Related loans refer to loans that are linked together due to a certain (or several) relationship(s) and these loans as a whole are likely to cause group default. Because of the complicated cross-bank loan and concealed influence relationship in related loans, it is difficult for banks to identify related loans and take effective measures. Based on the loan guarantee data of several commercial banks, this paper constructs a multi-layer complex network, then designs an algorithm to identify the related loan structure and analyzes the ef-fectiveness; the default rate of different related loans structures is calculated and compared with 4 risk indicators; finally, the signifi-cance of default risk of different related loans structures is tested. The result shows:(1) the multi-layer network related loan model and the recognition algorithm constructed in this paper greatly improve the efficiency and accuracy of related loan identification, and overcome the dual concealed problem of related loans that cannot be solved by the single layer network; (2) the betweenness and clustering coeffi-cient indicators are more consistent with the true default rate of related loans, while the indicators based on the clearing payment capacity and risk distance fail to predict the true default rate; (3) when there are circle-linked structure and sink structure in related loans net-work, the default risk of loans increases significantly. The model and method constructed in this paper provide a theoretical basis for identifying multi-bank and multi-relationship related loans, and have practical significance for banks to detect risk network structures and to control related loan risks.

Predicting potential default of small listed companies (small listcos for short) is of great significance for banks to issue loans, for investors to make an informed decision and for regulatory authorities to supervise the market. Based on the big data perspective, this paper selects a set of indicators from more than 300 indicators including small listcos' financial and non-financial indicators and macro-economic indicators, and uses the set of indicators to establish a default prediction model for China's small listcos. The contributions of this paper are as follows:in the first stage, the minimum value of Gini of the indicator Xi is used as the node to divide the small listcos into defaulting ones and non-defaulting ones; a set of features is used to construct a decision tree and then multiple sets of indicators are used to construct multiple decision trees, which are used to calculate the importance value VI (Xi), with indicators of high importance value retained; a set of indicators with the minimum Bayesian criterion value are selected from the retained indicators. The research shows that:(1) The indicators selected in this study can predict the default status of small listcos and conform to the principle of credit 5C. The indicator that has a key impact on the default status of small listcos in the next 0-5 years is “retained earnings per share”; the indicator that has a key impact on the short-term default forecast of small listcos is “other receivables”; an indicator that has a key im-pact on default forecasts is the “Industry Sentiment Index”; (2) the comparative analysis of multiple data sets, the comparative analysis of multi-index selection and the comparative analysis of multiple models show that the index selection method in this paper is significantly better than other three typical methods, and the results are robust; (3) small listcos in the eastern region have the highest credit qualifi-cation compared with those in other geographical regions, and non-backdoor-listed small listcos have the highest credit qualification com-pared with those listed in other ways.

The rapid development of China's Fintech online lending platforms has provided borrowers with more accesses to funds, espe-cially by “robbing Peter to pay Paul”. Using micro data from one of the largest cash loan platforms in China, this paper empirically stud-ies the paying behavior of borrowers “robbing Peter to pay Paul” from two perspectives:payday loans' order level and borrower level. This study shows borrowers who are “robbing Peter to pay Paul” have higher probability of default or late payment. The more frequently a borrower uses payday loan “huabei”, the more likely the borrower is to default or delay payment. Default or late payment is more likely to occur in male than in female, and in those who live in small cities than those who live in big cities. This paper tries to explain the bor-rowers' default from the aspect of “robbing Peter to pay Paul”, and the conclusions are helpful for supervising China' online lending market, improving personal credit system and regulating the cash loan market.

