Modeling the Factors Affecting the Visitor Satisfaction at Ecolodges: Implications for Ecotourism Development in Sri Lanka

Abstract

Tourism is one of the largest and fastest growing industries in the world. After 30 years of long debacle, Sri Lanka’s tourism sector is now showing signs of robust growth. At present, the tourism sector has emerged as the fourth largest foreign exchange earning of the country’s economy. As negative environmental and socio-cultural impacts of mass tourism become more apparent, the appeal of alternative form of tourism, especially ecotourism has increased globally. As an industry response to this dynamic and heterogeneous demand for environmentally responsible tourism products, novel concepts in the hotel and accommodation sector have emerged. Among these, the accommodation concept known as “ecolodge” has gained a broader recognition, particularly in the nature-based tourism sector. As such, development of eco-lodge industry has wider implications for developing tropical destinations such as Sri Lanka, especially when considered the country’s high potential for ecotourism, and the need to provide alternative forms of accommodation for rising tourist arrivals. With rising demand for alternative accommodation options, eco-lodge operators and managers are under pressure to meet diverse expectations of consumers. In tourism literature, visitor satisfaction has been studied by many scholars. However, visitor satisfaction of nature-based eco-lodge patrons and factors affecting their satisfaction has been seldom investigated. On the other hand, eco-lodge industry is relatively undeveloped in Sri Lanka, and very few or no studies have attempted to explore characteristics of visitors who seek accommodation in eco-lodges. Such knowledge is vital in planning and systematic development of the eco-lodge industry in Sri Lanka. This study attempts to develop distinct visitor profiles of eco-lodge patrons based on their demographic characteristic, trip characteristics and travel motivation while developing an empirical model to explain drivers of satisfaction at eco-lodges. This study utilized a random sampling method to collect visitor perception data in thirteen ecolodges around the island, between the period from January 2014 and January 2015. Upon completion of the questionnaire, the respondents were asked to put the completed questionnaire in a drop box at the front desk during check out, or return it to the front desk. Those who declined to participate in the survey were treated as non-respondents. Of the 385 questionnaires distributed, 362 were usable, which accounted for a response rate of 69% present. Visitors to studied eco-lodges are generally well educated, middle aged, on average stayed 1-3 days and fi iv travelled with their spouses or another adult to learn and explore environmental sensitive areas and experience the culture. These were often free and independent travellers who rely on personal experience, word of mouth and self-search based on the Internet for searching information in making travel decision. The study used Structural Equation Modeling to test the hypotheses and relationships among variables that possibly influences ecolodge patrons’ satisfaction. The result identified four factors for ecolodge attributes i.e. location, service, comfort and stimulation, and two motive factors i.e push and pull. Empirical results indicate that eco-lodge motives positively influence satisfaction and indirectly influence revisit intention. Eco-lodge attributes positively influence satisfaction and indirectly influence revisit intention, while eco-lodge attributes positively influence ecolodge motives and indirectly influence revisit intention. Visitors’ satisfaction had a positive influence on revisit intention, and satisfaction proved a significant mediating variable within satisfaction model. The proposed satisfaction model suggested that ecolodge attributes and ecolodge motives are more important to overall satisfaction. In addition most of patrons are willing to recommend ecolodge to the other persons. Broad implication of visitors’ profiling and behaviour modeling are also discussed.