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

Abstract

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.

Strategic decision concerning tourist origins portfolio: A decision process based on the ELECTRE method and applied to French Polynesia

“…Following the literature (Botti, et al, 2012;Zhang et al, 2015;Rakotondramaro and Botti, 2018), we use the number of overnight stays from different tourist origins as risky assets constituting the portfolio of the destination. Zhang et al (2016) and Rakotondramaro and Botti (2018). Figure 2 exposes the four real portfolios and their respective efficient frontiers.…”

Evaluating Tourist Destination Performance: Expanding the Sustainability Concept

“…Kozak (2002) measured destination performance by comparing Spain and Turkey, and was one of the first to use the term "destination performance" [36]. Today, research on TDP has increased substantially, and is especially rich in the following areas: tourism enterprises [31][32][33][34][37][38][39][40], hotels industry [29][30][31][32][33][34], partnerships [41], research performance in tourism and hospitality [42], marketing [43,44], environmental performance in the lodging sector [45][46][47], public transport destination satisfaction [48,49], assessing destination performance [50][51][52][53][54], sustainable performance indicators of tourism development policies [55], website information, and destination brand quality [56]. These studies illustrate the diversity of performance research.…”

“…However, investigations of TDP and its evaluation indices more broadly, have not been done in depth. More attention has been paid to economic indicators in service production, while the use of quantitative tools, such as data envelopment analysis (DEA) [51], a Bayesian approach [50], and mean-variance space [53], which provide only economic efficiency evaluations of destination performance, while ignoring the crucial elements of social development and environmental improvement.…”

“…Effectiveness seems to be the best expression of performance in organizational and strategic management [57]. While prescriptions for improving and managing TDP are widely available, the academic community has been preoccupied with discussions and debates about issues of definition [49][50][51][52][53]. Most studies use production efficiency as a proxy meaning for performance by equating the destination with a firm for the purpose of measuring competitiveness [51,58].…”

Differences in perception of the importance of generic competencies among destination regions

“…In the literature about tourism, the regional aspect is very important and is usually referred to in connection with efficiency assessment (L. Zhang, Botti, & Petit, 2016), regional development (Arnaud, 2016;Korent, Vuković, & Brčić, 2015;Z. Yang & Cai, 2016), price competitiveness (Tkalec & Vizek, 2016), destination image (Ryu, L'Espoir Decosta, & Andéhn, 2016), climate and seasonality (Razumova, Rey-Maquieira, & Lozano, 2016;Scott, Simpson, & Sim, 2012), destination resources (Hadjikakou, Miller, Chenoweth, Druckman, & Zoumides, 2015;Naidoo & Sharpley, 2016;Ram, Björk, & Weidenfeld, 2016), tourism demand (Brida, Disegna, & Osti, 2013;Merida & Golpe, 2016;Naef & Ploner, 2016;Y.…”