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The risk measurement of financial credit industry is an important research issue in the field of financial risk assessment. The design of financial credit risk measurement algorithm can help investors avoid greater risks and obtain higher returns, so as to promote the benign development of financial credit industry. Based on the combined deep learning algorithm, this paper studies the risk measurement of financial and credit industry, and proposes a fusion algorithm of deep auto-encoder (DAE) and Long Short-Term Memory (LSTM) network. The algorithm recombines the value of fixed features by using the unsupervised mechanism of DAE, and extracts non fixed features for measurement combined with the memory characteristics of LSTM network. The experimental results show that: compared with single generalized regression neural network and LSTM network, the average accuracy of DAE-LSTM algorithm is improved by about 6.49% and 3.25% respectively, which has a better application effect in credit risk measurement.

The purpose of this study is to reveal the dark side the Internet and establish a hierarchical framework to provide its governance path based on users' negative psychology. However, this hierarchical framework must consider unnecessary attributes and the interrelationships between the aspects and the criteria. Hence, fuzzy set theory is used for screening out the unnecessary attributes, a decision-making and trial evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes, and interpretive structural modeling (ISM) is used to divide the hierarchy and construct a hierarchical theoretical framework. The results show that: (1) the institutional system is the driver of Internet governance improvement (2) personal values are the last link in the governance process (3) the governance transition from institutional system to values must cross the barriers of ethics and technology. This paper proposes a more systematic and integrated hierarchical framework which provides theoretical guidance to govern the dark side of the Internet.

The influential factors of green logistics development have been an important research topic for academics. However, little attention has been devoted to studying the issue of the prioritization and the hierarchical structure of these factors. The purpose of this study is to identify the key factors influencing the development of green logistics, and to explore the prioritization and the hierarchical structure of the influential factors. An indicator system for influential factors of green logistics development is first developed based on the theory of triple bottom line, including sixteen indicators or factors. The comprehensive influences and the prioritization of these sixteen factors are then analyzed using the DEMATEL method and the multi-level hierarchical structure of these factors is constructed by applying the ISM method. The results indicate that government policies, public supports, laws and regulations, green education, green technology innovations, consumer green demands, quantity and quality of green logistics talents are more influential than the other factors. Social factors including laws and regulations and government policies, public supports and green education are the underlying factors affecting the development of green logistics. Economic factors are at the middle levels and environmental factors are at the surface-level of the hierarchical structure. Recommendations are finally given to governmental agencies and business firms. These findings will be beneficial to promoting the sustainable development of green logistics.

This study aims to explore phenomena and laws that occur when different users on social network platforms obtain health information by constructing an opinion mining model, analyzing the user’s position on selected cases, and exploring the reflection of the phenomenon of truth decay on platforms. It selects group posts regarding the COVID-19 vaccination dispute on the Douban platform, analyzes the positions of different users, and explores phenomena related to users obtaining health information on domestic social platforms according to different topics and information behaviors. The results reveal a linear relationship between the negative and neutral attitudes of netizens on social networking platforms. Moreover, netizens tend to hold subjective language when expressing their views and attitudes, and their views on social platforms will not change easily. The study explores the health information acquisition behavior of netizens on social platforms based on the constructed user opinion mining model. The study is helpful for relevant units and platforms to make scientific decisions and provide guidance according to different positions of Internet users.

Psychological research shows that as the main component of enterprise decision-making, CEOs are not completely rational, cognitive and psychological biases often influence their decision-making process. CEO narcissism has gradually attracted academic attention. Based on upper echelon theory and subconscious theory, this paper uses advanced artificial intelligence technology to quantify CEO narcissism as a kind of emotional intelligence. Taking A-share listed companies in China from 2010 to 2019 as research objects, this paper empirically tests the impact of CEO narcissism on debt financing and innovation performance. The results show that CEO narcissism has a significant positive impact on firm innovation performance. Debt financing plays a mediating role in the relationship between CEO narcissism and firm innovation performance. CEO narcissism can have a positive impact on firm innovation performance through debt financing. Compared with non-SOEs, SOEs' CEO narcissism has a more significant positive effect on debt financing and enterprise innovation performance. The research in this paper enriches psychology and organizational management and provides a reference for an enterprise's management decisions and for investors' investment decisions.

This chapter utilizes cognitive theory to explain how entrepreneurial passion influences the speed of new venture's technology commercialization and explore the roles of cognitive bias (illusion of control and risk propensity) played in this process. The results show that both entrepreneurial passion and cognitive bias positively impact on the speed of technology commercialization. The authors also find that illusion of control and risk propensity play a partial mediating role in the relationship between entrepreneurial passion and the speed of technology commercialization. This conclusion can make up for the gap of existing theoretical research.

This special issue, “Internet Finance, Green Finance, and Sustainability”, is focused on the prosperous financial industry and the relationship between finance and sustainability. It especially gathers papers pertaining to the hot topic of internet finance and green finance in this field, as well as the manuscripts exploring the operating mechanism between finance and sustainability, both of which are closely linked to the hot spots and pressing demands of society. Therefore, this special issue is of particular valuable for both academic research and the development of society.

Little is known about sustainable information-sharing in virtual communities, although it is increasingly recognized as a useful information-sharing tool. The aim of this study is to explore the influential factors and the realization mechanism of sustainable information-sharing in virtual communities. Starting from the similarity between biological fermentation and the information-sharing process in virtual communities, the present study creatively introduces the knowledge fermenting theory used in the analysis. Six factors influencing sustainable information-sharing in virtual communities are first identified based on this theory, which include sharing bodies, interactive topics, communication mechanism, supporting technology, communication environment, and platform scale. The relations among these six factors are then analyzed using the Decision-Making and Trial Evaluation Laboratory (DEMATEL) method. The results indicate that the factor of sharing bodies has the strongest influence on other factors and the factor of interactive topics receives the most influences from the other factors. On this basis, the realization mechanism of sustainable information-sharing in virtual communities is elaborated from the following four aspects: the four stages of the information-sharing realization, the guide role of “strain,” the catalytic role of “enzyme,” and the effect of environment. The results indicate that sustainable information-sharing in virtual communities is a process of spiral evolution. Finally, recommendations are given to virtual community managers, users, and business firms.

This research aims to create a hierarchical framework for the development of a platform business model based on big data. However, this hierarchical framework must consider unnecessary attributes and the interrelationships between the aspects and the criteria. Hence, fuzzy set theory is used for screening out the unnecessary attributes, a decision-making and trial evaluation laboratory (DEMATEL) is proposed to manage the complex interrelationships among the aspects and attributes, and interpretive structural modeling (ISM) is used to divide the hierarchy and finally construct a hierarchical framework. The results reveal that (1) value proposition and community building in value production are fundamental links; (2) information technology and information management in value production are technical supports; (3) customer development in value marketing is the power source; and (4) value acquisition is the last link, which is established on the basis of and influenced by value marketing and value network. This hierarchical framework aims to guide the platform toward the application of big data. This study also proposes engagement of stakeholders for promoting value creation and establishing a sound business model from multiple levels and links.