The Tourism Efficient Frontier

Abstract

The objective of this research was to identify efficient travel segment mixes that allow destination tourism policy-makers and marketers to efficiently plan, develop, and market their destinations, so that they can have greater and more stable tourism receipts. Factor-cluster analysis and quadratic programming were conducted to find the French outbound travel activity segments and the efficient travel segment mixes. A hierarchical cluster analysis, using activity factor scores as the basis for the clustering, produced five distinct segments with similar activity participation patterns. With the variance-covariance matrix of the tourism receipts across the five segments, quadratic programming identified the efficient segment mixes. In addition, based on financial portfolio theory, a Tourism Efficient Frontier was drawn from the set of efficient travel segment mixes. One of the most unique contributions of this research is that it suggested travel segment mixes associated with different tourism receipt-variance trade-offs and quantified the changes that were required to attain them.

Tourist characteristics that influence shopping participation and expenditures

“…These findings coincide with several studies identifing the existence of a relationship between motivations in choosing a destination and the activities that tourists do during their stay (Crompton, 1979;Crandall, 1980;Dann, 1981;Gitelson and Kerstetter, 1990;McIntosh et al, 1994;Moscardo et al, 1995;Wong and Lau, 2001;Johns and Gyimò thy, 2002;Lee et al, 2002;Chhetri et al, 2003;Lau and McKercher, 2004;Prebensen, 2004Prebensen, , 2006. Through their effect on tourist activities during trips, it is expected that tourist motivations in choosing a destination affect the type and amount of tourist expenditures (Spotts and Mahoney, 1993;Jang et al, 2004). Lau and Au (2000) model the relations that exist among a set of mixed numerical and non-numerical tourist shopping data.…”

Analysing the Influence of Tourist Motivations on Tourist Expenditure at a Sun-And-Sand Destination

“…Other tourism research not based on expenditure segmentation shows the same main trip-related variables to be determinants of tourist expenditure: the size of the travel group (Mak et al, 1977;Seiler et al, 2002;Downward and Lumsdon, 2003), length of stay (Taylor et al, 1993;Seiler et al, 2002;Downward and Lumsdon, 2003;Jang et al, 2004a), repeat visitation (Jang et al, 2004a;Alegre and Juaneda, 2006;Alegre and Cladera, 2009), type of holiday package Pou, 2006, 2008), travel mode (Downward and Lumsdon, 2003;Fredman, 2008) and holiday activities (Bryant and Morrisson, 1980;Taylor et al, 1993;Nogawa et al, 1996;Leones et al, 1998;Jang et al, 2004c). To summarize, key factors that have been identified as affecting visitor expenditure include age, marital/family status, income, visitor origin, size of party, type of board, holiday activities and length of stay.…”

“…This relationship has been identified in several studies (Crompton, 1979;Crandall, 1980;Dann, 1981;Gitelson and Kerstetter, 1990;McIntosh et al, 1994;Moscardo et al, 1995;Wong and Lau, 2001;Johns and Gyimòthy, 2002;Lee et al, 2002;Chhetri et al, 2003;Lau and McKercher, 2004;Prebensen, 2004Prebensen, , 2006Prebensen and Kleiven, 2006) and can help to explain the link between motivations in choosing a destination and expenditure patterns. Tourists' motivations are expected to affect tourists' activities at a destination and, by extension, the amount of expenditure (Spotts and Mahoney, 1993;Jang et al, 2004c).…”

Destination Marketing: Optimizing Resource Allocation Using Modern Portfolio Theory

“…Tourism is not without commercial risk, and a significant amount of risk comes in the form of volatility (Sinclair 1998; Board, Sinclair, and Sutcliffe 1987; Jang, Morrison, and O’Leary 2004; Jang and Chen 2008; Chen, Jang, and Peng 2011). Fluctuations in tourism figures are found over the long run, especially in inbound tourism flows.…”