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Driven by the disruptive effects of the Covid-19 pandemic, the ongoing debate about the international location of firms' manufacturing activities has increasingly highlighted the specific benefits and costs of near-shoring versus far-shoring. However, the effects of near-shoring versus far-shoring on customer perceived quality and purchase intention have not been examined. Thus, this study aims to develop a conceptual model and provide new evidence to fill this gap. In particular, the study explores the roles of brand familiarity and corporate social responsibility (CSR) to explain the different levels of perceived quality and purchase intention in relation to near-shoring versus far-shoring.

This study includes two analyses of data collected from a sample of Italian customers. The first analysis consists of a 2 (high/low brand familiarity) × 3 (domestic insourcing, near-shoring, far-shoring) factorial design, and data are assessed via analyses of variance (ANOVA). The second analysis evaluates the suggested model in the two scenarios (near-shoring and far-shoring) via partial least squares–structural equation modelling (PLS-SEM) multigroup analysis.

Results showed that customer perceived quality and purchase intention were significantly higher for near-shoring than for far-shoring, but only when brand familiarity was low. No significant difference was found for participants with a high level of brand familiarity. In addition, the level of a brand's pre-offshoring perceived CSR was negatively related to perceived quality, and this was conceptually justified by the CSR-washing effect. Again, this effect was found only when brand familiarity was low.

The findings contribute to advancing the current understanding of the multiple effects of the offshoring decision and clarify that near-shoring and far-shoring have different effects for customers with low brand familiarity. The findings also emphasise that the far-shoring decision can elicit the perception of decoupling between the firm's CSR claims and CSR actions, thus decreasing perceived quality.

This study provides managers with additional inputs to make more informed decisions regarding offshoring. While the post-pandemic scenario seems to favour near-reshoring over far-shoring due to agility considerations, this study also provides additional evidence of the superiority of near-reshoring from the customer's perspective.

This is the first study to examine and prove the differential effects of near-shoring versus far-shoring on the customer's perceptions and behaviours.

Manufacturing offshoring has received substantial attention within international business studies that have explored where activities are located and how they are governed. However, recent examples of manufacturing relocation to the home country/region have put the advantages of offshoring under scrutiny, since the location of production activities in high-cost countries may have positive impacts in terms of innovation and marketing opportunities. Despite the growing interest in offshoring and “relocations of second degree,” there is a lack of knowledge on the alternative strategies firms may implement after offshoring. This chapter aims to propose a comprehensive framework to summarize and classify the multiple alternatives firms may implement after the initial relocation abroad of manufacturing activities. Based on an extensive literature review and a comparative analysis of Italian case studies, the chapter suggests theoretical advancement in the theory of location of business activities, offering multiple post-offshoring strategic options that may be implemented individually or in combination. In so doing, the analysis also stresses the variety of strategic paths and the complexity of choices concerning manufacturing location, emphasizing reshoring as a nuanced phenomenon and exploring how domestic and foreign locations can complement each other and be mutually reinforcing.

This study aims to empirically investigate the effects of labor displacement on US management consulting (MC) firms.

This paper leverages standard linear regressions to identify and discuss correlations between progresses made in terms of labor displacement and the evolution of MC firms performance indicators.

In the context of US MC practices, the study shows that for every percent of work displaced, production costs are reduced by $3.7/h on average. It also highlights that as prices also go down by $3.3/h on average per percent of work displaced, off/near-shoring increases MC practices profitability. Displacing labor is yet a transformation that occurs mainly in very large firms (i.e. more than 1,000+ employees) and its full potential takes more than 4–5 years to realize.

This study provides new empirical benchmarks of the effect of labor displacement on MC firms. This study shows how long off/near-shoring takes to reach its full maturity.

The advantages of offshoring are increasingly under scrutiny, and coronavirus disease 2019 (COVID-19) has advanced the debate, calling for a redefinition of firms' production location strategies. While attention has primarily focused on the relocation of second-degree strategies, such as back-shoring, near-shoring and further offshoring, there are also other alternatives, including home country-based domestic product and process innovations, and the development of new business activities. The objective of the authors' paper is to identify which factors influence decision-makers when they select and implement such post-offshoring strategic alternatives.

The authors consider 11 Italian manufacturing companies that implemented these strategies and analyze triggers, drivers, enabling factors and barriers of the decision phase, as well as content, governance mode and timing of the implementation phase.

