Search results

The purpose of our study is to investigate the effects of politically-connected boards (PCBs) on over-(under-)investment in labor. We also examine the impacts of the supervisory board (SB)’s optimal tenure on the association between PCBs and over-investment in labor.

We constructed the proxy for PCBs using a dummy variable set to 1 (one) if a firm has politically-connected boards and zero (0) otherwise. For the robustness check, we used the number of politically-connected members on the boards as the proxy for PCBs.

We find that the presence of PCBs reduces over-investment in labor. Consistent with our prediction, we found no significant association between PCBs and under-investment in labor. We also find that the SB with optimal tenure strengthens the negative association between PCBs and over-investment in labor. In our channel analysis, we find that the presence of PCB mitigates over-investment in labor through a higher dividend payout ratio.

Due to the unavailability of data in firms’ annual reports regarding the number of poorly-skilled and highly skilled employees, we were not able to examine the effect of low-skilled and high-skilled employees on over-investment in labor. Also, we were not able to examine over-(under-)investment in labor by drawing a distinction between general (generalist) and firm-specific human capital (specialist) as suggested by Sevcenko, Wu, and Kacperczyk (2022). Generally, it is more difficult for managers to hire highly-skilled employees, specialists in particular, thereby driving the choice of either over- or under-investing in the labor forces. In addition, in the firms’ annual reports, there is no information regarding temporary employees. Therefore, if and when such data become available, this would provide another avenue for future research.

Our study offers several practical implications and insights to stakeholders (e.g. insiders or management, shareholders, investors, analysts and creditors) in the following ways. First, our study highlights significant differences between capital investment and labor investment. For instance, labor investment is considered an expense rather than an asset (Wyatt, 2008) because, although such investment is human capital and is not recognized on the firm’s balance sheet (Boon et al., 2017). In addition, labor investment is characterized by: its flexibility which enables firms to make frequent adjustments (Hamermesh, 1995; Dixit & Pindyck, 2012; Aksin et al., 2015), its non-homogeneity since every employee is unique (Luo et al., 2020), its direct impact on morale and productivity of a firm (Azadegan et al., 2013; Mishina et al., 2004; Tatikonda et al., 2013), and its financial outlay which affects the ongoing cash flows of a firm (Sualihu et al., 2021; Khedmati et al., 2020; Merz & Yashiv, 2007). Second, our findings reveal that the presence of PCBs could help to reduce over-investment in labor. However, if managers of a firm choose to under-invest in labor in order to obtain better profit in the short-term through cost saving, they should be aware of the potential consequences of facing a financial loss when a new business opportunity suddenly arises which requires a larger labor force. Third, our findings help stakeholders to re-focus on the labor investment. This is crucial due to the fact that labor investment is often neglected by those stakeholders because the expenditure of labor investment is not recognized on the firm’s balance sheet as an asset. Instead, it is written off as an expense in the firm’s income statement. Fourth, our findings also provide insightful information to stakeholders, suggesting that an SB with optimal tenure is more committed to a firm, and this factor plays an important role in strengthening the negative association between PCBs and over-investment in labor.

First, our findings provide a valuable understanding of the effects of PCBs on over-(under-)investment in labor. Stakeholders could use information disclosed in the financial statements of a publicly-listed firm to determine the extent of the firm’s investment in labor and PCBs, and compare this information with similar firms in the same industry sector. Second, our findings give a better understanding of the association between investment in labor and political connections , which are human and social capital that could determine the long-term survival and success of a firm. Third, for shareholders, the appointment of board members with political connections is an important strategic decision to build political capital, which is likely to have a long-term impact on the financial performance of a firm; therefore, it requires thoughtful consultation with firm insiders.

Our findings highlight the role of PCBs in reducing over-investment in labor. These findings are significant because both investment in labor and political connections as human and social capital can play an important role in determining the long-term survival and success of a firm.

This paper studies the relationship between CEO pay-performance sensitivity and CEO pay for luck as well as the asymmetric benchmarking of CEO pay in which good luck is rewarded but bad luck is not penalized symmetrically. We further explore the impact of the regulatory changes on executive compensation taking effect in the 2000s on CEO pay for luck and asymmetry.

In this study, we examine the relationship between CEO pay-performance sensitivity and CEO pay for luck and the asymmetric benchmarking of CEO compensation. The sample consists of DJIA component companies over a 71-year period from 1950 to 2020. CEO pay-performance sensitivity is measured by both delta and Jensen-Murphy pay-performance sensitivity.

