Hotel job burnout: The role of personality characteristics

In hospitality and tourism academia, most research focuses on the work domain as a major source of hospitality job stress, with little attention given to employee characteristics. This study examines the effect of the Big Five personality dimensions (extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience) on hotel employees’ job burnout. After controlling for two commonly known job burnout antecedents (autonomy and quantitative workload), study results indicate that personality attributes explain significant proportions of three job burnout factors. The most noteworthy finding is the predictability of the agreeableness trait in hotel employees’ job burnout. Because of the mixed results reported on the relationship between this trait and job stress in other disciplines, more vigorous future research is recommended to validate the value of this personality to the hospitality industry.     

Using qualitative approach to forecasting regime switches

Drastic changes (named regime switches) often exist in economic and financial time series causing the forecasting of time series difficult. Hence, we need robust models to detect and forecast the regime switches. Most previous studies apply quantitative methods to forecast time series and regime switches. Contrast to these studies, this study attempts a novel approach to use a qualitative method to forecast regime switches. Fuzzy set/qualitative comparative analysis (fsQCA), based on fuzzy set and logic theory, yields the relationships between antecedent combinations and outcome. Studies support fsQCA analysis is more proper to reflect the real situations. Hence, this study uses fsQCA to analyze the autoregressive relationships of the upward and downward regime switches in the in-sample data. Then, the relationships are used to forecast the regime switches in the out-of-sample data. Taiwan Capitalization Weighted Stock Index is taken as the data for analysis. The empirical results show that fsQCA provides strong predictive validities.     

Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels

Stationary bootstrapping is applied to a CUSUM test for common mean break detection in cross-sectionally correlated panel data. Asymptotic null distribution of the bootstrapped test is derived, which is the same as that of the original CUSUM test depending on cross-sectional correlation parameter. A bootstrap test using the CUSUM test with bootstrap critical values is proposed and its asymptotic validity is proved. Finite sample Monte-Carlo simulation shows that the proposed test has reasonable size while other existing tests have severe size distortion under cross-section correlation. The simulation also shows good power performance of the proposed test against non-cancelling mean changes. The simulation also shows that the theoretically justified stationary bootstrapping CUSUM test has comparable size and power relative to other, theoretically unjustified, moving block or tapered block bootstrapping CUSUM tests.     

Substituting and Complementing Models of Economic Development in East Asia

This paper assesses the relative merits and demerits of different East Asian models by placing them in a historical perspective. It re-interprets Gerschenkron's model of late industrialization, and extends it to compare East Asian economies in view of substituting and complementing models. It then explains divergent performances among East Asian economies from the late 1990s by examining the different challenges they faced as their economies became mature and more fully open to forces of globalization. In conclusion, the paper discusses the applicability of the East Asian models for today's developing countries.     

What makes consumers use VoIP over mobile phones? Free riding or consumerization of new service

Consumer acceptance of technological innovations is crucial to marketing strategy and policy development. This study analyzes consumer behaviors in mobile voice over Internet protocol (mVoIP), focusing on the antecedents of consumers' intentions. Using a context-specific extension of the Technology Acceptance Model, mVoIP acceptance was investigated based on the salient belief of perceived usefulness, perceived ease of use, and facilitating factors. The results show that quality factors of mVoIP significantly influence the usefulness and ease of use, which subsequently affect the adoption of the technology. Call and service quality were found to be significant factors, followed by mobility and coverage. The policy and managerial implications of mVoIP are discussed based on the model. In conclusion, this study provides in-depth analysis and heuristic data on the consumer drivers, market dynamics, and policy implication within the mVoIP ecosystem.     

Empirical prediction intervals revisited

Empirical prediction intervals are constructed based on the distribution of previous out-of-sample forecast errors. Given historical data, a sample of such forecast errors is generated by successively applying a chosen point forecasting model to a sequence of fixed windows of past observations and recording the associated deviations of the model predictions from the actual observations out-of-sample. The suitable quantiles of the distribution of these forecast errors are then used along with the point forecast made by the selected model to construct an empirical prediction interval. This paper re-examines the properties of the empirical prediction interval. Specifically, we provide conditions for its asymptotic validity, evaluate its small sample performance and discuss its limitations.