How and why auditors’ social exchange relationships influence their attitudes and behaviors: Implications for audit quality

External auditors regularly interact with various parties at work, such as their accounting firms, engagement team members, and clients. These interactions can help shape the nature of auditors’ social exchange relationships with these entities, which in turn may influence their behavior toward these targets. This installment of Accounting Matters draws from recently published research by Herda and colleagues to (1) explain how constructive auditor-target connections can develop and lead to beneficial outcomes like reduced auditor burnout and turnover intentions, as well as more citizenship behavior, and (2) discuss how these upshots might ultimately affect audit quality. This topic is important because audit quality translates into improved financial reporting, which helps stakeholders who rely on audited financial statements to make informed business decisions. Specifically, we underscore the key role auditors’ perceptions of fair treatment from a relationship partner play in fostering a strong psychological bond with the target via perceived support. We further consider how auditors’ consequent commitment to the target can result in favorable organizational outcomes, including enhanced audit and financial reporting quality. We also discuss practical implications for accounting firms.     

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。     

草地确权对牧户草地转入的影响

确权政策的实施稳定了地权，保障了牧户的产权权益。基于内蒙古自治区锡林郭勒盟、鄂尔多斯市和乌兰察布市的调研数据，运用Tobit回归模型得出以下结论：确权对于牧户草地转入具有显著的抑制作用；户主特征中性别、年龄对于土地转入作用不显著，受教育程度具有显著的促进作用；家庭特征中家庭收入、家庭承包草场面积和牲畜存栏量对于草场转入具有显著的促进作用。     

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.     

知识型员工冗余对中小上市公司二元创新的影响：环境特征的调节作用

以277家中小板和创业板上市公司2012-2017年平衡面板数据为样本，利用泊松模型，实证分析知识型员工冗余与企业二元创新的关系，并探讨外部环境特征（要素市场发育程度和市场不确定性）的调节机理。研究表明：企业应保持一定的知识型员工冗余，促进企业二元式创新，过多或过少的知识型员工冗余均不利于企业开展创新活动；不同的环境特征对二者间关系的调节作用存在异质性，要素市场发育程度会减弱知识型员工冗余与探索式创新、利用式创新间关系，而市场不确定性会加强知识型员工冗余与探索式创新、利用式创新间关系。     

险资股权投资的结构性改革研究*——基于险资投资的倒U型效应分析

保险资金作为重要的机构投资者能否发挥促进公司绩效提升的作用在已有研究和监管政策制定上都存在较大争议。本文以2005-2017年A股上市公司为研究样本，发现险资持股比例对上市公司绩效以及估值影响存在显著的倒U型曲线效应，相应机制研究表明险资持股通过显著影响两类代理成本的渠道发挥治理作用。在适度持股比例以下，险资增持能够降低被投资公司管理费用率和其他应收款占比，并提高资产周转率，从而降低两类代理成本；持股超过一定比例反而造成两类代理成本上升。险资持股比例变化对保险机构调研次数的影响则从公司治理参与角度印证了以上结论。对倒U型曲线效应的深入分析既有助于深化对机构投资者影响公司绩效的多重效应和机制的认识，同时为在金融机构层面落实金融供给侧结构性改革、增强险资服务实体经济能力提供参考。     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。     

财政政策与货币政策的动态调控效应*——基于时变参数向量自回归模型的检验

本文廓清了财政政策与货币政策搭配动态调控宏观经济的机理，揭示了两者协调影响经济的“黑箱”机制及其在经济不同阶段的搭配方式；运用中国2004—2019年的经济季度数据，构建TVP SV VAR模型探究两类政策对宏观经济的调控效应。研究发现：财政政策与货币政策共同把控流动性“闸门”实现互动协调；财政政策搭配货币政策具有时变性，在整体上“同向发力”推动经济发展；两类政策对产出的影响并非始终如理论一致，在结构层面仍有优化靶向性操作的余地。