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When is it more profitable for multinational manufacturers to manufacture in high-cost environments and when in low-cost environments? While the literature offers many cues to answer this question, too little empirical research directly addresses this. In this study, we quantitatively and empirically investigate the financial effect of companies' production footprint in low-cost and high-cost environments for different types of production networks.

Using the data of 770 multinational manufacturing companies, we analyze the relationship between production footprints and profitability during four calendar semesters in 2018 and 2019 (N = 2,940), investigating the moderating role of companies' production network type.

We find that companies with networks distinguished by both high levels of product complexity and process sophistication profit the most from producing to a greater extent in high-cost countries. For these companies, shifting production to low-cost countries would be associated with negative performance implications.

Our findings suggest that the production geography of companies should be attuned to their network type, as defined by the companies' process sophistication and product complexity. Manufacturing in low-cost countries is not always the best choice, as doing so can adversely affect profits if the products are highly innovative and the production processes are complex.

We contribute to the scarce empirical literature on managing global production networks and provide a data-driven analysis that contributes to answering some of the enduring questions in this critical area.

This study aims to examine the role relational dynamics, grounded in the theories of social exchange and social capital, play within the context of geographic indication (GI) food supply chain network (FSCN) performance.

A total of 30 qualitative interviews were undertaken with key informant stakeholders across a variety of organizations within Turkish GI FSCNs. An open, axial and selective grounded theory coding process was used for the analysis, teasing out critical themes that underpinned the conceptual framework.

The findings identify the formal and informal mechanisms which govern GI FSCNs. These two forms of governance mechanisms influence network performance, which was found to comprise logistics, production, business and socio-economic performance dimensions. Transparency, GI traceability, trust and psychological contract violations were found to mediate the link between governance and network performance outcomes.

To the best of the authors’ knowledge, this study is the first to explore GI FSCNs from the perspective of relationship marketing and through the lens of social exchange and social capital theory. Accordingly, both academics and practitioners can benefit from the study, as it unveils relevant relational factors underpinning such networks.

The changing roles of the United Nations (UN) and national institutions have made addressing climate change a critical concern for many multinational enterprises’ (MNEs) survival and growth. This chapter discusses how such institutions, which vary in their nature and characteristics, shape firm strategies for climate change adaptation. Exploring different versions of institutional theory, the chapter demonstrates how and why institutional characteristics affect typical patterns of firm ownership, governance, and capabilities. These, in turn, influence companies’ internationalisation and climate-change strategies. Climate change poses challenges to how we understand firms’ strategic decisions from both an international business (IB) (HQ–subsidiary relations) and global value chains (GVC) (buyer–supplier relations) perspective. However, climate change also provides opportunities for companies to gain competitive advantages – if firms can reconfigure and adapt faster than their competitors. Existing IB and GVC research tends to downplay the importance of climate change strategies and the ways in which coherent or dysfunctional institutions affect firms’ reconfiguration and adaptation strategies in a globally dispersed network of value creation. This chapter presents a perspective on the institutional conditions that affect firms’ climate change strategies regarding ownership, location, and internalisation (OLI), and GVCs, with ‘investment’ and ‘emerging standards’ playing a significant role. The authors illustrate the discussion using several examples from the Global South (i.e. Bangladesh) and the Global North (i.e. Denmark, Sweden, and Germany) with a special emphasis on the garment industry. The aim is to encourage future research to examine how a ‘business systems’, or varieties of capitalism, institutional perspective can complement the analysis of sustainability and climate change strategies in IB and GVC studies.

Objective is to investigate the effects of COVID-19 on the performance and productivity of infodemic research. A comprehensive bibliometric analysis is conducted using data extracted from Thomson Reuters' Web of Science, and the analysis is facilitated by the bibliometrix and biblioshiny tools.

Data was extracted from the Web of Science (WoS) database provided by Thomson Reuters. Therefore, literature published outside of the WoS database was not included. Results were extracted about the Document Type, Research Area, Language, Publication year, and country or countries for all authors because this study was interested in scholarly international collaboration. The researcher also used the Thomson Reuters Web of Science’s InCites Essential Science Indicators database, which allowed the researcher to measure the scientific output performance of countries over a period of time. In addition to InCites data, citation data and international collaboration for all countries were also downloaded.

