A Study on the Operating Efficiency of Taiwan Tourist Hotels

Feng-sheng Julian Chien
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  The SIJ Transactions on Industrial, Financial & Business Management (IFBM), Vol. 2, No. 3, May 2014   ISSN: 2321-242X © 2014 | Published by The Standard International Journals (The SIJ) 62   Abstract   —  Travel is an indispensable lifestyle that grows along with a person’s income. The tourism  industry helps many countries increase their foreign exchange, offer job opportunities, and protect the environment through economic development. This study mainly investigates managerial efficiency in Taiwan tourist hotels and compares their efficiency among different areas of the country The research herein employs Data Envelopment Analysis (DEA) of the CCR and BCC models to explore tourist hotels’ operational any difference between “managerial” and “operational” efficiency. The findings are as  follows. First, the CCR model shows the highest technical efficiency in 2009. The BCC model exhibits that 2008 and 2009 are superior than in 2010. Data from 2008 present that the non-Taipei area is the highest in the CCR model. However, the non-Taipei area and the scenic area are equivalent in the BCC model. Final, data from 2009 find that the scenic area is the highest no matter for the CCR or BCC model. Results from 2010 are the same as 2009. Keywords   —  Data Envelopment Analysis; Managerial Efficiency; Taiwan’s Tourist Hotel . Abbreviations   —  Association for Relations Across the Taiwan Straits (ARATS); Data Envelopment Analysis (DEA); Decision-Making Unit (DMU); Marginal Rate of Substitution (MRS); Straits Exchange Foundation (SEF). I.   I NTRODUCTION   ITH developmental progress throughout time, an increase in national income causes leisure and tourism to become a greater indispensable part of society. The tourism industry not only increases a country’s  foreign exchange earnings and improves employment opportunities through its non-polluting nature, but also  protects the environment from disaster during economic growth. Hence, promoting tourism has become the trend and focus of economic development for many countries. However, with internationalization, globalization, and the influence from a rapidly changing business environment and customer needs, even the tourism industry can encounter  problems. The end result could be that tourist-related companies fail to respond to such dynamic changes and lose their competitiveness or, even worse, get pushed out of the market. China’s statistics indicate that up to 4million China  people are willing to come to Taiwan for scenic sightseeing, demonstrating that Chinese tourists have a great desire to visit Taiwan [Shi-Chi Chen & Wei-Suei Tu, 2002]. Professor Lung of the Law School of Chinese People’s University noted that’s sample survey found  that up to 86% of Chinese people prefer Taiwan to be their first choice when travelling abroad. Their motives behind this are different from most ordinary tourists around the world, as Chinese  people are curious about Taiwan’s five decades of political democracy, economic development, open society, and citizens’ lifestyle. Thus, it is their hope to travel to Taiwan once in their life [Yang, 2008]. In 2008 there was a great leap in cross-strait relations when the Straits Exchange Foundation (SEF) and the Association for Relations Across the Taiwan Straits (ARATS) signed a document that included, but was not limited to, “Agreement for Cross -strait Views of China Residents’ Journey to Taiwan”. Since then, the number of Chinese tourists coming over Taiwan has rapidly grown like a mushroom. In April 2009, for the first time the number of Chinese tourists to Taiwan surpassed Japanese tourists, making them the largest and most important segment of tourists for the island country. This study suggests that Taiwan’s tourism  situation may have a big impact on the local hotel industry. Therefore, the study examines the operating efficiency of Taiwan’s travel and tourism industry, trying to make a comparison between each travel agency’s operating efficiency and operating efficiencies in various regions under this current competitive market environment. The year 2008 is this study’s target  period, because that was when a large number of Chinese tourists came over to Taiwan. This study has two main  purposes. 1) In what manner can many Chinese tourists to Taiwan lead to better operating efficiencies for Taiwan’s  hotels? 2) In terms of geographical area, what difference arise  behind Taiwan hotels’  operating efficiency. W *Ph.D. Student, National Sun Yat-Sen University of Business Management, 70 Lienhai Rd., Kaohsiung 80424, TAIWAN, R.O.C. E-Mail: Julian{at}hp-oa{dot}com Feng-sheng Julian Chien* A Study on the Operating Efficiency of Taiwan Tourist Hotels  The SIJ Transactions on Industrial, Financial & Business Management (IFBM), Vol. 2, No. 3, May 2014   ISSN: 2321-242X © 2014 | Published by The Standard International Journals (The SIJ) 63   II.   