LAs and FSAs. Prior management research has not examined the impact of decaying LAs on new FSA-creation in the realm of technology-based manufacturing.

The purpose of this paper is to examine effects of regional economic integration on the concentration of manufacturing firms in provinces of Thailand on the border with Cambodia. It aims to clarify the interactions between dispersion and agglomeration forces within a firm’s location choice in the presence of economic integration and thereby to explain the feasibility of the border SEZs.

The theory of industrial clustering and New Economic Geography provides a theoretical framework to understand the locations of economic activities when regional economies are integrated. This paper employs provincial level data to calculate industry location quotients across a 10-year period from 2007 to 2017 in central Thailand and uses firm-level data from industrial censuses in 2006 and 2011 to estimate logit models for two border provinces with Cambodia and three eastern seaboard provinces. Two base models and extended models are tested to explain the persistent agglomeration of Thai firms in each manufacturing industry.

The authors found a positive correlation between the agglomeration level in 2006 and the choice of firms toward the border provinces in 2011. The disaggregated analysis shows that depending on the initial level of concentration in each industry, there can be agglomeration or dispersion effects. The advantage of low trade costs and labor costs of unskilled migrant workers are not significant factors attracting firms to the border. Firms in industries with increasing returns are more likely to stay in the hub.

The disaggregated analysis by industry provides very important implications for SEZ policy interventions. The important role of agglomeration economies limits the extent to which such policies can be successful. It would be an enormous challenge for policy makers to initiate forces which are strong enough to induce firms to relocate away from areas with high agglomerations. Policy interventions with attractive incentives should be very selective to industries already have a certain degree of concentration in the provinces so as to reinforce the agglomeration effects.

The research extends the empirical literature on SEZs by offering a unique case study of an emerging economy with a strong market foundation rather than a transitional or developed economy. It is also different from other research on SEZs when taking into account the effects of regional integration on border SEZ formation and firms’ location choices. In addition, this study employs firm-level data rather than provincial data to bring empirical insights and fill in the knowledge gap on agglomeration economies in Thailand with the presence of regional economic integration.

The purpose of this paper is to reveal benefits and factors (elements) of proximity manufacturing that enhance triple bottom line (TBL) sustainability in the clothing industry and discusses previous proximity manufacturing studies.

A systematic review is used in searching and extracting data (primary studies artifacts and proximity manufacturing elements) from peer-reviewed articles. Extracted elements are gathered and analyzed in constructed tables under TBL. Four subgroups are inducted under the business bottom line.

This paper shows the potential of proximity manufacturing to enhance TBL sustainability, the scope of proximity manufacturing, and the trend and absence of existing studies. The most frequently mentioned elements are time-to-market, job creation, product quality, quick response, and trade policies. Governments and clusters are also important players.

Future research can further explore elements potentially improving TBL sustainability to fill gaps in existing studies, including how proximity manufacturing can drive environmental and social practices, and how governments can encourage proximity manufacturing in various markets.

Besides perceiving the benefits of proximity manufacturing, businesses may use the derived elements to make manufacturing decisions.

Public policies giving privileges to the locally produced garment industry have great potential to drive the economy and employment as well as sustain local clothing knowledge and the environment.

Proximity manufacturing strategies toward sustainability are under-researched academically and under-practiced industrially; this paper provides insight into sustainability benefits of proximity manufacturing.

Risk management has always been an area of concern for every global firm. The firm's supply chain management (SCM) practices are also affected by the degree of risk involved in almost all decisions. The purpose of this paper is to address the issue of assessment of risk associated with global supply chain.

The suggested methodology consists of two phases. The aim of the first phase is to select the location of a global facility with least risk and in the second phase, least risky configuration of supply chain is selected. The methodology adopted in the paper is demonstrated using the hypothetical case of an industrial valve manufacturing global firm.

The paper presents a tool for strategic and planning level. It supports a supply chain manager at strategic level to find the least risky location for manufacturing facility; while at the same time, the methodology supports a supply chain planning manager when selecting the least risky configuration of suppliers and distributors.

There are many models in the literature that addressed the issue of risk minimization in supply chain, but after an exhaustive literature review, it was noticed that there is no model that minimizes risk in locating a global facility and resulting supply chain simultaneously. The paper thus accomplishes this task by using PROMETHEE‐II and goal programming tools to suggest a decision framework for assessment of risk associated with global supply chain.

This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the second objective is to minimize the carbon emission resulting from production, transportation, and disposal processes using carbon cap and carbon tax regularity policies. In the third objective, we maximize the service level of retailers by using maximum covering location as a measure of service level. To model the proposed problem, a physical programming approach is developed. This work contributes to the literature in designing an optimum CLSC network considering the service level objective and product substitution.