Inclusion and exclusion criteriax: this study focused on literature published by authors identified by each author’s affiliation in each publication. Thus, the WoS topic field was searched by “infodemic” or “information epidemic” or “info ebidemic”. The time span selected for this study started from 2018 to 2022, allowing the researcher to survey the nature of the literature during the last 6 years before COVID-19 and 4 years after COVID-19 to identify the effects of COVID-19 on research in the world regarding both performance and productivity. The study included various types of materials, such as articles, early access, and review articles.

A comprehensive bibliometric analysis is conducted using data extracted from Thomson Reuters' Web of Science, and the analysis is facilitated by the bibliometrix and biblioshiny tools. The findings reveal that prior to the COVID-19 outbreak, researchers contributed a total of 3,960 documents, with the United States leading with 2,933 publications, followed by China with 2,561. However, the production of infodemic research doubled following the onset of the pandemic, resulting in a total of 6,979 documents. Both before and after COVID-19.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

Modular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.

We develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.

The experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.

To the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.

This paper aims to identify potential barriers to Industry 4.0 adoption for manufacturers and examine the changes that must be made to production processes to implement Industry 4.0 successfully. It aims to develop technology by assisting with the successful implementation of Industry 4.0 in the manufacturing process by using smart system techniques.

Multiple case studies are used in this paper by using the smart system and Matlab, and semi-structured interviews are used to collect qualitative data.

Standardization, management support, skills, and costs have been cited as challenges for most businesses. Most businesses struggle with data interoperability. Complexity, information security, scalability, and network externalities provide challenges for some businesses. Environmental concerns are less likely to affect businesses with higher degrees of maturity. Additionally, it enables the Technical Director’s expertise to participate in the measurement using ambiguous input and output using language phrases. The outcomes of the numerous tests conducted on the approaches are extensively studied in the provided method.

In this research, a multiple-case study aims to carry out a thorough investigation of the issue in its actual setting.

The purpose of this paper is to propose a method that can calculate the transportation infrastructure network service capacity enhancement given by planned transportation infrastructure projects construction. Managers can sequence projects more rationally to maximize the construction effectiveness of infrastructure investments.

This paper designed a computational network simulation software to generate topological networks based on established rules. Based on the topological networks, the software simulated the movement path of users and calculated the average travel time. This software allows the adjustment of parameters to suit different research objectives. The average travel time is used as an evaluation index to determine the most appropriate construction sequence.

In this paper, the transportation infrastructure network of Sichuan Province in China was used to demonstrate this software. The average travel time of the existing transportation network in Sichuan Province was calculated as 211 min using this software. The high-speed railways from Leshan to Xichang and from Xichang to Yibin had the greatest influence on shortening the average travel time. This paper also measured the changes in the average travel time under two strategies: shortening the maximum and minimum priorities. All the transportation network optimisation plans for Sichuan Province will be somewhere between these two strategies.

The contribution of this research are three aspects: First, a complex network analysis method that can take into account the differences of node elements is proposed. Second, it provides an effective tool for decision makers to plan transportation infrastructure construction. Third, the construction sequence of transportation infrastructure development plan can effect the infrastructure investment effectiveness.

The paper positions social and technological innovation as pivotal counterforces to conservative resistance against change, particularly in light of the recurrent economic and technological upheavals characterizing the present shape of capitalism.

The research adopts a qualitative methodology, rooted in a comparative case study approach, offering a critical retrospective analysis of societal disruptions and transformations. Central to this methodological framework is the construct of sensemaking, which is characterized as the process by which collective entities retrospectively develop plausible narratives that rationalize their experiences. The approach is informed by the dynamics of socio-ecological systems, which are understood to undergo cyclical phases of growth, stabilization, collapse, and regeneration.

The study shows evidence that resilience and adaptability are more authentically gauged by socio-technological responses to cyclical disruptions and recoveries. It delineates sensemaking as a crucial socioecological mechanism through which elicitation emerges and societies and organizations navigate these cycles, forging shared narratives from collective experiences that are driven by plausibility rather than mere accuracy.

The research calls for the development of policies that synthesize disruptive innovations with strategies for social cohesion. Such policies must ensure the protection of the socioeconomic texture from implicit structural precariousness arising from innovation. The ability to integrate and institutionalize change is emphasized as crucial, demanding a synergy between innovative creativity, new normative frameworks, and the preservation of fundamental societal values.

The paper challenges reductionist technological interpretations of societal changes, advocating for a holistic perspective that accounts for the redistributive and elicitation roles as vital to the evolution of socio-economic systems. The value of this research lies in its comprehensive framing of these transformations, underscoring the importance of a multi-faceted understanding in the effective management of socioeconomic change.