Abstract: This paper analyzes the internal mechanisms for facilitating the domestic and international circulation of industrial chains under the new development pattern through the innovation of intermediate goods, from the perspective of intermediate goods and by constructing a game theory model. Two scenarios are examined: one in which intermediate goods are monopolized by a foreign manufacturer, and the other in which intermediate goods are produced simultaneously domestically and abroad. Building on this, the paper discusses how to incentivize innovation in intermediate goods to elevate the value chain. Our findings indicate that achieving breakthroughs in the innovation of intermediate goods domestically can structurally alter the profit distribution pattern within the industrial chain, potentially changing the impact of intermediate goods trade costs on various economic variables and helping to mitigate risks associated with the domestic and international circulation of the industrial chain. Furthermore, the paper finds that altering certain external economic conditions can effectively enhance firms’ willingness to engage in the innovation of intermediate goods.
Abstract: In recent years, frequent geopolitical conflicts and the potential formation of alliances based on shared values have undermined the efficiently functioning, tightly interdependent network of global value chains (GVCs). This study proposes a novel conceptual framework for assessing GVC vulnerability, develops composite metrics to quantify GVC vulnerability at the economy and sector levels, and systematically investigates how current geopolitical risks amplify GVC vulnerabilities across economies and sectors. The empirical results indicate that accounting for geopolitical risks leads to increases in the vulnerabilities of economies participating in GVCs, to varying degrees. The amplification effect is particularly pronounced for the United States and economies with high GVC dependency on the U.S. At the key sector level: in the computer, electronic, and optical equipment manufacturing sector, major supply-hub countries in the value chain such as the U.S., Germany, and the U.K. exhibit relatively low vulnerability; in the basic pharmaceutical products and drug formulations manufacturing sector, China has the lowest vulnerability globally, though it is more sensitive to geopolitical risks. A scenario simulation analysis of the U.S.-Japan-India-Australia Quadrilateral Security Dialogue (Quad) alliance indicates that eliminating geopolitical risks among member states has a very limited effect on enhancing the security of their participation in GVCs. If the Quad further escalates into consistent geopolitical tensions with China, it will instead exacerbate the GVC vulnerability of the U.S., Japan, and Australia.
Abstract: Intellectual property (IP) protection constitutes a fundamental institutional safeguard for firm-level digitalization and high-quality economic development. Using the establishment of National Intellectual Property Demonstration Cities (NIPDC) as a quasi-natural experiment, this paper constructs a multi-period difference-in-differences model to empirically examine the impact of enhanced IP protection on firms’digitalization. The results show that NIPDC significantly promotes firm-level digitalization, and this baseline conclusion remains robust after a series of endogeneity and robustness checks. Mechanism analyses reveal that strengthened IP protection alleviates financing constraints and effectively stimulates firms’digital innovation, thereby facilitating endogenous digitalization. Moreover, strengthened IP protection fosters the agglomeration of digital service providers, expanding exogenous channels for firms’digitalization and further improving their digitalization level. Heterogeneity analyses indicate that the promoting effect is more pronounced for digital follower firms, firms with digitally skilled executives, firms with lower patent density, and firms located in cities with lower degrees of marketization. This study expands the understanding of the channels enabling firms’digital transformation and delivers useful policy implications for strengthening IP governance and promoting enterprise digitalization.
Abstract: The social credit system is an important support for fostering a new development pattern. In recent years, China has taken a distinctive path, which is systematic, comprehensive, and digital, in the construction of the social credit system. Based on the policy background of credit construction pilot cities in China, this paper uses new firm registration data from the State Administration for Industry and Commerce of China (SAIC) to study the effect of social credit system construction on entrepreneurship vitality with a difference-in-differences framework. The study finds that the establishment of credit construction pilot cities, an important measure to promote the credit system, has significantly promoted urban entrepreneurship. It is proved that the policy has improved the levels of business, government, and judicial integrity. The results of the mechanism test indicate that the construction of credit cities could promote entrepreneurship by alleviating financing constraints and reducing policy uncertainty. Further analysis shows that the positive effect of credit city construction on entrepreneurship is greater in regions with high levels of social trust and the rule of law, indicating that the development of a culture of trust and the rule of law are both important supports for social credit system construction. This research assesses the economic effects of social credit system construction from the perspective of entrepreneurship and provides Chinese evidence that an effective government can help develop an efficient market. The findings are important for further promoting social credit system construction and for high-quality economic development.
Abstract: Venture accelerators provide essential professional training and entrepreneurial resources that are critical to the growth of social enterprises. To attract the attention of accelerators, social enterprises must effectively employ signaling mechanisms to convey their unique advantages. Drawing upon signaling theory and the literature on social entrepreneurship, this study conducts an empirical analysis based on a unique dataset of 11 369 social enterprises from the Global Accelerator Learning Initiative (GALI) from 2016 to 2019. The findings reveal that founders’ capital investment serves as a key signal that increases the likelihood of a social enterprise being selected by an accelerator. Further analysis shows that a single-founder structure and the possession of patents strengthen the signaling effect, whereas the level of internationalization in the enterprise’s home country can partially substitute for the signal of founder capital investment. This research not only deepens our understanding of social enterprise financing mechanisms and fills the gap in studies on accelerator selection, but also enriches the analytical framework of signaling theory from a multi-source signal fitting perspective, offering valuable theoretical and practical implications for both social enterprises seeking resources and accelerators making selection decisions.
Abstract: This paper examines the transition from employees to entrepreneurs and their subsequent innovation behaviors using data from the China Family Panel Survey(CFPS) and the Enterprise Survey of Innovation and Entrepreneurship in China(ESIEC). The analysis reveals that entrepreneurs’innovation activities are positively correlated with their research and management skills from previous occupations, but not with their external social skills. Furthermore, among the population of Chinese employees, individuals with higher research and management skills are less likely to become entrepreneurs, whereas those with stronger external social skills are more likely. Finally, improving the business environment significantly increases the entrepreneurial likelihood among individuals with higher research and management skills, which could also help explain the differences in entrepreneurial skill structures between China and the United States. From the micro perspective of the employee-employer transition among individuals with different occupational skill sets, this paper analyzes the mechanisms by which the business environment affects the overall innovation level in the economy, offering insights for policymaking aimed at accelerating the development of new quality productive forces.