L  ITERATURE   2.1.   Allowing Chinese Tourists to Taiwan 2.1.1.   The Evolution of Chinese Tourists to Taiwan Shao Qi-Wei divided the development of related policies and China’s  tourism development into various time periods. 1) Starting from when New China was founded until the time  prior to its first reforms. 2) From the late 1970s up to the early 1990s. 3) In the 1990s. 4) Four time periods in the new twenty-first century. Taiwan scholars Wu-Chung Wu & Shi-Ping Fang (2004) divided the development into two periods: 1949 to 1977 - that is, the reception of foreign affairs; and starting from China’s  reforms in 1978 and up to the present. The first period is further divided into 1949-1959, 1960-1965, 1966-1968, and 1969-1977. The second period is separated into 1978-1988, 1989, 1990-2002, 2003, and after 2003. Ryan et al., (2009) divided the development into periods such as the economic reform period before 1978, 1978-1985, 1986-1991, 1992-2001, and 2002-present [Yu-Ching Liu, 2011]. In 1997 the PRC State Council approved the National Tourism Administration and the Ministry of Public Security to issue “Interim   Measures for Chinese Citizens’ Travelling   Abroad at their Own Expenses”. In addition, Hong Kong and Macau tourism, as well as boundary tourism, were included into the scope of management [Wu-Chung Wu & Shi-Ping Fang, 2004]. This allowed China citizens, who were srcinally supposed to exit to Hong Kong and Macau for relatives to have the right to travel and sightsee overseas. With the advancement of “Administrative Measures for Chinese Citizens’   Travelling Abroad”  during 2001 and 2004, China’s  overseas tourism industry experience average annual growth of 29.3%, with approximately 28.8 million residents travelling abroad. The World Tourism Organization predicts that China’s  overseas tourism industry will hit 100 million  people in 2020. Furthermore, according to country destination data provided for public research by China  National Tourism Administration, a total of 110 countries have opened up their gates for Chinese citizens’ tourism. China has thus  become the world’s fastest growing exporter of residents for tourism [Shi-Ping Fang, 2010]. In November 2001, Taiwan’s R.O.C. government  promoted “China People Coming over to  Taiwan for Tourism Initiatives”  [The Mainland Affairs Council, Executive Yuan, 2009]. On the basis of this initiative, Taiwan identified three categories for Chinese tourists to come to Taiwan. First category: Chinese coming to Taiwan through Hong Kong and Macao. Second category: Chinese travelling abroad or on  business trips who transferred to Taiwan for sightseeing activities. Third category: Chinese who studied abroad or lived abroad acquiring, permanent stay authority from overseas [The Mainland Affairs Council, Executive Yuan, 2009]. The sequence of these categories that opened up tourism and sightseeing was initially “third category” in January 2002, then “second category” in May 2002, and lastly “first category” in July 2008.  Following in 2008, after nearly 10 years of delay due to cross-strait negotiations, Chinese tourists, who failed to come to Taiwan (first category), were permitted access to Taiwan in July 16, 2008. On June 11, 2008, both countries entered into “Agreement for Cross - strait Views of China Residents’ Journey to Taiwan”  [Tourism Bureau, The Ministry of Transportation, 2010A], which enabled Chinese citizens who were cl assified into the “first category” and failed to come to Taiwan for tourism to finally be able to visit Taiwan. This led to a variance behind the number of cross-strait tourists, showing asymmetry after individuals classified under “first category” were al lowed into Taiwan in July 2008. Since July 2008, China’s citizens have been allowed to travel to Taiwan, and as of July 2010, various provinces and cities in China were in full liberalization to allow their residents to come to Taiwan. An average of 1,661 Chinese daily came to Taiwan in tour groups in 2009, rising to a daily average of 3,440 in the latter half of 2010 [Tourism Bureau, Ministry of Transportation, 2010B]. Compared to an average of 230 people each day in 2007, the numbers have obviously  balloo ned. In fact, statistics extracted from Taiwan’s  Immigration Department, Ministry of the Interior, and Ministry of Tourism show that the number of Chinese tourists leapfrogged over Japanese tourists for the first time in 2010 to become the number one exporter of tourist to Taiwan. In order to make Chinese tourists have a smooth trip to Taiwan, Taiwan’s authority has  gradually stream lined the application process and reduced restrictions. Taiwan has also initiated regulations over the quality behind Chinese tourists and sightseeing activities in Taiwan, including the protection of passenger rights, assuring the integrity behind the travel industry’s  operations and services, and prohibiting zero or negative fares in order to maintain tourism market order, thus adequately protecting Chinese tourists’  interests and rights of travel in Taiwan [Tourism Bureau, Ministry of Transportation, 2009]. 