Chief Audit Executive as Supervisory Board Member and Executive Compensation Contracts

This paper studies a unique phenomenon in China's corporate governance—that chief audit executives (CAEs) sit on supervisory boards (CAE duality)—and examines its effects on executive compensation contracts. Using a sample of listed firms between 2010 and 2018, we find a significant positive relation between CAE duality and pay-for-performance sensitivity, which suggests that the dual position helps integrate monitoring resources and reduces agency costs. This positive relation is more pronounced when companies face a stricter monitoring environment and in non-state-owned enterprises (non-SOEs) than in SOEs. In addition, we find that the recent reforms on compensation strengthen the role of CAE duality in SOEs. Further analysis identifies the reliability of performance information (i.e., earnings quality) and reduced executive self-interested behaviours (i.e., perquisite consumption) as the influencing mechanisms that increase the demand for performance-based compensation and thus improve pay-for-performance sensitivity.     

The Benefit of Frequent Corporate Philanthropy

Applying behavioural economic theory, we argue that the frequency of philanthropic activity is important in determining corporate philanthropy's economic outcome. Using Chinese data from 2003 to 2016, we find that firms with more frequent philanthropic activities obtain more government subsidies than firms that only engage in one-off charitable donations. Firms with better corporate governance, such as higher management ownership and more independent directors, are more likely to adopt a strategy of frequent donation. Furthermore, firms are more likely to be frequent donors when management or local government officers have a long tenure. Our findings provide insight into the giving process and suggest that firms can maximize the benefit of corporate philanthropy if they strategically consider the donation frequency and donation amount simultaneously.     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

The effects of anticipated goal‐inconsistent behavior on present goal choices

Prior work has examined how, in the pursuit of long‐term goals, past goal behavior influences present goal choices. Instead, the present work focuses on how anticipating future goal behavior, specifically future goal‐inconsistent behavior, influences present goal choices. For example, how anticipating overspending on an upcoming vacation influences current spending behavior. The authors propose that the effect of anticipated goal‐inconsistent behavior on present goal choice is moderated by the perceived changeability of the future behavior. When future goal‐inconsistent behavior is perceived as changeable, consumers tend to imagine it away, and it has no systematic effect on present goal choices. However, when future goal‐inconsistent behavior is perceived as unchangeable, consumers accept it as a matter of fact, and systematic effects occur. Specifically, some consumers not only fail to buffer against future goal‐inconsistent behavior's negative consequences, but tend to exacerbate those consequences by increasing their goal‐inconsistent behavior in the present. Four studies examine this surprising behavior, using an individual difference (the response‐to‐failure scale) to identify when and for whom it occurs. The studies demonstrate the role of perceived changeability using various manipulations across multiple critical goal domains such as spending, eating, and academics.     

我国大麦价格波动特征及其影响因素分析

[目的]大麦价格剧烈波动会直接影响大麦种植户的生产积极性和大麦产业的平稳发展,研究大麦价格波动特征及其影响因素,有助于提升大麦产业链相关主体识别和应对市场风险的能力,促进大麦产业的健康发展。[方法]文章先采用HP滤波法和ARCH类模型分析了2011年4月至2017年2月我国大麦价格波动特征,然后采用脉冲响应函数分析了我国大麦价格波动影响因素。[结果]我国大麦价格波动存在明显的季节性和周期性,样本期内总体上呈现逐渐下降趋势;我国大麦价格具有显著的波动集聚性,我国大麦价格具有显著的不对称性;在该文选择的影响因素中,大麦进口量和国际大麦价格是影响我国大麦价格波动的主要因素。[结论]该文提出必须保障并提高国内大麦合理产能、完善大麦价格监测预警体系、加强国内大麦进口企业整合和推动大麦进口来源多元化的政策建议。     

Is Oil Palm Expansion a Challenge to Agroecology? Smallholders Practising Industrial Farming in Mexico

Agroecology has become a powerful alternative paradigm for rural development. In contrast to conventional approaches, this paradigm shifts the emphasis from technology and markets to local knowledge, social justice and food sovereignty, to overcome rural poverty and environmental degradation. However, the spread of this approach faces several obstacles. This paper deals with one of these obstacles: the ‘preference’ of smallholders for industrial farming. We specifically analyse the widespread uptake up of oil palm by smallholders in Chiapas. Contrary to agro‐ecological assumptions, oil palm proved favourable to smallholders in Chiapas because of historical and contemporary state–peasant relations and the advantageous economic circumstances within the oil palm sector. Based on this research, we identify four challenges for agroecology: (i) the existence of contradictory interests within the peasantry as a result of social differentiation; (ii) the role of the state in making conventional development models relatively favourable to smallholders; (iii) the prevalence of modernization ideologies in many rural areas; and (iv) the need for this paradigm to acknowledge smallholders' agency also when engaged in industrial farming. These challenges need to be tackled for agroecology to offer viable alternatives in a context of agro‐industrialization.     

Move fast,travel slow: the influence of high-speed rail on tourism in Taiwan

High-speed rail (HSR) and tourism are closely related economic activities because improved mobility is perceived to facilitate tourist behavioral changes. This study examines the influence of HSR on the travel patterns of individual tourists in Taiwan in relation to time, space and carbon emissions. A framework is first provided to discuss how changes in the speed of intercity transportation will affect visitors’ choice of the journey, behavior at destinations and trip quality. In addition, HSR is expected to influence five general aspects of travel decisions relating to mobility and trip emissions, including mode selection, travel distance, length of stay per trip, annual travel frequency and total travel days. In the example of Taiwan, information by onsite sampling of 400 domestic travelers found that HSR had a weak influence on travel distance and length of stay per trip, but was observed to facilitate extended time at each stop, a deeper engagement with the locality, and an approximate 10% reduction in transport carbon emissions through intermodal substitution. These phenomena are in line with the slow travel concept of sustainable tourism consumption.     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.     

Experimental investigation into the role of trust in collusion

Trust has traditionally been regarded as conducive to ethical decision making. However, empirical studies on the relationship between trust and ethical decision making are rare, especially those concerning the negative effects of trust. Therefore, our study aimed to provide empirical evidence in this area. An experiment was designed to investigate whether trusted parties are more likely than non‐trusted parties to enter into a collusion that will have unfair consequences for a third party. The results showed that trusted parties are significantly more likely to collude than are non‐trusted parties. Furthermore, an ancillary analysis revealed the mechanism of trust. First, participants with a stronger need to collude were the most likely to collude in the trust group. Second, experimental and hypothetical settings generated different results, and we suspect that real harm plays a vital role. Overall, we conclude that the absence of trust serves as an impediment to collusion.     

Variety in the video game industry: An empirical study of the Wundt curve

This study analyzes the effect of variety on consumer utility using historical behavioral information for 1,397 consumers participating in 729,049 unique rounds of play. We show that consumers generally exhibit a preference for variety as part of their gameplay utility. The relationship between variety and utility is nonlinear and follows, at least for some types of variety, an inverted u‐shape as predicted by the Wundt curve. Our results represent the first such evidence on the importance of variety in video gaming, which has significant implications for consumption through optimization of gameplay utility to satisfy the demand for variety.