The boom in the real estate market sharply contrasts with the sluggish investment in some sectors of the real economy, espe-cially the downstream industrial chain. Using data from listed companies, this paper reveals the differential impact of rising house prices on the real sector's investment behavior from the industrial chain perspective. The study shows that rising house prices have a crowding-out effect on the investment of the real sector, with the degree of impact depending on where the real sector is located in the industry chain, and can cause investment imbalance between upstream and downstream industries. Rising house prices have a strong investment crowding-out effect on upstream sectors of the industrial chain before 2010 and on downstream sectors after 2010. Further study finds that the difference in the ownership structure of sectors amplifies the differential crowding out effect of rising house prices on firms' invest-ment. At the same time, real estate regulation policies can partially decrease the crowding-out effect. Based on the industry chain per-spective, this paper confirms that rising house prices are an important influencing factor for the heterization of investment behavior in the real economy and provides actionable policy recommendations for the government to formulate policies to promote the healthy development of the real estate market and enhance the modernization of the industrial chain in the real economy.

The phenonenon of a bidder suffering a loss due to winning an auction at an overvalued price is called winner's curse. In this paper, based on the limited attention theory from information economics and the over-action and Herd effect theory from behavior eco-nomics, we extend the first price common value auction model. Using data including 6,690 samples from on-line Taobao Judicial Foreclo-sure in Zhejiang province, China in 2020 to test the theoretical hypothesis, we find that (1) large crowd size leads to a high premium that may cause the winner to suffer a loss, and this is called the winner's curse effect of the crowd; (2) the effect is caused by bidders' over-reaction and conformity behavior in the presence of the crowd, but the path of information transfer through the crowd is not empiri-cally detected. Our conclusions are theoretically extended from the classical common value auction model, consistent with the implica-tions from the over-reaction and Herd effect theory, and fully tenable in the robustness test. This paper could be a useful empirical proof as the economic anomaly in auction markets.

It is quite challenging for China to find out how to change the resource-based industrial cluster or use regional innovation net-works to avoid path locks and achieve sustainable development. This study uses DEA method to measure the economic development effi-ciency of resource-based industrial cluster and the innovation efficiency of regional innovation network. Based on the spatial factors, this study builds a spatial econometric model of resource-based industrial cluster and regional innovation network to explore the mechanism of how the spatial spillover effect caused by factors such as technology, people, and information acts on resource-based industrial cluster and regional innovation network. The study finds that cluster and regional innovation network in resource-based cities have a significant “siphonic effect”; regional innovation network has a significant supporting effect on resource-based cluster, and resource-based cluster contributes less to regional innovation network; technology, infrastructure and people in regional innovation network have a significant spatial spillover effect, while the spatial spillover effect of resource-based industrial cluster is not significant.

Studying the influence of policy tools on the original innovation ability of enterprises is not only the basic premise to enhance the original innovation ability of enterprises, but also an important basis for the government to formulate original innovation policies. Based on the national scientific and technological activity data of large industrial enterprises from 2011 to 2019, this study selects six rel-evant original innovation policy tools, which are divided into supply, demand and environmental types. Then, by improving the Cobb-Douglas production function, this paper makes a regression analysis from two perspectives of policy tool coordination and policy tool com-bination. This study expands the original innovation policy toolbox, and reveals the impact of various policy tools on the original innova-tion capability of enterprises in practice. According to the results of empirical analysis, the relevant departments should further develop and apply demand-oriented and environmental-oriented policy tools, optimize the innovation policy tool system, strengthen the collabora-tive management of enterprise original innovation policy tools, and strengthen supervision to ensure the effectiveness and sustainability of original innovation of the enterprises.

In the era of the digital economy, the process and boundary of radical innovation are changing. Digital innovation capability has become important for strategic emerging industries to achieve radical innovation in a complex and changeable environment. Based on dynamic capability theory, this paper discusses two directions and four digital innovation capability upgrading activities. Taking 320 stra-tegic emerging industries as samples, using the hierarchical regression method to explore how digital agility and recombinative capability influence the strategic emerging industry radical innovation, and technological dynamics, market dynamics adjustment between the two. The results show that digital agility and recombinative capability positively affect radical innovation in strategic emerging industries. And the opportunity awareness, operation coordination, adaptive restructuring and reorganization of exploratory play a role in the four activi-ties, technology dynamics and market dynamics play a role in positive adjustment, but the adjustment effect varies from case to case. This study aims to further reveal the mechanism of how digital innovation capability influences radical innovation and provide a theoretical basis and decision-making reference for strategic emerging industries to achieve radical innovation results by taking advantage of digital opportunities.

