A Framework for the Establishment of an Optimal Service Quality Level in a Hospitality Operational Setting

Yasin, Mahmoud M.; Czuchry, Andrew J.; Dorsch, Jeffrey J.

doi:10.1300/j150v04n02_03

Cited by 17 publications

(9 citation statements)

References 3 publications

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“…According to studies presented in Table 1 (e.g., Anderson et al, 2000;Barros, 2005), input resources for the hotel industry include variables such as staff, capital and equipment. These resources produce tangible and intangible services through front office and back office operations (Yasin, Czuchry, & Dorsch, 1996). The present study employs three input indicators: (1) total number of full- (1) Full-time workers, (2) cost of labor, (3) book value of property, (4) external costs.…”

Section: Defining Input-output Indicatorsmentioning

confidence: 99%

Dynamic efficiency assessment of the Chinese hotel industry

Huang

Mesak

Hsu

et al. 2012

Journal of Business Research

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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.

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Section: Defining Input-output Indicatorsmentioning

confidence: 99%

Dynamic efficiency assessment of the Chinese hotel industry

Huang

Mesak

Hsu

et al. 2012

Journal of Business Research

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“…Input resources for the management of international tourist hotels include materials, staff, capital and equipment. These resources produce tangible and intangible services through front-office and back-office operations (Yasin et al, 1996). Four inputs were identified: number of rooms (I1); number of full-time employees in room departments (I2); total floor area of food and beverage departments (I3); and number of full-time employees in food and beverage departments (I4).…”

Section: Defining Input-output Factorsmentioning

confidence: 99%

Measuring the Cost Efficiency of International Tourist Hotels in Taiwan

2006

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This study employs data envelopment analysis (DEA) to evaluate the relative cost efficiency of 49 international tourist hotels in Taiwan. The study uses five different measures: overall efficiency (OE), allocative efficiency (AE), technical efficiency (TE), scale efficiency (SE) and pure technical efficiency (PTE). Applying efficiency measures derived from the DEA estimation, hotel efficiency determinants are evaluated using the Tobit regression model. A bootstrapping technique is applied to overcome the interdependency problem of the DEA efficiency scores adopted in the regression analysis. The empirical results demonstrate that the international tourist hotel industry in Taiwan is inefficient, with most efficiency losses attributable to technical inefficiencies, of which scale inefficiencies are the primary cause – the scale of operations of international tourist hotels in Taiwan being too small to enable the cost-savings associated with larger-scale operations. The Tobit regression results indicate that the proportion of foreign individual travellers (FIT), online transaction function (WEB) and franchising (HOTELTYPE) are related to a better performance of international tourist hotels in Taiwan. The number of years a hotel has been operating (AGE) is not significantly related to any of the efficiency measures.

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“…The selection of variables should represent the inputs and outputs used by China's hotel industry in its service production process and the results obtained in empirical research performed prior to the investigation (Such Devesa and Mendieta Peñalver, 2013). For a TFP study, each input is classified as either an indicator of labor or capital reflecting resources such as staff, capital, and equipment deployed in producing tangible products and intangible services (Huang et al, 2012;Yasin et al, 1997;Zhou et al, 2008). As a result, we considered two inputs (i.e.…”

Section: Data and Variablesmentioning

confidence: 99%

Total factor productivity growth and regional competitive analysis of China’s star-rated hotels

Liu

Tsai

2018

Tourism Economics

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This study investigates the total factor productivity (TFP) growth, technological progress, pure technical efficiency change, scale efficiency change, and mix efficiency change of star-rated hotels in China by employing a Hicks–Moorsteen index approach. The results show that the TFP of star-rated hotels in China had an annual average growth rate of 13.11%, mainly attributed to an annual average growth rate of operational efficiency of 21.85% and a mix efficiency growth rate of 13.52%. The growth rate of optimal production technology in the Western region markedly outperformed those in other regions and yet its growth rate of operational efficiency significantly underperformed. We also found that catch-up effects in the Central and Western regions were progressing in terms of operational efficiency and optimal production technology, respectively. The findings suggest that policy makers and practitioners should focus on TFP growth and its components, drawing the attention of star-rated hotels to upgrade their optimal production technology and enhance their operational efficiency as a means of improving TFP and competitiveness. Lastly, this study advances a new research perspective in efficiency assessment in the hotel industry by considering both financial and service production outputs.

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A Framework for the Establishment of an Optimal Service Quality Level in a Hospitality Operational Setting

Cited by 17 publications

References 3 publications

Dynamic efficiency assessment of the Chinese hotel industry

Dynamic efficiency assessment of the Chinese hotel industry

Measuring the Cost Efficiency of International Tourist Hotels in Taiwan

Total factor productivity growth and regional competitive analysis of China’s star-rated hotels

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