A Choice Modeling Application for Greek Heritage Attractions

Apostolakis, Alexandros; Jaffry, Shabbar

doi:10.1177/0047287504272035

Cited by 105 publications

(56 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Due to its explanatory value, Lancaster's characteristic theory has been used widely in a tourism context to identify the determinant attributes of destination choice, being adopted and refined over many years (e.g. Apostolakis & Jaffry, 2005;Morley, 1994;Papatheodorou, 2001;Rugg, 1973;Seddighi & Theocharous, 2002). More recently, Tussyadiah et al (2006) extended Lancaster's theory to explain how tourists choose their destination from multiple options.…”

Section: The Characteristic Theory and Preference Estimationmentioning

confidence: 99%

Digging deeper into decision-making of Chinese long-haul outbound tourists: A two-stage preference - estimation approach

McCabe

2017

Journal of Destination Marketing & Management

View full text Add to dashboard Cite

A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. ABSTRACT:Investigating and understanding tourists' preferences is of great importance for both decision-making theories and destination marketing practice. In the current study we investigate the process of consideration-set formation together with conjoint analysis to estimate destination preferences of Chinese long-haul outbound tourists. Through the integration of choice-set and characteristic theories, this study explores how to obtain more comprehensive insights into destination choice processes. The findings show that preferences can be analysed effectively in a two-stage model, which can reveal detailed additional insights regarding tourists' preferences towards destination attributes, thus contributing to marketing insight on destination choice and selection.

show abstract

Section: The Characteristic Theory and Preference Estimationmentioning

confidence: 99%

Digging deeper into decision-making of Chinese long-haul outbound tourists: A two-stage preference - estimation approach

McCabe

2017

Journal of Destination Marketing & Management

View full text Add to dashboard Cite

show abstract

“…Following Morey and Rossmann's (2003) recommendations, researchers should always account for the possibility that a proposed policy initiative could be good for some and bad for others. In this respect, the incorporation of taste heterogeneity via flexible preference specification models is a key aspect of this empirical study (Walker and Ben-Akiva 2002;Apostolakis and Jaffry 2005). In addition, the analysis also proposes to examine the potential sources of heterogeneity among individuals through the interaction of individual preferences for future policy scenarios with respondents' attitudinal and sociodemographic characteristics.…”

Section: Introductionmentioning

confidence: 99%

Evaluating individual preferences for the British Museum

Jaffry

Apostolakis

2010

J Cult Econ

Self Cite

View full text Add to dashboard Cite

show abstract

“…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

View full text Add to dashboard Cite

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...

show abstract

A Choice Modeling Application for Greek Heritage Attractions

Cited by 105 publications

References 41 publications

Digging deeper into decision-making of Chinese long-haul outbound tourists: A two-stage preference - estimation approach

Digging deeper into decision-making of Chinese long-haul outbound tourists: A two-stage preference - estimation approach

Evaluating individual preferences for the British Museum

Measuring Tourists’ Preferences – Which Road to Choose?

Contact Info

Product

Resources

About