Competition with asymmetric regulation of mobile termination charges

The aim of this paper is to explore the effectiveness of asymmetric regulation, which allows a new mobile network operator to set higher termination rates than the incumbent operator. We assume that there are two market segments: one in which operators compete on equal terms, with a new technology, and the other in which the entrant is at a disadvantage since the technology it offers is inferior to the incumbent??s. Results show that asymmetric regulation can create favorable conditions that allow the entrant to strengthen its market positioning, and enhance consumer net utilities and social welfare. This highlights the importance of the degree of network asymmetry and the ways in which consumers are split between the two market segments. Lastly, we show that asymmetric regulation can create greater investment incentives for the entrant which could effectively enhance social welfare. These findings can provide useful insights for regulatory policy.     

How Can We Better Understand Current and Future Workforce Values in the Global Business Environment?

Our study tested the predictive power of socioeconomic development theory and age differences theory to explain work values across cultures and across age groups. We compared the values orientations of future managers, business students under the age of 25, with those of current managers and professionals, who we split into three decade groups (30 to 39, 40 to 49, and 50 to 59). Our respondents (n = 1,518) come from six diverse societies: Brazil, Germany, Indonesia, Russia, the United States, and Vietnam. Our findings indicate that both theories contribute to our understanding of work values and behaviors. One implication is that while socioeconomic development theory makes an important contribution, it is clearly not sufficient by itself to explain work values/behavior differences in the global context. The study findings and the discussion of them will hopefully provide multinational managers with a clearer assessment of current and future workforce values/behavior. © 2012 Wiley Periodicals, Inc.     

Who Are the Potential Smokers of Smuggled Cigarettes?

Although smuggled cigarettes have been a prevalent problem and a severe challenge to public health and welfare around the world, little is known about the behavior associated with smoking smuggled cigarettes and the issue is difficult to study due to data limitations. By means of a population‐based tobacco survey conducted in Taiwan, the present paper applies a latent class model to identify potential smokers who are either currently or will at some point in the future be consuming smuggled cigarettes. This methodology, in contrast to the traditional discrete models, allows potential smokers who are more inclined to smoke smuggled cigarettes to be endogenously classified. The empirical results indicate that socio‐demographic factors do increase the inclination to smoke smuggled cigarettes after unobserved heterogeneity has been accounted for.     

Tourist behavioural intentions in relation to service quality and customer satisfaction in Kinmen National Park,Taiwan

This study assesses tourist satisfaction and its links with service quality using a hierarchical model that combines four primary determinants and eight corresponding sub‐dimensions. A sample of 616 tourists departing from Kinmen Airport was surveyed with a structured questionnaire after they had just visited Kinmen National Park. A series of analyses was performed to explore tourist satisfaction with the four main service quality attributes as well as their willingness of repeat visits and recommendation. As a result, it was consistently found that service quality has positive significant relationship with tourist satisfaction. It is thus suggested that national park managers have to satisfy tourists with a high level of service quality, based on the concept that service quality may have a significant influence on long‐term behavioural intentions through high levels of customer satisfaction. Copyright © 2010 John Wiley & Sons, Ltd.     

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 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.     

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.     

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.     

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.