Impact of the Environment on Holiday Destination Choices of Prospective UK Tourists: Implications for Tropical North Queensland

Huybers, Twan; Bennett, Jeffrey

doi:10.5367/000000000101297451

Cited by 87 publications

(61 citation statements)

References 2 publications

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“…Morley, 1994). A slightly different approach, in line with a long tradition in transportation studies, has been that of applying discrete choice modelling to destination choice, both for international tourist demand (Huybers, 2003a;Huybers and Bennett, 2000), and for modelling factors that determine inbound tourism flows for short trips (Huybers, 2003b).…”

Section: Introductionmentioning

confidence: 99%

Uncovering the Macrostructure of Tourists' Preferences: A Choice Experiment Analysis of Tourism Demand to Sardinia

Brau

Cao²

2006

SSRN Journal

106

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Section: Introductionmentioning

confidence: 99%

Uncovering the Macrostructure of Tourists' Preferences: A Choice Experiment Analysis of Tourism Demand to Sardinia

Brau

Cao²

2006

SSRN Journal

106

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“…In particular, it is examined how tourist preferences are differentially affected by high or low degrees of accessibility to the tourist attraction, by the existence of protected areas in the vicinity of the accommodation, by the quality of the natural resources, by the overcrowding of tourist destinations and by the availability of recreational services. Hence (in line with the perspective by Huybers and Bennett, 2000), it is implicitly assumed that the environment is only one component of tourists' preferences, and that a better evaluation of its role in determining tourists' destination choices is achieved by making explicit the existence of characteristics which may be in conflict with natural resource preservation. It is likely that the appeal of these characteristics varies across different destinations, but some "benefit transfer" should be possible when considering areas that are to a large degree similar.…”

Section: Demand-driven Sustainable Tourism? a Choice Modelling Analysismentioning

confidence: 99%

“…An appropriate empirical method, also used in this paper, for the analysis of tourism demand consistent with this perspective is the discrete choice modelling technique, as originally shown by Huybers and Bennett (2000). In the last 15 years, literature on tourism economics has shown growing interest in stated preference approaches applied to the analysis of tourism demand (e.g.…”

Section: Demand-driven Sustainable Tourism? a Choice Modelling Analysismentioning

confidence: 99%

Demand-Driven Sustainable Tourism? A Choice Modelling Analysis

Brau

2008

Tourism Economics

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This paper studies the preferences of tourists visiting Sardinia (Italy), using a choice modelling approach. The focus is on the evaluation of specific 'demand-enhancing effects' which, according to economic theory, provide a basis for implementing sustainable tourism policies. Multinomial logit estimates reveal that strong negative effects result from the congestion of tourist attractions and the transformation of coastal environments, though tourists clearly gain utility from the other components of a tourism destination. The extent of the effects related to environmental preservation seems to support planning tourism development policies that will not have strong irreversible effects on coastal areas.

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“…The stated choice modeling using the set of established discrete choice modeling tools has often been used to analyze tourists' preferences, for example, by Huybers and Bennett [8], Apostolakis and Jaffry [9], Brau and Cao [10], Brau et al [11] and Figini and Vici [12].…”

Section: Editorialmentioning

confidence: 99%

Measuring Tourists’ Preferences – Which Road to Choose?

Ferreira

Pereira²

2014

J Tourism Hospit

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EditorialThe continuous growth in the tourism industry leads that destinations today must compete more than ever to attract tourists. Understanding destination competitiveness and attractiveness as well as modeling and forecasting tourism demand are critical to decision makers and destination managers, since it is known that tourism affects their regional and national economy through direct and indirect tourism revenues. For example, Song and Witt [1] refer that estimates of future tourism demand constitute a very important element in all planning activities of tourism-related business and, consequently, have a key role as a determinant of their profitability. Furthermore, Dwyer and Kim [2] mention that destination competitiveness would appear to be linked to the ability of a destination to deliver goods and services that perform better than other destinations on those aspects of the tourism experience considered to be important by tourists, because tourists would be expected to choose the destination that generates the highest level of utility.To assess the performance of a destination at aggregate level (e.g. at country or region levels), researchers have developed several different approaches to measure destination competitiveness using a large set of indicators and a wide range of methodologies. Some have used survey data of tourists' perceptions to measure competiveness [2][3][4][5]. Others have used published data (about the economy, environment, infrastructure, etc) to assess and compare the competitiveness of tourist destinations across a range of countries [6]. However, as far as we know, none of these researches have included an indicator of consumers' preferences, which was considered by Dwyer et al. [7], one of the three main elements of tourism demand as determinant of tourism competitiveness.At less aggregate levels, destination attractiveness and market share have been studied using stated preferences methods. Discrete choice modeling in economic theory complies with lancaster's new approach to the individual utility maximization problem in consumer theory [13] and with the random utility theory [14,15]. Discrete choice-based approaches use the random utility function where the stochastic component includes all unidentified factors that affect choices. Under the random utility theory, individual preference can be elicited by asking respondents to rank a set of alternative options from most to least preferred (contingent ranking data) or to choose their most preferred option (first-choice data). The measurement scale for the dependent variable determines the model to be estimated.With first-choice data, the choice experiment determines the multinomial logit, which is the most commonly used discrete choice model [14]. The appeal of the multinomial logit arose from the fact that it is simple to estimate. However, the problem with the multinomial logit is that it makes very strong assumptions about consumer behavior. The assumption that has received the most attention is the independence of irrelevant...

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Impact of the Environment on Holiday Destination Choices of Prospective UK Tourists: Implications for Tropical North Queensland

Cited by 87 publications

References 2 publications

Uncovering the Macrostructure of Tourists' Preferences: A Choice Experiment Analysis of Tourism Demand to Sardinia

Uncovering the Macrostructure of Tourists' Preferences: A Choice Experiment Analysis of Tourism Demand to Sardinia

Demand-Driven Sustainable Tourism? A Choice Modelling Analysis

Measuring Tourists’ Preferences – Which Road to Choose?

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