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Simulating and Modeling Dual Market Segmentation Using PSA Framework

Citation

Liu, J and Wei, Z and Bai, Q, Simulating and Modeling Dual Market Segmentation Using PSA Framework, Multi-agent and Complex Systems: Studies in Computational Intelligence, Springer, Q Bai, F Ren, K Fujita, M Zhang and T Ito (ed), Berlin, pp. 3-18. ISBN 978-981-10-2563-1 (2017) [Research Book Chapter]

Copyright Statement

Copyright 2017 Springer Science+Business Media Singapore

DOI: doi:10.1007/978-981-10-2564-8_1

Abstract

Market segmentation refers to the analytical process of dividing a broad market into segments taking into account multiple factors such as consumer needs, interests and tastes; it has been considered one of the most important marketing strategies as it helps a business to identify hidden market trends, define target segments, and design marketing plans. Market segmentation may also be viewed as a computational challenge: Given the massive amount of data describing interactions between consumers and commodities, the task is to partition the set of consumers and commodities into subsets that corresponds to market segments - two consumers are in the same segments when they exhibit a similar purchasing pattern, while two products are in the same segments when they are purchased by a similar group of consumers. In this work, we focus on the definition and simulation of market segments. We employ the Propose-Select-Adjust (PSA) framework, introduced in an earlier work [10], to simulate the forming of market segments. Our approach is distributed and can be applied to large and dynamic market data set. The experimental results suggest that the proposed approach is a promising technique for supporting intelligent market segmentation.

Item Details

Item Type:Research Book Chapter
Keywords:market segmentation, PSA framework, simulation, agent-based modelling, data mining
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140735
Year Published:2017 (online first 2016)
Web of Science® Times Cited:2
Deposited By:Information and Communication Technology
Deposited On:2020-09-02
Last Modified:2020-10-16
Downloads:0

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