When Moral Tension Begets Cognitive Dissonance: An Investigation of Responses to Unethical Pro-Organizational Behavior and the Contingent Effect of Construal Level

Journal of Business Ethics - Research on unethical pro-organizational behavior (UPB) has predominantly focused on its antecedents, while overlooking how engaging in such behavior might affect...     

Trust Erosion During Industry-Wide Crises: The Central Role of Consumer Legitimacy Judgement

Journal of Business Ethics - Widespread unethical corporate misconduct in an industry triggers industry-wide crises. This research investigates how industry misconduct affects consumers’...     

Uncovering asset stripping during China's privatization

This paper empirically studies the occurrence and extent of asset stripping via undervaluing public assets during the mass privatization of state-owned and collectively owned enterprises in China. Using three waves of a national survey of private firms, we provide evidence that state-owned and collectively owned assets were substantially underpriced, indicating the presence of corruption during privatization. Further analysis shows that the extent of underpricing is more severe in regions with less market competition or weaker property rights protection, and more pronounced for intangible assets such as intellectual property rights and land use rights. When comparing firm efficiency between privatized firms and de novo private firms, we find that the former group continues to enjoy considerable preferential treatments, yet significantly underperforms the latter, possibly due to continued government control and intervention. Finally, we provide evidence that insider privatization is an important source of corruption during the privatization process.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.     

The impact of crude oil inventory announcements on prices: Evidence from derivatives markets

This study examines the impact of weekly crude oil storage announcements on oil futures and options prices. We document evidence of a strong announcement day effect on both markets, and find prices to move in anticipation of the inventory surprise. Futures returns significantly decrease with positive surprises and increase with negative surprises. There is no evidence of an asymmetric impact on futures prices. Near‐the‐money options exhibit the greatest price sensitivity, and the magnitude of the price response of both futures and options declines with maturity. The results remain robust even after controlling for various macroeconomic and other storage‐related news variables.     

A tale of two clusters: knowledge and emergence

Cluster emergence is an important topic but weakly conceptualized in the literature. Focusing on the interaction of the local knowledge pool and firm growth, the paper develops a comprehensive framework to understand cluster emergence. In the framework, the cluster formation process starts with the collision of local and external knowledge which generates an innovation and stimulates the creation of local pioneering firms in a new field. To support the growth of follow-up entrants in the new industry, the local knowledge pool needs to be expanded and deepened through local knowledge sharing and external knowledge inflows. The enlarged local knowledge pool enables local firms to grow and explore other fields further. To promote cluster emergence, public policies need to facilitate the interaction of the local knowledge pool and firm growth. The paper illustrates the interactive framework with two aluminum extrusion clusters in China that emerged in different ways over different time periods.     

全过程、立体化校企合作培养高职旅游人才的探索与实践

本文对高职旅游专业人才培养亟待通过校企合作解决的问题进行分析,回顾北京经济管理职业学院旅游管理专业2004年开办以来进行的相关探索,在此基础上提炼出全过程、立体化校企合作培养高职旅游人才机制,并对机制运行的实践效果进行总结,以期对高职旅游人才培养提供可借鉴的有效经验.     

绿色城市理论与实践探索

从20世纪七十年代开始,国际上开展了绿色城市广泛的实践活动。力图在中外实践的基础上构建起绿色城市理论的体系框架;明确绿色城市理论支撑、研究范畴与目标愿景,辨析绿色城市的定义内涵;构建绿色城市发展原则、发展目标与指标体系的全空间目标体系;提出完整的绿色城市的全要素技术体系;提出绿色城市规划建设管理与评估监督的全过程标准体系;覆盖不同地域、规模、类型、专业领域的绿色城市的全领域示范体系。     

Structural holes and hedge fund return comovement: evidence from network-connected stock hedge funds in China

Using data from a new hedge fund database, we examine the impact of social networks on the return comovement of stock hedge funds in China. We use structural holes in the college alumni networks of managers to measure the managers’ social network positions. We perform an empirical analysis on a sample of 3,012 hedge fund products in China from 2010 to 2017. We find that greater structural holes are associated with higher return comovement. The positive impact of the structural holes on return comovement is not affected by market cycles, a manager's major in college, or his or her abilities.     

中国粮食仓储的历史与展望

粮食仓储作为中国历史发展中的重要载体,对于社会的繁荣、稳定和发展具有重要意义。本文主要论述了中国古代和现代粮食仓储的发展历史及其价值,并对粮食仓储未来的发展进行展望。