Supporting multi-criteria decision-making across websites: the Logikós approach
Online customers frequently conduct activities that involve multi- criteria decision-making. They analyze and compare alternatives considering a set of shared characteristics. Websites present the information of products without special support for these activities. Moreover, the products of interes...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | Argentina |
| Institución: | Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
| Repositorio: | CIC Digital (CICBA) |
| Idioma: | inglés |
| OAI Identifier: | oai:digital.cic.gba.gob.ar:11746/11412 |
| Acceso en línea: | https://digital.cic.gba.gob.ar/handle/11746/11412 |
| Access Level: | acceso abierto |
| Palabra clave: | Ciencias de la Computación e Información Multi-criteria decision support Analytic Hierarchy Process E-commerce Web Augmentation |
| Sumario: | Online customers frequently conduct activities that involve multi- criteria decision-making. They analyze and compare alternatives considering a set of shared characteristics. Websites present the information of products without special support for these activities. Moreover, the products of interest for the customer are frequently scattered across various shops, with no support to collect and compare them in a consistent and customized manner. We argue that multi-criteria decision-making methods (such as Analytic Hierarchy Pro- cess) can be e ectively o ered to online customers. In this article, we present an approach and supporting tools to enable multi-criteria decision-making on any website and across websites. They are based on web-augmentation to extract information items from websites, and the Analytic Hierarchy Process (AHP) to model multi-criteria decisions. The approach and tools were experimentally evaluated with end-users in two di erent countries. An illustrative scenario provides insight into the application of the approach and the role of the sup- porting tools. Evaluation showed that users appreciate creating AHP models speci c to their needs, and trust the decisions they make using these models. Participants were reluctant to trust reusable decision pro les (i.e., AHP mod- els created by other users). The numerous pairwise comparisons required by AHP in the presence of multiple criteria and alternatives, was reported as a drawback. However, participants indicated that the proposed smart-ranking functionality represented a good mechanism to cope with it. |
|---|