2.2.   The Literature on Allowing Chinese Tourists to Visit Taiwan In recent years, Chinese tourists coming to Taiwan have shown rapid growth, resulting in positive impacts to Taiwan’s tourism sector, economy, and environment. The findings in some studies come from surveys made on Chinese tourists’  socio economic backgrounds, indicating that the majority of them are male, unmarried, and aged 25 to 49, have an average monthly income of between RMB 4,501 to 6,000, have a  bachelor degree, and most are employees working for private firms [Yang, 2008; Jin, 2010]. In addition, most Chinese tourists were on their first trip to Taiwan and their trip averaged 5-7 days. For tours, the number of group members was about 7-16 [Chi-Yueh Lee, 2007; Yang, 2008; Jin, 2010]. Li-Chun Chen (2011) found that an improvement in hotel room condition can be observed from occupancy rates. Hotel staff felt an obvious booming effect from Chinese tourists coming over to Taiwan. Such positive growth has resulted in some studies indicating that most respondents  The SIJ Transactions on Industrial, Financial & Business Management (IFBM), Vol. 2, No. 3, May 2014   ISSN: 2321-242X © 2014 | Published by The Standard International Journals (The SIJ) 64    perceived positive effects were greater than negative ones. Respondents also believed that the greatest positive effect from tourism development would be on the local economy [Yu-Ching Liu, 2011]. In addition to the above perceptions held by Taiwanese on Chinese tourists’, the quality of tourism service, overall satisfaction for services and products, and protection of rights and interests behind tourism are also worthy of attention. The findings of Chun-Chi Chen (2008) indicate that Chinese tourists’ variance of socio -economic backgrounds shows a discrepancy behind their perception of satisfaction level from their trip and their degree of willingness to revisit Taiwan [*srcinal sentence made no sense. Guessing here.*]. Furthermore, the image of tourist attractions, shops, product attributes, attitudes by hotel staff, etc. have significant correlati ons with Chinese tourists’ perception of travelling in Taiwan [Yu-meng Chuang, 2009; Shun-Chin Lin, 2010; Ong, 2011]. 2.3.   Literature of Taiwan Tourism Businesses’ Operational Efficiency In the past, there have been many domestic and foreign studies in the literature with themes on the operating efficiency of tourism, wherein the research methods adopted are as varied as the research purposes. They can be summarized as data envelopment analysis, cost function analysis, balanced score card, regression analysis, etc. Moery & Dittman (1995) utilized 54 hotels throughout the United of States as subjects, where their operating  performance was measured through DEA of the CCR model. The number of rooms, occupancy rate, average room rate, operating cost of the room service department, energy cost,  payroll cost, operating cost, payroll cost of advertisement, other advertising costs, fixed marketing cost, payroll of management cost, and other administrative costs were selected as input variables, while total revenue, service satisfaction index, and facility satisfaction index were selected as output variables. The findings indicate that the overall average operating efficiency value of a hotel was 0.89 (the lowest efficiency value among all hotels was 0.64). Anderson et al., (2000) analyzed variable operating efficiency in the hotel industry through the DEA method, where the number of full-time employees, number of rooms, costs and expenses as to casino operations, catering cost, and other expenses were selected as input variables, while total operating revenue was selected as the output variable. The findings show an overall efficiency value of only 42%, whereby the main reason was poor performance in efficiency for technology and allocation. Hence, hotel managers should think more about how to allocate resources instead of managing resources. Hwang & Chang (2003) investigated the changes made in operations among 45 Taiwan international tourist hotels during 1994~1998 through the DEA method. Due to the highly competitive situation in the hotel industry, differences