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.

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.

Economic globalization promotes industrial division and forms a large stream of products between countries all over the world, which leads to serious environmental problems. The purpose of this study is to explore the relationship between green logistics and international trade. Heckman’s two-stage procedure is employed to estimate an augmented gravity model that specifically includes green logistics variables with the data of 113 countries and regions over the period between 2007–2014. The findings show that the logistics performance index (LPI) of exporting and importing countries are positively correlated with trade volume, and that the LPI of exporting countries positively affects trade probability. Taking the entire sample into account, the green logistics performance of exporting countries positively affects export probability and volume. For trade flows between developing–developing countries, developed–developed countries, and developed–developing countries, the green logistics performance of importing countries has a negative impact on the export volume of exporting countries. In terms of trade flow between developing–developed countries, the green logistics performance of importing countries has a negative impact on export probability and a positive impact on export volume. The present research results will assist governments and exporters in understanding the relationship between green logistics and international trade, and help improve their policies and green operations toward sustainable development.

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.