Abstract: This paper constructs an indicator to evaluate the city-level business environment in China from 2011 to 2020. From the perspective of corporate bond issuance, the effect of the city business environment on financial asset pricing is examined. The results show that an improved city business environment can reduce bond issuance spreads for local firms. In addition, this effect becomes more pronounced following the acceleration of the bond market marketization (The breaking of rigid payment and the net-value transformation of the asset management products guided by the “New Asset Management Regulations”). Mechanism analysis reveals that optimizing the business environment significantly reduces business uncertainty and enhances the information transparency of local firms, thereby reducing the credit risk premium and liquidity premium of their bonds. Heterogeneity tests show the effects of the business environment on bond issuance spreads are more pronounced during periods of higher macroeconomic policy uncertainty, local government leadership transitions, and for longer-maturity bonds. Meanwhile, the different dimensions of business environment have varying impacts on bond issuance pricing. This study reveals that the business environment is a key factor in explaining the inter-regional differences in financial asset pricing and enriches research on its economic consequences by highlighting its role in enhancing the efficiency of regional financial resource allocation.
Abstract: Enhancing firm total factor productivity (TFP) is critical for achieving high-quality economic development. As a key application of financial technology (FinTech) in the real economy, supply chain finance (SCF) remains underexplored in its internal mechanisms for TFP improvement. Existing studies primarily focus on technological progress, credit constraints, and inclusive finance, leaving a gap in understanding the role of SCF depth. Using panel data from Chinese A-share listed manufacturing firms (2012-2021), this study examines how FinTech development affects firm TFP from the perspective of core enterprises. The results indicate that: 1) FinTech significantly improves firm TFP; 2) The effect is heterogeneous across firm types, with resource-processing industries, local state-owned enterprises, and private firms benefiting more prominently; 3) SCF depth mediates this relationship by alleviating short-term funding pressures, enhancing liquidity, and optimizing financial structures on both supply and sales sides. These findings provide empirical evidence for policymakers and practitioners to leverage FinTech and SCF for productivity growth in China.
Abstract: Digital financial platforms have created favorable conditions for asset managers to maximize their own interests by leveraging the flow effect. However, this development has also led to a significant deviation from their primary fiduciary duty of investing on behalf of clients. A prominent manifestation of this phenomenon is fund flow implantation: A novel strategy in which managers highlight the industry attributes of fund products to simultaneously cater to platform algorithms and investor preferences. As such, it represents a new form of agency conflict in the digital era. This study finds that fund flow implantation effectively attracts investor capital and contributes to fund size growth. Mechanism analysis reveals that this strategy aligns with the information display rules of digital financial platforms, leveraging popular industries and increased marketing expenditure to appeal to investors’salience-like preferences. However, its economic consequences include heightened investor risk exposure, diminished future returns, and a worsening misalignment of interests between funds and investors. These findings confirm that fund flow implantation intensifies agency conflicts, providing a critical policy basis for addressing the issue of “funds make money, but investors do not,” as well as for enhancing the regulation of digital financial platforms and the protection of investor rights.
Abstract: Trust is an essential informal system in human society, serving as the foundation for the smooth functioning of financial markets. The erosion of investor trust can impede the efficient transfer of information, leading to a decline in the accuracy and reliability of stock prices in the market. This paper employs the financial fraud filing as a shock to the trust system and finds that, although such filing event improves the quality of accounting information in the market, the resulting loss of trust causes share price synchronization among other companies in the same industry segment to increase significantly in the long run. The contagion effect is more pronounced in instances where individual investors exhibit low attention levels, demonstrate an inactive search for financial report information, exhibit a low level of internal corporate governance, and engage in low levels of investor communication. It is imperative that regulators proactively guide listed companies to communicate with investors in a two-way manner while enhancing enforcement of disclosure violations.
Abstract: The existing literature highlights a significant research gap regarding the influence of servitization in manufacturing on inter-firm performance. To address this gap, this study adopts a novel perspective focusing on risk-sharing mechanisms, exploring how servitization enables manufacturing service providers to collaboratively assume greater risks with their clients. Utilizing U.S. manufacturing data from 2003 to 2022, this research employs stock market excess returns as quantitative indicators for risk-sharing and risk exposure. Empirical analyses using large-scale panel data are conducted to validate these effects. The findings reveal that firms with higher degrees of servitization exhibit enhanced capabilities in sharing risks with their clients, thereby reducing the risks faced by the latter. However, it is important to note that the social embeddedness of manufacturers in the service sector may negatively impact this positive relationship. Specifically, manufacturers with higher levels of service embeddedness may experience a decline in their risk-sharing intensity with clients during the transition to servitization. This study not only addresses the research gap in the field of servitization from a supply chain management perspective but also advances the application of social embeddedness theory in strategic management practices within enterprises.
Abstract: This study focuses on the resource scheduling problem of the precooling service platform, aiming to provide technical methods for the post-harvest precooling issue of smallholders in China. Considering the time sensitivity of precooling demands and the cost-effectiveness of service operations, and incorporating both fixed precooling and mobile precooling resources, this problem is formulated as a multi-depot vehicle routing problem with heterogeneous service efficiencies and time windows. A mixed-integer linear programming multi-objective optimization model is formulated to minimize the scheduling cost of precooling services while also reducing precooling delay times. Furthermore, considering the heterogeneity of precooling resources, an EC-ALNS multi-objective optimization algorithm, based on an enhanced Box splitting method and an adaptive large neighborhood search algorithm, is developed to efficiently obtain an approximately accurate Pareto frontier for this problem. The effectiveness and advantages of the EC-ALNS are verified through comparisons with the CPLEX solver and two classical algorithms. Finally, a case study is conducted to validate the robustness of our model, and management implications are derived through numerical experiments and parameter sensitivity analysis under various order scenarios.
