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Human dynamics in repurchase behavior based on comments mining

Author

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  • Yang, Tian
  • Feng, Xin
  • Wu, Ye
  • Wang, Shengfeng
  • Xiao, Jinghua

Abstract

Hundreds of thousands of individual deals and comments are analyzed to ask: what kinds of patterns appear in their repurchase process? Our results suggest that, in the empirical description, the intervals between two consecutive purchases obey a power-law distribution. Notwithstanding a wide range of individual preferences, shoppers’ repurchase behaviors show some similar patterns, called long-scale quiet and short-scale emergence, and the alternating appearance of them form an endless chain in repurchase. In agreement with the empirical results, these short-scale and long-scale patterns suggest an adaptive model with alterable exponents complying with a power-law distribution. And it also implies that each user behaves his own intrinsic pattern such as unique repurchase intensity and silence-emergence cycle, which contributes to customer life-time value from the new view of dynamics and repurchase cycles.

Suggested Citation

  • Yang, Tian & Feng, Xin & Wu, Ye & Wang, Shengfeng & Xiao, Jinghua, 2018. "Human dynamics in repurchase behavior based on comments mining," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 563-569.
    • Handle: RePEc:eee:phsmap:v:502:y:2018:i:c:p:563-569
    DOI: 10.1016/j.physa.2018.02.137
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    References listed on IDEAS

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    1. Li, Nan-Nan & Zhang, Ning & Zhou, Tao, 2008. "Empirical analysis on temporal statistics of human correspondence patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(25), pages 6391-6394.
    2. Peng, Dan & Han, Xiao-Pu & Wei, Zong-Wen & Wang, Bing-Hong, 2015. "Punctuated equilibrium dynamics in human communications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 36-44.
    3. Mryglod, O. & Fuchs, B. & Szell, M. & Holovatch, Yu. & Thurner, S., 2015. "Interevent time distributions of human multi-level activity in a virtual world," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 681-690.
    4. Vazquez, Alexei, 2007. "Impact of memory on human dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 747-752.
    5. Hu, Hai-Bo & Han, Ding-Yi, 2008. "Empirical analysis of individual popularity and activity on an online music service system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5916-5921.
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    Cited by:

    1. Hwang, Syjung & Kim, Jina & Park, Eunil & Kwon, Sang Jib, 2020. "Who will be your next customer: A machine learning approach to customer return visits in airline services," Journal of Business Research, Elsevier, vol. 121(C), pages 121-126.

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