We find that an increase in CEO pay-performance sensitivity as measured by both delta and Jensen-Murphy pay-performance sensitivity leads to an increase in the degree of CEO pay for luck but tends to reduce the level of CEO pay for luck asymmetry. In addition, we find that the major pay-related regulatory changes in recent years have mitigated the degree of CEO pay for luck and pay asymmetry, in which CEO pay structure and the associated CEO pay-performance sensitivity are major mechanisms through which the regulatory changes take effect.

Our findings provide empirical evidence supporting the argument that both optimal contracting and rent extraction should be considered as important determinants of CEO compensation.

When a firm designs the pay packages for its CEO to align CEO wealth to firm performance, CEO pay-performance sensitivity is expected to improve. However, the improved CEO PPS can also lead to an increased CEO pay for non-performance (Luck), which is an undesired outcome from the shareholder view. Therefore, a firm should thoroughly consider various advantages and disadvantages when compensating its top executives. Third, pay-related regulations have indeed achieved some intended outcomes such as the diminished pay for luck and asymmetry, but they also exacerbated the positive relationship between CEO pay-performance sensitivity and the asymmetric benchmarking of CEO pay. It seems that executive pay-related regulations cannot achieve perfect outcomes without side effects. Continuous reforms and regulations on corporate governance should be a dynamic process under various changing situations.

This study contributes to the literature on executive pay for luck and asymmetry in several ways. First, our study is among the few studies empirically testing the relationship between CEO pay-performance sensitivity and pay for luck and asymmetry. We find that CEO pay-performance sensitivity tends to increase the degree of CEO pay for luck but reduce the level of asymmetric benchmarking of CEO pay. These findings partly support the rent extraction theory grounded on the managerial power hypothesis and partly support the optimal contracting theory. Our findings confirm that the optimal contracting theory and the rent extraction theory are both important for explaining the practices and historical trends of CEO compensation.

This study aims to investigate the effects and implications of overconfidence in a competitive game involving multiple newsvendors. This study explores how overconfidence influences system coordination, optimal stocking strategies and competition among newsvendors in the context of the well-known newsvendor stocking problem.

The study applies robust optimization theory and the absolute regret minimization criterion to analyze the competitive game of overconfident newsvendors. This study considers the asymmetric information held by newsvendors regarding market demand and obtains a closed-form solution for the competing game. The effects of overconfidence on system coordination and optimal stocking strategies are examined.

The results of the study indicate that overconfidence can act as a positive force in reducing the effects of overstocking caused by competition and asymmetric information among newsvendors. The analysis reveals that there exists an optimal level of overconfidence that coordinates the ordering system of multiple overconfident newsvendors, leading to first-best outcomes under certain conditions. Additionally, numerical examples confirm the obtained results. Furthermore, considering newsvendors' expected profit, the study finds that a higher degree of overconfidence does not necessarily result in lower actual expected profit.

Despite the significant contributions of this study to theoretical and managerial insights, this study does have certain limitations. First, in the establishment of the belief demand function, the substitution ratio, which quantifies the transfer, is assumed to be an exogenous variable. However, in reality, this is often influenced by factors such as the price of goods and the distance between stores. Therefore, one direction worth studying in the future is to explore the uncertainty associated with the demand substitution ratio and integrate that as an endogenous variable into the optimization model. Second, this study does not address the type of product and solely focuses on quantitatively analyzing the effect of salvage value on the optimal stocking strategy. Future studies can explore the effect of degree of perishability and selling period of the product on the stocking. Third, the focus of uncertainty in this study revolves around market demand, and the implications of this uncertainty are significant. A recent study (Rahbari et al., 2023) addressed an innovative robust optimization problem related to canned foods during pandemic crises. The recent study's findings highlighted the effectiveness of expanding canned food exports to neighboring countries with economic justification as the best strategy for companies amidst the disruptions caused by the coronavirus disease 2019 (COVID-19) pandemic. Incorporating the issue of disruptions into the authors' research would be interesting and challenging.

From a managerial perspective, the authors' study provides a research paradigm for game-theoretic inventory problems in scenarios where the market demand distribution is unknown. While most inventory problems are analyzed and solved based on expectation-based optimization criteria, which rely on an accurate distribution of market demand, obtaining this information in practice can often be challenging or expensive for decision-makers. Consequently, a discrepancy arises between real-world observations and theoretical identifications. This study aimed to complement previous research and address the inconsistency between observations and theoretical identification.

The authors' research contributes to the existing understanding of overconfidence and assists individuals in making appropriate stocking strategies based on the individuals' level of overconfidence. Diverging significantly from the traditional view of overconfidence as a negative bias, the authors' results show the view's potential positive impact within a competitive environment, resulting in greater actual expected profits for newsvendors.

This study contributes to the existing literature by examining the effects of overconfidence in a competitive game of newsvendors. This study extends the analysis of the well-known newsvendor stocking problem by incorporating overconfidence and considering the implications for system coordination and competition. The application of robust optimization theory and the absolute regret minimization criterion provides a novel approach to studying overconfidence in this context.