Abstract: With the development of online video industry, a new profit model (paid membership), and a new supply chain mode (account sharing mode) were emerged. However, the existing online video pricing theories and methods based on the traditional supply chain mode (buyout mode) are difficult to meet the needs of practical development. Therefore, we study the pricing strategies of paid membership video platforms under two different supply chain modes, and then analyze the impact of supply chain modes and video quality on the pricing, profit and demand of the paid membership video platform. The result shows that: the video platform will adopt “free to members”, “discount to members” and “symmetrical pricing” successively with the increase of video quality in the buyout mode, while only “discount to members” and “symmetrical pricing” will be adopted successively with the increase of video quality in the account sharing mode. Meanwhile, the selection strategy of the optimal supply chain mode is mainly determined by video quality. Further analysis indicates that the high copyright rate under the buyout mode has a negative impact on the development of the online video industry, and the account sharing mode can make up for the deficiency of the buyout mode. At the same time, the research shows that the paid membership video platform does not directly obtain VOD revenue from ordinary users, and its revenue structure is determined by the proportion of existing members. In addition, the results of extending the model to member-only videos prove the robustness of the main conclusions of the paper. The conclusion of the study can provide useful management implications for paid membership video platforms and online video industry.
Abstract: The blurred boundaries, temporary absence of regulation, and dynamic changes in the roles and interactions of members in the emerging field have led to the difficulty for actors with complementary resources in the field to form a clear perception of the "advanced" value proposition of platform enterprises, challenging the original logic of value co-creation within the platform ecosystem based on the premise of the comprehensible value proposition. In this vein, how platform enterprises promote the value co-creation in the context of emerging field has become an important theme that needs to be clarified in practice and theoretical research. Through the comparative analysis of two case companies, i.e., Weiyi and Xinye, this paper identifies two major value co-creation dilemmas in the platform ecosystem in the emerging field context, namely "ambiguous co-creation goals" and "ambiguous co-creation modes", which impede the complementors ' initiative to co-creating value in the focal platform ecosystem. Based on this, we further refines the strategic paths for platform enterprises to stimulate value co-creation of complementors in this context - the "traction" model with the core of explaining value proposition and the "boost" model with the core of co-creating value proposition. The identity positioning of platform enterprises as "leader of the ecosystem" or "partner of other complementors" is the core motive of their strategic actions. Overall, the theoretical model of "co-creation dilemma—identity position—strategic actions" is built, which is the driving mechanism of value co-creation in the platform ecosystem. Based on the characteristics of the emerging field, this paper proposes a strategic path for platform enterprises to promote ecological value co-creation under the premise of participants within the ecosystem have ambiguous perceptions of platform value proposition, and contributes to the research on value co-creation in platform ecosystems.
Abstract: An enterprise’s financial statements provide investors with highly verifiable and comparable information about its financial position, operating results, and cash flows, and this information plays an important role in company valuation, contract formation, and capital market supervision. The advent of big data, however, has presented many challenges for traditional financial statements in terms of integrity and timeliness due to strict reviews of information, requirements of accounting standards, and restrictions on the form and frequency of disclosure. Based on the valuation function and contract function of accounting information, this paper researches the elements and the methods of realization of the “Fourth Statement”. Then, this paper further proposes the potential application scenario of the “Fourth Statement” in company valuation, contract signing, and capital market supervision.
Abstract: We build a market microstructure model within the framework of Rational Expectations Equilibrium and deliberately factor uncertainty into our model so as to study from the perspective of uncertainty whether and how stock market information asymmetry would contribute to stock crash. Our model demonstrates that market information asymmetry does contribute to stock crash, and that the greater the information asymmetry, the deeper stocks would plunge, the greater the uncertainty in the market, the greater the impact information asymmetry would have on stock crash. We then calculate the probability of informed trading of A equities listed on the Shanghai and Shenzhen stock markets according to the relevant tick data from 2010 to 2015 and use the calculated probability of informed trading as a measure of information asymmetry of the Shanghai and Shenzhen stock markets. And we conduct empirical tests according to the calculated probability of informed trading to find that there exists a significant positive correlation between market information asymmetry and stock crash, and usually the greater the market information asymmetry, the deeper stocks would plunge. In addition, we also formulate uncertainty indexes for A equities listed on the Shanghai and Shenzhen stock markets, using the uncertainty indexes for measuring stock market uncertainty, and in the light of the uncertainty indexes we discover that market uncertainty tends to increase the impact information asymmetry would have on stock crash, i.e. the greater the uncertainty in the market, the greater the impact information asymmetry would have on stock crash. Our findings do not only add to the existing knowledge about the causes of stock crash, but also sheds new light on how to prevent abnormal volatility on stock markets.
Abstract: This paper analyzes the impact of convex incentives in delegated portfolio management to prices and volatility of the risky assets by using a theoretical model in continuous-time financial framework. First of all, we establish a multiple-stock dynamic equilibrium pricing model in which the institutional and retail investors have heterogeneous beliefs, and the institutional investors facing convex incentives which are associated with a benchmark portfolio's performance. Secondly, using the martingale method, we derive closed-form solutions for the risky asset’s equilibrium price and volatility. Finally, numerical results show that the stock in benchmark portfolio has higher price and volatility than the stock not in. The convex incentives to institutional investors can always boost the risky asset prices and the volatility of stock in benchmark portfolio. When institutional investors are more pessimistic than retail investors, the increase of convex incentives will reduce the volatility of the stock not in benchmark portfolio, and the increase of institutional market share will reduce the degree of bubble of stock not in benchmark portfolio.
Abstract: As an important and basic resource of social production and civil life, water plays a crucial role in constructing national ecological civilization and realizing healthy economic development. Based on the utilization efficiency of water resources and water pollution of Chinese listed firms during 2007-2017, this study examines the impact of the CEO's drought experience in the childhood on water protection performance. The findings show that the CEO's drought experience in the childhood (5-15 years old) is significantly positively associated with water protection performance, implying that the drought experience and risk awareness towards water imprint the CEO's behavior and improve water protection performance. In addition, CEOs' current perception of water shortage strengthens the positive effect of the CEO's drought experience in the childhood on water protection performance. Above results are still valid after a series of robustness tests and using the change model to address the potential endogeneity. Furthermore, results in additional tests show that the pollution control department has an intermediary effect between CEOs’ childhood drought experience and corporate water protection performance, the implementation of the Environmental Protection Law strengthens the positive effect of the CEO's drought experience in the childhood on water protection performance, and the positive relation between CEOs’ childhood drought experience and corporate water protection performance is more pronounced for firms in manufacturing and polluting industries.
