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Link to original content: https://doi.org/10.1007/s10660-019-09393-0
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Segmenting market structure from multi-channel clickstream data: a novel generative model

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Abstract

Competitive analysis has long been recognized as the cornerstones of firm’s strategic management and business activities. With the advent of the multi-channel clickstream, this paper studies the competitive market structure by developing a novel generative model. We first aggregate the multi-channel clickstream data to construct a consideration set for each user. Then, a novel sparse influence topic model (SITM) is proposed to segment an overall market into submarkets by leveraging the consideration sets at the individual level. Compared with the current generative models, the proposed SITM model considers the limited interest and the influence of products to generate users’ choice behaviors. Based on the multi-channel clickstream data from 109,081 users on 3779 cars, we empirically analyze the competition structure in China’s automotive market. Experimental results show that the proposed model can obtain deep insights of the competitive market structure and the competition power of each car in the market. It can also help managers understand user’s personalized interesting in the competitive market.

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Notes

  1. https://github.com/soberqian/SITM.

  2. http://www.zamplus.com/.

  3. https://github.com/soberqian/SparseTM.

  4. https://github.com/soberqian/InfluenceTM.

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Acknowledgements

This work is supported by the Major Program of the National Natural Science Foundation of China (91846201, 71490725), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (71521001), the National Natural Science Foundation of China (71722010, 91746302, 71872060), The National Key Research and Development Program of China (2017YFB0803303). This work is also sponsered by Zhejiang Lab (NO. 2019KE0AB04).

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, Anhui, People’s Republic of China

    Yang Qian, Yuanchun Jiang, Yanan Du, Jianshan Sun & Yezheng Liu

  2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, 230009, Anhui, People’s Republic of China

    Yang Qian, Yuanchun Jiang, Jianshan Sun & Yezheng Liu

  3. School of Health Management, Anhui Medical University, Hefei, 230032, Anhui, People’s Republic of China

    Yanan Du

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  1. Yang Qian
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Correspondence to Yuanchun Jiang.

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Qian, Y., Jiang, Y., Du, Y. et al. Segmenting market structure from multi-channel clickstream data: a novel generative model. Electron Commer Res 20, 509–533 (2020). https://doi.org/10.1007/s10660-019-09393-0

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