In this study, the authors demonstrate the inherent connections between bank risk-taking, performance and executive compensation in the banking sector of China by developing a theoretical model and performing empirical tests with simultaneous equation models.

The authors construct a multi-task principal-agent model to capture agency problems in China, and the model can be extended to various cases. In empirical tests, simultaneous equation models are used to examine the theoretical predictions by eliminating endogenous concerns efficiently compared with the methods in the existing literature.

The results indicate that the regulator fails to provide bank managers with positive incentives to control risk, whereas the compensation guidance policy (2010) proposed by the CBRC alleviates this problem in China. Additionally, the authors established that shareholders reward bank managers for better and more stable performance. The authors propose the introduction of restricted stock options into the compensation design, as the existing compensation design fails to balance the performance and risk-taking of banks.

First, the executive compensation structure and details in China are not available. In addition, the equity-based incentive compensation is forbidden. Therefore, this paper cannot provide more details about how the compensation structure affects bank manager behaviours. Secondly, the database consists only 25 listed commercial banks. Luckily, the assets of these banks could account for the vast majority of China's banking assets. The authors also expect that new methodologies such as machine learning and deep learning will be adopted in the research on bank risk management.

First, the regulator should optimise the compositions and payment rule of bank executive compensations. Secondly, it is advisable to adopt restricted deferred share reward or stock option compensation in due course. Thirdly, the regulator can require the banks that undertake excessive risks and troubled by moral hazard to increase the independent director proportion on the bank board according to the authors' empirical tests that higher independent proportion prevents the risk accumulations effectively. Fourthly, except for absolute compensation, the gap between executives' salary and average employee's income should be taken account.

This study provides a theoretical framework that incorporates the manager behaviours, executive compensation and bank regulations, and it provides empirical tests by solving endogenous concerns. Additionally, this study examines the effects of China's compensation guidelines issued in 2010. The authors believe that this study adds value to the existing literature by illustrating the compensation mechanism in China.

This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

Press reports have indicated that firms frequently underprice restricted stock and employee stock options. I test for underpricing of stock and options.

I examined a sample of 5,333 private firm stock and option issuances between 1985 and 2017. I tested for underpricing using two approaches: assuming investors have no special market-timing ability and assuming instead they have perfect market-timing ability.

I find evidence of widespread stock and option underpricing by private firms before they go public reflecting large discounts that exceed reasonable compensation for lack of marketability. Unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded, but the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect. Underpricing is still detected even when the actual DLOMs are tested against a benchmark that assumes investors have perfect market-timing ability.

Firms frequently underprice restricted stock and employee stock options. Firms tend to underprice stock options more frequently than restricted stock, but restricted stock tends to be priced at deeper discounts when recipients are assumed not to have any special market-timing ability.

Private firms issue restricted stock and options as incentive compensation. Lowballing the valuation transfers wealth from outside stockholders to employees/insiders. Wealth transfers take place through the issuance of equity claims to employees/insiders before firms go public. I found that more than a quarter of the DLOMs exceed the theoretical maximum by, on average, between 16% (median) and 20% (mean). This finding raises two questions worthy of investigation. First, to what extent do the frequency and magnitude of DLOMs above the theoretical maximum depend on whether a board of directors obtains an independent appraisal of a stock’s fair market value? Second, if DLOMs above the theoretical maximum are observed even when the stock is independently appraised, how do appraisers justify such large DLOMs?

The wealth transfers that take place through the issuance of equity claims to employees/insiders before firms go public benefit employees/insiders at the expense of outside shareholders.

My paper is the first to furnish evidence of widespread stock and option underpricing by private firms before they go public; demonstrate that the unreported underpricing is more frequent in the last pre-IPO private equity transactions that offer the last opportunity to give such discounts before the stock is publicly traded and show that the discounts are greater in the earlier pre-IPO transactions where unreported discounts are presumably tougher for the SEC to detect.

This paper aims to clarify the relationship between digital transformation and labor structure from the perspectives of microenterprise business strategies and factor allocation efficiency. It attempts to address the gap in existing research by explaining the impact of digital transformation on multidimensional workforce structures and the positive effects of this structural adjustment on labor allocation efficiency. In addition, the study further explores the economic ramifications of digital transformation, clarifying the correlation between changes in labor force structure and enterprise human resource allocation, thus enhancing the employment mobility effects of digital innovation at the enterprise level.

In contrast to prior research, our approach uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures.