Abstract: The investment strategy of mutual funds is the focus of common concern among academia, regulators and market participants. Based on the behavioral asset pricing theory, this paper quantifies fund investment strategies as the market sentiment sensitivity of portfolio returns and it is classified as sentiment catering strategy and contrarian strategy according to market conditions for the first time at the micro-level. To explore the systematic influence of investment strategy selection on fund flow, risk and manager’s effort by theoretical models and empirical tests, and analyze the influence mechanism of fund performance from the perspective of behavioral principal-agent. The result shows that, funds are more attractive to investors, especially individual investors when adopting the sentiment catering strategy, however, it will cause hidden infringements on the interests of investors, which is manifested by increased risks and reduced returns of the fund in the future, and fund managers achieve higher returns without having to pay more efforts. Further analysis shows that the passive laissez-faire behavior of fund managers only to please investors is an important reason for their poor performance; when the fund adopts the contrarian strategy, the effects are completely opposite. This study provides new approaches and enlightenment for the investment practice of small- and medium-sized, fund governance and supervision, and the explanation of fund market anomalies.
Abstract: This paper examines the effectiveness of the optimization and adjustment of state-owned capital layout from the perspective of value creation using the setting of Chinese central state-owned enterprises (CSOEs) M&As. The results show that the optimization and adjustment of state-owned capital layout has the effect of value creation, which can improve the efficiency of state-owned capital, but this effect only exists after the reform of the Third Plenary Session of the 18th CPC Central Committee. Further research shows that the value creation effect of state-owned capital layout optimization is heterogeneous. Compared with the CSOEs of specific functional and public service, the value creation effect of state-owned capital layout optimization is more significant in the commercial CSOEs, and the value creation effect of CSOEs through professional integration and holding merger is more significant. The study also confirm that the optimization of state-owned capital layout reduces the competition among CSOEs, and achieves the advantage of resource integration. Overall, this paper provides a new perspective for understanding the optimization of state-owned capital distribution, which has important practical guiding value for SASAC to promote the strategic reorganization of state-owned capital at microcosmic level and achieve the goal of state-owned economy.
Abstract: Based on the improved Greenwood et al. (2015) model, this paper studies China’s banking systemic risk caused by cross-border lending. The results show that: (1) Under the impact of cross-border lending, the systemic risk is mainly determined by the asset side’s shock, and China’s banking systemic risk has four stage characteristics. (2) Systemic risk is affected by risk exposure, institutional asset size, leverage and indirect correlation, and these factors play different roles in different shocks and different stages. As an external shock, the risk exposure is less important than the internal characteristic factors such as the scale of institutional assets and indirect correlation. (3) The increase of systemic risk caused by cross-border lending can lead to adverse changes of macroeconomic variables in the future, and the systemic risk’s index is effective.
Abstract: In the context of continuous economic downturn, China has launched a fiscal policy of tax and fee reduction in recent years. This paper studies the pricing problem of deposit insurance considering bank income tax and obtains the explicit solution of deposit insurance price. We also test the mechanism of bank income tax affecting deposit insurance price. It clearly shows that the premium per unit deposit decreases with the decrease of income tax rate, which proves the positive effect of tax and fee reduction policy on banks. The empirical results show that the increase of bank income tax rate will increase the deposit insurance rate by increasing the risk-taking level of the bank. The study in this paper provides theoretical basis and practical reference for further promoting the implementation of tax and fee reduction policies in the commercial bank system in the future.
Abstract: Based on the theory of price overadjustment and Pigou wealth effect, this paper first analyzes the dynamic mechanism of monetary policy on CPI from the theoretical level. It is found that the increase of money supply will not only directly increase CPI, but also indirectly affect CPI through the overshoot effect of asset prices. Secondly, markov zone transfer model is further introduced to analyze the zone system of monetary policy. Finally, TVP-SV-VAR model and NARDL model are used to measure the dynamic influence relationship of monetary policy on asset price and CPI from the perspective of time variation and asymmetry. The results show that: first, monetary policy has obvious characteristics of two zones of expansion and contraction. Second, in the short run, monetary policy has an overshoot effect on asset prices compared with CPI, while in the long run, monetary policy indirectly affects CPI through the Pigou vian intermediary effect of asset prices. Thirdly, monetary policy has asymmetric effects on both asset prices and CPI. The effect of expansionary monetary policy is smaller than that of contractionary monetary policy. Meanwhile, asset prices also have asymmetric effects on CPI, and the "loss aversion" effect is obvious.
Abstract: The investor irrationality in China"s stock market has always been important in asset pricing. In order to test the influence of investor irrational, Using stock trading data from 1997 to 2018, this paper builds an irrational belief variable based on the heterogeneous belief variable, and empirically explores the influence on stock anomalies. The results show that irrational beliefs have negative predictive power for future returns. To test the variable to explain the anomalies returns ability, this paper builds a belief factor model including market factor (MKT), size factor (SMB) and belief factor(FMG). And we copy the 102 anomalies of market friction, momentum-reversed, value-growth, investment, profits and intangible assets. Finally, this paper uses the CAPM model, FF-5 model, CH-3 model and B-3 model and finds that belief factor model has relative advantage from the results of both adjust alpha and significance of GRS tests. This suggests that irrational belief may be the main factor of stock anomalies.
Abstract: We proposed a time-varying higher-order co-moment estimate based on a single factor time-varying semi-nonparametric (SF-TVSNP) model. The model specification, model estimation and model selection approaches are given in this paper. The single factor model can efficiently reduce “the curse of dimensionality” problem in the time-varying higher-order co-moments estimation, and the semi-parametric structure can improve the robustness of the SF-TVSNP model. The empirical studies show that the SF-TVSNP model can effectively capture the time-varying structure of higher-order co-moments of asset returns, and it is more suitable for the latent structure of asset returns. High-dimensional dynamic portfolio based on the SF-TVSNP model can generate higher and stable economic value, which is further confirmed by robust analysis.
Abstract: Revealing the subject research hotpots and thematic evolutionary trends have been the focus of the academic community. Using 12,920 papers published in 46 international authoritative journals from the year 2010 to 2019, this study explores the research progress and development trends of Management Science and Engineering (MSE) subject in China using the author keywords of the papers. The results show that: first, the MSE research hotspots of China have changed significantly; second, the MSE research hotspots of China have fully considered its own actual scenario, and show a trend of keeping in line with the global research hotspots; third, the MSE of China has maintained a stable expansion in core research fields, and have made significant shifts in new research themes; fourth, the research hotspots of the main MSE subfields of China focus on the topics such as China, pricing, dynamic programming, social networks and supply chain management.
