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Authors: Richard Kerongo Mose, Christopher Ngacho, Pius Odunga

Abstract: This study sought to examine the role of sector vulnerability in the relationship between rainfall and wildlife tourism sector performance in Maasai Mara ecosystem, Kenya. This study is important because the Maasai Mara being a semi arid area is extremely vulnerable to the effects of climate change. The study adapted a pragmatic research approach that advocates for mixed methods research design. The study was based on a null hypothesis that sector vulnerability does not mediate the relationship between rainfall and wildlife tourism performance. Qualitative and quantitative data was collected using a questionnaire that was randomly administered to 466 respondents. Further qualitative data was collected by use interviews from 30 key informants purposively selected for the study. The results were analyzed using SPSS version 22 and AMOS version 21. The results showed that sector vulnerability mediated the relationship between rainfall and wildlife tourism performance β = – 0.439, t= -4.179, P<.001 this results were further collaborated by content analysis of qualitative data. The study concludes that wildlife tourism is extremely vulnerable to climate change indicator such as rainfall thus sector specific studies should be carried out so as to develop sector specific adaptations.

Keywords: Vulnerability, climate change, rainfall, wildlife tourism performance

DOI: 10.5937/turizam28-48274

Article info: 70-83

Received: December 2023 February 2024

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Authors: Aaron Tham, Hiram Ting, Risidaxshinni Kumarusamy

Abstract: The purpose of this paper is to evaluate the value of ChatGPT in terms of its responses and depth of progressing responsible tourism education. It is one of the first attempts to ascertain how ChatGPT responds to human-led queries, and whether it can formulate innovative ideas to advance responsible tourism theories into educational curriculum and assessments in the future. An ‘interview’ was conducted with ChatGPT to explore the chatbot’s responses to a series of questions related to responsible tourism education. The questions were informed by developments on the concept of responsible tourism, and to ascertain whether the chatbot can synthesise and generate radically innovative ideas to advance how the concept can be taught in the future. ChatGPT provided quick responses to ‘interview’ questions posed on its platform. It does engage with the conversation and can formulate preliminary insights to educate students on responsible tourism stakeholder engagement for women and minority groups, though it does not necessarily have the depth to explain how these stakeholders can be equipped to realise desired outcomes. In addition, the ideas emanating from ChatGPT appear rather obvious, with few radical or innovative outcomes to drive the educational landscape of responsible tourism forward.

Keywords: Tourism curriculum, sustainable tourism, community engagement, human-machine
interaction, chatbot

DOI: 10.5937/turizam28-47380

Article info: 84-97

Received: October 2023 Jun 24

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Authors: Milena Turčinović, Aleksandra Vujko, Miroslav Knežević

Abstract: The paper deals with the concept of sustainable tourism in mountainous, rural areas of Serbia and its economic indicators, i.e., the impact of economic indicators of sustainability on the local community, to point out the potential directions of tourism development. The research was conducted in selected rural areas of Zlatibor, Kopaonik, Stara Planina, and Fruška Gora. Respondents expressed their opinions on the issue of sustainable tourism development, how sustainable tourism has contributed to the local community and the local population, which elements of sustainability have been fulfilled, and in what way. It was concluded that residents of rural mountain destinations believe that truism directly and positively affects the sustainable development of rural destinations. Development indicators such as Income, Standard of living, employment possibility, Tourism, Investments, Women’s entrepreneurship, and women empowerment, have shown a significant increase from the tourism development. Thus confirming the initial hypothesis H that the economic indicators of sustainable tourism development provide a better quality of life for local communities.

Keywords: sustainable development, sustainable tourism, economic indicators of sustainable tourism, rural development

DOI: 10.5937/turizam28-49099

Article info: 98-111

Received: February 2024, Jun 2024

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Authors: Nwokorie Edwin Chigozie, Igbojekwe Polycarp Amaogananya, Ukabuilu Emmanuel Nnabugwu

Abstract: This study examined the effect of customer intelligence on customer repurchase behaviour in hotels in South-West Nigeria. The model for the research was developed on the consequent variables of the study to test the research hypotheses. A total of 1972 copies of usable questionnaires were retrieved from customers of 160 conveniently sampled midscale and luxury hotels, and used for analysis. Descriptive statistics were used to analyze the demographic elements, while multivariate analyses were conducted to reveal the statistical relationship between customer repurchase behaviour and the customer intelligence constructs. The Pearson’s correlation was employed to test the research hypotheses to determine significant associations and relationships between the consequent variables of the study. Results showed the effectiveness of the regression model in identifying relationships between the consequent variables, in which the four null hypotheses were rejected. The study concludes that a consideration of the factors that have a significant effect on the various dimensions of customer repurchase behaviour, and the emergence of customer attrition and retention, can help hotel organizations make better product marketing decisions. Recommendations include that hotels should ensure that their customer analysis is directly targeted, to ensure the continuous retrieval of actual information that will directly influence business decisions.

Keywords: Consumer behaviour, customer analytics, customer attrition, customer loyalty, guest expectation.

DOI: 10.5937/turizam28-49907

Article info: 112-138

Received: April 2024, Jun 2024