This paper looks at the security of China's supply chain from two dimensions:sensitivity and elasticity of supply chain, and empirically examines the influence of supply chain sensitivity and elasticity on manufacturing industry's independent innovation capability based on China's 2001-2020 industrial data from 16 manufacturing sectors that suffer foreign stranglehold on core technolo-gies. It is found that supply chain sensitivity has a negative impact and supply chain elasticity has a positive impact on manufacturing in-dustry's independent innovation capability; as a moderating variable, industrial technology density weakens both the negative influence and the positive influence; industrial vulnerability enhances the negative influence but weakens the positive influence.

As live e-commerce livestreaming develops into a mature sales model, streamer's verbal skill has become a key factor influen-cing consumers' live purchase behavior. Based on information processing theory, this study explores how the positive emotional commu-nication, negative emotional communication and cognitive communication of streamers affect consumers' purchase behavior. The study finds that positive emotional communication and cognitive communication have a positive effect on consumers' purchase behavior, and there is an interaction effect between them. In addition, the study also finds that type of streamers (in-house personnel vs outside celebrity) and type of products (private consumer goods vs public consumer goods) have a moderating effect. Consumers are more likely to be influ-enced by emotional communication for celebrity streamers and public consumer goods, and more likely to be influenced by cognitive com-munication for in-house streamers and private consumer goods. This study enriches the research on emotion and cognition in the field of e-commerce livestreaming, and expands the practical application of information processing theory in e-commerce livestreaming. The find-ings are of great guiding significance for live streamers to develop an appropriate verbal pattern, for producers to select an effective lives-treaming strategy, and for audiences to shop rationally.

As an essential tool for corporate brand marketing, social media influencer marketing brings significant traffic to brand com-munication. Based on the Elaboration Likelihood Model and the Persuasion Knowledge Model, this study utilizes real data from social media platforms to investigate the impact of four core factors of influencer-generated content on consumer engagement behavior. The re-sults reveal that the format of influencer-generated content, contents' hedonic value, campaign incentives, and campaign intent all have significant direct effects on consumer engagement behavior. Specifically, influencer-generated content presented in video format, with high hedonic value, campaign incentives, or brand-promoting intention, is more likely to elicit consumers' likes, comments, and sha-ring behavior. These effects are further moderated by campaign intent. Specifically, posts using videos (vs. text-image) and campaign in-centives (vs. no incentives) are more effective in generating comments and sharing behavior when the intent is to promote brand, where-as posts high in hedonic value (vs. low hedonic value) are more effective in generating comments when the intent is to increase trials.

In recent years, an emerging word “breeding” has been widely used among Chinese consumers on the Internet. Building on constructivist grounded theory, this study develops a theoretical model revealing the paths from word-of-mouth “breeding” to actual con-sumption and the underlying key factors. First, the theoretical model identifies four key factors affecting word-of-mouth “breeding”:in-formation source characteristics, message characteristics, product characteristics and audience characteristics. Second, word-of-mouth recommendation may lead to “breeding” through informational influence, normative influence or value expression influence. Third, word-of-mouth “breeding” can be specifically demonstrated through consumers' curiosity, consumption expectation, purchase intention, and plan of consumption. In particular, there is a time difference between word-of-mouth “breeding” and actual consumption. The time difference may be caused by various reasons and lead to consumers' coping behaviors. After word-of-mouth “breeding”, consumers may either actually consume or give up consumption. The findings of this research not only contribute to the theory of word-of-mouth recom-mendation and interpersonal influence, but also have important practical implications for marketers to understand the effects of word-of-mouth in the era of digital media, and help consumers understand their own consumption decision-making process and behaviors.