Abstract: The technical default of urban investment?bonds and the default of urban?investment companies' non-standard financing have broken the long-standing “belief” in the rigid payment of urban investment?bonds, and the credit risk has become the focus of attention. Under the background of the implementation of the urban agglomeration strategy in China, based on the gravitational network of production factors within the Yangtze River Delta Urban Agglomeration, this paper empirically analyzes the impact of urban agglomeration spatial spillover on the credit risk of urban investment bonds. The study finds that: 1) There is a spatial overflow of credit risk within the urban agglomeration, and the credit risk premiums of urban investment?bonds in different cities fluctuate in the same direction. 2) The financial development of other cities especially peripheral cities is positive externality, which can reduce the risk. 3) There may be negative externalities in the economic development of urban agglomerations especially the peripheral cities, which will increase the credit risk. It provides a theoretical and factual basis for local governments to make effective use of the development opportunities of urban agglomeration, reasonably formulate fiscal policies and prevent and control regional financial systemic risks.
Abstract: FinTech is a comprehensive term that encompasses various financial activities aimed at promoting financial services to be more convenient,cheaper,more inclusive,and safer in virtue of mobile internet,blockchain,artificial intelligence,big data,and other ways of scientific and technological innovations. It tightly combines financial services with application scenarios in a digitized,intelligent,and secure way. It accomplishes the goals of financial service suppliers for liquidity,profitability,and security,as well as meeting the functional demands of financial service demanders for paying,financing,investment,and trading. Starting from the analysis of mobile internet,big data,artificial intelligence,blockchain,and other emerging technologies and the financial innovations promoted by them,this paper takes the three major business processes of financial services as the breakthrough point. It combs the documents from three aspects: payment and settlement,credit and financing,and asset management services. In addition,the study considers and reflects financial regulation from four perspectives: the reformation of the regulatory concepts,the expansion of regulatory content,the reconstruction of regulatory mechanism,and the innovation of regulatory technology. Finally,it discusses prospects for future research.
Abstract: Given the increasing presence of female directors in firms,the roles they play in leading firms’decision-making have attracted extensive attention. However,little is known about why firms choose to appoint female directors at boards. Based on the framework of awareness-motivation-capability( AMC) ,this paper employs fuzzy-set qualitative comparative analysis method. This research investigates the configuration effects of seven congruent factors,including industry female director ratio,female leader,diversification,gender equality culture,regional marketization,financial performance,as well as their causal complex mechanisms on the appointment of female directors. The results suggest that the driving mechanisms behind the presence of a high number of female directors can be categorized into four types: “pressure and atmosphere driver”,“pressure and capability driver”,“pressure and desirability driver”and“desirability and capability driver”. Further, female leaders and industry female director ratio are critical driving factors. There is an asymmetric causal relationship between the mechanisms of high-degree female directors and those of non-high-degree female directors.
Abstract: The application of collaborative delivery systems based on trucks and drones have attracted more and more attention from the academia. This study investigates a routing problem of multiple trucks and drones cooperative delivery, and formulates a mixed-integer programming model with the objective of minimizing the total cost. A solution method based on column generation is proposed to solve the model. An accelerating technique based on variable neighborhood search is also embedded in the solution method to reduce the computation time. Numerical experiments are also conducted to validate the effectiveness of the proposed model and efficiency of the proposed solution method. Some potentially useful managerial implications are also outlined based on some sensitivity analysis.
Abstract: Two pillar policies constitute a crucial part of the post crisis financial stabilization framework. As regards ameliorating the two pillar regulatory framework and mitigating banking sector risks, it is crucial to examine the effect of two pillar policies on bank risk taking in a systematical way. Hence, this paper analyzes the transmission mechanism between the two pillar policies and bank risk taking from a micro perspective. Based on this, an empirical study is conducted using bank level panel data from 262 commercial banks in China from 2007 to 2020, to test the effects. The findings are as follows: Contractionary monetary policy and macro prudential regulation both exert a marginal reducing effect on bank risk taking, while loose monetary policy exerts a risk spillover effect on banks, which can be mitigated by macro prudential regulation. Mechanism analysis shows that macro prudential regulation mitigates the spillover effect of monetary policy by alleviating the negative impact of low interest rate monetary policy on bank charter value and by attenuating the procyclical adjustment of bank leverage, thereby performing a coordinated risk abating effect. In terms of cross sectional dimension, interbank connection exerts an asymmetric influence on the coordination effect of two pillar policies on bank risk taking. In a monetary easing environment, an increase in the interbank connection level weakens the mitigating effect of macro prudential regulation on the risk spillover generated by loose monetary policy. In a monetary tightening environment, an increase in interbank connection level worsens the weakening effect of macro prudential regulation on the risk reducing effect of contractionary monetary policy. Besides, two pillar policies generate a better coordinated risk abating effect on larger banks or those with a lower proportion of non interest rate revenue. In terms of the time dimension, interest rate marketization strengthens the coordinated risk abating effect of two pillar policies, while increased monetary policy uncertainty weakens that effect.
Abstract: Since the multifractal detrended partial correlation analysis method (MF DPXA) cannot measure the asymmetric dependence relationship under different trends (upward and downward), this paper proposes the multifractal asymmetric detrended partial cross correlation analysis method (MF ADPXA). Furthermore, the paper proposes a removing factors time delayed detrended cross correlation analysis (ETD DCCA) to study the risk transmission direction between stock markets. Taking Shanghai Component Index, Shenzhen Component Index, and Hang Seng Index as research objects, this paper empirically analyzes the asymmetric cross correlation and risk transmission between pairwise stock markets after removing the common influencing factors. The results show that, after removing the influence of one stock market, the long memory cross correlation between the other two stock markets is weak. When the return trend is upward, the long memory cross correlation increases, and when the return trend is down, the cross correlation shows anti persistence. The degree of asymmetry is greater when the fluctuation is large. The local cross correlation between the pairwise stock markets shows a weakening trend over time. As the time lag increases, the anti persistent cross correlation between the two two stock markets is enhanced. The risk of the Shenzhen Component index is mainly transmitted to the Shanghai Component Index, and the risk of the Shanghai Component Index is mainly transmitted to the Hang Seng Index. The Hang Seng Index has a stronger impact on the Shenzhen Component Index. This study has implications for re understanding the intrinsic dependent structure and risk transmission of Shanghai, Shenzhen, and Hong Kong stock markets, cross market portfolio, and risk management.
