Domestic tourists' loyalty to a local natural tourist setting: Examining predictors from relational and transactional perspectives using a Zambian context. (October 2016)

• Record Type: Journal Article
• Authors: Kwenye, Jane M.; Freimund, Wayne
• Is Part Of: Tourism management perspectives. Volume 20(2016)
• Page Start: 161
• Page End: 173
• Publication Date: 2016-10
• Subjects: Destination loyalty -- Place attachment -- Service quality -- Perceived value -- Satisfaction -- Natural tourist settings; Tourism -- Periodicals; 338.4791
• DOI: 10.1016/j.tmp.2016.08.006
• Languages: English
• ISSNs: 2211-9736

Abstract

Abstract: Developing long-term relationships between domestic tourists and local natural tourist settings still remains a challenge for most developing countries, particularly, Zambia. To address this challenge, this study explored the concept of destination loyalty by investigating its antecedents from relational and transactional perspectives thereby extending the theoretical understanding of the concept. Data for this study were collected using on-site self-administered surveys from 1060 Zambian domestic tourists at the Victoria Falls World Heritage site and analyzed using Structural Equation Modeling. Empirical results showed that to foster destination loyalty, both transactional and relational antecedents of loyalty are fundamental with the relational variable being slightly more powerful as a predictor. Consequently, practitioners and policy-makers, especially in Zambia can promote domestic tourists' longterm relationships to local natural tourist settings by encouraging relational connections to the settings in addition to providing high service quality, as well as valuable and satisfactory experiences at the natural tourist settings. Highlights: Predictors of loyalty to a natural tourist setting examined using a Zambian context. Effects of transactional and relational antecedents of loyalty examined. Both transactional and relational antecedents had significant effect on loyalty. Relational antecedent was slightly more powerful as a predictor.