A decision support system for market-driven product positioning and design

LEI, Ningrong and MOON, Seung Ki (2015). A decision support system for market-driven product positioning and design. Decision Support Systems, 69, 82-91.

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Official URL: https://www.sciencedirect.com/science/article/pii/...
Link to published version:: https://doi.org/10.1016/j.dss.2014.11.010


This paper presents a Decision Support System (DSS) for market-driven product positioning and design, based on market data and design parameters. The proposed DSS determines market segments for new products using Principal Component Analysis (PCA), K-means, and AdaBoost classification. The system combines the data integrity, security, and reliability of a database with the unparalleled analytical capability of the Matlab tool suite through an intuitive Graphical User Interface (GUI). This GUI allows users to explore and evaluate alternative scenarios during product development. To demonstrate the usefulness of the proposed system, we conducted a case study using US automotive market data. For this case study, the proposed DSS achieved classification accuracies in a range from 76.1% to 93.5% for different scenarios. These high accuracy levels make us confident that the DSS can benefit enterprise decision makers by providing an objective second opinion on the question: To which market segment does a new product design belong? Having information about the market segment implies that the competition is known and marketing can position the product accurately. Furthermore, the design parameters can be adjusted such that (a) the new product fits this market segment better or (b) the new product is relocated to a different market segment. Therefore, the proposed system enables enterprises to make better informed decisions for market-driven product positioning and design.

Item Type: Article
Uncontrolled Keywords: Decision Support System; Data mining; Market segmentation; Product positioning; Product design; AdaBoost
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
Identification Number: https://doi.org/10.1016/j.dss.2014.11.010
Page Range: 82-91
Depositing User: Ningrong Lei
Date Deposited: 26 Jan 2018 11:55
Last Modified: 18 Mar 2021 16:30
URI: https://shura.shu.ac.uk/id/eprint/18501

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