Abstract: Listed companies’violations have been an important issue that attracts the attention of the capital market. While studying the causal relationship between single-dimensional variables and this issue is crucial,constructing an effective holistic prediction model is also of great significance. This paper constructs a prediction model of listed companies’violations based on important company characteristics and managerial individual characteristics from the perspective of internal governance. Using a sample of Chinese A-share listed companies from 2008 to 2019,this study introduces two machine learning algorithms,LightGBM and SHAP,to examine the predictive ability,importance ranking,and prediction mode of the two types of characteristics on violation behaviors. The results show that the model can predict corporate violations to a certain extent,and corporate characteristics have a greater impact on the prediction than managerial individual characteristics. Specifically,higher information transparency of listed companies,higher net profit margin of total assets,lower asset-liability ratio,higher managerial shareholding ratio,lower performance volatility,and higher analyst attention are associated with a lower tendency for the model to predict violations. In addition,the model predicts an increased tendency for violations when executives are young and when the chairman and CEO roles are combined. Moreover,most corporate characteristics and managerial individual characteristics exhibit a non-linear relationship in predicting corporate violations,which is consistent with the findings of traditional theoretical and empirical studies. Overall,our study enriches the research on the characteristics of corporate executives in China from a predictive perspective and provides empirical evidence for regulatory authorities and investors to improve supervision and investment efficiency and for companies to optimize internal governance mechanisms.
Abstract: Supply chain stability is an important component of national economic security. As a common item in supply chain purchase and sale transactions, the allowance for doubtful accounts is particularly noteworthy for its potential impact on the duration of supply chain relationships. The paper examines the impact of customer allowance for doubtful accounts on the duration of supply chain relationships, using a research sample of A share listed companies on Shanghai and Shenzhen Stock Exchanges from 2008 to 2022. The study finds that customer allowance for doubtful accounts is significantly negatively related to the duration of the supply chain relationship. Mechanism tests indicate that customer allowance for doubtful accounts increases firms’finance, credit, and market risks through the supply chain risk contagion effect, prompting firms to interrupt current supply chain relationships due to risk aversion motivations. Further analysis shows that the negative impact of customer allowance for doubtful accounts is more significant in samples with lower prudence in allowance for doubtful accounts, higher downstream discourse power of suppliers, lower upstream discourse power of customers, and lower supply chain relationship survivability. Economic policy uncertainty exacerbates the negative impact of customer allowance for doubtful accounts on the duration of supply chain relationships, while a good business environment can weaken this adverse effect. The paper enriches the research related to the supply chain risk contagion effect and the duration of supply chain relationships from the perspective of customer allowance for doubtful accounts, and also has policy implications for enhancing supply chain resilience and risk resistance, as well as maintaining supply chain security and stability.
Abstract: In order to stimulate the technological innovation of new energy enterprises, the Chinese government has issued a large number of relevant subsidy policies. However, the complex influence mechanism of government subsidies on technological innovation of new energy enterprises is still unclear, and the incentive effect has not yet reached a consensus. Therefore, this paper focuses on the data of China’s A-share listed new energy manufacturing enterprises from 2011 to 2020, and constructs a two-way fixed effect model of panel data to investigate the influence of government subsidies on technological innovation of new energy enterprises. The findings are as follows: 1) Government subsidies generally promote the technological innovation of new energy enterprises. In the sample interval, for every 1〖WTXT〗%〖WTBZ〗 increase in government subsidies, the patent applications of new energy enterprises increase by 0.82〖WTXT〗%〖WTBZ〗; 2) R&D investment and innovative human capital play a partial intermediary role in the process of government subsidies to promote technological innovation of new energy enterprises, while enterprise financialization plays a moderating effect which enhances the promoting role of government R&D subsidies to the technological innovation of new energy enterprises; 3) There are significant differences between R&D and non-R&D subsidies on technological innovation of new energy enterprises: for every 1〖WTXT〗%〖WTBZ〗 increase in R&D subsidies in the short term, the patent applications of new energy enterprises increase by 1.064〖WTXT〗%〖WTBZ〗, and the relationship between R&D subsidies and technological innovation of new energy enterprises shows an inverted U-shape in the long term; for every 1〖WTXT〗%〖WTBZ〗 increase in non-R&D subsidies, the patent applications of new energy enterprises increase by 0.61〖WTXT〗%〖WTBZ〗; 4) The promoting effect of government subsidies on technological innovation of new energy enterprises is significant in the areas with high intellectual property development level, but not in the areas with low intellectual property development level. These research results will provide powerful decision-making reference for the government to formulate new energy industry policies and new energy enterprises to make good use of government subsidies.
Abstract: Two pillar policies constitute a crucial part of the post crisis financial stabilization framework. As regards ameliorating the two pillar regulatory framework and mitigating banking sector risks, it is crucial to examine the effect of two pillar policies on bank risk taking in a systematical way. Hence, this paper analyzes the transmission mechanism between the two pillar policies and bank risk taking from a micro perspective. Based on this, an empirical study is conducted using bank level panel data from 262 commercial banks in China from 2007 to 2020, to test the effects. The findings are as follows: Contractionary monetary policy and macro prudential regulation both exert a marginal reducing effect on bank risk taking, while loose monetary policy exerts a risk spillover effect on banks, which can be mitigated by macro prudential regulation. Mechanism analysis shows that macro prudential regulation mitigates the spillover effect of monetary policy by alleviating the negative impact of low interest rate monetary policy on bank charter value and by attenuating the procyclical adjustment of bank leverage, thereby performing a coordinated risk abating effect. In terms of cross sectional dimension, interbank connection exerts an asymmetric influence on the coordination effect of two pillar policies on bank risk taking. In a monetary easing environment, an increase in the interbank connection level weakens the mitigating effect of macro prudential regulation on the risk spillover generated by loose monetary policy. In a monetary tightening environment, an increase in interbank connection level worsens the weakening effect of macro prudential regulation on the risk reducing effect of contractionary monetary policy. Besides, two pillar policies generate a better coordinated risk abating effect on larger banks or those with a lower proportion of non interest rate revenue. In terms of the time dimension, interest rate marketization strengthens the coordinated risk abating effect of two pillar policies, while increased monetary policy uncertainty weakens that effect.
