新一代车险“理赔难”

保险作为现代服务行业之一,服务质量问题始终贯穿其中。其中,“理赔难”的现象层出不穷。从1929年11月在中国上海成立第一家保险公司太平保险,到目前保险行业已发展90余年,中国的车险理赔还难吗?依然难,只是难点变了,老矛盾得到部分解决,新矛盾层出不穷,唯独对理赔服务质量的评价参差不齐是永恒的。     

Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

Shariah compliance and corporate cash holdings

This study investigates the influence of Shariah compliance status on cash holding levels and the speed of adjustment of non-financial listed firms in six Gulf Cooperation countries from 2005 to 2016. The results show that Shariah compliance status has a significant effect on firms’ cash holding decisions. Shariah-compliant firms have significantly higher cash holding levels than non-Shariah-compliant firms. Further, Shariah-compliant firms adjust more quickly towards their target cash holdings than their conventional counterparts. In our view, Shariah-compliant firms are subject to multiple restrictions that limit their external financing channels. Therefore, holding larger cash reserves is important as it helps gain from the transaction cost motive of holding cash. The findings of this study have important implications for regulators, investors and managers. To the best of our knowledge, this study is the first to compare the effect of Shariah compliance on firms’ cash holdings and the speed of adjustment towards the trade-off theory’s optimal cash holding target.     

智慧居家养老服务协同供给的优化路径研究——以广西钦州市智慧居家养老项目的实践经验为例

智慧居家养老服务的协同供给可以形成社会联动效应，降低公共服务成本。运用公共服务协同供给分析框架，通过交叉分类方法从协同主体的利益与目标两个变量的耦合性出发分析广西钦州市智慧居家养老项目中养老服务主体间不同种类的协同关系，可以从加强政府领导、形成合作联盟、建立市场标准、创新扶持政策4个方面完善政府、企业、社会组织之间不同类型的协同供给，实现社会资源的高效利用以及向智慧居家养老服务的发展和转变。     

论数据权益的刑法保护——民刑交错视角下的法益保护论探讨

关于“数据权益的刑法保护”问题，在理论层面上，可从“刑法解释论”和“刑法立法论”两种路径进行探讨。“刑法解释论”探讨路径以现行《刑法》罪名体系为出发点，主要任务是揭示哪些罪名的犯罪构成之设置是以“数据权益”为规范保护目的；“刑法立法论”探讨路径是在刑法立法层面上探讨立法者为在刑法政策上实现数据权益的刑法保护这一目的，动用刑罚禁止何种行为类型才具正当性的问题。然而，两种探讨路径都将依赖于“数据权益”的内涵确定以及法益格的认定问题，换言之，是刑法法益理论在数据权益刑法保护问题上的具体运用。《民法典》第127条并非是关于数据的确权性规定，且在民法理论界关于数据权益的法律属性存在诸多争议的状况下，“数据权益”内涵不明、法律属性不清导致其并不具备作为刑法保护客体的“法益”格。当前刑法理论界存在的关于“数据权益”的刑法类法益保护模式探讨路径，是对刑法法益保护方式的误读，并未触及“数据权益刑法保护”之规范层面问题的实质。“数据安全”法益观的探讨路径则不仅混淆了现象层面与规范层面上的“数据犯罪”概念的界分，也由于没有论证“数据安全”如何能够构成刑法的保护法益，而导致结论过于武断。在理论探讨上，应该明确作为行为客体的物理层面上的“数据”概念与作为保护客体的法益层面上的“数据权益”概念之间的区别，据此明确“数据权益的刑法保护”在规范层面上是否构成新问题。     

Bibliometric and Scientometric analysis on CSR practices in the banking sector

This paper provides a bibliometric and Scientometric analysis of the corporate social responsibility (CSR) in banking sector. Our study analyzes 551 articles from the Scopus database to find out the relationship between CSR and banking. A bibliometric method was used to visualize the results using R-studio and VOS viewer software. The Scientometric analysis was conducted to determine the findings and mappings of the research themes, directions of current and future research, impact, co-occurrence, co-citations and impact and collaboration trends. We explore how CSR literature has evolved over the years in the banking sector between 1993 and 2021. We find that publication in the CSR and banking domain has increased significantly during 2017 and 2021. Social aspects, board of directors, CSR, environment, competitions, Islamic banking, sustainability, disclosure, ethics, legitimacy theory, sustainable banking, loyalty, and brand equity are the popular research trends and collaboration trends identified. We also provide further scope of the study based on the extensive review of the past literature. Our findings may provide help to future researchers, bankers, and regulators in understanding the current trends and future research progression in the CSR and banking sector.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

互联网使用、金融素养与金融决策*——基于2013—2017年中国家庭金融调查的研究

基于中国家庭金融调查2013—2017年面板数据，本文研究了互联网使用对我国家庭金融素养和金融决策的影响。本文借助2013年“宽带中国”战略实施带来的政策冲击构建工具变量，采用面板工具变量模型识别互联网使用的因果效应。研究发现，互联网使用促进了家庭对正规金融产品的投资，金融素养在二者之间发挥了显著的中介效应。互联网使用还有助于缩小我国城乡家庭在金融素养和金融决策方面的差距。本文为改善我国家庭金融素养和金融决策提供了启示。