The key to advancing collaborative innovation within a team lies in addressing the issue of team motivation. Traditional team incentives, achieved through mechanisms of shared benefits, are designed to foster teamwork. However, poor performers within the team not only hinder the team's progress but also impact the rewards of other team members. To mitigate the negative effect of “tandem pun-ishment for performance”, it becomes particularly crucial to explore the self-correction mechanisms in team incentives. This paper com-prehensively applies the three points of attribution theory (locus of control, controllability and stability), the three conditions of guilt production (drag down others, internal attribution and high controllability), three premises of performance improvement (expectancy, instrumentality and valence) and three aspects of motivational strategy (emotion, cognition and behavior) to construct a two-stage media-tion model with three interactions, aiming to reveal the benign mechanism of “tandem punishment against mediocrity”. Under this back-ground, the interval estimation Bootstrap method and Johnson-Neyman method are used to conduct a hypothesis testing based on 116 teams in 24 enterprises. The results show that if an employee performs poorly due to internal controllable factors under the conditions of performance pay, he or she will feel guilty and become motivated to perform well. Furthermore, if spurred by colleagues on the basis of the attribution, the poor performer who feels guilty will have a stronger motivation to perform well. This study offers fresh insights into the traditional Chinese military wisdom of the “tandem punishment for performance” system from a self-driven perspective. Simultaneously, it also offers theoretical and practical implications for contemporary organizations on how to break the “team incentive dilemma”.

Leader bottom-line mentality (BLM) refers to one-dimensional thinking that revolves around securing bottom-line outcomes to the neglect of competing priorities. Based on self-determination theory, this paper explores the effect of leader BLM on employees' fol-lowership behavior and examines the mediating role of employees' basic psychological need thwarting and the moderating role of collec-tivism orientation. Through a scenario experiment (N=130) and a three-wave field study (N=302), we find that leader BLM can posi-tively affect employees' basic psychological needs thwarting, which in turn positively affects employees' negative followership behavior and negatively affects employees' positive followership behavior. And employees' collectivism orientation not only moderates the direct effect of leader BLM on employees' basic psychological needs thwarting, but also moderates the indirect effect of leader BLM on employ-ees' followership behavior through basic psychological need thwarting. That is, the higher the employees' collectivism orientation, the weaker the effect of leader BLM on followership behavior. This paper also further discusses theoretical implications, practical implica-tions, and future research directions.

Cost stickiness reflects the enterprise resource allocation efficiency and firm risk. Based on financial data of the listed manu-facturing companies over the period 2010-2020, we use the word embedding model of machine learning method to research the impact of the application of intelligent manufacturing technology on cost stickiness. The results show that the application of intelligent manufac-turing technology helps to alleviate cost stickiness, which mainly occurs in enterprises with high innovation culture. The above conclu-sions still exist after replacing the main variables and testing methods, adding control variables for robustness tests, and using methods such as fixed effects, instrumental variables, and propensity score matching methods to alleviate endogeneity issues. The mechanism test shows the technology empowerment and information empowerment are the important path between the relation of intelligent manufacturing technology and cost stickiness. Heterogeneity test shows the above effect will be more pronounced in an environment of strong economic policy uncertainty and strong industry competitiveness.