Abstract: The application of collaborative delivery systems based on trucks and drones have attracted more and more attention from the academia. This study investigates a routing problem of multiple trucks and drones cooperative delivery, and formulates a mixed-integer programming model with the objective of minimizing the total cost. A solution method based on column generation is proposed to solve the model. An accelerating technique based on variable neighborhood search is also embedded in the solution method to reduce the computation time. Numerical experiments are also conducted to validate the effectiveness of the proposed model and efficiency of the proposed solution method. Some potentially useful managerial implications are also outlined based on some sensitivity analysis.
Abstract: FinTech is a comprehensive term that encompasses various financial activities aimed at promoting financial services to be more convenient,cheaper,more inclusive,and safer in virtue of mobile internet,blockchain,artificial intelligence,big data,and other ways of scientific and technological innovations. It tightly combines financial services with application scenarios in a digitized,intelligent,and secure way. It accomplishes the goals of financial service suppliers for liquidity,profitability,and security,as well as meeting the functional demands of financial service demanders for paying,financing,investment,and trading. Starting from the analysis of mobile internet,big data,artificial intelligence,blockchain,and other emerging technologies and the financial innovations promoted by them,this paper takes the three major business processes of financial services as the breakthrough point. It combs the documents from three aspects: payment and settlement,credit and financing,and asset management services. In addition,the study considers and reflects financial regulation from four perspectives: the reformation of the regulatory concepts,the expansion of regulatory content,the reconstruction of regulatory mechanism,and the innovation of regulatory technology. Finally,it discusses prospects for future research.
Abstract: The rapid development of artificial intelligence (AI) means that humans are no longer the only subject of knowledge generation, so how to achieve effective collaborative learning between humans and AI becomes a focal issue. In the practice of human AI synergy to achieve organizational learning, this paper explores the impact mechanism of adding AI on the existing organizational learning approach. Based on a multi subject modeling and simulation approach, the paper finds that: 1) When environmental dynamics are not taken into account, high learning ability AI has a substitution effect of on organizational members. On the one hand, the exploratory learning needs of organization members are weakened, and on the other hand, the exploitative learning of organization is replaced. 2) The degree of collaboration between human and AI has a nonlinear effect on organizational knowledge level. When the organization is dominated by exploitative learning, the growth rate of organizational knowledge will slow down gradually as the synergy degree increases. When the organization is based on exploratory learning, only a higher degree of collaboration can improve organizational knowledge. 3)In the scenarios of high uncertainty, high learning ability AI has a complementary effect with organization members. The improvement of the organization’s knowledge level depends on more exploratory learning by the organization members, and the new knowledge generated by the cooperation between the organization members and AI needs to be quickly transformed into the organization’s routine. This paper breaks through the implicit assumption that human is the only learner in an organization, and reveals the characteristics and rules of collaborative learning between human and AI in different scenarios based on simulation, which provides enlightenment for promoting the rational allocation of scarce resources and the improvement of organizational learning performance in the era of digital economy.
Abstract: The supply chain is a core channel for inducing knowledge spillover effects among companies, but studies onthe micro-mechanism of knowledge spillover along supply chain of green technology innovations are scarce. From the perspective of supply chain relationship, this paper systematically examines the impact of manufacturing customer companies’ green technology innovations on supplier companies in both “quantity” and “quality” dimensions, and further reveals the chain reaction in supplier company performance. This study finds that customer companies’ green technology innovations help improve green innovations by supplier companies both qualitatively and quantitatively. The heterogeneity analysis shows that supply chain spillover effects of green technology innovations are more pronounced in case of higher customer concentration, non-state-owned enterprises, or southern regions. Further investigations reveal that customer companies’green technology innovations also have spillover effects on supplier companies’future economic and environmental performance. This paper sheds new light on the implicit contribution of supply chain spillover effects in green technology innovations amongst Chinese manufacturing companies, which has theoretical and practical significance for the transformation and upgrading of Chinese manufacturing industries and for smoothing the domestic circulation.
Abstract: This paper predicts stock returns in the Chinese market by using an improved autoencoder machine learning approach and financial big data encompassing approximately one hundred firm characteristics. The findings demonstrate that the autoencoder factor can extract predictors from a large amount of information containing company characteristics to forecast returns and can achieve significant excess returns in the cross sections. Additionally, the analysis on the significance of factors reveals that the anomalies are time varying in the Chinese stock market. Additionally, the predictive efficiency of the autoencoder method correlates with macroeconomic conditions and economic policies. The autoencoder based long short portfolios can effectively mitigate market risk especially during substantial market bubbles and heightened speculative periods, demonstrating well resilience to the shifts of fiscal and monetary policy induced economic conditions.
Abstract: The essence of recommender systems is to model the implicit preferences in consumer behavior. The human behavior is inseparable from psychology, and there are rich internal motives behind the superficial behavior. However, the current studies mainly focus on the behavioral data modeling, rarely involving the internal psychological activities and the information processing process of decision-making. Therefore, this paper studied a new idea of recommender systems by introducing AIDMA decision model from the perspective of consumer decision journey. A new deep review-based recommender system is proposed, which applies the AIDMA decision journey into the deep learning framework. Experiments showed that the recommendation performance of the proposal is significantly better than the state-of-the-art methods. This paper follows the big data-driven research paradigm of “model driven+data-driven”, realizing in-depth methodological innovation with theoretical support.
Abstract: As e-commerce applications evolve from breadth to depth, personalization has become an important direction for e-commerce service innovation. In order to accurately predict consumers’personalized demand, this paper proposes a personalized demand prediction method with a limited preference constraint by integrating information of product description texts and display images. Inspired by the hypothesis of limited attention, this paper models the limited personalized preference of consumers, and combines the image and text features to construct a Sparse Text-Image Linked Topic Model with a limited preference constraint. The model predicts the individual demands of consumers through group interest modeling, individual preference modeling, and purchase decision modeling. Experiments on the Amazon public data set show that the proposed model can effectively predict group interests and personalized preferences of consumers. The integration of text and image information improves the interpretability of personalized demand prediction.
Abstract: Based on mental accounting theory, this research explores the effect of windfall money on purchase intention for new products through six studies. The results show that consumers who receive unexpected windfall money are more willing to purchase new products than those who do not receive unexpected windfall money (Studies 1a, 1b, and 2). Moreover, perceived risk is the underlying mechanism (Studies 3a and 3b). Product involvement plays a moderating role: The effect of windfall money on purchase intention disappears for high involvement new products but persists for low involvement new products (Study 4). This research expands the research scope of windfall money, enriches the influencing factors of purchase intention for new products, and provides evidence for companies to present the discount information.