behind customer resources and management resulted in significant performance differences. Thus, many local hotels were willing to introduce the management mode of international hotels. The findings indicate significant improvements displayed in operational efficiency, which has  become a trend for the hotel industry in Taiwan to follow in the future. In addition, since the DEA method was considered as the most effective method in assessing inputs/outputs, many domestic research studies focusing on the operational efficiency of hotels used it for in-depth discussions [Wen-Min Lu, 2006; Wei-Huang Hsieh, 2007; Wang, 2008; Yang, 2008; Wan-Yi Yang, 2009; Shu-Jing Yeh, 2011; Qiu, 2011]. In addition to employing DEA on the operating  performance of tourism, cost function analysis has also been considered by studies. Chen & Soo (2007) analyzed 47 Taiwan international hotels, their cost structure, and their  production growth rate during 1997 to 2001 through a trans log cost function module, where the cost function mainly includes three input functions and three output functions. The findings indicate that the production growth rate grew during the three-year-period of 1997-1999, while it fell from 2000 to 2001 due to the lagging effects from the Asian financial crisis. Chen (2007) analyzed the cost efficiency of Taiwan’s  international tourist hotels, where the cost function mainly includes three inputs and one output (total revenue). The findings indicate that on average Taiwan’s international tourist hotels have efficient operations at 80%, in which chain hotels exhibited better efficiency than that of hotels operated independently. Other studies have used two or more than two kinds of analysis methods, such as the balanced scorecard being selected first to choose the benchmark of each dimension, and then the difference behind efficiency of international tourism was assessed through the DEA method [Wang & Hsu-Hung, 2006]. The findings indicate that up to 77% of the international hotels in Taipei and Kaohsiung are relatively inefficient, because of poor performance in the output items including but not limited to profitability of the room service department and catering service department, customer satisfaction, market share, ratio of service to revenue, and employee productivity leading to poor performance in the current period. The findings behind multivariate analysis of differences suggest how a hotel can adjust its overall volume of improvements in each variable so as to enhance its overall operational efficiency. The operating efficiency of a hotel varies significantly with geographical location and management mode, and a hotel’s operating efficiency does not display significance due to different sources of tourists and scale of rooms. Yu Ching Wang (2009) placed 50 Taiwan international tourist hotels as the samples in his study and employed DEA and the Malmquist model to assess the root causes of the differences behind the relative operating efficiencies of these hotels during 2002-2006 so as to achieve strategic management goals.  The SIJ Transactions on Industrial, Financial & Business Management (IFBM), Vol. 2, No. 3, May 2014   ISSN: 2321-242X © 2014 | Published by The Standard International Journals (The SIJ) 65   III.   M ETHOD   3.1.   Sample This study selects a large number of Chinese tourists coming over Taiwan during 2008 to 2010 as the sample for discussing the operating efficiency of tourist hotels. The data source selected is from statistics of the Tourism Bureau, Ministry of Transportation. From the srcinal case hotels in 2008, 2009, and 2010, 75, 77, and 85 hotels were respectively selected. For ease of analysis, the study herein also divides the country into Taipei region, non-Taipei region (included Kaohsiung, Taichung, Hualien, and Taoyuan / Hsinzhu / Miaoli), and scenic region (statistics of the Tourism Bureau, Ministry of Transportation), with 31 hotels categorized into the Taipei region, 28 into the non-Taipei region, and 16 into the scenic region in 2008, 31 hotels into the Taipei region, 31 into the non-Taipei region, and 15 into the scenic region in 2009, and 35 hotels into the Taipei region, 34 into the non-Taipei region, and 16 into the scenic region in 2010. Differences are displayed in the number of hotels for each year, caused by new tourist hotels opening up and the shutting down of some tourist hotels. 3.2.   Measurement 3.2.1.    