Deepening the level of capital market liberalization is an important measure for the Chinese government to promote the regula-tory transformation of capital market in recent years. However, it remains unknown whether the opening of the stock market has affected the front-line regulation tendency and realized the original intention of promoting reform through opening up. Therefore, based on the fi-nancial report inquiry letter, this paper discusses the relationship between foreign ownership and the front-line regulation of the exchanges under the background of the continuous opening of the stock market in China. We find that foreign ownership can significantly reduce the probability, rounds and amount of financial report inquiry letters received by firms. The results are still valid after reducing the endoge-nous problems. In addition, the impact of foreign ownership exists mainly in private enterprises, enterprises with higher analysts' atten-tion and less degree of equity concentration. Further analysis shows that firms with foreign ownership are less likely to receive comment letters requiring verification opinions from third-party professional organizations, and the letters received by these firms usually involve fe-wer questions. Correspondingly, these firms have a lower probability of delaying the reply of comment letters and the overall amount of the replying announcements is also less. Finally, we find that the above results are mainly reflected in the firms held by foreign capital through Mainland-Hong Kong Stock Connect programs. The findings show that stock market liberalization indeed affects the front-line reg-ulation behavior of stock exchanges through foreign investors, thus having important implications for further opening of capital market and improving the regulatory system in the future.

The complexity, dynamics, and uncertainty of public health emergencies put forward higher requirements for emergency man-agement cooperation. Therefore, building and optimizing a cross-departmental cooperation network is of great significance for effective re-sponse to public health incidents. Based on the relationship data between emergency organizations in Wuhan during the COVID-19 epi-demic in 2020, this paper uses the social network analysis method to integrate both abnormal and normal social states, and comprehen-sively analyzes the evolution and performance of the emergency cooperation network for major public health emergencies. The research shows that cooperative relationship and complex cooperation network are more likely to form among organizations with similar organiza-tional attributes. However, there are significant differences between the abnormal emergency cooperation network and the normal emer-gency cooperation network, and the overall performance of the abnormal emergency cooperation network is stronger. Based on this, scien-tific and efficient emergency management needs to take into account abnormal emergency and normal prevention and control, coordinate key tasks and organizations involved in different stages according to changes in emergency situations, and take the close inter-organiza-tional dependence relationship as a robust function for maintaining organizational trust, promoting resource sharing and information ex-change, to further explore feasible ways to improve the effectiveness of emergency cooperation networks.

Inter-organizational commercial defamation often causes affected enterprises to suffer victim crisis against the backdrop of in-tensifying competition. Since commercial defamation is targeted, destructive and unclear in terms of responsibility, there is a perceived risk of purposefulness in impression management as to whether the strength of an enterprise's response is commensurate with the magni-tude of responsibility assumed. In this paper, we construct measures for crisis response tone analysis based on machine learning and sen-timent lexicon in the context of commercial defamation of A-share listed enterprises:action, certainty and tone intensity, and empirically test the effect and interaction of strong response tone of defamed enterprises in different audiences. The final experiment verifies the pur-poseful risk perception mechanism of “diffidence”. The results show that investors react negatively to the strong response of the defamed company after the business defamation incident, and the underlying mechanism is the perceived purposive risk of diffidence. Further re-search finds that journalists (vs. stock analysts) have a negative (vs. positive) attitude toward the tone of the strong response. Finally, different image dimensions have a moderating effect on the audience's risk perceptions. This study extends the study of defensive risk in-duced by crisis response tone to further deepen the understanding of corporate responses to different audiences.

This paper takes the A-share listed companies in Shanghai and Shenzhen from 2001 to 2018 as the research object and takes government work report as the quantitative index of local government's concern for environment to investigate its impact on the environ-mental governance behavior of local enterprises. It is found that when the local government pays more attention to the environment, local enterprises are more likely to disclose their efforts in environmental governance. That is, the larger environmental investment made by an enterprise, the more environmental information it would disclose. This result remains significant after a series of robustness tests. The mechanism test shows that when the government pays more attention to the environment, the enterprises are more likely to receive envi-ronmental subsidies from the government, pay pollution fees, and produce more green innovations. In addition, heterogeneity analysis finds that the more pollutions produced by an enterprise that receives much attention from media and operates in a province where envi-ronment is strictly regulated, the more effectively the local government's concern for environment can promote the enterprise's environ-mental governance and motivate the enterprise to disclose its efforts in environmental governance.

