With the rise of the internet, consumers can consider an ever growing amount of alternatives of a certain product they intend to buy. Sequentially, recommendation systems have become a widely observed phenomenon in electronic commerce. Much is known about the effect of these product recommendation on the outcome of the purchase decision of the consumer, but research now also concludes that the process of the product search is transformed in the presence of recommendation systems. EUR Professor Benedict Dellaert and Gerard Haubl from the University of Alberta explain how we traditionally approach searching for a product and how RAs transform the way we search. We trade in the well documented normative model of consumer search (i.e. Hauser & Wernerfelt, 1990), where we continue to search for additional alternatives until we believe that the potential improvement of our product selection, which the newly examined alternative might represent, does not weigh up against the effort of search we need to put in, for a model where we search in choice mode. In choice mode, we let the recommendations guide us on which alternatives to consider and we continuously compare the alternatives we have assessed among each other. Furthermore, we consider a smaller set of alternatives than we would without the RAs and consider these in more depth. The higher the variability in the (perceived) attractiveness of the alternatives, the stronger this effect becomes, a finding that contrasts the prediction of normative search theory (see Weitzman, 1979). Luckily for us, the research indicates that the choices we make using the choice mode match our preferences a lot better than the normative model search, following the average match of 82% with the RA versus a mere 47% without the RA. On top of that, we save time as we do so. Though, there might be a fly in the ointment; more recent research from Adomavicius, Bockstedt, Curley & Zhang (2013) reports that the recommendation system can manipulate consumer preferences and can give rise to a bias. The consumer may choose for a particular alternative, because he believes that its high position on the recommendation system means that that particular alternative is a ‘correct’ answer to the uncertainty he faces. Whether that is true depends greatly on the quality of the recommendations. Also, the consumer might be biased when reporting its satisfaction with the product, as subconsciously he adapts his preferences to the product characteristics of the product bought using a recommendation system. In the end, it seems we can make truly better and more time-efficient product choices with the help of recommendation systems, on the conditions that we critically asses the quality of these systems and remain loyal to our original preferences.
Adomavicius, G., Bockstedt, J. C., Curley, S. P., & Zhang, J. (2013). Do recommender systems manipulate consumer preferences? A study of anchoring effects. Information Systems Research, Vol. 24, No. 4, pp. 956-975.
Dellaert, B. G.C., Häubl, G., (2012) Searching in Choice Mode: Consumer Decision Processes in Product Search with Recommendations. Journal of Marketing Research, Vol. 49, No. 2, pp. 277-288.
Hauser, J.R., & Wernerfelt, B ., An Evaluation Cost Model of Consideration Sets, Journal of Consumer Research, Vol. 16, No. 4 (Mar., 1990), pp. 393-408 Weitzman, M., Optimal Search for the Best Alternative, (1979), Econometrica, Vol. 47, No. 3, pp. 641–54.