Qian-Li Dong

The risk of frequent disasters is becoming a huge challenge for enterprises and their supply chains. In particular, sudden global public health events have brought a great test to the supply chain. How to make sustainable planning and preparedness and smoothly carry out supply chain operations and obtain sustainable firm performance in the complex market environment requires urgent attention from industries and academia. The different effects of supply chain operational capability and dynamic capability on the long-term performance and short-term performance of enterprises are still unclear; therefore, a model was established to discuss this. Based on the theory of dynamic capability, a relational model between supply chain dynamic capability, supply chain operational capability, and firm performance was constructed, a hypothesis testing method and Amos software were used to verify the set model, and the mechanisms of supply chain dynamic capability and supply chain operational capability on firm performance were discussed. The empirical results show that supply chain operational capability has a mediating effect on supply chain dynamic capability and firm performance, and supply chain dynamic capability has a moderating impact on supply chain operational capability and firm performance. The supply chain and its enterprises should cultivate and continuously improve the supply chain dynamic capability as soon as possible, so that in the face of emergencies, the supply chain operation capability can be reasonably configured to avoid damage, improve firm performance, and gain competitive advantages.

This study aims to examine the effect of FinTech adoption on the sustainability performance of banking institutions in an emerging economy such as Bangladesh. Besides, this study also investigates the mediating role of green finance and green innovation in the relationship between FinTech adoption and sustainability performance. To examine the relationship among the study variables, this study used data from 351 employees of banking institutions operating in Bangladesh during the period January to March 2021 using a convenience sampling method. Furthermore, the study utilized a two-staged structural equation modeling and an artificial neural network (SEM-ANN) approach to analyze the data. The findings show that FinTech adoption significantly influences green finance, green innovation, and sustainability performance. Similarly, the results indicate that green finance and green innovation have a significant positive influence on sustainability performance. Furthermore, the results reveal that green finance and green innovation fully mediate the relationship between FinTech adoption and the sustainability performance of banking institutions. Moreover, the present study contributes to the existing literature on technological innovation, green finance, and sustainability performance greatly as it is the first study to examine both linear and non-linear relationships among these variables using the SEM-ANN approach. As a result, the study highlights the importance of FinTech adoption, green finance, and innovation in the attainment of sustainability performance, as well as the urgent need to incorporate new technologies, green initiatives, and financing into banking strategies to help achieve the country’s sustainable economic development.

This article aims to evaluate sustainable supply chain risks using a novel fuzzy VIKOR–CRITIC technique. The research contributions of this study are twofold. First and foremost, this is the first attempt to integrate the fuzzy VIKOR approach with the CRITIC method in order to eradicate the inadequacies of the VIKOR method. Second, this is the first study to look at the sustainable supply chain risk management in Pakistan’s logistics industry. Four logistics companies were chosen for the study, and thirty criteria were established and divided into four categories using acquired data and literature studies. According to the findings, organizational risks are the most important to consider, whereas environmental hazards have the least influence. Supply delays, freight rate/oil price fluctuations, bankruptcy, and natural catastrophe are the four most important criteria in these categories. Limited suppliers, cargo tracking, IT system failure, and international politics are the four least significant criteria in the four risk categories. The findings are useful for the logistics industry operating in CPEC for risk mitigation and sustainable operation. The research may be used as a guideline for risk identification and management by practitioners and decision-makers in Pakistani logistics organizations.