Digital government construction has become the forefront of China's modernization, and it is an important part of innovating the concept of government governance and comprehensively forming a new pattern of digital governance. To further improve the policy sys-tem of digital government construction, under the three-dimensional framework of “Objective-Tool-Effectiveness”, this paper comprehen-sively uses the content analysis method and PMC index model to conduct a quantitative inspection of 54 digital government construction policies, which were issued at the national level from 2015 to 2021. The study finds that although the policy objectives of digital govern-ment construction reflect the people-centered and data-enabled government service reform motivation, the policy tools have a wide cover-age and the overall policy effectiveness is good, there are still many problems such as inadequate diversity of policy objectives, unbal-anced structure of policy tools, and lack of policy content prediction and feedback mechanism. Therefore, we should continue to optimize the top-level design of digital government construction in China from three aspects:strengthening the big-picture thinking in policy de-sign, making full use of the policy toolbox that includes both hard and soft tactics, and maintaining general review and regular inspection of policies.

As a supporting space for rural entrepreneurship, the rural entrepreneurship ecosystem is of great significance to promoting ru-ral entrepreneurship. However, the existing studies remain silent on community-based enterprises' leading role in developing a rural en-trepreneurial ecosystem, thus failing to reveal the unique logic underlying community-based enterprises' addressing significant resource inadequacy. Taking Company M of Yongmei Village in Guangdong province as an example, this paper makes an analysis deep into the process of community-based enterprises leading the construction of rural entrepreneurial ecosystem in the context of indigenous entrepre-neurship based on Henri Lefebvre's space production theory and the theory of entrepreneurial ecosystem. The findings of this paper indi-cate that:the development of rural entrepreneurial ecosystem basically follows the logic chain of ‘value proposition to positive response to action to value spillover'. In this process, community-based enterprises connect the core action-takers of local and remote areas through value propositions, and then match the ‘embedded action' to activate the production of local social resources in villages, and the ‘re-embedded action' to combine the traditional entrepreneurial ecosystem resource elements that are scarce locally but abundant elsewhere, forming a resource relationship order with both resource production and resource combination. The value spillover of rural revitalization through value exchange between rural entrepreneurial ecosystem and village society is an important symbol of the successful construction of rural entrepreneurial ecosystem. This discovery promotes the theoretical analysis on the micro level of entrepreneurial ecosystem and provides new ideas for the practice of rural revitalization.

The digital economy has given rise to numerous new technologies, deeply transforming the development environment and inter-action mode of digital platforms, and reconstructing their governance modes and mechanisms. The core issue of digital platform govern-ance lies in how to manage participants for value co-creation and promote healthy platform development. Based on the perspective of value co-creation, this paper explores the governance modes and mechanisms of digital platforms. Through a longitudinal case study of 51WORLD, a leading digital platform in the digital twinning field, this paper proposes a binary governance mode that integrates digital and non-digital governance. In the initial stage, platform owners employ resource integration mechanisms and reputation governance mechanisms to stimulate participants' capabilities and willingness for value co-creation, thus achieving foundational value co-creation. In the growth stage, platform owners utilize technology adaptation mechanisms and multilateral trust mechanisms to enhance participants' capabilities and willingness for value co-creation, thus achieving scalable value co-creation. In the mature stage, platform owners employ technology sharing mechanisms and benefit commitment mechanisms to reinforce participants' willingness and capabilities for value co-creation, thus realizing sustained value co-creation. Through in-depth analysis, we find that digital governance and non-digital governance have both complementary and reinforcing effects, with digital governance enhancing participants' ability for value co-creation and non-digital governance stimulating their willingness for value co-creation, both of which jointly promote the realization of value co-creation by participants. The research conclusion reveals the multi-dimensional structure of digital platform governance, deepens our un-derstanding of the relationship between digital and non-digital governance, contributes to the development of digital platform governance theory and the connotation of governance mechanisms, and provides a new perspective and theoretical support for digital platform govern-ance.