Destination performance: Introducing the utility function in the mean-variance space

Economic characteristics of home countries can cause considerable variations in the tourism demand. For example, the average level of expenditure per tourist varies from one origin to another and these variations may alter overtime. Thus different tourist nationalities are associated with different level of expenditures and risks. Therefore strategies aimed at minimizing the variations may become an important issue for the policy makers. In this paper, we aim to use the productivity measurement theory in a mean-variance space to a French region (Nord Pas-de-Calais) by introducing the utility function in a mean-variance framework. With this method, we can calculate the optimal portfolio share for each origin and give some useful political advices to the policy decision makers to improve the performance of the tourist sector.

[1]  Sara Sbai,et al.  Moroccan tourist portfolio efficiency with the mean-variance approach , 2013, European Journal of Tourism Research.

[2]  C. Barros,et al.  Productivity in the tourism industry , 2004 .

[3]  Can Deniz Köksal,et al.  Efficiency evaluation of A-group travel agencies with data envelopment analysis (DEA): A case study in the Antalya region, Turkey ☆ , 2007 .

[4]  Gérard Cliquet,et al.  Plural form chain and efficiency: Insights from the French hotel chains and the DEA methodology , 2009 .

[5]  C. Barros,et al.  The Measurement of Efficiency in Portuguese Hotels Using Data Envelopment Analysis , 2006 .

[6]  R. Färe,et al.  Theory and Application of Directional Distance Functions , 2000 .

[7]  Juan Gabriel Brida,et al.  Tourism as a factor of long-run economic growth: An empirical analysis for Chile , 2009, European Journal of Tourism Research.

[8]  Margaret J. Daniels,et al.  Beyond Input-Output Analysis: Using Occupation-Based Modeling to Estimate Wages Generated by a Sport Tourism Event , 2004 .

[9]  Jonas Schmitt.  Portfolio Selection Efficient Diversification Of Investments , 2016 .

[10]  C. Barros,et al.  The Future Outlook for Portuguese Travel Agents , 2011 .

[11]  Richard C. Morey,et al.  Mutual fund performance appraisals: a multi-horizon perspective with endogenous benchmarking , 1999 .

[12]  Richard C. Morey,et al.  Evaluating a hotel GM's performance , 1995 .

[13]  Valentina Bosetti,et al.  Benchmarking in Tourism Destination, Keeping in Mind the Sustainable Paradigm , 2006 .

[14]  Laurent Botti,et al.  French Destination Efficiency , 2012 .

[15]  Laurent Botti,et al.  Performance of French destinations: Tourism attraction perspectives , 2011 .

[16]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[17]  Rajiv D. Banker,et al.  Efficiency Analysis for Exogenously Fixed Inputs and Outputs , 1986, Oper. Res..

[18]  A. George Assaf,et al.  Benchmarking the Asia Pacific tourism industry: A Bayesian combination of DEA and stochastic frontier , 2012 .

[19]  L. Botti,et al.  Tourism destination competitiveness: the french regions case , 2009, European Journal of Tourism Research.

[20]  Productivité du secteur touristique français : une comparaison interrégionale , 2007 .

[21]  Vincent Kennedy.  Risk management in the Irish tourism industry: the contribution of a portfolio investment approach , 1998 .

[22]  Nicolas Peypoch,et al.  On Measuring Tourism Productivity , 2007 .

[23]  We Chiang,et al.  A DEA evaluation of Taipei hotels. , 2004 .

[24]  N. Peypoch,et al.  Research Note: Technical Efficiency in the Tourism Industry , 2006 .

[25]  W. Briec,et al.  Single-Period Markowitz Portfolio Selection, Performance Gauging, and Duality: A Variation on the Luenberger Shortage Function , 2002 .

[26]  D. Luenberger.  Benefit functions and duality , 1992 .

[27]  Lawrence M. Seiford,et al.  Data envelopment analysis: The evolution of the state of the art (1978–1995) , 1996 .

[28]  R. C. Morey,et al.  Evaluating a hotel GM's performance A case study in benchmarking , 2003 .

[29]  Kristiaan Kerstens,et al.  Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach , 2007, Manag. Sci..

[30]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[31]  R. Färe,et al.  Profit, Directional Distance Functions, and Nerlovian Efficiency , 1998 .

[32]  Enis Uysal,et al.  Revisiting Mean-Variance Optimization , 2001 .

[33]  Shiuh-Nan Hwang,et al.  Using data envelopment analysis to measure hotel managerial efficiency change in Taiwan , 2003 .

[34]  C. Tang,et al.  How stable is the tourism-led growth hypothesis in Malaysia? Evidence from disaggregated tourism markets , 2013 .

[35]  Carlos Pestana Barros,et al.  A Stochastic Cost Frontier in the Portuguese Hotel Industry , 2004 .