Based on the collected findings, the authors suggest a set of propositions for further research. First of all, firms can simultaneously manage multiple strategies by adopting an ambidextrous approach through which to mitigate supply chain risks. They may integrate their domestic and international production activities, but the home country remains central for innovations and production of high-end products and Industry 4.0 technologies increases the probability of investing in their home country. At the same time, lack of competence induces selective near- and back-shoring, while full back-shoring is mainly a consequence of managerial mistakes. Competence availability acts as a barrier to relocation in the home country, inducing the implementation of either an insourcing strategy or a combination of insourcing and outsourcing.

The authors' work identifies post-offshoring as a dynamic process and provides insights into the post-pandemic scenario. The conceptual framework may represent a useful tool for company managers in re-evaluating their initial offshoring strategies.

This paper aims to measure carbon footprints (CFs) of products at the sectoral levels. The paper also aims to provide potential solutions to adopt greener supply chains to minimise CFs.

The assessment of CFs uses a data set for nine sectors and environmental extended input output tables, as well as other six models. The analysis uses modules for regional economy, freight, logistics and mode choice, among other modules. The output of these modules includes increases or cuts in carbon dioxide (CO₂) emissions following a shift in supply chains.

The authors identify five supply chains that are closely connected to the growth of CFs. The highest CF is found for the electronics and textiles products. Offshoring manufacturing capacity produces an increase of emissions (production and freight transport sectors) of 42 million tonnes of CO₂ emissions, or 12 per cent of the Kyoto target of 341 million tonnes of CO₂. Using a different metric to measure emissions, offshoring the same volume of production appears as a reduction in European Union (EU)-wide CO₂ emissions. To reduce CO₂ emissions, the authors propose a carbon tax on imports, increasing R&D subsidies to industry and freight sectors and on-shoring a greater volume of production into the EU economies, among other measures.

This paper only measures CFs at the sectoral level. Further work should include survey data on CFs, longer historical data series and larger set of products for assessment. Another limitation is the lack of analysis of freight transport flows of non-EU regions, (i.e. China and Latin America).

The authors propose the following measures: at least five policies to offset offshoring of production, several measures to reduce carbon emissions, propose introducing mandatory audits for CFs and mandatory labelling. This work has implications for carbon taxation of exports and imports in an effort to decarbonise European and global supply chains.

Social implications include the need to lower personal goods consumption in the EU to minimise the impact of supply chains on carbon emissions; the need to tax exports/imports may have an impact on jobs in the EU, among other effects.

This paper is the only study that uses the TRANS-TOOLS model and the only study to measure CFs of products within the context of freight transport flows within the EU. The analysis relies on inputs from several modules that apply data on 24 EU economies.

In September 2010 Suresh Krishna, vice president of operations and integration at Polaris Industries Inc., a manufacturer of all-terrain vehicles, Side-by-Sides, and snowmobiles, needed to recommend a location for a new plant to manufacture the company's Side-by-Side vehicles.

The economic slowdown in the United States had put considerable pressure on Polaris's profits, so the company was considering whether it should follow the lead of other manufacturers and open a facility in a country with lower labor costs. China and Mexico were shortlisted as possible locations for the new factory, which would be the first Polaris manufacturing facility located outside the Midwestern United States. By the end of the year Krishna needed to recommend to the board whether Polaris should build a new plant abroad (near-shored in Mexico or off-shored in China) or continue to manufacture in its American facilities.

• Evaluate tradeoffs between different geographic locations when establishing a manufacturing facility (off-shoring, near-shoring, and on-shoring)

• Run a sensitivity analysis on total cost

• Assess the impact of transportation costs, exchange rates, labor cost rates, lead times, and other assumptions on total costs

• Identify qualitative factors to be considered when deciding between non-U.S. facility locations, transportation time variability, consumer perceptions, and cultural differences

Evaluate tradeoffs between different geographic locations when establishing a manufacturing facility (off-shoring, near-shoring, and on-shoring)

Run a sensitivity analysis on total cost

Assess the impact of transportation costs, exchange rates, labor cost rates, lead times, and other assumptions on total costs

Identify qualitative factors to be considered when deciding between non-U.S. facility locations, transportation time variability, consumer perceptions, and cultural differences