The paper asserts that digital transformation significantly influences labor structure changes, evidenced by increased proportions of high-skilled, non-routine and younger laborers, as well as decreased shares of low-skilled, routine and older-age workers. Furthermore, it captures internal labor structure impacts, influenced by enterprise size, ownership, industry density and regional digitization levels. Mechanism analysis indicates moderation of digital transformation effects on labor structure by innovative tasks, labor productivity and management shareholding.

The paper reveals the specific impact of corporate digital transformation on workforce structure, enriching the employment mobility effects of digital innovation at the enterprise level and providing theoretical support for the formulation and implementation of relevant policies.

First, this paper delves into the impact of digital transformation on the internal labor structure from a microlevel perspective, elucidating its mechanisms. Second, in contrast to prior research, it uses text analytics to assess the internal labor structure, incorporating labor skill, position and age into the analytical framework. This approach yields a more comprehensive data set, shedding light on variations in multidimensional employment structures. Lastly, the study investigates the economic ramifications of shifts in employment structures. The findings of this study furnish novel empirical evidence for the debate regarding whether digital transformation can indeed enhance labor allocation efficiency.

Corporate site visits increase labor investment efficiency.

Our empirical model for the baseline analysis follows those of Jung et al. (2014) and Ghaly et al. (2020).

We show that corporate site visits are associated with significantly higher labor investment efficiency; more specifically, site visits reduce both over-hiring and under-hiring of employees. The effect of site visits on labor investment efficiency is more pronounced for firms with higher labor adjustment costs, greater financial constraints, weaker corporate governance and lower financial reporting quality. We also find that site visits mitigate labor cost stickiness.

First, while the literature has suggested how the presence of institutional investors and analysts may affect labor investment decisions, we focus on institutional investors and analysts’ activities and interactions with firm executives. We provide direct evidence that institutional investors and analysts may use corporate site visits to improve labor investment efficiency. Second, our study adds to a line of recent studies on how corporate site visits reduce information asymmetry and agency conflicts. We show that corporate site visits allow institutional investors and analysts to influence labor investment efficiency. We also provide new evidence that corporate site visits reduce labor cost stickiness.

We expect to provide a complete theoretical framework and large sample evidence on the impact of corporate social responsibility (CSR) on the efficiency of labor investment. We also hope to provide micro-evidence based on labor investment behavior for the two-sided impact of corporate CSR behavior.

This paper measures labor investment efficiency by estimating the difference between actual and expected net hiring of enterprises. CSR is measured on the basis of the CSR score of Chinese listed companies published by Hexun.com. A regression model is constructed to analyze the relationship between CSR and labor investment efficiency. Possible endogeneity problems are controlled by lagging independent variables, propensity score matching method and difference-in-difference method.

Results show that CSR can improve labor investment efficiency by reducing over-hiring and under-hiring in emerging markets. The existence of the mediating effect of agency cost, information disclosure quality and employment fluctuation confirms that CSR improves labor investment efficiency through two mechanisms of corporate governance and labor market friction. The improvement effect of CSR on labor investment efficiency is more significant in non-state-owned, high CEO shareholding ratio and high-average urban wage enterprises.

In conclusion, our study is an important supplement to the existing research on the factors affecting labor investment efficiency. Our research conclusions will be helpful for enterprises in developing countries or enterprises in labor-intensive industries to improve labor investment inefficiency. The conclusion of the mechanism analysis in this paper provides more complete and reliable microscopic evidence for accurately identifying the specific path of CSR's impact on labor investment efficiency. This paper verifies the positive impact of CSR from the perspective of labor investment efficiency in the context of a developing country, which provides evidence for the theoretical conflicts related to CSR based on the effectiveness of enterprise labor investment decisions.

This study aims to establish an analytical framework to help investors accommodate their environmental, social, and corporate governance (ESG) preferences. The analytical solutions were complemented by empirical analyses to shed light on their benefits and tractability.

This study proposes an expected multi-attribute utility analysis for ESG investors in which stocks can be treated as more green or less green (brown) than the market, represented by an index, all modeled in a one-factor structure. The solution is found via the Hamilton-Jacobi-Bellman (HJB) equation with proper treatment of various sources of risk. For the empirical analysis, we use the RepRisk Rating of US stocks from 2010 to 2020 to select companies that are representative of various ESG ratings.

This study finds closed-form solutions for optimal allocations, wealth and value functions. Our empirical analysis reveals drastic increases in wealth allocation toward high-rated ESG stocks for ESG-sensitive investors, even as the overall level of pecuniary satisfaction remains unchanged.

This study broadens the existing analytical framework by introducing a market portfolio along with green and brown stocks. As by-products, we first demonstrate that investors do not need to reduce their pecuniary satisfaction to increase green investment. Second, we propose a parameterization to capture investors' preferences for green assets over brown or market assets, independent of asset performance.