A Study about Improving Decision Quality Through Preference Relaxation
Abstract. In online shopping scenarios, it can be difficult for consumers to process the vast amounts of information available and to make satisfactory buying decisions. Interactive decision aids are a potential solution to this problem. However, decision aids that filter a very large set of alternatives based on initial preferences may eliminate potentially valuable alternatives early in the decision process and possibly negatively impact decision quality. To address this issue we introduce a new kind of decision aid that enables consumers to consider high quality alternatives they initially eliminated. We develop a model of such a decision aid and evaluate it on a set of 2650 car advertisements gathered from popular used car advertiser website.
Introduction: Consumers often face a task to select a best option from a large set of alternatives, such as choosing a car to buy, an apartment to rent, or an unforgettable trip to book. Ecommerce sites often provide search functionality, usually by asking a user to fill in a form asking about the requirements that a desired product has to satisfy (preferences). This process is used, for example, when searching for a used car (http://carzone.ie/), or a flight (http://orbitz.com/) on popular websites, and is referred to as preference-based search [1] or parametric search [2]. Although such choice-based approaches are prevalent, both users and retailers can find them unsatisfying [3] as users are often not able to correctly transform their preferences into requirements using online forms, and thus they are rarely provided with the information they need. Keep reading…
