Attributes of Destination Competitiveness: A Factor Analysis

Dwyer, Larry; Mellor, Robert B.; Livaic, Zelko; Edwards, Deborah; Chulwon, Kim

doi:10.3727/1083542041437558

Cited by 243 publications

(179 citation statements)

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“…3;2017 13 destination and tourism services, previous studies might be major source of information. In the study of Cucculelli & Goffi (2015), they found that, the majority of studies look at competitiveness for a single country or a group of countries (e.g., Ahmed & Khron, 1990;Bahar & Kozak, 2007;Dwyer et al, 2003Dwyer et al, , 2004Dwyer et al, , 2012Gomezelj & Mihalic, 2008;Gooroochum & Sugiyarto, 2005;Haahti, 1986;Haahti & Yavas, 1983;Kaynak & Marandu, 2007;Kim & Dwyer, 2003;Kozak & Rimmington, 1999;Lee & Chen, 2010;Mazanec, Wober & Zins, 2007;Miller, Henthorne, & George, 2008;Sirse & Mihalic, 1999;Zhang & Jensen, 2007). Other empirical studies concentrate on islands (Croes, 2010;Mechinda et al, 2010), big cities (Enright & Newton, 2004Minghetti & Montaguti, 2010), particular types of destinations (Botha, Crompton, & Kim, 1999;D'Hautserre, 2000;Lee & King, 2009), famous resort destinations (Kozak, 2002), and regions/provinces (Cracolici & Nijkamp, 2008;Faulkner, Opperman, & Fredline, 1999;Pestana et al, 2011;Zhang et al, 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Furthermore, Dwyer & Kim (2003) and Dwyer, Mellor, Livaic, Edwards, & Kim (2004) also undertook to contribute to the development of a general model of destination competitiveness. Through a series of development, Dwyer et al (2014) extracted 55 indicators from 135 initial indicators through factor solution analyses using Quartimax rotation.…”

Section: Literature Reviewmentioning

confidence: 99%

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Determining Drivers of Destination Attractiveness: The Case of Nature-Based Tourism of Bangladesh

Islam¹,

Hossain²,

Noor³

2017

IJMS

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The purpose of this study is to identify the most important drivers for developing destination competitiveness of Bangladesh nature-based tourism by evaluating tourists' perception. A nationwide structured questionnaire survey of total 432 Bangladeshi tourists is carried out by dividing the whole country into two parts for equal representation. Based on this data, a profile of the tourists is constructed before ranking of attributes from most important to least important on a five-point Likert scale. An Exploratory Factor Analysis (EFA) has been conducted finally to identify the most important factors from 24 selected attributes related to nature-based tourism of Bangladesh. The key findings indicate that seven attributes are more important to respondents than others as all these has average importance value more than 4 out of 5 while only two is least important. From the EFA of these attributes, supported by a parallel analysis, four major factors are extracted namely, tourism infrastructure; historical and cultural attractors; natural attractors; and communication facilities and lifestyle similarities. Thus, this study will help both policy makers to develop long term destination policy focusing on natural attractors and service providers to customize their services according to tourists' expectation. Consequently, this paper conceptualizes the importance of focusing on specific sectors of tourism and the way of developing competitiveness of nature-based tourism of Bangladesh. However further studies can be conducted to match tourists' evaluation of attributes on importance and performance and/or evaluating same perception from service providers rather than tourists.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Determining Drivers of Destination Attractiveness: The Case of Nature-Based Tourism of Bangladesh

Islam¹,

Hossain²,

Noor³

2017

IJMS

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“…The growing interest in tourism destination competitiveness reflects in the proliferation of the literature on this field (Vila, Darcy & Elisa, 2015). Many of these research projects set out with the objective of identifying the competitiveness of specific destinations, including the United States of America (Ahmed & Krohn 1990), Las Vegas (Chon & Mayer, 1995), European cities (Mazanec, 1995), Southeast Asia (Pearce, 1997), Sun/Lost City in South Africa (Botha, Crompton & Kim, 1999), Southern Australia (Faulkner, Opperman & Fredline, 1999), a United States casino resort (D'Hauteserre, 2000), cultural tourism in Toronto (Carmichael, 2002), Mediterranean resorts (Papatheodorou, 2002), Australia (Dwyer et al, 2004), South Korea and Australia , Spain and Turkey (Kozak 2003), a ski resort in Canada (Hudson, Ritchie & Timur, 2004), Asia-Pacific (Enright & Newton 2005), Slovenia , the Caribbean (ECLAC, 2009), Brazil (Ritchie & Crouch, 2010) and Portugal (Estevão & Ferreira, 2014, Estevão & Ferreira, 2015.…”

Section: Tourism Competitivenessmentioning

confidence: 99%

Tourism sector competitiveness in Portugal: applying Porter's Diamond

Estevão

Ferreira

Fernandes

2018

TMS

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The tourism sector has stood out for its enormous capacity for growth on a global scale and holding a relevant role both as a tool for the competitiveness and as a driver of regional development. This profile stems not only from its multiplier effects but also the opportunities susceptible to identification within the scope of offsetting regional disparities in growth and prosperity. The objective of this research consists of evaluating the competitiveness of the regional areas and directorates of tourism in Portugal. We have used primary data (a sample of 446 companies), through a questionnaire aimed at companies displaying the activities characteristic of the World Tourism Organisation satellite account. Through the application of Porter's Diamond Model, we attained at a conceptual model through recourse to the Partial Least Square -Path Modelling technique with the objective of analysing the relationships unfolding among the determinant variables to competitiveness in the tourism sector. Despite the results returned proving clear, we also verify that encapsulating competitiveness proves no easy task given how Portugal reports regions with simultaneously very varied and very specific characteristics.Keywords: Tourism, competitiveness, Porter's diamond, regional tourism area, Portugal. ResumoO sector do turismo destaca-se pela enorme capacidade de crescimento a nível mundial, desempenhando um papel relevante tanto como ferramenta para a competitividade como enquanto motor do desenvolvimento regional. Este perfil decorre não apenas dos seus efeitos multiplicadores, mas também das oportunidades suscetíveis de identificação no âmbito da compensação das disparidades regionais no crescimento e prosperidade. O objetivo desta investigação consiste em avaliar a competitividade das áreas regionais e direções do turismo em Portugal. Utilizamos dados primários (uma amostra de 446 empresas), através de um questionário destinado a empresas que exibem as atividades características da conta satélite da Organização Mundial de Turismo. Através da aplicação do Modelo de Diamante de Porter, alcançamos um modelo conceitual através do recurso à técnica de Partial Least Square -Path Modelling com o objetivo de analisar as relações que se desdobram entre as variáveis determinantes para a competitividade no setor de turismo. Apesar de os resultados retornados serem claros, verificamos também que o encapsulamento da competitividade não se revela uma tarefa fácil, dado o fato de Portugal englobar regiões com características simultaneamente muito variadas e muito específicas.Palavras-chave: Turismo, competitividade, diamante de Porter, área regional de turismo, Portugal.

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“…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].…”

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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Attributes of Destination Competitiveness: A Factor Analysis

Cited by 243 publications

References 16 publications

Determining Drivers of Destination Attractiveness: The Case of Nature-Based Tourism of Bangladesh

Determining Drivers of Destination Attractiveness: The Case of Nature-Based Tourism of Bangladesh

Tourism sector competitiveness in Portugal: applying Porter's Diamond

Measuring Tourists’ Preferences – Which Road to Choose?

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