Dynamic efficiency assessment of the Chinese hotel industry

Abstract

The paper introduces for the first time a totally dynamic two-stage approach to analyzing the hotel industry's technical efficiency at the sub-national level. The first stage uses data envelopment window analysis (DEWA) to assess regional hotel sectors' technical efficiency over time. Unlike previous studies, the second stage uses a dynamic Tobit model to investigate the impact of macro contextual factors on the hotel sector efficiency. The study chooses the Chinese hotel industry during the period 2001-2006 as its application setting. The findings of the investigation indicate that the Chinese hotel industry is approaching an efficient operation in general, recovering from a major dip in 2003 resulting from the Severe Acute Respiratory Syndrome (SARS) outbreak. In addition, the study introduces a novel two-dimensional efficiency-based matrix to assess the competitive advantage of different regions of the Chinese hotel sector. The paper presents strategic market implications for hoteliers, government decision-makers, and destination management organizations. The proposed methods are applicable for situations in which an exogenous event of a destabilizing impact (e.g., SARS) does occur.

Performance evaluation of the hotel industry in an emerging tourism destination: The case of Oman

“…In the second stage, each of these ratios is regressed on a set of environmental variables using Tobit model (Tobin, 1958). A similar approach is also used in Chen, Hu, and Liao (2010), Honma and Hu (2012) and Huang, Mesak, Hsu, and Qu (2012). Simar and Wilson (2007) argue that the efficiency estimates are serially correlated, which renders the standard inference approaches used in the conventional two-stage DEA procedure statistically invalid.…”

The effects of customer voice on hotel performance

“…Hotel size has been linked to the resources that a hotel has. It also represents a prominent contingency variable that distinguishes hotels (Dahlstrom et al, 2009;Huang et al, 2012). Hotel size can, for example, influence a hotel's learning opportunities, and the size of promotions (Barros and Dieke, 2008).…”

The Effect of Sustainability as Innovation Objectives on Innovation Efficiency

“…Therefore, estimation of regression coefficient by ordinary least squares (OLS) has a problem of its regression coefficient being inconsistent and biased estimates. Therefore, we perform tobit regression analysis to measure the effects of environmental variables on innovation efficiency, following studies that used tobit regression when the dependent variable was set as efficiency score [56,57]. In this study, we use slack based DEA model and tobit regression analysis to find out the effect of sustainability consideration factors on innovation efficiency.…”