PERFORMANCE BENCHMARKING FOR TAIWAN'S INTERNATIONAL TOURIST HOTELS

INFOR, Aug 2006 by Yang, Chyan, Lu, Wen-Min

ABSTRACT

This study proposes an alternative data envelopment analysis (DEA) method to explore the managerial performance, the input congestion, and the benchmarks of international tourist hotels (ITHs) for a small open economy, Taiwan. Several empirical results are shown: (1) most ITHs operate at decreasing returns to scale, indicating that ITHs are facing a highly competitive environment; (2) the international chain ITHs are generally more efficient than independent-owned ones; (3) ITHs located in resort areas operate slightly better on average than ones located in metropolitan areas; (4) ITHs that are close to CKS international airport operate slightly worse on average than ones far from CKS international airport; (5) congestion analysis reveals that inefficient ITHs lack the ability to integrate their resources, especially in the total area of the catering division and the number of guest rooms; and finally, (6) the reference-share measure shows that efficient international chain ITHs are able to more easily become benchmarks. The findings show that efficient international chain ITHs are more competitive and they should provide examples of operating practice.

Keywords: Data envelopment analysis; Performance measurement; Input congestion; Referenceshare measure.

(ProQuest Information and Learning: ... denotes formulae omitted.)

1. INTRODUCTION

This study proposes an alternative data envelopment analysis (DEA) method to examine the managerial performance, input congestion, and the benchmarks of fifty-six Taiwanese international tourist hotels (ITHs) in 2002. The results of this study can provide Taiwanese ITHs' operations with insights into resource allocation and competitive advantage and help with strategic decision-making, especially regarding operational styles under an intense competitive environment through high ITH density.

Taiwan's ITH industry is experiencing competitive pressure due to the rapid growth of new ITHs, a decreasing number of tourists, deteriorating economic conditions, and inefficient management. Inefficient management is the key issue that top managers should pay attention to. In other words, the total number of Taiwan's ITHs has increased from 44 to 62 within the period of 1985 to 2004, while the total number of ordinary tourist hotels has decreased from 79 in 1985 to 25 in 2004. Moreover, as a result of the Asia Financial Crisis in 1997, Taiwan's 921 earthquake in 1999, the 911 terrorist act in 2001, the second Persian Gulf War in 2003, and the SARS epidemic in 2003, the number of foreign tourists visiting Taiwan are decreasing. With the external reasons stated above and inefficient hotel management, eight four-star ITHs closed down in 1998. To survive, the island's ITHs need to identify the critical input/output factors to improve their operating efficiency and managerial performance.

Much of the research on the hotel industry often uses performance indicators. These studies mostly focus on single indicators such as cost-volume-profit (Fay et al., 1971, Jaedicke et al., 1975 and Coltman, 1978), the lodging industry's sales receipt information (Van Doren and Gustke, 1982), the concept of perishable asset revenue management to measure performance (Kimes, 1989), lodging index (Wassenaar and Stafford, 1991), the RevPar (revenue per available room) index (Ismail et al., 2002), a revenue performance indicator (Baker and Riley, 1994), and an efficiency indicator (Wijeysinghe, 1993). Although these accounting and financial indicators in terms of simple ratios provide important and useful information for benchmarking a hotel's financial performance, there are in fact many factors relative to hotel performance, and obviously these techniques have not taken into account the mix and nature of services provided. As suggested by Anderson et al. (1999), measuring the relative efficiency of a hotel requires methods that are more sensitive than accounting and ratio measures and that can explicitly consider the mix of service outputs produced.

To overcome the drawbacks mentioned above, DEA has been used to measure hotel performance over the last decade. DEA has many desirable features (Charens et al., 1994) which may explain why researchers are interested in using it to investigate the efficiency of converting multiple inputs into multiple outputs. Furthermore, DEA is also a theory-based, transparent, and reproducible computational procedure. In comparison to the traditional approaches such as ratio analysis and regression analysis (Sherman, 1986), DEA has gained several more advantages. One major advantage is that DEA has emerged as the leading method for efficiency evaluation in terms of both the number of research papers published and the number of applications to real world problems (Seiford, 1997; Gattoufi et al., 2004). Previous studies that used DEA to investigate the relative efficiency of the hotel industry are now described as follows.

Bell and Morey (1995) employed DEA to measure the relative efficiency of 31 travel departments in the United States. Morey and Dittman (1995) implemented DEA to probe the generalmanager performances of 54 owner-managed hotels of a nationally known chain, geographically dispersed over the continental United States. This study provides the owners of single properties with the ability to benchmark a manager's performance. By using the stochastic frontier approach (SFA), Anderson et al. (1999) evaluated the managerial efficiency of 48 hotels using operating data in the year 1997. Anderson et al. (2000) employed DEA to re-evaluate the managerial efficiency of 48 hotels using the data in Anderson et al. (1999). This study contradicts previous studies, which find the hotel industry to be nearly perfectly competitive and efficient. The major reason is that they use a more comprehensive efficiency measure and are able to capture more inefficiency.