International trade can be severely disrupted by failures in international logistics processes. Therefore, an understanding of international logistics risk is imperative for the smooth operation of international trade, systematically studying the causes, responsible parties, and possible consequences of international logistics risk. On this basis, international logistics risk is classified from the perspective of the consequences caused by logistics risk, combined with the influencing factors and types of risk, establishing the index system and evaluation model of international logistics risk; Fuzzy Comprehensive Evaluation (FCE) and Analytic Hierarchy Process (AHP) methods were used to evaluate international logistics risk, and the international logistics risk in the international trade of the Regional Comprehensive Economic Partnership (RCEP) is also discussed. The results show that generally, international logistics risks are mainly logistics loss risk, logistics cost risk, and logistics timeliness risk. The logistics risks in the transaction with RCEP mainly include logistics loss risk, logistics cost risk, logistics timeliness risk, environmental risk, and logistics information risk. The risk causes include five risks: general causes, accidents, bankruptcy or ultra vires of logistics companies, customs clearance problems, and cargo characteristics. By establishing the international logistics risk measurement index system, it can hopefully play a preventive and guiding role in the research of international logistics risk assessment and the international logistics risk management of RCEP enterprises.

Access to financial services is regarded as one of the most pressing issues confronting communities worldwide sequel to the COVID-19 pandemic. In this regard, FinTech applications such as mobile financial service (MFS) play an essential role in building resilience during the pandemic. Hence, the aim of the study is to investigate the role of MFS platforms in economic resilience by empirically evaluating the determinants that influence the intention of Bangladeshi users toward adopting MFS platforms during the COVID-19 pandemic, through an extension of the Unified Theory of Acceptance and Use of Technology (UTAUT). Using the core structures of the UTAUT, the theoretical model was constructed based on the consumption attributes of financial services such as perceived value, as well as additional situational factors from the extended valence framework, including risk and trust. To test the model, data was obtained from 227 potential MFS users in Bangladesh with the aid of a structured questionnaire survey. Subsequently, the Structural Equation Modeling (SEM) approach was used to analyze the data. The findings showed that social influence, perceived trust, and perceived value are strongly related to the intention of users to adopt MFS platforms, whereas, perceived risk, performance expectancy, and effort expectancy were observed to influence users’ perceived value of the MFS platforms during the COVID-19 pandemic. Interestingly, the study results indicated that the users’ perceived risk did not influence their intention to adopt MFS platforms during the pandemic. Therefore, the suggested adoption of the MFS framework during and after the pandemic could contribute to the existing research on the adoption of information technology (IT) through the expansion of the UTAUT, in which the performance and effort expectancy of users influence their intention to indirectly adopt MFS through perceived value. Finally, the significant policy implications and future research directions are further addressed.

China’s economy has stepped up from the high-speed growth stage to the high-quality development stage. With the high-quality development of the economy, the logistics industry is bound to move towards high-quality development. By establishing the index system of high-quality economic development and logistics, this work has measured their high-quality development level and analyzed their coupling coordination degree by using the coupling coordination model. The results show that there are great regional differences in high-quality economic development, high-quality logistics development and their coupling coordination degree in China. In the areas with high-quality economic development, the logistics industry is not necessarily high quality, and the coupling coordination degree between the logistics industry and high-quality economic development is generally not high. The main reason for this is that the coordination between the logistics industry and high-quality economic development is poor. While vigorously improving the high-quality level of the logistics industry, it should strengthen the high-quality connection between the logistics industry and the economy, so as to form a situation of mutual promotion and common development.

Improving the logistics ecological efficiency (LEE) has become a significant part of ensuring a sustainable development and tackling environmental pollution. Previous studies in the logistics industry seldom considered air pollutants and the association of spatial information. Therefore, innovatively considering SO₂, NO_x, and PM, this study adopted the super-SBM-undesirable model to calculate the LEE of 30 provinces in China from 2005 to 2019 and, thereafter, developed information-based matrix to explore its influencing factors by using the spatial Dubin model. The results indicated that (1) the overall LEE was low with the average of 0.657, presenting a three-stage trend of “decreasing first, then rising, and later stable,” and significant regional differences with the decreasing gradient pattern of the “Eastern-Central-Western.” (2) A spatial directionality distributed from the northeast to southwest and a significant spatial autocorrelation were observed. (3) The LEE had a significant positive spillover effect. Industrial structure, urbanization level, environmental regulation, and technological innovation level had a positive impact on the local LEE, and industrial structure displayed the most promoting effects. Energy intensity, economic level, energy structure, and opening level had a significant effect on the local LEE with varying degree of inhibition. Local energy intensity and environmental regulation had a positive influence on the LEE in neighboring areas, while local opening level had inhibiting effects. In addition, policy recommendations for enhancing the LEE were made.

