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1 – 10 of 38Haihan Li, Per Hilletofth, David Eriksson and Wendy Tate
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Abstract
Purpose
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Design/methodology/approach
Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.
Findings
In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).
Research limitations/implications
Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.
Practical implications
This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.
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Dan Danes, Patrick van Eijck, Johan P. Lindeque, Mona A. Meyer and Marc K. Peter
Cities remain an understudied unit of analysis for understanding the motives of multinational enterprises’ (MNE) foreign direct investment (FDI), with subnational locations in…
Abstract
Purpose
Cities remain an understudied unit of analysis for understanding the motives of multinational enterprises’ (MNE) foreign direct investment (FDI), with subnational locations in International Business (IB) research to date predominantly captured via the phenomenon of agglomeration. As regional integration projects, such as the European Union and to a lesser degree NAFTA, increasingly reduce the importance of national institutional environments, this paper argues regional and subnational levels become more important for studying MNE location choice. This paper aims to evaluate the explanatory contribution of regional and subnational levels of analysis to understanding MNE location choice.
Design/methodology/approach
A qualitative deductive bottom-up multiple-case study research design is adopted to study the city location choices and FDI motives of six automotive and six commercial banking companies. These purposefully sampled manufacturing and service MNEs have different home countries and regional orientations. Data on their foreign investments across the extended Triad of Europe, North America and Asia-Pacific were collected for the time period of 2000–2021.
Findings
Findings suggest that different classes of city tend to attract specific types of FDI and that these patterns might vary across sectors and be influenced by the regional strategic orientations of MNEs. Industry-specific findings reveal the importance of related and support industries and partners in a city location for the automotive MNEs, while the commercial banks seek investment opportunities in cities that allow acquisition targets that have an attractive customer based and will improve their local market knowledge.
Originality/value
The findings provide evidence in support of MNEs in manufacturing and service industries perceiving the attractiveness of three city types in different ways across the Triad regions.
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Jurema Tomelin, Mohamed Amal, Nelson Hein and Andreia Carpes Dani
This study aims to identify to what extent the economic factor effect is more salient in shaping inward foreign direct investment (IFDI) than are institutional factors in G-20…
Abstract
Purpose
This study aims to identify to what extent the economic factor effect is more salient in shaping inward foreign direct investment (IFDI) than are institutional factors in G-20 inflow patterns.
Design/methodology/approach
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied using the World Bank Governance and Development Indicators, followed by a panel data technique over the period 2005-2015 to estimate the connections between the different dimensions of economics, institutions and IFDI in the G-20.
Findings
Results showed that countries with better economic performance contrasting with the governance indicators are more effective at attracting IFDI. However, the correlation between FDI intensity and governance indicators has been found relatively weak, which may suggest a more controversial role of institutions as determinants of IFDI.
Research limitations/implications
This quantitative approach uses a country-level set of variables; therefore, the authors suggest the development of more firm-level analysis of the impact of institutions. Also, the limitation of the TOPSIS method itself is based on heuristic assumptions.
Practical implications
The main findings point to a relatively low impact of institutions on IFDI. The authors suggest that the global financial crisis has changed the rationale of decision-making by multinational companies.
Originality/value
The originality of the present study was to apply a multi criteria decision-making technique on FDI’s analysis combined with institutional data.
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Ilan Alon, Vanessa P.G. Bretas, Alex Sclip and Andrea Paltrinieri
This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML)…
Abstract
Purpose
This study aims to propose a comprehensive greenfield foreign direct investment (FDI) attractiveness index using exploratory factor analysis and automated machine learning (AML). We offer offer a robust empirical measurement of location-choice factors identified in the FDI literature through a novel method and provide a tool for assessing the countries' investment potential.
Design/methodology/approach
Based on five conceptual key sub-domains of FDI, We collected quantitative indicators in several databases with annual data ranging from 2006 to 2019. This study first run a factor analysis to identify the most important features. It then uses AML to assess the relative importance of each resultant factor and generate a calibrated index. AML computational algorithms minimize predictive errors, explore patterns in the data and make predictions in an empirically robust way.
Findings
Openness conditions and economic growth are the most relevant factors to attract FDI identified in the study. Luxembourg, Hong Kong, Singapore, Malta and Ireland are the top five countries with the highest overall greenfield attractiveness index. This study also presents specific indices for the three sectors: energy, financial services, information and communication technology (ICT) and electronics.
Originality/value
Existent indexes present deficiencies in conceptualization and measurement, lacking theoretical foundation, arbitrary selection of factors and use of limited linear models. This study’s index is developed in a robust three-stage process. The use of AML configures an advantage compared to traditional linear and additive models, as it selects the best model considering the predictive capacity of many models simultaneously.
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Malin Johansson and Jan Olhager
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
The experience of Swedish manufacturing plants reported here can be used as a point of reference for internal manufacturing operations.
Originality/value
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.
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Ilan Alon, Julian Chang, Marc Fetscherin, Christoph Lattemann and John R. McIntyre
Ahmed Nazzal, Maria-Victòria Sánchez-Rebull and Angels Niñerola
This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies…
Abstract
Purpose
This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.
Design/methodology/approach
The study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.
Findings
The results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.
Originality/value
The current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.
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