Abstract: Digital transformation has fundamentally reshaped the landscape of traditional industries, necessitating institutional entrepreneurship to overcome existing constraints. Despite its significance, the process of institutional entrepreneurship during digital transformation remains underexplored in current literature. This study leverages institutional entrepreneurship theory and enterprise survey data to investigate how digital leadership impacts digital transformation performance. Our findings reveal that digital leadership significantly enhances digital transformation outcomes by fostering institutional change activities. Furthermore, the capability for information search is found to positively moderate the relationship between digital leadership and institutional change activities. By integrating institutional entrepreneurship theory into the realm of digital transformation, this research broadens the theoretical framework and offers fresh insights. It also advances the application and development of institutional entrepreneurship theory within the context of digital transformation, providing valuable guidance for enterprises seeking to improve their digital transformation performance.
Abstract: This paper examines the static and dynamic risk spillover effects of global financial markets from the time-frequency perspective and network connection respectively. It also analyzes the optimal investment strategies of pairwise portfolios to provide reference for investors’risk management. The results show that 21.1〖WTXT〗%〖WTBZ〗 of the global financial market shocks are caused by risk spillovers from external financial markets, and the risk spillovers are mainly concentrated in the short and medium term. The financial risk events exhibit characteristics of short-term risk spillover index rising first, and then the medium and long-term risk spillover index gradually rising. From the network connection perspective, in the short term, the financial market risk spillovers show the characteristics of the same type of market aggregation and regional aggregation.In the long-term, risk spillovers across different financial markets are more widespread. Finally, the paper offers some policy suggestions for improving China’s financial risk prevention system.
Abstract: Listed companies’violations have been an important issue that attracts the attention of the capital market. While studying the causal relationship between single-dimensional variables and this issue is crucial,constructing an effective holistic prediction model is also of great significance. This paper constructs a prediction model of listed companies’violations based on important company characteristics and managerial individual characteristics from the perspective of internal governance. Using a sample of Chinese A-share listed companies from 2008 to 2019,this study introduces two machine learning algorithms,LightGBM and SHAP,to examine the predictive ability,importance ranking,and prediction mode of the two types of characteristics on violation behaviors. The results show that the model can predict corporate violations to a certain extent,and corporate characteristics have a greater impact on the prediction than managerial individual characteristics. Specifically,higher information transparency of listed companies,higher net profit margin of total assets,lower asset-liability ratio,higher managerial shareholding ratio,lower performance volatility,and higher analyst attention are associated with a lower tendency for the model to predict violations. In addition,the model predicts an increased tendency for violations when executives are young and when the chairman and CEO roles are combined. Moreover,most corporate characteristics and managerial individual characteristics exhibit a non-linear relationship in predicting corporate violations,which is consistent with the findings of traditional theoretical and empirical studies. Overall,our study enriches the research on the characteristics of corporate executives in China from a predictive perspective and provides empirical evidence for regulatory authorities and investors to improve supervision and investment efficiency and for companies to optimize internal governance mechanisms.
Abstract: With the emergence of new consumer behaviors and the continuous awakening of demand individuation on the service demand side, the innovation model of the service supply side needs to be reconstructed urgently. Deep digitalization represented by the Internet has become a new engine to bridge the “service divide”. This article focuses on the healthcare industry that is deeply integrated with the “Internet +” trend. It selects the service model cases of Xiamen “healthcare+Internet” and WeDoctor “Internet+healthcare”, and systematically explores the service reshaping mechanism that bridges the service divide based on digital empowerment. The study found that the service divide can be deconstructed into three aspects: information asymmetry, resource mismatch, and data islands. The process of service reshaping based on digital empowerment is the key path to bridging the service divide, which could be mainly manifested in the reshaping process of service design, service delivery and service interaction. The service reshaping mechanism of “healthcare+Internet” and “Internet+healthcare”follows the service digitization logic and digital servitization logic respectively. Specifically, the former focuses on service-dominant logic and the transformation of the service nature based on digital technology, while the latter focuses on the application and innovative diffusion of digital technology. The theoretical framework finally formed in this article can contribute to the theoretical gap caused by the existing literature on the path of bridging the service divide. The logic of service digitization and digital servitization, based on the service reshaping mechanism under digital empowerment, further deepens the exploration of the theoretical laws behind the deep integration of digital technology and service fields.
Abstract: Will the digital transformation of firms be affected by policy uncertainty? This paper investigates the mechanisms by which policy uncertainty affects corporate digital transformation behavior through a theoretical model. Based on this, this paper uses the data of China’s A-share listed companies to conduct an empirical study on the relationship between policy uncertainty measured by local government official changes and corporate digital transformation. The results show that the increase in policy uncertainty can significantly impede the process of digital transformation. In addition, the relationship between policy uncertainty and digital transformation is moderated by the professional background of officials and corporate financial constraints. This paper provides evidence for better driving the digital transformation of Chinese firms.
Abstract: This paper addresses the common joint replenishment and delivery (JRD) problem that occurs in a multi-item inventory system. An ε-optimal algorithm and a dual lower bound are proposed via deeply analyzing the mathematical properties of the model. The randomized numerical experiments show that the proposed ε-optimal algorithm outperforms the existing meta heuristics both in terms of both accuracy and efficiency, and the largest increase in accuracy can reach 31〖WTXT〗%〖WTBZ〗. The dual lower bound is very tight, with the gap averaging below 0.84〖WTXT〗%〖WTBZ〗. Moreover, the proposed ε-optimal algorithm is also very fast, and a 100-item instance can be solved in twenty-three seconds. In addition, the time complexity of the ε-optimal algorithm is analyzed. The ε-optimal algorithm can achieve O(n) polynomial-time complexity under real-world situations, which enriches the algorithmic design theory of the JRD research. Finally, the effect of coordinated delivery is analyzed. Experiments show that coordinated delivery can achieve cost reduction when the inventory management level of the central warehouse is higher than that of the retailers.
You are the th visitor
Address:Room 908, Building A, 25th Teaching Building, Tianjin University, 92 Weijin Road, Nankai District, Tianjin Postcode:300072
Telephone:022-27403197
Email:jmsc@tju.edu.cn