IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v233y2015i1p263-27910.1007-s10479-013-1443-z.html
   My bibliography  Save this article

Online purchaser segmentation and promotion strategy selection: evidence from Chinese E-commerce market

Author

Listed:
  • Ying Liu
  • Hong Li
  • Geng Peng
  • Benfu Lv
  • Chong Zhang

Abstract

Online customer segmentation is a significant research topic of customer relationship management. Previous literatures mainly studied the differences between non-purchasers and purchasers, lacking further segmentation of online purchasers. There is still existing significant heterogeneity within purchaser-groups. This paper focuses on Chinese online purchaser segmentation based on large volume of real transaction data on Taobao.com, we firstly extracted and investigated Chinese online purchaser behavior indicators and classified them into six types by cluster analysis, these six categories are: economical purchasers, active-star purchasers, direct purchasers, high-loyalty purchasers, risk-averse purchasers and credibility-first purchasers; then we built an empirical model to estimate the sensitivity of each type of online purchasers to three mainstream promotion strategies (discount, advertising and word-of-mouth), and found that economical purchasers are the most sensitive to discount promotion; direct purchasers are the most sensitive to advertising promotion; active-star purchasers are the most sensitive to word-of-mouth promotion; finally, the implications of online purchaser classification for marketing strategies were discussed. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Ying Liu & Hong Li & Geng Peng & Benfu Lv & Chong Zhang, 2015. "Online purchaser segmentation and promotion strategy selection: evidence from Chinese E-commerce market," Annals of Operations Research, Springer, vol. 233(1), pages 263-279, October.
    • Handle: RePEc:spr:annopr:v:233:y:2015:i:1:p:263-279:10.1007/s10479-013-1443-z
    DOI: 10.1007/s10479-013-1443-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-013-1443-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-013-1443-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bhatnagar, Amit & Ghose, Sanjoy, 2004. "A latent class segmentation analysis of e-shoppers," Journal of Business Research, Elsevier, vol. 57(7), pages 758-767, July.
    2. C. Raju & Y. Narahari & K. Ravikumar, 2006. "Learning dynamic prices in electronic retail markets with customer segmentation," Annals of Operations Research, Springer, vol. 143(1), pages 59-75, March.
    3. Kukar-Kinney, Monika & Ridgway, Nancy M. & Monroe, Kent B., 2012. "The Role of Price in the Behavior and Purchase Decisions of Compulsive Buyers," Journal of Retailing, Elsevier, vol. 88(1), pages 63-71.
    4. Rohm, Andrew J. & Swaminathan, Vanitha, 2004. "A typology of online shoppers based on shopping motivations," Journal of Business Research, Elsevier, vol. 57(7), pages 748-757, July.
    5. Grewal, Dhruv & Iyer, Gopalkrishnan R. & Krishnan, R. & Sharma, Arun, 2003. "The Internet and the price-value-loyalty chain," Journal of Business Research, Elsevier, vol. 56(5), pages 391-398, May.
    6. Thomas P. Novak & Donna L. Hoffman & Yiu-Fai Yung, 2000. "Measuring the Customer Experience in Online Environments: A Structural Modeling Approach," Marketing Science, INFORMS, vol. 19(1), pages 22-42, May.
    7. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    8. Erin Anderson & Barton Weitz, 1989. "Determinants of Continuity in Conventional Industrial Channel Dyads," Marketing Science, INFORMS, vol. 8(4), pages 310-323.
    9. Jinfeng Li & Kanliang Wang & Lida Xu, 2009. "Chameleon based on clustering feature tree and its application in customer segmentation," Annals of Operations Research, Springer, vol. 168(1), pages 225-245, April.
    10. Ganesh, Jaishankar & Reynolds, Kristy E. & Luckett, Michael & Pomirleanu, Nadia, 2010. "Online Shopper Motivations, and e-Store Attributes: An Examination of Online Patronage Behavior and Shopper Typologies," Journal of Retailing, Elsevier, vol. 86(1), pages 106-115.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jie Wu & Zhixin Chen & Xiang Ji, 2020. "Sustainable trade promotion decisions under demand disruption in manufacturer-retailer supply chains," Annals of Operations Research, Springer, vol. 290(1), pages 115-143, July.
    2. Madjid Tavana & Debora Di Caprio & Francisco J. Santos-Arteaga, 2016. "Loyal customer bases as innovation disincentives for duopolistic firms using strategic signaling and Bayesian analysis," Annals of Operations Research, Springer, vol. 244(2), pages 647-676, September.
    3. Lei Li & Ting Chi & Tongtong Hao & Tao Yu, 2018. "Customer demand analysis of the electronic commerce supply chain using Big Data," Annals of Operations Research, Springer, vol. 268(1), pages 113-128, September.
    4. Farid Huseynov & Sevgi Özkan Yıldırım, 2019. "Online Consumer Typologies and Their Shopping Behaviors in B2C E-Commerce Platforms," SAGE Open, , vol. 9(2), pages 21582440198, May.
    5. Hui Yuan & Wei Xu & Qian Li & Raymond Lau, 2018. "Topic sentiment mining for sales performance prediction in e-commerce," Annals of Operations Research, Springer, vol. 270(1), pages 553-576, November.
