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Predicting Customer Recommendation Towards Homestay at West Pahang Region

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Homestay is a potential economic activity in tourism sector. The Homestay concept is quite new in the tourism sector, which could contribute to the economic growth of the country. Surprisingly, this concept is gaining high demand from time to time. It opens business opportunities to the locals yet bring more tourists to know Malaysia deeper and closer. This “win–win” situation should wake the government up as agency to manage and give full blast in this sector properly and remain intact. The resilience of Homestay concept should be highlighted from many aspects such as the facilities, promotion, services and hospitality, etc. Therefore the objectives of this study are (1) predicting the best model of customers’ recommendations towards Homestay and (2) to know the significant factors contributing to customers’ recommendations. The questionnaires taken from the Tourism Malaysia website have been distributed to 500 Homestay’s customers in the West Pahang region. This study is analyzed by using descriptive and binary logistic regression with IBM SPSS 20.0 to predict the best model of the Homestay to be recommended with three predictor variables; services, facilities and promotion tool. The findings show that on the average, Homestay hosts provided poor services and moderate facilities, also internet becomes the most effective tools to promote the Homestays. Additionally, internet and facilities factors are significant in developing the best recommended model with positive relationship towards customers’ satisfaction. Therefore, hopefully this study could contribute the ideas to the related parties in an effort to improve Homestay operations in order to satisfy the tourists yet could create opportunities to attract more new tourists in the future.
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Keywords: Customers Satisfaction; Homestay; Tourism

Document Type: Research Article

Affiliations: 1: Faculty of Business Management 2: Faculty Computer and Mathematical Sciences 3: Faculty of Accountancy

Publication date: April 1, 2017

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