The effect of mandatory CSR disclosure on firm profitability and social externalities: Evidence from China

We examine how mandatory disclosure of corporate social responsibility (CSR) impacts firm performance and social externalities. Our analysis exploits China's 2008 mandate requiring firms to disclose CSR activities, using a difference-in-differences design. Although the mandate does not require firms to spend on CSR, we find that mandatory CSR reporting firms experience a decrease in profitability subsequent to the mandate. In addition, the cities most impacted by the disclosure mandate experience a decrease in their industrial wastewater and SO₂ emission levels. These findings suggest that mandatory CSR disclosure alters firm behavior and generates positive externalities at the expense of shareholders.     

Industrial upgrading efficiency and free markets in emerging economies: A two-stage meta-frontier approach

This paper establishes an industrial upgrading model by dividing the industrial upgrading process into two: the foundation–construction and industrial upgrading stages. Eighty-one sample countries, from 2006 to 2012, were divided into two groups according to their degree of market freedom. The meta-frontier method was employed to explore technology gaps in the groups caused by the different markets. It was found that emerging economies with a free market have a better upgrading performance than those with a restricted market, and the efficiency gap between the two groups was seen to be continually increasing.     

Converting volunteers to donors: Fundraising strategies for professional associations

The use of fundraising strategies in professional associations is on the rise as member donations have become an increasingly important revenue stream for the associations. This study aims to understand why member volunteers are potential donors to professional associations and to examine whether association solicitation is effective in increasing member volunteer donations. A moderated mediation model was tested with data that consisted of 3,224 professional association members. The results suggest that member satisfaction significantly mediates the relationship between member volunteering and financial giving, and solicitation only makes a difference to member volunteers who are satisfied with their membership. This study concludes that targeting satisfied member volunteers for donations could yield financial benefits to professional associations.     

Rainbow trend options: valuation and applications

Asset selection and timing decisions are major investment concerns. To resolve these issues simultaneously, a new class of rainbow trend options is proposed. The diversification effect of rainbow options can reduce the importance of asset selection decisions and trend options can mitigate unfavorable effects on market entry and exit decisions. We consider a general framework to facilitate the derivation of analytic pricing formulas for simple, pure, and Asian rainbow trend options using the martingale pricing method. The properties of these options and their Greeks are analyzed. We also investigate the performance of the dynamic delta hedging strategy for issuers of rainbow trend options. Last, this paper explores the applications of rainbow trend options for hedging price risks, designing executive stock options, modifying countercyclical capital buffer proposed by Basel Committee, and acting as control variates of the Monte Carlo simulation.     

Investment in quality upgrade and regulation of the internet

This paper studies the investment decision by a monopolistic internet service provider (ISP) in different regulatory environments. We consider that the ISP can technically provide separate quality upgrades to two vertically differentiated content providers (CPs). Our results show that if unregulated, the ISP could optimally provide asymmetric quality upgrades to both CPs, in favor of the high-quality CP. This subsequently increases the degree of content differentiation, softening competition between the CPs. Imposing a nondiscrimination regulation that forces the ISP to provide an equal quality upgrade to both CPs, however, reduce the ISP’s investment incentive and social welfare. Furthermore, the social planner provides preferential treatment to the high-quality CP if the degree of substitutability is sufficiently low. In contrast, it is socially optimal to prioritize the low-quality CP if the contents are sufficient substitutes, or provide exclusivity if vertical differentiation is high.

     

Complex Network of Aviation E-Services in the Belt and Road Initiative: A Heuristic Study of Small Data based on Block Modeling

ABSTRACT

The aviation e-service system is an important part of support for business communication in regions covered by Belt and Road initiative. In exploring the role of airline companies in this system, we examine the structure of the network, which consists of airlines interconnections based on small data of individual attributes of aviation companies in aviation e-services, and study these interconnections across different groups using block modeling. The heuristic solution of airline companies in development of international communication and cooperation is further discussed. Among our policy implications for global managers, we suggest the enhancement of cross-regional cooperation among airlines.     

Bayesian Inference in Spatial Sample Selection Models

In this study, we consider Bayesian methods for the estimation of a sample selection model with spatially correlated disturbance terms. We design a set of Markov chain Monte Carlo algorithms based on the method of data augmentation. The natural parameterization for the covariance structure of our model involves an unidentified parameter that complicates posterior analysis. The unidentified parameter – the variance of the disturbance term in the selection equation – is handled in different ways in these algorithms to achieve identification for other parameters. The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study and an empirical application.     

The Effects of Four Dimensions of Strategic Orientation on Firm Innovativeness and Performance in Emerging Market Small- and Medium-Size Enterprises

We investigate the effects of technology, entrepreneurial, market, and learning orientations on firm innovativeness, and the mediating effect of firm innovativeness on these relationships, using a survey of 374 small- and medium-size enterprises in Korea. The results reveal that, while technology, entrepreneurial, and learning orientations significantly influence firm innovativeness, firm innovativeness has a significant effect on firm performance. We also find that firm innovativeness has a statistically significant mediating role in the relationships of technology, entrepreneurial, and learning orientations to firm performance. Our study contributes to strategic management and emerging market literature by identifying the pivotal role of innovativeness for firms that seek to benefit from various types of strategic orientations.     

Heteroskedasticity-consistent covariance matrix estimators for spatial autoregressive models

In the presence of heteroskedasticity, conventional test statistics based on the ordinary least squares (OLS) estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of heteroskedasticity-consistent covariance matrices (HCCMs) have been developed in the literature. In contrast to the standard linear regression model, heteroskedasticity is a more serious problem for spatial econometric models, generally causing inconsistent extremum estimators of model coefficients. This paper investigates the finite sample properties of the heteroskedasticity-robust generalized method of moments estimator (RGMME) for a spatial econometric model with an unknown form of heteroskedasticity. In particular, it develops various HCCM-type corrections to improve the finite sample properties of the RGMME and the conventional Wald test. The Monte Carlo results indicate that the HCCM-type corrections can produce more accurate results for inference on model parameters and the impact effects estimates in small samples.