    6. Qing Zhu & Renxian Zuo & Shan Liu & Fan Zhang, 2020. "Online dynamic group-buying community analysis based on high frequency time series simulation," Electronic Commerce Research, Springer, vol. 20(1), pages 81-118, March.
    7. Alaleh Razmjoo & Petros Xanthopoulos & Qipeng Phil Zheng, 2019. "Feature importance ranking for classification in mixed online environments," Annals of Operations Research, Springer, vol. 276(1), pages 315-330, May.
    8. Nan Hu & Kevin E. Dow & Alain Yee Loong Chong & Ling Liu, 2018. "Double learning or double blinding: an investigation of vendor private information acquisition and consumer learning via online reviews," Annals of Operations Research, Springer, vol. 270(1), pages 213-234, November.
    9. Haoyu Liu & Kim Hua Tan & Xianfeng Wu, 2023. "Who’s watching? Classifying sports viewers on social live streaming services," Annals of Operations Research, Springer, vol. 325(1), pages 743-765, June.
    10. Xinghua Fang & Jian Zhou & Hongya Zhao & Yizeng Chen, 2022. "A biclustering-based heterogeneous customer requirement determination method from customer participation in product development," Annals of Operations Research, Springer, vol. 309(2), pages 817-835, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bressolles, Grégory & Durrieu, François & Senecal, Sylvain, 2014. "A consumer typology based on e-service quality and e-satisfaction," Journal of Retailing and Consumer Services, Elsevier, vol. 21(6), pages 889-896.
    2. Schneider, Patricia J. & Zielke, Stephan, 2020. "Searching offline and buying online – An analysis of showrooming forms and segments," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    3. Calderwood, Eric & Freathy, Paul, 2014. "Consumer mobility in the Scottish isles: The impact of internet adoption upon retail travel patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 192-203.
    4. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    5. Sebald, Anna Kathrin & Jacob, Frank, 2020. "What help do you need for your fashion shopping? A typology of curated fashion shoppers based on shopping motivations," European Management Journal, Elsevier, vol. 38(2), pages 319-334.
    6. Zhenjie Wang & Chunling Zhu & Shanwu Tian & Ping Li, 2019. "Differentiation and pricing power of online retailers," Frontiers of Business Research in China, Springer, vol. 13(1), pages 1-20, December.
    7. Shen, George Chung-Chi, 2015. "Users' adoption of mobile applications: Product type and message framing's moderating effect," Journal of Business Research, Elsevier, vol. 68(11), pages 2317-2321.
    8. Padmavathy, Chandrasekaran & Swapana, Murali & Paul, Justin, 2019. "Online second-hand shopping motivation – Conceptualization, scale development, and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 19-32.
    9. Brand, Christian & Schwanen, Tim & Anable, Jillian, 2020. "‘Online Omnivores’ or ‘Willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    10. Yoganathan, Vignesh & Osburg, Victoria-Sophie & Akhtar, Pervaiz, 2019. "Sensory stimulation for sensible consumption: Multisensory marketing for e-tailing of ethical brands," Journal of Business Research, Elsevier, vol. 96(C), pages 386-396.
    11. Suhail Ahmad Bhat & Mushtaq Ahmad Darzi, 2019. "Exploring the Influence of Consumer Demographics on Online Purchase Benefits," FIIB Business Review, , vol. 8(4), pages 303-316, December.
    12. Massoud Moslehpour & Van Kien Pham & Wing-Keung Wong & İsmail Bilgiçli, 2018. "e-Purchase Intention of Taiwanese Consumers: Sustainable Mediation of Perceived Usefulness and Perceived Ease of Use," Sustainability, MDPI, vol. 10(1), pages 1-17, January.
    13. Chaparro-Peláez, Julián & Agudo-Peregrina, Ángel F. & Pascual-Miguel, Félix J., 2016. "Conjoint analysis of drivers and inhibitors of e-commerce adoption," Journal of Business Research, Elsevier, vol. 69(4), pages 1277-1282.
    14. Doris Morales-Solana & Irene Esteban-Millat & Alejandro Alegret Cotas, 2022. "Experiences in consumer flow in online supermarkets," Electronic Commerce Research, Springer, vol. 22(4), pages 1195-1226, December.
    15. Subhro Sarkar & Arpita Khare, 2017. "Moderating effect of price perception on factors affecting attitude towards online shopping," Journal of Marketing Analytics, Palgrave Macmillan, vol. 5(2), pages 68-80, June.
    16. Sultan, Fareena & Urban, Glen & Shankar, Venkatesh & Bart, Iakov, 2003. "Determinants and Role of Trust in E-Business: A Large Scale Empirical Study," Working papers 4282-02, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    17. Steven M. Shugan, 2006. "Editorial: Fifty Years of," Marketing Science, INFORMS, vol. 25(6), pages 551-555, 11-12.
    18. Gao, Wei & Li, Wenqian & Fan, Hua & Jia, Xingping, 2021. "How customer experience incongruence affects omnichannel customer retention: The moderating role of channel characteristics," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    19. Christophe Bezes, 2012. "Une comparaison empirique du profil des acheteurs monocanal et multicanaux," Post-Print hal-02086749, HAL.
    20. Jindal, Rupinder P. & Gauri, Dinesh K. & Li, Wanyu & Ma, Yu, 2021. "Omnichannel battle between Amazon and Walmart: Is the focus on delivery the best strategy?," Journal of Business Research, Elsevier, vol. 122(C), pages 270-280.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:233:y:2015:i:1:p:263-279:10.1007/s10479-013-1443-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.