Image Segmentation and Implications for the Development of a Nature-Based Destination

Obenour, William; Groves, David; Lengfelder, Julie

doi:10.1300/j150v14n01_03

Cited by 10 publications

(10 citation statements)

References 38 publications

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“…While a person’s image of a particular destination can be influenced by many factors, one of the most important determinants of a destination’s image is the physical attributes of the destination itself (Obenour, Groves, and Lengfelder 2006; Turner and Reisinger 1999). Given the importance of destination image as a determinant of consumption behavior (Tasci and Gartner 2007), this study is concerned with understanding how tourists’ willingness to engage in pro-environmental behavior may vary in different types of destinations.…”

Section: Literature Reviewmentioning

confidence: 99%

Image Matters: Incentivizing Green Tourism Behavior

Line

Hanks

2017

Journal of Travel Research

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Understanding the factors that motivate tourists to engage in pro-environmental behavior is an increasingly important topic in the tourism industry. In order to incentivize such green behavior, lodging properties often offer incentives to tourists who are willing to participate in property-level sustainability programs. Unfortunately, incentivizing participation in such initiatives is a difficult task, as tourists’ willingness to engage in pro-environmental behavior often depends on a number of situation-specific factors. Accordingly, the purpose of this research is to advance the understanding of the motivating factors that underlie tourist reactions to sustainability programs. Based on the tenets of motivation crowding theory, this research demonstrates that such reactions depend not only on the nature of the incentive that is offered but also on the image of the destination in which the property is located.

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Section: Literature Reviewmentioning

confidence: 99%

Image Matters: Incentivizing Green Tourism Behavior

Line

Hanks

2017

Journal of Travel Research

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“…Estimations of a response rate seem to be lower when the researchers draw a sample from a larger general population, such as, for example, members of online communities (Govers et al, 2007a(Govers et al, , 2007bY.-H. Lin, Wu, & Chang, 2006) or subscribers to LISTSERV (RezendeParker, Morrison, & Ismail, 2003): response rate in these studies is under 4%. Response rate tends to be higher when invitations are sent to individuals to form focus groups (Byrne & Skinner, 2007) or when responses are solicited from experts (Obenour et al, 2006;Obenour et al, 2005;Tasci & Kozak, 2006); response rate in these studies is over 20%.…”

Section: Methodological Issues In DI Researchmentioning

confidence: 91%

Destination Image: A Meta-Analysis of 2000–2007 Research

Степченкова

Mills

2010

Journal of Hospitality Marketing & Management

226

139

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“…Moreover, as travel behavior, including the activities in the destination, is a consequence of destination image among other variables (Pesonen & Tuohino, 2015); the use of destination image in segmenting the tourism market is more encompassing. Squarely, destination image off ers advantage over other possible segmentation variables as it is the genesis of tourism demand (Obenour et al, 2006).…”

Section: Tourism Market Segmentationmentioning

confidence: 99%

“…Th e main limitation of the available studies on tourist segmentation basing on destination image is the use of one image component, usually the cognitive part (Dryglas & Salamaga, 2017;Leisen, 2001;Obenour et al, 2006;Prayag, 2010) with very few considering the aff ective destination image component (Martin & Rodriguez del Bosque, 2008). None of the existing studies seem to have used both image components in segmenting the tourism market, thus preventing a comprehensive knowledge on destination image.…”

Section: Tourist Destination Imagementioning

confidence: 99%

Segmenting Inbound Tourists Using Destination Image

Maliva

Jani

2021

Tourism (Zagreb, Online)

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The purpose of this study was to segment inbound tourists to Tanzania using destination image. A self-administered structured questionnaire was conveniently distributed to inbound tourist to Tanzania in two major international airports in Tanzania. The questionnaire captured destination image using a five point Likert type scale while the demographics, sources of travel information, and travel behavior were captured using dichotomy or multiple choice questions. A total of 625 dully filled questionnaires were used for data analysis. A factor-cluster analysis was used in analyzing the data, with factor analysis serving in reducing the items into few dimensions that were subsequently subjected to stepwise cluster analysis. A hierarchical cluster analysis was used to explore the possible numbers of clusters followed by hierarchical cluster analysis (k-means) that confirmed the appropriate number of clusters. A three cluster solution was obtained with follow up one way ANOVA, t-tests, and Chi-square indicating statistical significance differences between the clusters basing on travel motives and travel behavior. The findings offer practical implications to destination managers on the use of destination image in marketing destinations to different tourist segments. This study explored the possible tourist segments basing on destination image of less researched African context.

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Image Segmentation and Implications for the Development of a Nature-Based Destination

Cited by 10 publications

References 38 publications

Image Matters: Incentivizing Green Tourism Behavior

Image Matters: Incentivizing Green Tourism Behavior

Destination Image: A Meta-Analysis of 2000–2007 Research

Segmenting Inbound Tourists Using Destination Image

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