The South African National Department of Tourism has recently initiated the National Tourism Sector Strategy aimed at developing a sustainable tourism economy, and making the country a Top 20 global tourism destination by 2020.China is one of South Africa’s major non-African sources of tourist arrivals. To ensure a growing share of this booming market, South African tourism scholars and practitioners have to pay close attention to the behaviour of Chinese outbound tourists, particularly their destination choice behaviour. The Theory of Planned Behaviour (TPB)– an extension of the Theory of Reasoned Action (TRA)– can serve as a basis for researching destination choice. According to the TPB literature, intention is the most immediate and important determinant of behaviour. Three direct predictors of intention, namely, attitude, subjective norms, and perceived control, are functions of latent behavioural, normative, and control beliefs, respectively. The TPB is parsimonious but open to the inclusion of additional predictors if there is evidence that these predictors may explain a significant proportion of the variance in intention and behaviour after the basic predictors (attitude, subjective norms, and perceived control) have been accounted for. The current research successfully extended the TPB model for predicting potential Chinese tourists’ intentions to visit South Africa by adding two additional variables: travel motivation and travel constraints. The push-pull motivation framework discussed in the study postulates that people travel because they are pushed by internal forces (inner needs) and pulled by external forces (destination attributes). Typical barriers to travel include intrapersonal, interpersonal, and structural constraints. The new model makes an important contribution to the literature on destination choice, and provides South Africa’s destination marketers with suggestions for attracting and serving Chinese tourists. In addition, the research shows that both travel motivation and travel constraints can be used as bases for segmenting the outbound Chinese tourist market interested in visiting South Africa. A survey approach and a structured questionnaire distributed electronically to the online panel members of a Chinese market research company were instrumental in collecting the empirical data for the study. The questionnaire was originally written in English and translated into Chinese (Mandarin) via a blind translation-back-translation method. Attitude, subjective norms, perceived control, and visit intention were all operationalised as unidimensional and used scales adapted from previous studies. New scales were developed for travel motivation and travel constraints– both operationalised as multidimensional. Quota sampling, used to identify respondents aged 18 or older and living in Beijing, Shanghai, and Guangzhou, resulted in 630 usable questionnaires obtained from 1,510 sent invitation e-mails, yielding a response rate of 41.7%. The raw data collected were prepared through the sequential steps of editing, coding, and filing, and then analysed using both descriptive and inferential statistics. Descriptive analysis suggested that broadening personal horizons, viewing the natural scenery, and seeing something different were the top motives for visiting South Africa, while language, fear of crime, and lack of travel companions were the top barriers to visiting South Africa. According to the factor analysis, travel motivation had three underlying dimensions – learning, escape, and aesthetics and appreciation, while operational, risk and fear, and social barriers were three underlying dimensions of travel constraints. Regression analysis showed that the proposed extended TPB model had higher predictive power for visit intention than both TRA and TPB models; the basic predictors – attitude, subjective norms, and perceived control – all had a significant impact on visit intention; and in terms of the additional predictors, learning, operational constraints, and social constraints had a significant impact on visit intention. The analysis of variance indicated that travel frequency and age were the most profound background factors with an influence on the extended TPB model. Finally, cluster analysis resulted in two market segments with distinct profiles, that is, High-Motivation/ Low-Constraint (HMLC) tourists and Low-Motivation/High-Constraint (LMHC) tourists. Based on the theoretical and empirical findings of the current research, it is recommended that destination marketers in South Africa: advertise specific benefits of touring South Africa, namely, increasing knowledge, relieving stress, and enjoying high environmental quality, to advance Chinese residents’ perceptions of the country; develop tourism experiences that can be taken in a week or shorter to cater for the unique annual leave and public holiday policy in China; launch a media relations campaign in China to ensure that the facts about South Africa are communicated without distortion; collaborate with other destination stakeholders such as government and businesses, to actively attract and retain Chinese tourists for example by educating the public about Chinese culture and training employees to improve the quality of service; target the HMLC tourists via the Internet (particularly the social media) and by developing holiday packages that include activities related to cultural tourism, rest and relaxation, and nature-based tourism; and target the LMHC tourists by cooperating with local travel agencies and by developing holiday packages that highlight the diversity of tourism activities and offer value-added products/services.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:nmmu/vital:9325 |
| Date | January 2014 |
| Creators | Han, Xiliang |
| Publisher | Nelson Mandela Metropolitan University, Faculty of Business and Economic Sciences |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis, Doctoral, DPhil |
| Format | xvii, 310 leaves, pdf |
| Rights | Nelson Mandela Metropolitan University |
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