International Journal of Contemporary Hospitality Management, Volume 26, Issue 8, September 2014.
Purpose This paper employs data envelopment analysis (DEA) models to evaluate the efficiency level and the change of efficiency of the hotel industry in major Chinese cities from 2001 to 2011. The study also investigates the determinants of this efficiency. Design/methodology/approach The DEA models were used to calibrate the scores of technical efficiency, pure technical efficiency, and scale efficiency in each city, and the Malmquist productivity index was introduced to trace the efficiency change. Furthermore, the panel Tobit and linear regression models were applied to look into various factors contributing to efficiency scores. Findings The inefficiency of the hotel industry generally comes from the pure technical inefficiency. Moreover, the efficiency of the hotel industry has been considerably improved over the research period due to the change in technical efficiency. In addition, we found that political hierarchy, degree of openness, and level of tourism dependence help explain the cross-city differences in efficiency scores; whereas ownership structure dominantly contributes to the improvement of efficiency over time. Practical implications The benchmark analysis of efficiency is of great importance to cities with an unproductive hotel industry as it helps them make critical adjustments towards the efficiency frontier. Originality/value This study represents one of the first studies to rigorously and systematically investigate the efficiency and efficiency change of the hotel industry in major Chinese cities and identify the possible factors explaining the efficiency score.
Purpose This paper employs data envelopment analysis (DEA) models to evaluate the efficiency level and the change of efficiency of the hotel industry in major Chinese cities from 2001 to 2011. The study also investigates the determinants of this efficiency. Design/methodology/approach The DEA models were used to calibrate the scores of technical efficiency, pure technical efficiency, and scale efficiency in each city, and the Malmquist productivity index was introduced to trace the efficiency change. Furthermore, the panel Tobit and linear regression models were applied to look into various factors contributing to efficiency scores. Findings The inefficiency of the hotel industry generally comes from the pure technical inefficiency. Moreover, the efficiency of the hotel industry has been considerably improved over the research period due to the change in technical efficiency. In addition, we found that political hierarchy, degree of openness, and level of tourism dependence help explain the cross-city differences in efficiency scores; whereas ownership structure dominantly contributes to the improvement of efficiency over time. Practical implications The benchmark analysis of efficiency is of great importance to cities with an unproductive hotel industry as it helps them make critical adjustments towards the efficiency frontier. Originality/value This study represents one of the first studies to rigorously and systematically investigate the efficiency and efficiency change of the hotel industry in major Chinese cities and identify the possible factors explaining the efficiency score.