Understanding China's long-haul outbound travel market: An overlapped segmentation approach

Li, Xiang; Meng, Fang; Uysal, Muzaffer; Mihalik, Brian J.

doi:10.1016/j.jbusres.2011.09.019

Cited by 91 publications

(67 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Referring to Li, Meng, Uysal & Mihalik (2013), Word-of-Mouth, based on involvement, is divided into (1) Product Involvement, showing a user tending to discuss about a purchase experience and the acquired pleasure, (2) Ego-Involvement, referring to user experiences in certain purchase in order to seek for attention, identity, or concerns from others, and (3) Other Involvement, revealing a user sharing the knowledge or experiences to help other consumers.…”

Section: Word-of-mouthmentioning

confidence: 99%

A Study on the Effects of Word-of-Mouth on Brand Trust in Tourism Industry

2017

EURASIA J MATH SCI T

View full text Add to dashboard Cite

From the statistical data of World Tourism Organization on the number and average growth of travelers and the travel income, Asia-Pacific Region presents the best potential in tourism markets. A lot of visitors would choose to receive information through Word-of-Mouth when planning a tour. The Word-of-Mouth experiences and shared information could induce a visitor's travel demands. It therefore becomes a primary issue for the marketing in tourism industry to understand the function of Word-of-Mouth on a visitor's trust and employment of a tourism business brand. Taking EasyTravel as the research subject, the questionnaire survey is preceded through e-mails. With convenience sampling, total 1000 copies of questionnaires are distributed to the web members of EasyTravel, and 382 valid copies are retrieved, with the retrieval rate 38%. The research results show the significantly positive correlations between 1.Word-of-Mouth and Brand Reliability in Brand Trust and 2.Word-of-Mouth and Brand Intention in Brand Trust; besides, 3.demographic variables reveal remarkable effects on the correlations between Word-of-Mouth and Brand Trust.

show abstract

Section: Word-of-mouthmentioning

confidence: 99%

A Study on the Effects of Word-of-Mouth on Brand Trust in Tourism Industry

2017

EURASIA J MATH SCI T

View full text Add to dashboard Cite

show abstract

“…While the push attributes generally refer to motives for travel, the pull attributes are related to the features, attractions, and other attributes of the destination itself [53]. The pull attributes have also been described as images [42,54] and hence, segmented in an effort to evaluate perceptions of place [e.g., 14,30,55].…”

Section: Image Segmentationmentioning

confidence: 99%

“…Existing studies on segmentation of destination images or pull attributes have relied on a variety of techniques including, cluster analysis [31,56], factor-cluster analysis [29,30,55], factor analysis and t-test/ANOVA [51], factor analysis and regression [57], canonical correlation analysis [14], and multi-dimensional scaling [48] amongst many others. The use of a factorcluster approach for segmentation in general has been heavily criticized [see 1,58].…”

Section: Image Segmentationmentioning

confidence: 99%

“…Two trained interviewers approached potential respondents outside convenient locations such as high street shopping centers, leisure centers, tourist attractions, and local universities, following a procedure adapted from the study of Hsu et al [68] on the Chinese market. A screening question, adapted from Li et al [14] and Pan and Li [40], on the potential respondent intention to travel to Western Europe was used to identify the correct target population of 18 to 44 years old. Intention to travel may not accurately reflect actual behaviour [69], but can be used as a reliable indicator to understand tourism outbound markets [14].…”

Section: Data Collection and Sample Characteristicsmentioning

confidence: 99%

“…Conceptually, one consumer's higher statistical probability to belong to one segment does not necessarily mean that s/he only belongs to this segment [13]. For example, a tourist may well desire more than one attribute or benefit from a destination and hence can belong to multiple groups [14]. Among the different fuzzy clustering methods present in the literature, fuzzy C-means (FCM) [15] is the most popular.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bagged fuzzy clustering for fuzzy data: An application to a tourism market

D’Urso

Disegna

Massari

et al. 2015

Knowledge-Based Systems

View full text Add to dashboard Cite

Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely used to understand consumer behaviour. In this study, we propose a strategy of analysis, by combining the Bagged Clustering (BC) method and the fuzzy C-means clustering method for fuzzy data (FCM-FD), i.e., the Bagged fuzzy C-means clustering method for fuzzy data (BFCM-FD). The method inherits the advantages of stability and reproducibility from BC and the flexibility from FCM-FD. The method is applied on a sample of 328 Chinese consumers revealing the existence of four segments (Admirers, Enthusiasts, Moderates, and Apathetics) of the perceived images of Western Europe as a tourist destination. The results highlight the heterogeneity in Chinese consumers' place preferences and implications for place marketing are offered.

show abstract

Chinese Citizens' Outbound Destination Choice: Objective and Subjective Factors

Wei

Meng

Zhang

2016

Int. J. Tourism Res.

Self Cite

View full text Add to dashboard Cite

This study examines the factors influencing Chinese citizens' outbound destination choice to Europe/the USA based on the objective (e.g. demographics and time/money constraints) and subjective measures (e.g. happiness). The study utilizes the nationwide dataset of China Economic Life Survey, which includes more than 100 000 households across 300 counties and 104 cities in China for the analysis. The results reveal that the demographic characteristics (age and education) and constraints (vacation time and money/income) significantly influence Chinese citizens' outbound destination choice. Compared with other outbound destinations, Europe/the USA are more attractive to young, better‐educated people with higher income and more leisure (vacation) time. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

Understanding China's long-haul outbound travel market: An overlapped segmentation approach

Cited by 91 publications

References 32 publications

A Study on the Effects of Word-of-Mouth on Brand Trust in Tourism Industry

A Study on the Effects of Word-of-Mouth on Brand Trust in Tourism Industry

Bagged fuzzy clustering for fuzzy data: An application to a tourism market

Chinese Citizens' Outbound Destination Choice: Objective and Subjective Factors

Contact Info

Product

Resources

About