Should the EFQM Excellence Model be Adapted for Specific Industries? A Restaurant Sector Example

As the scores in the current European Foundation for Quality Management (EFQM) excellence model are the same for all industries, the accuracy of the model has been questioned. Our objective is threefold: 1) to confirm the need to adjust the EFQM model, using the restaurant industry as an example; 2) to ensure the new scores from the restaurant experts are consistent and reliable through the Kruskal-Wallis test for intergroup consistency and Kendall’s W for interexpert reliability; and 3) to use the fuzzy analytic hierarchy process to give each attribute and sub-attribute a new, accurate score. Among the restaurant attribute and sub-attribute scores, Customer Results scored 190 points instead of 150 points, and Processes, Products & Services scored 140 points instead of 100 points in the current model. The findings show that the new scores differ substantially from the current EFQM model. We then argue that its evaluation scores should be modified by industry.     

How do hotels choose their location? Evidence from hotels in Beijing

This study aims to investigate potential factors contributing to the hotel location choice by an ordered logit model incorporating both hotel and location characteristics. The results suggest that, star rating, years after opening, service diversification, ownership, agglomeration effect, public service infrastructure, road accessibility, subway accessibility, and accessibility to tourism sites are important determinants. By examining location models for different periods, different star rating levels, and different ownership, we show that, downscale hotels tend not to actively seek the benefits of agglomeration effects while upscale ones are more sensitive to accessibility. Finally, agglomeration effects are further investigated by looking into agglomeration heterogeneity, agglomeration scope, scale related and ownership related agglomeration, and agglomeration zoning.     

A model of historical development and future trends of Italian cuisine in America

This study investigated both the historical development and future trends of restaurant cuisine in America. Italian cuisine is used as the basis of a prediction model. The study identifies the historical factors in menu trends in Italian–American cuisine; the factors that will influence culinary trends in the future, and whether the results can be applied to the development of a prediction model that will predict how restaurant cuisine in America may develop. This study used both qualitative (focus groups) and quantitative (online survey) methods. The growing popularity of Italian cuisine in the United States will continue to shape the evolution of America's restaurant cuisine.     

A spatial–temporal analysis of hotels in urban tourism destination

This study investigates the spatial associations of urban tourism phenomena by using GIS and statistical methods to examine the relationships between hotels and land use types, attractions, transportation facilities, and the economic variables of the tertiary planning units in which the hotels are located. Hong Kong is used as an example. The study first introduces the spatial characteristics of hotels and attractions development in Hong Kong. A geographical information system is then used to map hotels and investigate the characteristics of the land use, attractions, and transport facilities around hotels. The spatial relationships are then analyzed with a set of logistic regression models. The results reveal that commercial land type and the number of attractions around hotels are significantly related to the distribution of upper-grade hotels in Hong Kong. The determinants vary over time and the spatial structure changes accordingly. The analysis is important theoretically as it enriches the methodologies for analyzing the relationships between hotels and urban structure, and for conceptualizing and identifying tourism functional zones. It is important for practitioners as it provides useful information for selecting sites for hotels.     

Evaluation of the impact of the tourism nation promotion project on inbound tourists in Japan: a difference-in-differences approach

This study quantitatively evaluates the impact of the Tourism Nation Promotion Project on tourism demand. Data were obtained from Japan Tourism Agency’s quarterly survey from 2010Q2 to 2015Q4. Cox and zero-truncated negative binomial models and difference-in-differences approach were applied to analyze tourism demand and the project’s impact on inbound tourists’ length of stay and expenditure in Japan. Empirical results showed a positive and significant average treatment effect on length of stay and expenditure for tourists from Australia, China, Russia, and Thailand. These findings indicate that the Japanese government should use differentiated strategies considering different nationalities’ characteristics to attract foreign tourists.     

Tourist market segmentation with linear and non-linear techniques

The need for in-depth knowledge of tourist market segments and the need to overcome the limitations of using linear techniques to analyse non-linear relationships requires a re-assessment of generally used approaches such as cluster analysis and multiple linear regression. The objectives of the research are (1) to consider the use of self-organising (SOM) neural networks for segmenting tourist markets and (2) to analyse the predictive ability of backpropagation (BP) neural networks for classifying tourists from follow-up surveys by using the output provided by a SOM neural network. The findings of the SOM neural network modelling indicate three natural clusters. In addition, the predictive ability of the BP neural network model appears to be superior to that of MLR static filter and logistic regression models. The BP neural network model developed for this application appears suitable for deployment (i.e. classification of tourists from follow-up surveys).     

