A configuration-based recommender system for supporting e-commerce decisions

Abstract

Multi-attribute value theory (MAVT)-based recommender systems have been proposed for dealing with issues of existing recommender systems, such as the cold-start problem and changing preferences. However, as we argue in this paper, existing MAVT-based methods for measuring attribute importance weights do not fit the shopping tasks for which recommender systems are typically used. These methods assume well-trained decision makers who are willing to invest time and cognitive effort, and who are familiar with the attributes describing the available alternatives and the ranges of these attribute levels. Yet, recommender systems are most often used by consumers who are usually not familiar with the available attributes and ranges and who wish to save time and effort. Against this background, we develop a new method, based on a product configuration process, which is tailored to the characteristics of these particular decision makers. We empirically compare our method to SWING, ranking-based conjoint analysis and TRADEOFF in a betweensubjects laboratory experiment with 153 participants. Results indicate that our proposed method performs better than TRADEOFF and CONJOINT and at least as well as SWING in terms of recommendation accuracy, better than SWING and TRADEOFF and at least as well as CONJOINT in terms of cognitive load, and that participants were faster with our method than with any other method. We conclude that our method is a promising option to help support consumers' decision processes in e-commerce shopping tasks.

Predictors of customer acceptance of and resistance to smart technologies in the retail sector

“…Ordanini, Parasuraman, and Rubera (2014) suggest that the same innovation attributes can either foster or inhibit new service adoption depending on how they are configured with other attributes. Moreover, the multi-criteria decision-making literature (Bous et al, 2010, Scholz et al, 2017 suggest that consumers consider all attributes (conditions) at once in a holistic manner to arrive at a decision commensurate with their preferences. Thus, consumers may rely on various attributes in their decision to adopt or resist new technology.…”

A nonlinear dynamic age-structured model of e-commerce in spain: Stability analysis of the equilibrium by delay and stochastic perturbations

“…Now, from the second equation of (1), we obtain Then, from (2) and 3, c 1 = 0.0178252 and d 2 = 0.0217424.…”

“…Here, we highlight contributions based upon Making-Decision Theory mainly oriented towards the design of recommender systems [1,2] and the measure of quality quality of services and business [3,4]. These contributions rely on operational research (decision making support systems, multi-criteria optimization, etc.)…”

Model for definition of preferred product configuration

“…Подходы к выбору предпочтительной конфигурации используют генетические алгоритмы [16][17][18], механизмы управления вариабельными конфигура-циями [19], теорию полезности [20,21], методы выбора на основе специфических для пользователя функций ценности и весовой значимости [22,23] и др.…”