Buying decisions: The influence of recommendations in comparison to product attributes

Abstract

With an increasing amount of product alternatives to choose from, buying decisions become increasingly complex. To reduce complexity, consumers can rely on personal-individual, social recommendations by Internet communities or professional magazines. Due to the Internet, recommendations are increasingly available and instantly accessible. The relevance of these recommendations in comparison to product attributes for buying decisions has not been examined experimentally yet. In the current study, 163 participants (78 male, mean age 26, SD =9.03) selected in a choice-based conjoint analysis (CBCA) in 20 trials among three products each the one maximizing their expected utility. The CBCAs were conducted for two product categories – mobile phones and hotel reservations. Each product was represented by four recommendation sources (professional magazine, Internet community, close expert and close layperson) as well as four product attributes. Afterwards, utilities for each recommendation source and product attribute were calculated in a Hierarchical Bayes analysis. The utilities of the recommendation sources and the product attributes differ significantly (F(14, 2268) = 115, p=0.001). Recommendations have higher utilities than product attributes. The close expert is the most relevant source in both product categories. The results indicate, that recommendations by experts close to the decision maker are more important for buying decisions than other recommendation sources, for example professional magazines or Internet communities. The importance of recommendations for buying decisions is emphasized by the lower utilities of the product attributes.