IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v120y2020icp443-452.html
   My bibliography  Save this article

A quantile regression approach to gaining insights for reacquition of defected customers

Author

Listed:
  • Yoo, Changsok
  • Cha, Kyoung Cheon
  • Kim, Sang-Hoon

Abstract

As customer loyalty keeps declining, the importance of customer relationship management is paramount especially for online-service marketers. Reacquisition of defected customers is better than acquiring new customers in terms of marketing efficiency as well as effectiveness. However, the issue of winning back defected customers has been largely neglected among scholars. In this paper, we present empirical analyses based on real transactional data from 4000 users of one of the most successful online games in Korea to investigate the relationship between demographic, RFM, behavioral, and social network variables and the users’ response to reacquisition campaigns. Since the dependent variable is skewed, a quantile regression method was utilized for model estimation. To figure out what kind of characteristics would influence the likelihood of “staying alive” after the campaigns, the results from Period 1(win-back) were compared against those from Period 2(retention). The findings shed many useful insights in targeting and designing win-back campaigns.

Suggested Citation

  • Yoo, Changsok & Cha, Kyoung Cheon & Kim, Sang-Hoon, 2020. "A quantile regression approach to gaining insights for reacquition of defected customers," Journal of Business Research, Elsevier, vol. 120(C), pages 443-452.
    • Handle: RePEc:eee:jbrese:v:120:y:2020:i:c:p:443-452
    DOI: 10.1016/j.jbusres.2019.10.068
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296319306678
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2019.10.068?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. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    2. repec:dgr:rugsom:10008 is not listed on IDEAS
    3. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    4. Heeju Chae & Eunju Ko & Jinghe Han, 2015. "How do customers' SNS participation activities impact on customer equity drivers and customer loyalty? Focus on the SNS services of a global SPA brand," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 25(2), pages 122-141, March.
    5. Eric J. Johnson & John W. Payne, 1985. "Effort and Accuracy in Choice," Management Science, INFORMS, vol. 31(4), pages 395-414, April.
    6. Joonheui Bae & Dong-Mo Koo & Pekka Mattila, 2016. "Affective motives to play online games," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 26(2), pages 174-184, March.
    7. Sang Jin Kim & Kyung Hoon Kim & Chang Han Lee, 2016. "Role of user-created programs in online game consumer behavior," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 26(3), pages 217-226, June.
    8. Juran Kim & Seungmook Kang & Charles R. Taylor, 2018. "Technology driven experiences from mobile direct to virtual reality," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 28(1), pages 96-102, January.
    9. Yongjae Kim & Soojin Kim, 2013. "Segmenting sport video gamers by motivation: a cluster analysis," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 23(1), pages 92-108, January.
    10. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    11. Doreén Pick & Jacquelyn S. Thomas & Sebastian Tillmanns & Manfred Krafft, 2016. "Customer win-back: the role of attributions and perceptions in customers’ willingness to return," Journal of the Academy of Marketing Science, Springer, vol. 44(2), pages 218-240, March.
    12. Bijmolt, T.H.A. & Bl, 2010. "Should they stay or should they go? Reactivation and termination of low-tier customers," Research Report 10008, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    13. Hoffman, Donna L. & Novak, Thomas P., 2009. "Flow Online: Lessons Learned and Future Prospects," Journal of Interactive Marketing, Elsevier, vol. 23(1), pages 23-34.
    14. Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
    15. Paramaporn Thaichon & Thu Nguyen Quach, 2015. "The relationship between service quality, satisfaction, trust, value, commitment and loyalty of Internet service providers' customers," Journal of Global Scholars of Marketing Science, Taylor & Francis Journals, vol. 25(4), pages 295-313, September.
    Full references (including those not matched with items on IDEAS)

    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. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    2. C F Elliott & R Simmons, 2007. "Determinants of UK box office success: the impact of quality signals," Working Papers 584026, Lancaster University Management School, Economics Department.
    3. Gaenssle Sophia & Budzinski Oliver & Astakhova Daria, 2018. "Conquering the Box Office: Factors Influencing Success of International Movies in Russia," Review of Network Economics, De Gruyter, vol. 17(4), pages 245-266, December.
    4. David E. Allen & Abhay K. Singh & Robert J. Powell & Michael McAleer & James Taylor & Lyn Thomas, 2013. "Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression," Tinbergen Institute Discussion Papers 13-020/III, Tinbergen Institute.
    5. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    6. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
    7. Ben Rejeb, Aymen, 2017. "On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 794-815.
    8. repec:lan:wpaper:1090 is not listed on IDEAS
    9. Han, Sang-Lin & An, Myounga & Han, Jerry J. & Lee, Jiyoung, 2020. "Telepresence, time distortion, and consumer traits of virtual reality shopping," Journal of Business Research, Elsevier, vol. 118(C), pages 311-320.
    10. Elberse, Anita & Anand, Bharat, 2007. "The effectiveness of pre-release advertising for motion pictures: An empirical investigation using a simulated market," Information Economics and Policy, Elsevier, vol. 19(3-4), pages 319-343, October.
    11. Cristi A. Gleason & Sascha Kieback & Martin Thomsen & Christoph Watrin, 2021. "Monitoring or payroll maximization? What happens when workers enter the boardroom?," Review of Accounting Studies, Springer, vol. 26(3), pages 1046-1087, September.
    12. Cummins, Joseph R., 2017. "Heterogeneous treatment effects in the low track: Revisiting the Kenyan primary school experiment," Economics of Education Review, Elsevier, vol. 56(C), pages 40-51.
    13. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    14. Ludger Wößmann, 2003. "European education production functions: what makes a difference for student achievement in Europe?," European Economy - Economic Papers 2008 - 2015 190, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    15. Liu, Sezhu & Hite, Diane, 2013. "Measuring the Effect of Green Space on Property Value: An Application of the Hedonic Spatial Quantile Regression," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 143045, Southern Agricultural Economics Association.
    16. Raul A. Barreto & Anthony W. Hughes, 2004. "Under Performers and Over Achievers: A Quantile Regression Analysis of Growth," The Economic Record, The Economic Society of Australia, vol. 80(248), pages 17-35, March.
    17. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    18. Jehoshua Eliashberg & Anita Elberse & Mark A.A.M. Leenders, 2006. "The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions," Marketing Science, INFORMS, vol. 25(6), pages 638-661, 11-12.
    19. An, Myoung-a & Han, Sang-Lin, 2020. "Effects of experiential motivation and customer engagement on customer value creation: Analysis of psychological process in the experience-based retail environment," Journal of Business Research, Elsevier, vol. 120(C), pages 389-397.
    20. Michelle L. Barnes & Anthony W. Hughes, 2002. "A quantile regression analysis of the cross section of stock market returns," Working Papers 02-2, Federal Reserve Bank of Boston.
    21. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.

    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:eee:jbrese:v:120:y:2020:i:c:p:443-452. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.