Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical...Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.展开更多
Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision p...Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.展开更多
Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to...Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.展开更多
The National Independent Innovation Demonstration Zone has been assigned the unique mission of demonstrating and leading national innovation and playing a key supportive role in enhancing green innovation.Based on the...The National Independent Innovation Demonstration Zone has been assigned the unique mission of demonstrating and leading national innovation and playing a key supportive role in enhancing green innovation.Based on the sample data of A-share listed companies in China from 2007 to 2021,we apply a multi-period difference-in-differences model to analyze whether the implementation of the National Independent Innovation Demonstration Zone policies plays a leverage effect or a crowd out effect on the green innovation efficiency of enterprises and systematically test the regulatory mechanism of government grants and media attention in the process of this influence.The empirical results show that the imple-mentation of the National Independent Innovation Demonstration Zone policies has a positive impact on the green innovation efficiency of enterprises and that the green innovation induced by this reform is not the leverage effect of additional R&D investment on the basis of the existing innovation activities of enterprises but rather the result of the reallocation of resources to crowd out existing non-green innovation.It is further found that government grants and media attention positively moderate the positive driving effect of National Independent Innovation Demonstration Zone policies on the green innovation efficiency of enterprises.展开更多
The automatic diagnosis of depression plays a crucial role in preventing the deterioration of depression symptoms.The interview-based method is the most wildly adopted technique in depression diagnosis.However,the siz...The automatic diagnosis of depression plays a crucial role in preventing the deterioration of depression symptoms.The interview-based method is the most wildly adopted technique in depression diagnosis.However,the size of the collected conversation data is limited,and the sample distributions from different participants usually differ drastically.These factors present a great challenge in building a decent deep learning model for automatic depression diagnosis.Recently,large language models have demonstrated impressive capabilities and achieved human-level performance in various tasks under zero-shot and few-shot scenarios.This sheds new light on the development of AI solutions for domainspecific tasks with limited data.In this paper,we propose a two-stage approach that exploits the current most capable and cost-effective language model,ChatGPT,to make a depression diagnosis on interview-based data.Specifically,in the first stage,we use ChatGPT to summarize the raw dialogue sample,thereby facilitating the extraction of depression-related information.In the second stage,we use ChatGPT to classify the summarised data to predict the depressed state of the sample.Our method can achieve approximately 76%accuracy with a text-only modality on the DAIC-WOZ dataset.In addition,our method outperforms the performance of the state-of-the-art model by 6.2%in the D4 dataset.Our work highlights the potential of using large language models for diagnosis-based depression diagnosis.展开更多
To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game mod...To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.展开更多
To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with prof...To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.展开更多
This research investigates the influence of loneliness on consumers’preference for high-calorie foods,addressingthe dual epidemics of loneliness and obesity.It explores how the need for warmth mediates this relations...This research investigates the influence of loneliness on consumers’preference for high-calorie foods,addressingthe dual epidemics of loneliness and obesity.It explores how the need for warmth mediates this relationship and proposesan effective intervention to alter consumers’beliefs about the role of food.Employing one survey and three experiments,the study examines the connection between loneliness and preference for high-calorie foods,with the methodologyincluding linear regression analysis,analysis of variance(ANOVA),and mediation analysis.These findings demonstratethat loneliness significantly increases consumers’preference for high-calorie foods,with the need for warmth serving as akey mediating factor.The results further suggest that changing consumers’beliefs about food can serve as an effective andlow-cost intervention to mitigate this preference.This research advances the theoretical understanding of the impact ofloneliness on consumer behavior and offers a practical behavioral intervention strategy of significant value for governments,non-governmental organizations(NGOs),and companies,aiming to combat obesity and improve public health.展开更多
The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for ...The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for EV adoption.This study develops a model based on heuristic and systematic information processing,examining the impacts of factors such as perceived risk,information need,and experience and knowledge on users’utilization of online electric vehicle carhailing services.The results indicate that users’experience and knowledge increase their information need and promote both heuristic and systematic processing,leading to positive attitude change,although they don’t significantly affect perceived risk.Perceived risk increases information need and supports supports systematic processing but negatively impacts attitude change.Greater information enhances systematic processing and attitude change.Perceived risk and information need do not affect attitude change via heuristic processing.Finally,the paper concludes with implications and directions for future research.展开更多
文摘Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.
基金supported by the National Nature Science Foundation of China(71771201,72531009,71973001)the USTC Research Funds of the Double First-Class Initiative(FSSF-A-240202).
文摘Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.
文摘Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.
基金supported by the National Natural Science Foundation of China(72474034)the Young Elite Scientists Sponsorship Program by SAST(20240123)+1 种基金Humanities and Social Science Fund of Ministry of Education of China(21YJC630037,21YJC630057)Social Science Foundation of Xi’an(25JX218).
