Many online retailers often use interactive decision aids, such as recommendation agents on their websites. Gathering information from shoppers’ search patterns and terms the recommendation agents can infer aspects of the shoppers’ preferences and suggest similar selections. In other words, this technique can “recommend” products to the shopper. This thesis investigates the impact of the different configurations of an apparel website’s online recommendation agent on customer’s buying decision related to the variables satisfaction before purchase with a recommendation agent, motivation to search for information and involvement with a recommendation agent.
In order to give a clear answer to the research question, I have made use of previous theories of the marketing literature related to online recommendation agents. In chapter two, a literature review is given related to the three variables satisfaction, motivation and involvement. Also, demographics (gender and income) in relation with usages and purchases regarding a recommendation agent are reviewed. Based on these theories, eight hypotheses are formulated.
In chapter three, a description of the method used is given. For this study, an online survey was executed in order to investigate the role of the different configurations of recommendation agent on consumers’ buying decisions. The online questionnaire consisted of a total of 15 questions and was divided into four parts: satisfaction, motivation, involvement and demographics. Furthermore, the sample consisted of 104 respondents that have shopped online for clothes at least once. The obtained data were then analyzed using the software SPSS.
In chapter four the results of this study are discussed and in chapter five the results are interpreted and the conclusion is given at the end of that chapter. The hypotheses are tested using different statistical tests. The results show that not all hypotheses can be confirmed. The results show that 5 of the hypotheses are significantly supported and 3 are not significantly supported. There is a positive relationship found between high consumers’ satisfaction with an online recommendation agent that recommends different product categories and willingness to buy recommended products. Also, consumers’ motivation to search out of a recommendation agent displaying fewer recommendations has a positive impact on willingness to buy recommended products of this agent. In addition, consumers’ motivation to search out of an online recommendation agent with the presence of brands has a positive impact on the willingness to buy the recommended products. Furthermore, high individual involvement with a recommendation agent has a positive impact on willingness to buy recommended products. However, there is no relationship found between gender and the usage/purchase frequency regarding a recommendation agent. Also, income did not determine the decision to buy products recommended by a recommendation agent either. Finally, shopping experience is positively related to buy recommended products.
The answer to the central research question is expanded upon in full in the conclusion. As a result, it can be concluded that these different configurations of an apparel website’s online recommendation mechanism influence consumers’ buying decisions in a positive way.