The Impact of Attribute Preferences on Adoption Timing of Hotel Distribution Channels: Are OTAs Winning the Customer Race?
The evolution of distribution channels in the hospitality industry has followed diverse paths over time depending on the technology used. Distribution channels can be clustered into three generations, starting with the pre-WWW era; the middle generation comprising Internet-based direct booking channels and the latest generation including online intermediaries. This research focuses on the comparison of rates of adoption across different generations of distribution channels in the Swiss hotel sector taking into account substitution effects. Data for the study are a series of annual surveys (2002–2013) monitoring the evolution of market shares of 15 individual distribution channels. The objective of this research is the analysis of the evolution of market shares of different generations using multi-generation diffusion methods. Results suggest that decaying traditional and web-based direct channels have low or inexistent imitation effect. This research adds the explanation of mixed effects (innovation and imitation) across generations in the adoption processes.
KeywordsHotel Distribution OTA Switzerland Norton-Bass model Mixed effect analysis Negative exponential
- Bass, F. M., Jain, D., & Khishnan, T. (2000). Modeling the marketing-mix influence in new-product diffusion. In V. Mahajan, E. Muller, & Y. Wind (Eds.), New-product diffusion models. Boston, MA: Kluwer.Google Scholar
- Horan, P., & Frew, A. (2005). Electronic distribution effectiveness amongst small and medium-sized enterprises in the hotel sector. Retrieved from http://arrow.dit.ie/tfschmtcon/11
- Jang, S. S. (2005). The past, present, and future research of online information search. Journal of Travel & Tourism Marketing, 17(2–3), 41–47.Google Scholar
- Lilien, G. L., Rangaswamy, A., & Van Den Bulte, C. (2000). Diffusion models: Managerial applications and software. In V. Mahajan, E. Muller, & Y. Wind (Eds.), New-product diffusion models (pp. 295–336). Dordrecht: Kluwer.Google Scholar
- Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: The Free Press.Google Scholar
- SAS Institute Inc. (2011). SAS/STAT® 9.22 user’s guide. Cary, NC: SAS Institute Inc.Google Scholar
- Schegg, R., Scaglione, M., Liebrich, A., & Murphy, J. (2007). Internet use by hospitality SMEs in alpine destinations. In M. Sigala, J. Murphy, & L. Mich (Eds.), Proceedings of the ENTER conference 2007, Ljubljana, Slovenia: Information and communication technologies in tourism 2007 (pp. 469–480). New York, NY: Springer.Google Scholar
- Scott, N., Burgess, S., Monday, A., OBrien, P., Baggio, R., Sellitto, C., et al. (2010). Helping tourism SMEs plan and implement information and communication technology. Retrieved September 1, 2013, from http://espace.library.uq.edu.au/view/UQ:226964