공간계량경제모형을 적용한 호텔객실성과 결정요인분석

Abstract

The purpose of this study was to investigate the determinants of hotel RevPAR using data from 274 hotels in Korea's capital region. As the outset, it is imperative to clarify the concept of location due to fact that there is lack of consensus defining the hotel location. Based on the Mono-Centric Model and the Agglomeration Model, this study proposes an operational definition of hotel location. In addition, traditional explanatory variables such as room count, auxiliary facility size, and brand were considered as determinants. The least squares regression model (OLS), the spatial autoregressive model (SAR), and the spatial error model (SEM) were established in order using cross-sectional data. The SEM is chosen as the final model for this study because it overcomes the problem of spatial autocorrelation. The findings confirm that attributes such as room count, auxiliary facility size, brand, and location are important drivers of RevPAR. The number of companies in the hotel area, in particular, may improve RevPAR, whereas agglomeration may be detrimental to profit in the hotel room market. This study, in addition to having managerial implications, contributes to future research by providing a methodological guide on spatial regression models. It is suggested to spatial econometrics model, which overcoming the problem of spatial autocorrelation, is more appropriate than the traditional OLS in explaining hotel performance.