Predicting Korean lodging firm failures: An artificial neural network model along with a logistic regression model

Using financial variables as predictors, this study developed logistic regression and artificial neural network (ANN) models to predict business failures for Korean lodging firms. While both models demonstrated comparable Type I errors, the ANN model showed considerably lower Type II errors for both in-sample and hold-out sample predictions. This study also found that interest coverage is the most important signal of business failure for the Korean hotel industry. This ratio is directly related to the hotel's solvency, ability to service debts and productivity of profits and can thus be regarded as a survival indicator of Korean hotel firms.     

Does a low-cost carrier lead the domestic tourism demand and growth of New Zealand?

This study aims to provide a better understanding of the impact of New Zealand's low-cost carrier (LCC) on domestic tourism demand and growth. The panel data regression model and the two-stage least-square (2SLS) model (aims to control for the endogeneity effects) are used to empirically investigate the impact of LCC and the key determinants affecting New Zealand's domestic tourism using five regions (Auckland, Canterbury/Christchurch, Dunedin, Queenstown, and Wellington) from June 2009 to July 2015. The findings suggested that the LCC's services, GDP per capita, the regional tourism indicators (accommodation, and food and beverage), and land transport costs affected New Zealand's domestic tourism. The policy implications of the key finding regarding the significance of the LCC's operations on New Zealand's domestic tourism (local/regional tourism authorities and tourism operators), airline competition between incumbent airline (Air New Zealand) and the LCC (Jetstar), and airport authorities are discussed.     

主题公园游客满意度曲线研究——以深圳欢乐谷为例

游客量直接决定主题公园的经营绩效,游客满意度是影响游客量的关键要素之一。本文首先通过对深圳华侨城三大主题公园的预调研,构建了主题公园游客满意度曲线模型;然后以深圳欢乐谷为例,通过回归分析,对主题公园的游客满意度曲线进行了拟合检验,发现主题公园的游客满意度曲线表现为倒U形。为了使主题公园经营者能够有效地利用倒U形模型,本文将游客满意度曲线划分为5个区间,针对每个区间给出了提高游客满意度水平的策略,为主题公园稳定游客量提供了理论依据。     

Willingness to pay: Who are the cheap talkers?

The purpose of this paper is to determine who is willing to pay (WTP) for a greener event by applying a Contingent Valuation (CV) approach together with an experimental design. To identify the cheap talkers a survey was conducted at the Wacky Wine Festival in South Africa, were 474 respondents participated. Using a Heckman two-step approach, the results confirmed that the decision to contribute depends on behavioural and motivational factors, while the amount is income-dependent. The extent of cheap talking is significant, with a 50% deviation in stated and revealed behaviour. Besides cheap talkers, another category is identified, namely “ethicals”, who contribute their voucher to the tree planting project without indicating that they are willing to pay.     

Social-demographics, driving experience and yearly driving distance in relation to a tour bus driver’s at-fault accident risk

This study explored the at-fault accident risk of tour bus drivers based on 2023 drivers in Taiwan. Of the observed drivers, 4.1% had at least one accident in a year period, of these, 68.7% were at-fault for the accident. The results of logistic regression model revealed that a driver’s driving experience was the most influential factor (Wald = 32.291, p = 0.000) leading to at-fault accident risk. Drivers whose driving experience was from 6 to 8 years possessed the lowest at-fault accident rate (0.9%), which was lower than the over-all average at-fault accident rate of 2.8%. Novice drivers whose driving experience less than 3 years had the highest at-fault accident rate (12.4%). The driver’s yearly driving distance and the use of an Automatic Vehicle Location (AVL) system were also significantly associated with a driver’s at-fault accident. However, a driver’s age and educational level were not significantly associated with at-fault accident.     

旅游管理本科生就业倾向与本行业关联性分析及对策

旅游管理本科生本行业就业率低一直是困扰旅游教育界和旅游实务界的一大难题,奉文在运用因子分析概括出影响旅游管理本科生本行业就业倾向因素的基础上,采用Logisac田归模型分析了旅游管理本科生就业倾向与奉行业就业的关联性.结果表明.教学与实习、培养模式、待遇与前景、企业声誉及对口性、受重视程度、专业能力是促进旅游管理本科生本行业就业倾向的因素;行业性质、家庭及工作地、非专业能力、性别盖畀、个人价值取向是押制旅游管理本井生本行业就业倾向的因素;而宏现就业政策对旅游管理本科生奉行业就业倾向没有显著影响.最后从社会、企业、高枝、家庭和学生5个角度提出了改善旅游管理本科生本行业就业倾向的策略.