文摘The National Independent Innovation Demonstration Zone has been assigned the unique mission of demonstrating and leading national innovation and playing a key supportive role in enhancing green innovation.Based on the sample data of A-share listed companies in China from 2007 to 2021,we apply a multi-period difference-in-differences model to analyze whether the implementation of the National Independent Innovation Demonstration Zone policies plays a leverage effect or a crowd out effect on the green innovation efficiency of enterprises and systematically test the regulatory mechanism of government grants and media attention in the process of this influence.The empirical results show that the imple-mentation of the National Independent Innovation Demonstration Zone policies has a positive impact on the green innovation efficiency of enterprises and that the green innovation induced by this reform is not the leverage effect of additional R&D investment on the basis of the existing innovation activities of enterprises but rather the result of the reallocation of resources to crowd out existing non-green innovation.It is further found that government grants and media attention positively moderate the positive driving effect of National Independent Innovation Demonstration Zone policies on the green innovation efficiency of enterprises.
基金supported by the Science and Technology Innovation 2030 Project of China(2021ZD0202600).
文摘The automatic diagnosis of depression plays a crucial role in preventing the deterioration of depression symptoms.The interview-based method is the most wildly adopted technique in depression diagnosis.However,the size of the collected conversation data is limited,and the sample distributions from different participants usually differ drastically.These factors present a great challenge in building a decent deep learning model for automatic depression diagnosis.Recently,large language models have demonstrated impressive capabilities and achieved human-level performance in various tasks under zero-shot and few-shot scenarios.This sheds new light on the development of AI solutions for domainspecific tasks with limited data.In this paper,we propose a two-stage approach that exploits the current most capable and cost-effective language model,ChatGPT,to make a depression diagnosis on interview-based data.Specifically,in the first stage,we use ChatGPT to summarize the raw dialogue sample,thereby facilitating the extraction of depression-related information.In the second stage,we use ChatGPT to classify the summarised data to predict the depressed state of the sample.Our method can achieve approximately 76%accuracy with a text-only modality on the DAIC-WOZ dataset.In addition,our method outperforms the performance of the state-of-the-art model by 6.2%in the D4 dataset.Our work highlights the potential of using large language models for diagnosis-based depression diagnosis.
基金supported by the National Natural Science Foundation of China(71973001).
文摘To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.
基金supported by the National Natural Science Foundation of China(72474034,72104034)Humanities and Social Science Fund of the Ministry of Education of China(21YJC630037,22XJC910001)China Postdoctoral Science Foundation(2022T150072)。
文摘To address the charging infrastructure challenges associated with slow electric vehicle(EV)industry growth,this study investigates the collaboration between private charging-pile-sharing platforms struggling with profitability and automotive companies.This collaboration is crucial,as it demands a balanced price and service quality management due to consumer expectations.This paper introduces a Stackelberg game model to explore the relationship between a charging platform and an automotive company.Through numerical analysis,we assess how this cooperation might improve the platform’s efficiency and benefit society,potentially overcoming existing industry hurdles.Our findings indicate that such partnerships could benefit all parties involved,despite possible negative environmental impacts.However,after collaborat-ing,platforms may increase consumer prices and payments to suppliers,potentially lowering service quality for brand-associated consumers due to a compromise between shorter waiting times and service quality.This research offers valu-able insights for stakeholders on the effects of cooperation,enabling better strategic decisions in the EV charging sector.
基金supported by the National Natural Science Foundation of China(72072169).
文摘This research investigates the influence of loneliness on consumers’preference for high-calorie foods,addressingthe dual epidemics of loneliness and obesity.It explores how the need for warmth mediates this relationship and proposesan effective intervention to alter consumers’beliefs about the role of food.Employing one survey and three experiments,the study examines the connection between loneliness and preference for high-calorie foods,with the methodologyincluding linear regression analysis,analysis of variance(ANOVA),and mediation analysis.These findings demonstratethat loneliness significantly increases consumers’preference for high-calorie foods,with the need for warmth serving as akey mediating factor.The results further suggest that changing consumers’beliefs about food can serve as an effective andlow-cost intervention to mitigate this preference.This research advances the theoretical understanding of the impact ofloneliness on consumer behavior and offers a practical behavioral intervention strategy of significant value for governments,non-governmental organizations(NGOs),and companies,aiming to combat obesity and improve public health.
基金supported by the National Natural Science Foundation of China(72374061)the Ministry of Education Humanities and Social Science Research Youth Project(22YJC630056)+2 种基金the Anhui Provincial Natural Science Foundation(2208085UD02)the Scientific Research Fund of the Hunan Provincial Education Department(23C0677)the Changsha Municipal Planning Project of Philosophy and Social Sciences(2025CSSKKT25)。
文摘The transportation sector’s reliance on petroleum fuels exacerbates environmental issues,emphasizing the need for sustainable development.Online electric vehicle(EV)car-hailing services present a key opportunity for EV adoption.This study develops a model based on heuristic and systematic information processing,examining the impacts of factors such as perceived risk,information need,and experience and knowledge on users’utilization of online electric vehicle carhailing services.The results indicate that users’experience and knowledge increase their information need and promote both heuristic and systematic processing,leading to positive attitude change,although they don’t significantly affect perceived risk.Perceived risk increases information need and supports supports systematic processing but negatively impacts attitude change.Greater information enhances systematic processing and attitude change.Perceived risk and information need do not affect attitude change via heuristic processing.Finally,the paper concludes with implications and directions for future research.
