The cross‐cultural study of LMX and individual employee voice: The moderating role of conflict avoidance

This article examines the role of national culture, measured by conflict avoidance, on the relationship between leader–member exchange (LMX) and individual employee voice. Using data collected from automotive industry employees in the United States and Korea, the findings show that conflict avoidance is negatively related to employee voice and also moderates the relationship between LMX and employee voice in the Korean sample. In particular, the relationship between LMX and voice becomes less positive when conflict avoidance is high. On the other hand, conflict avoidance does not have a direct effect on employee voice as well as an interactive effect with LMX on employee voice in the U.S. sample. This study, therefore, highlights the importance of the national culture in the comparative study of employee voice.     

Recognition versus disclosure of finance leases: Evidence from Japan

This study examines whether credit market participants—bond investors and credit rating agencies—treat recognized and disclosed finance leases differently when assessing firms’ credit risk in Japan. I use firms’ credit risk, measured by bond spreads and credit ratings, to investigate the relations between recognized versus disclosed finance lease obligations and firms’ credit risk following the adoption of Statement No. 13, Accounting Standard for Lease Transactions. For a sample of firms issuing new bonds, I find that, unlike recognized finance leases, disclosed finance leases are not associated with bond spreads. Moreover, the associations between recognized versus disclosed finance leases and bond spreads are substantially different. Conversely, recognized and disclosed finance leases are associated with credit ratings and are processed similarly when credit ratings are determined. Taken together, my results suggest that the sophistication of capital market participants influences their credit risk assessments of recognized versus disclosed finance leases.     

How Owners Matter? An Examination of Ownership Type in Corporate Disaster Relief Giving

Little research has investigated the effect of ownership identity (or type) and corporate philanthropy experience on giving. In this research, relying on legitimacy theory, we first assess the effect of ownership identity on corporate philanthropy (CP) in the context of the 2008 earthquake in China. Then we explore moderation effects of firms' prior CP experience and size as proxies for perceived legitimacy on owners' efforts at increasing giving and legitimacy. We find that state and CEO ownership are deterrents, while non‐SOE and institutional ownership enhances giving probability and amount. In addition, there is evidence that firm size and prior CP weaken the effects of institutional ownership on CP. This study provides a complete assessment of owner behaviour. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Pursuing your leader development: Lessons from 101 executives

To lead effectively in a VUCA (i.e., volatile, uncertain, complex, and ambiguous) environment, leaders must quickly and continuously acquire new skills. However, formal development opportunities aren’t nearly enough to support the ongoing skill development leaders need to manage the level of complexity and change they are facing. Instead, leaders must take ownership of their own development. In this paper, we describe a straightforward, four-step process that leaders can implement to pursue their individualized development through leader development planning. Specifically, we walk leaders through the evidence-based steps of creating their unique leader development plan (LDP), including (1) identifying their leadership strengths and weaknesses, (2) setting effective leader development goals, (3) designing SMART strategies, and (4) reflecting, refining, and realigning their plan. Throughout the article, we detail positive examples as well as common pitfalls that we observed from our work supporting 101 mid- to senior-level leaders in designing their LDPs. Our purpose in doing so is to provide tools and examples to enable leaders at all levels to drive their development at their own pace.     

Best classification algorithms in peer-to-peer lending

A proper credit scoring technique is vital to the long-term success of all kinds of financial institutions, including peer-to-peer (P2P) lending platforms. The main contribution of our paper is the robust ranking of 10 different classification techniques based on a real-world P2P lending data set. Our data set comes from the Lending Club covering the 2009–2013 period, which contains 212,252 records and 23 different variables. Unlike other researchers, we use a data sample which contains the final loan resolution for all loans. We built our research using a 5-fold cross-validation method and 6 different classification performance measurements. Our results show that logistic regression, artificial neural networks, and linear discriminant analysis are the three best algorithms based on the Lending Club data. Conversely, we identify k-nearest neighbors and classification and regression tree as the two worst classification methods.     

Ownership discrimination and private firms financing in China

This study examines the financing/funding of private firms in China. Our results show that private firms are significantly less funded through formal financing channels such as bank loans than state-owned firms, and hence have to resort to alternative financing such as trade credit. Consistent with the theoretical expectation and literature, there is a substitution effect between trade credit and bank loans for private firms, but this effect is much weaker compared to that of state-owned firms. Moreover, while the univariate comparisons indicate that private firms obtain more notes payable than state-owned firms, the multivariate regression analyses show that the relation between bank loan and notes payable is positive and indifferent between private and state-owned firms.     

严监管背景下农信社合规风险管理体系建设

2018年,银行业监管环境进一步趋严,不但强调对银行的监管,更提出了对监管人员职责的监管,这种严格的外部监管环境对农信社的合规风险管理带来了极大的挑战。农信社合规风险管理体系的建设和完善已势不容缓。论文提出了农信社合规风险管理体系建设要从战略定位、文化渗透、防线搭建、专业专职化、考核和追究六个维度入手,推进合规风险管理长效机制的建设。     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.