Estimating the Importance of Consumer Purchasing Criteria in Digital Ecosystems

Abstract

The purchasing process is not an isolated or unique fact, but a process that contains distinct phases. One of these phases is the evaluation of alternatives, in which the consumer compares the benefits that will be obtained from each brand, product or service, depending on a set of characteristics or criteria. Knowing these criteria and their importance is essential to companies for the supply and development of their products. Commonly this process is developed through multiple criteria decision-making methods, where experts, using surveys and their own experience, ascertain the consumers' purchasing criteria, as well as the importance of them. But this process to determine the importance of the criteria is not simple, as the thought, attitude and learning that direct purchases contain relations that consumers are not able to express explicitly; and secondly because the current information society in which we live causes consumers to receive large volumes of information at all times, causing perception changes regularly. This causes growing discrepancies between the rankings offered by experts and the actual purchase ranking of products and services. In this paper we propose a model to estimate the importance of the criteria and alternatives driving purchases making use of the information expressed by consumers in digital ecosystems. This model takes a set of comparable alternatives defined by the client and valuation criteria defined by experts, and by making use of the assessments that consumers make in digital ecosystems, determines the synergies implicit between the criteria and calculates their weight. Lastly, making use of the Choquet integral, the model aggregates the information and determines International Symposium on the Analytic Hierarchy Process

Application of Choquet Integral-Fuzzy Measures for Aggregating Customers’ Satisfaction

“…In another customers' satisfaction research, Peláez, et al [20] proposed a new purchase decision prediction model in investigating the rank of consumer purchasing factors in digital ecosystem. Evaluations of alternatives and criteria were made by considering the opinions expressed by consumers in digital ecosystems.…”