Aaltodoc publication archive (Aalto University institutional repository)
School of Business | Department of Marketing | Marketing | 2014
Thesis number: 13682
Consumer adoption of access-based consumption services - Case AirBnB
|Title:||Consumer adoption of access-based consumption services - Case AirBnB|
|Year:||2014 Language: eng|
|Department:||Department of Marketing|
|Index terms:||markkinointi; marketing; palvelut; service; arviointi; evaluation; kulutus; consumption; kuluttajakäyttäytyminen; consumer behaviour|
» hse_ethesis_13682.pdf size:2 MB (1804337)
|Key terms:||collaborative consumption; sharing economy; access-based consumption; AirBnB|
Increasing internet and smart phone penetration has given rise to a new business model, in which the service companies act as intermediaries and allow consumers to exchange value between them. Usually this is done by facilitating resource exchange between the consumers - one party that needs a resource such as a car, a designer bag or a place to stay rents or shares this resource with another party that has no need for the resource at the moment. This phenomenon has been dubbed collaborative consumption, the sharing economy or access-based consumption and is the focus of this research. The current growth of this sector is extremely high, and several companies operating in this field have received valuations in excess of 10 billion USD and are preparing for large-scale initial public offerings.
Because this phenomenon is quite a recent one, scant quantitative research currently exists that studies why consumers engage in using these services. This study attempts to fill this gap by studying the consumer adoption process of AirBnB. The main questions are; what factors influence consumer adoption of AirBnB and what is the relative importance of the different factors. By using established theories from marketing, psychology and information systems research, a multi-tiered structural equation model is created based on empirical data from a survey of 124 consumers to test different factors influencing adoption.
The results indicate that expected performance and hedonic motivations are the primary drivers of adoption of AirBnB. Social influence is another driver of adoption, albeit to a lesser extent than expected performance and hedonic motivations. In addition, the more materialistic the consumer, the less likely she/he is to adopt AirBnB. Moreover, expected performance is positively influenced by perceived price value and trust. Trust in turn is positively influenced by perceived effectiveness of the feedback mechanisms and the perceived quality of the web site.
Based on the results, it can be argued that adopters of AirBnB are willing to exchange regulation and the safety that comes with it - that are inherent in traditional services such as hotels - in exchange for increased price value, increased perceived fun, and a working trust architecture.
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