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.     

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。     

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.     

长三角港口腹地动态演变及耦合协调度研究

明确港口腹地演变趋势、分析港腹耦合协调度,对长三角地区港腹联动发展具有重要意义。量化港口系统—腹地系统综合指标评价体系,运用高斯烟羽模型在2006、2011、2016年3个时间节点上测算长三角地区主要港口影响强度,并对腹地范围进行划分,利用耦合协调模型定量分析港口系统和直接腹地经济系统耦合协调度。研究结果表明:长三角地区港口呈现"一超多强"的格局,以上海港为中心,各港口多极发展;港口腹地范围整体稳定,局部波动,上海港的边缘腹地不断缩减;港口与腹地的耦合协调度处于上升态势,宁波—舟山港腹耦合协调度最高。     

Strategic entry or strategic exit? International presence by emerging economy enterprises

By proposing an integrated strategic choice framework, we theorize the distinctive dynamics of international expansion by emerging economy enterprises. Specifically, we explicate how these firms build international presence based on combined strategic entry (i.e., prompted by internal capabilities such as innovation and diversification) and strategic exit (i.e., pushed out by external handicaps at home such as institutional obstacles and market competition). Further, a firm’s cooperative ties with foreign multinationals in the former’s home country fortify the strategic entry intent, while ties with home government institutions weaken the strategic exit intent. We also demonstrate that building international presence helps bolster firm performance, highlighting the economic catch-up consequence of international expansion. Analyses of a two-year imbalanced panel data of 2136 firms statistically support our hypotheses.     

The optimal level of corporate social responsibility based on the duopoly model

This paper constructs a duopoly model considering corporate social responsibility (CSR) and market's sensitivity to CSR (e) and analyzes the equilibrium results, the condition of CSR implementation and the optimal CSR level (β^* ) of Model CC (two enterprises implement CSR) and Model CN (only one enterprise implements CSR). The results show that β^* is affected by competitors and e. e, marginal cost (c) and cost difference affect the equilibrium results and the comparative results. Reducing c and improving e can promote social welfare. Consumer surplus under Model CC is highest. CSR has a negative effect on social welfare under certain conditions.     

The Impact of Farmland Transfers on Agricultural Investment in China: A Perspective of Transaction Cost Economics

There is growing concern that farmland transfers lead to less agricultural investment, which may adversely affect agricultural productivity growth in China. Prior research has primarily focused on the differences between owned cultivated land and rented plots, but little is known about how farmland transfers between relatives, which are popular in rural China, specifically affect agricultural investment. In this paper, we present a conceptual framework of transaction cost economics to compare different contracting strategies in China's farmland rental markets. As farmland rental markets in China are immature, land transfer between relatives establishes bilateral governance, which has the advantage of addressing the opportunistic activities of both parties and can ultimately increase investment by tenants. Based on data from two waves of household surveys, we empirically examine the impact of bilateral governance on the application of organic fertilizer, an indicator for agricultural investment. Our findings show that apart from economic factors, kinship is important to the functioning of farmland rental markets in rural areas.     

Defining Supply Chain Management: In the Past,Present, and Future

The article titled “Defining Supply Chain Management” published in 2001 in the Journal of Business Logistics has been cited over 4,900 times in the last 17 years. In this paper, we first provide a historical review of how the article originated and the contributions the article made to both the theory and practice of supply chain management (SCM). Next, we highlight the key market and technological changes that have emerged in SCM followed by how the theory proposed in the 2001 article can still be relevant to support SCM research and practice going forward. We also propose ways of configuring a supply chain and partnering across companies to serve customers in an optimal way. We conclude with a call for research on developing new frameworks to better describe, explain, predict, and shed light on the evolving nature of SCM.