Improving the logistics ecological efficiency (LEE) has become a significant part of ensuring a sustainable development and tackling environmental pollution. Previous studies in the logistics industry seldom considered air pollutants and the association of spatial information. Therefore, innovatively considering SO₂, NO_x, and PM, this study adopted the Super-SBM-Undesirable model to calculate the LEE of 30 provinces in China from 2004 to 2017, and thereafter, developed information-based matrix to explore its influencing factors by using the spatial Dubin model. The results indicated that: (1) The overall LEE during the study period was low, presenting a U-shaped trend of an initial decrease and subsequent rise, and significant regional differences with the decreasing gradient pattern of the “Eastern-Central-Western.” (2) A spatial directionality distributed from the northeast to southwest, and a significant spatial autocorrelation were observed. (3) The industrial structure had the greatest positive influence on the local LEE, followed by the urbanization level, technology innovation level, environmental regulation, while the energy intensity was identified as the main inhibiting factor, followed by the economic level, energy structure and opening level. (4) The LEE had a significant positive spillover effect; the energy intensity and environmental regulation positively affected the LEE in neighboring areas, while the opening level had negative impacts. In addition, policy recommendations for enhancing the LEE were made.

International capacity cooperation is easily affected by the interweaving of its internal and external environment. As the risk accumulation exceeds the threshold, a supply chain crisis and even emergency will occur and serious losses will be caused. Regarding multinational operation and international capacity cooperation, 208 cases were summarized to identify risk types and high-incidence areas, and a risk measurement index system was established. A Fuzzy AHP (Analytic Hierarchy Process) method was used to evaluate the importance of each risk index. It was found that country risk was the main cause of supply chain emergencies in international capacity cooperation. Construction, water and electricity supply, mining and manufacturing were major areas of emergencies. In international capacity cooperation, country risk and cross-cultural risk were more important in external risks, while in internal risk, financial risk and decision risk were more important.

Globalization policies are encouraging manufacturing companies to produce environment-friendly products that offer a sustainable competitive advantage. Currently, product recovery and zero-waste supply chains have caught the attention of manufacturers and professionals. Reverse logistics (RL) is considered as the most significant part of supply chain management in developed countries; unfortunately, its implementation in developing countries is in the initial stages due to certain barriers. This study aims to identify and verify the barriers to implementation of reverse logistics using a two-stage methodology: the Delphi Method and Structural Equation Modeling. A comprehensive literature review was considered to identify a primary set of barriers. Using the Delphi Method, a team of experts screened out barriers after performing three iterations. A survey-based questionnaire was then sent out to supply chain and logistics employees in the manufacturing industry and relevant government authorities. Five hundred and forty-seven useful responses were analyzed in the Statistical Package for the Social Science (SPSS) & AMOS 21 softwares using Structural Equation Modeling to verify barriers, and ranked according to their severity. The most critical barriers with respect to each category are: high cost of reverse logistics adoption (finance and economics), lack of skilled professionals (knowledge and experience), lack of government supportive policies (law and regulation), poor organizational culture (management), lack of human resources (infrastructure and technology), lack of environmental law awareness (environment), lack of community pressure (market) and company policies (reverse logistics in policy). Overall, the top five barriers found in this study include lack of initial capital, lack of skilled professional in RL, companies’ policies against RL, lack of new technologies and information systems, and lack of community pressure. Knowledge about barriers to reverse logistics allows manufacturing companies to prepare a priority list of actions for better implementation of the reverse logistics system.