Adaptive Constraint and Rule-Based Product Bundling in Enterprise Networks

Abstract

Product bundling refers to the combination of several products for sale as one product. Current bundling approaches lack the ability to adapt, focusing mostly on the creation of pre-computed static bundles, which prove to be inefficient considering the dynamically changing prospective customer needs and product availability, as is particularly the case in enterprise networks. This paper describes a novel approach for dynamic generation of personalized, constrained and rule-based product bundles in such environments. The proposed agent-based approach involves estimation of substitution and complementarity associations between products and constructing bundles according to individual customer preferences. The process adapts automatically to changing circumstances, such as customer profile, product availability and constraint and rule diversity. The proposed approach is discussed in the context of e-Furniture, an agentbased system supporting networking of furniture and wood product manufacturing enterprises.Index Terms-Adaptive product bundling, constraint-based bundling, rule-based product bundling, enterprise networks.

EvoRecSys: Evolutionary framework for health and well-being recommender systems

“…In recommender systems, an output recommendation may contain multiple items, which we call a bundle. For instance, Rapti et al (2014) introduced an agent-based approach for generation of personalised product bundles for enterprise networks. The core process includes complementary associations between products and building bundles according to the customer preferences.…”

A Data-Driven Approach to Personalized Bundle Pricing and Recommendation

“…Cavusgil and Zou (1994) provides an overview of the growth and expansion of this early literature. Netessine et al (2006) is a key pivotal work that combined these fields by analyzing models with stochastic arrivals for the joint problem of cross-selling and pricing in which a consumer has one primary product of interest and is offered one additional complementary product at a discounted price for both; in Rapti et al (2014) the authors extend this dynamic programming setting by proposing a rule-based approach to the joint bundle selection and pricing problem. New directions such as Xue et al (2015) consider request for quote (RFQ) models where consumers interactively participate in the pricing process.…”