Performance analysis of the Gulf hotel industry: A Malmquist index with bias correction

This study uses the Malmquist index with bias correction to analyze the performance of hotel chains from the UAE, Saudi Arabia and Oman. We show that Saudi Arabia hotel chains have the highest productivity growth, followed by the UAE and Omani hotel chains. A further decomposition of productivity indicates that a small number of hotel chains experienced an increase in revenues for lower occupancy rate, while most other hotel chains experienced an increase in occupancy rate for lower revenues. Related market discussions of the results are provided.     

Hotel efficiency: A bootstrapped metafrontier approach

This paper introduces the metafrontier concept to account for the environmental and technological differences between various hotels groups. The interesting feature of the model is that it ensures that heterogeneous hotels are compared based on one homogenous technology. We test the model using a panel data sample of 78 Taiwanese hotels. The results clearly indicate that the size, ownership, and classification of a particular hotel have a significant impact on its efficiency. More implications of the results are provided.     

Quality of service and segmentation in the MICE industry: An approximation based on fuzzy logic

This article aims to evaluate the service quality experienced at academic conferences held at the Universidad Técnica Particular de Loja in Ecuador. Our approach is based on fuzzy logic and ideal solutions to calculate a global attendee satisfaction index for specific market segments: Gender, nationality, and age. Current literature on the service quality experienced by conference attendees is still scarce. Our results show that the analyzed segments experience varying levels of satisfaction, and that the more influential attributes to each of them are also different. Our results can be applied to improve the competitiveness of Loja and that of Universidad Técnica Particular de Loja.     

Profiling the segments of senior tourists throughout motivation and travel characteristics

Interest in tourism market segmentation of seniors has been increasing in recent years as the tourism industry has begun to be aware of their importance for the sector. This is a very heterogeneous group, with greater purchasing power and lifestyle-oriented entertainment and enjoyment of leisure time by performing travel than previous generations. This study strives to contribute towards the hitherto scarce research on segmentation in senior tourism. Specifically, this work aims to determine the existence of various profiles of senior tourism by means of using socio-demographic variables, motivation and characteristics of travel of seniors. For this, two complementary analysis techniques, the nonlinear canonical correlation (OVERALS) and a two-stage cluster analysis, were used. Five market segments were identified according to the behavioural variables analysed that allow marketers to target this group in the most convenient manner and to exploit new market opportunities.     

Where to vacation? An agent-based approach to modelling tourist decision-making process

Agent-based models (ABMs) are becoming more relevant in social simulation due to the potential to model complex phenomena that emerge from individual interactions. In tourism research, complexity is a subject of growing interest and researchers start to analyse the tourism system as a complex phenomenon. However, there is little application of ABMs as a tool to explore and predict tourism patterns. The purpose of the paper is to develop an ABM that increases knowledge in tourism research by (i) considering the complexity of tourism phenomenon, (ii) providing tools to explore the complex relations between system components and (iii) giving insights on the functioning of the system and the tourist decision-making process. A theoretical ABM is developed to improve knowledge on tourist decision-making in the selection of a destination to vacation. Tourists’ behaviour, such as individual motivation, and social network influence in the vacation decision-making process are hereby discussed.     

An integrated approach for ex-ante evaluation of public policies for sustainable agriculture at landscape level

An integrated methodological framework for ex-ante evaluation and planning of public policies for sustainable agriculture at agro-landscape level is proposed. The components of the framework are to: (1) determine the private, i.e. farmers’, and public benefits associated to agro-landscapes, consisting of an agricultural land-use system, according to its performance for several market and non-market functions. Market forces determine the market benefits and preferences of society the non-market benefits; (2) explore and select potential sustainable agro-landscapes based on the private and public benefits associated with possible land-use alternatives; (3) define efficient public policy mechanisms for improving social net benefit of agro-landscapes.The framework is illustrated with a case study in a small dairy farming dominated agro-landscape in The Netherlands, with gross margin, landscape quality, nature value and environmental health as the analysed ecosystem functions. Alternative landscapes consisting of hedgerow configurations and grassland management practices were explored, yielding a set of alternatives representing the solution space in terms of change in private and public benefits. Policy mechanisms were defined to move from the current to a desired landscape based on changes in social net benefits. Moreover, the necessity of a modification in the current agri-environmental support was analysed for each landscape. The analysis considered all farmers in the agro-landscape jointly. The results for the case study showed potential prototypes of landscapes and their performance compared to the current landscape. Extension was the most efficient policy mechanism to promote the change to the socially optimum landscape alternative.     

A quantile regression approach for estimating panel data models using instrumental variables

We introduce a quantile regression approach to panel data models with endogenous variables and individual effects correlated with the independent variables. We find newly developed quantile regression methods can be easily adapted to estimate this class of models efficiently.