Previous studies have found that reverse technology spillover effects can promote industrial technology modernization in developing countries. However, it is still unknown whether reverse technology spillover effects can improve green innovation efficiency in developing countries. In particular, institutional uncertainties characteristic of transition economies have a significant impact on industrial modernization. Therefore, researching the impact of the institutional environment on the relationship between reverse technology spillover effects and green innovation efficiency is of great significance. In this paper, we use data from G20 countries as well as China’s foreign direct investment (FDI) data to measure the effects of reverse technology spillovers and adopt the threshold effect model to explore the relationship between reverse technology spillover effects and green innovation efficiency as well as the influence of the institutional environment on this relationship, based on China’s provincial panel data from 2003 to 2015. The empirical results show that the reverse technology spillover effects can effectively improve green innovation efficiency. There is a threshold for the influence of the institutional environment on the relationship between reverse technology spillover effects and green innovation efficiency. When the institutional development level surpasses the threshold value, an acceleration effect is generated. In addition, we find that the legal system is the key bottleneck in terms of improving green innovation efficiency. How to improve and perfect the path of institutional construction in China and how to enable institutions to gain threshold speed-up effects have become the major problems the Chinese government faces in institutional construction. The research results of this paper offer a reference to developing countries in regard to improving their institutions and enhancing their green innovation efficiency.

The purpose of this study is to explore ways to apply information technologies such as big data, Internet of things (IoT), mobile internet, and so on to the healthcare industry. By analyzing the impact path of such high-techs on healthcare, it intends to propose an application system for the sustainable development of so called “smart healthcare”. It identifies the influencing factors of smart healthcare from three different perspectives: society, economy and environment. It then constructs an indicator system containing 14 factors, and comprehensively analyzes the importance and dependence of the factors by using Fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Modeling Method (ISM) based on a multi-level hierarchy model. Using the theoretical framework of scientific research methods, this paper reveals the hierarchical path of the sustainable development of the whole intelligent healthcare which starts from the social level, combines the social and economic levels to achieve the balanced development of benefits, and finally brings the benefits to the environmental level. Based on this finding, this paper develops a sustainable application system for intelligent medicine in three levels: government, enterprise and user. The development of the sustainable application system for smart healthcare can provide theoretical guidance for model application evaluation.

Incorporating economic policy uncertainty into the Melitz and Ottaviano theoretical model, this study systematically examines the impact of economic policy uncertainty on firm markups, contributing to our understanding of how macroeconomic conditions affect business sustainability. The results reveal a significant negative relationship between economic policy uncertainty and firm markups, with particularly adverse effects observed in labor-intensive industries, smaller firms, and export-driven companies. As investment irreversibility increases, so does the detrimental impact of economic policy uncertainty on business markups. Importantly, it is discovered that innovation efforts can mitigate these negative effects, promoting sustainable business practices under high policy uncertainty. This research extends the mechanism through which EPU affects markups and highlights the critical roles of investment irreversibility and innovation behavior as moderators. By exploring these dynamics, our findings contribute to the broader discourse on sustainability by identifying strategies for enhancing corporate resilience and competitiveness amidst economic uncertainties.

Evaluation on Sustainable Development of Smart Urban Rail Transit: Objective. The purpose of the current work is to analyze how to employ intelligent technologies, for instance Internet of Things (IoT) and big data to urban rail transit industry, exhibit the effect path of new and high-tech on the intelligent urban rail transit sustainable development and establish an application system for the intelligent urban rail transit industry sustainable development. Methods. This paper concludes the affecting factors of intelligent rail transit (IRT) from three terms of environment, economy, and society, establishes the index system constructed from 14 factors, explores the significance together with dependence of each factor through Fuzzy-Dematel and ISM, and establishes a structure model of hierarchy. Conclusion. The study concludes that the hierarchical structure model includes five levels, and the key to IRT sustainable development is line network planning and intelligent operation. This paper builds the application system of sustainable development of smart urban rail transit, which includes government, enterprises, and users. Contribution. In accordance with IoT, big data, and other integrated systems, this study establishes a theoretical framework to evaluate the IRT sustainable development in the context of intelligent technology. By using the scientific method to study the theoretical framework, this paper exhibits the hierarchical effect way of the IRT sustainable development and develops a sustainable development usage system (SDUS) of IRT which can provide theoretical guidance for model application evaluation.

The purpose of this study is to explore how to effectively prevent risks in the Marine Silk Road. This paper establishes a hierarchical theoretical framework by using the interpretive structural modeling (ISM) and explores an application system for intelligent prevention. The fuzzy set theory is also used to screen out the unnecessary attributes, and a decision-making and trial evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes. Finally, we suggest an applicable risk-prevention system for the Marine Silk Road. Our results: (1) the solution to international political and trade risks is the most critical for the risk prevention; (2) the solution to marine meteorological risks relies mainly on the improvement of ocean information sharing mechanism driven by big data which needs international cooperation in terms of information and technology; (3) the solution to marine energy and environmental risks also requires active international cooperation; (4) the application system should be built based on three levels, including the international level, the government level, and the company level. This theoretical hierarchical framework aims to guide the countries alongside the road to effectively prevent the risks on the Marine Silk Road, promote the sustainable development of the Marine Silk Road, and develop the transnational economies and cultures.

This paper systematically examines the core of new quality productive forces underpinning the sustainable development of the low-altitude economy industry. Based on the Triple Bottom Line theory, it analyzes the interrelationships among various factors of new quality productive forces and reveals the underlying mechanism through which new quality productive forces drive sustainable development in this sector. By employing an integrated Fuzzy Decision-Making Trial and Evaluation Laboratory—Interpretive Structural Modeling (Fuzzy-DEMATEL-ISM) approach, this study establishes a hierarchical structure for sustainable development in the low-altitude economy industry grounded in the logical framework of new quality productive forces. The findings indicate that: (1) the strategic origin layer represents the prerequisite and most critical task for the emergence of the low-altitude economy industry; (2) the technological breakthrough layer constitutes the core competitive strength enabling its development; (3) the resource guarantee layer provides essential resource support for operational sustainability; (4) the institutional synergy layer enhances industrial efficiency through coordinated governance; and (5) the value realization layer signifies the ultimate form of industrial evolution. These research outcomes offer significant forward-looking insights for advancing sustainable development in the low-altitude economy industry.