Evaluation of Operational Efficiency - DEA The previous chapter presents many ways utilized by studies of the operational efficiency of the tourism industry, such as data envelopment analysis, regression analysis, cost function analysis, etc., with various kinds of methods applicable for whatever reasons. On the basis of the research purpose herein, this study employs the DEA method. Data Envelopment Analysis (DEA) was first proposed by Farrell (1957), who used a multi-input and multi-output analysis model. Farrell utilized the concept of the frontier  production function to measure the level of production efficiency. DEA is a non-parametric frontier in efficiency measurement that does not employ a default function type, relying instead on a mathematical programming technique to identify the enveloping dimension of efficiency instead of  presetting the allocation between the production function and interference items for benchmarking each decision-making unit used in the measurement of efficiency. The analysis method applies inputs and outputs to the desired Decision-Making Unit (DMU) for assessment in the module, seeking the efficiency calculated from each DMU and then all efficiency values through a linear connection to form an envelopment, which is also known as the efficiency frontier. Productivity is divided into technical efficiency and allocative efficiency. Technical efficiency refers to a manufacturer’s ability behind the maximum output from the effective use of input elements given a certain level of technology . Allocative efficiency refers to a manufacturer’s ability behind the minimum cost from the optimized allocation of the ratio of the production factor to the inputs given a certain level of technology and factor prices. Suppose that the manufacturer’s Marginal Rate of Substitution (MRS) of both production factors equals the ratio of both input  prices, i.e. MRS = W1/W2. It is then claimed that the said manufacturer has allocative efficiency in its production  behavior. On the contrary, suppose that MRS of both factors of production is not equivalent to that of both input prices. It is then claimed that the manufacturer shall have non-allocative efficiency in its production behavior. Continuing from the assessment of efficiency affirmed through the non-parameter method suggested by Farrell (1957), Charnes et al., (1978) improved upon it further to acquire the production frontier for the evaluation unit via linear programming techniques and to calculate the relative efficiency of the subject. Any one subject whose relative efficiency lies on the production frontier (i.e. production  boundary) will be considered as the unit with the optimized efficiency when its performance indicator is 1, while the unit whose relative efficiency failed to be on the production frontier shall be referred to as being inefficient, whereby the relative performance indicator is able to be acquired from the efficiency point distanced with the envelope curve. This method is known as the CCR model, which assumes that constant scale of returns is generated from mass production - that is, when an input has an equally proportional increase, so does the output, whereas an input decline in equal proportion does the same for the output. However, mass production may also be classified under increased/decreased scale of returns, where its inefficiency displayed in the DMU may be caused  by operating under variable scale of returns. Hence, the state of scale of returns through an understanding of an individual DMU can be a reference for managers to improve. Given that not every DMU has its mass production under constant scale of returns, Banker et al., (1984) derived the BCC model where pure technical efficiency and scale efficiency can be measured from a set of four axioms and Shephard’s  distance function, which might be collected from mass production. The BCC model removes the assumption of an unchanged scale of returns in the CCR model and replaces it with a change in scale of returns. Thus, pure technical efficiency and scale efficiency can be separated. The approach is to divide the efficiency value of the CCR model  by that of the BCC model - that is, the scale efficiency of a DMU -so as to measure if mass production is at an optimal scale under changeable production technology of the subject. If scale efficiency shows a constant scale of returns, then it represents that the DMU is at a scale with ultimate  productivity, and the DMU’s efficiency value in the  CCR and BCC models is. If scale efficiency is expected to be increased, then it means that scale of the DMU is smaller than the optimal one, which thus needs to be expanded; otherwise, it means that the DMU is larger than the optimal one and needs to be scaled down. Hence, it can be a reference for a DMU manager in the decision-making phase. 3.2.2.    Input / Output Variables Based on the historical literature for tourist hotels and referring to the availability of accessing the information, this study sets up output and input variables as follows.
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