IDEAS home Printed from https://ideas.repec.org/p/rug/rugwps/05-299.html
   My bibliography  Save this paper

Investigating the post-complaint period by means of survival analysis

Author

Listed:
  • B. LARIVIÈRE
  • D. VAN DEN POEL

Abstract

Firms increasingly view each contact with their customers as an opportunity that needs to be managed. The primary purpose of this article is to gain a better understanding of the customers’ post-complaint period. Specific focus is placed on the impact of effective complaint handling on actual customer behavior throughout the time, whereas previous research has mainly focused on time-invariant or intentional measures. Survival analysis techniques are used to investigate the longitudinal behavior of complainants after their problem recovery. The proportionality assumption is tested for each explanatory variable under investigation. In addition, the impact for each variable is estimated by means of survival forests. Survival forests enable us to explore the evolution over time of the effects of the covariates under investigation. As such, the impact of each explanatory variable is allowed to change when the experiment evolves over time, in contrast to “proportional” models that restrict these estimates to be stationary. Our research is performed in the context of a financial services provider and analyzes the post-complaint periods of 2,326 customers. Our findings indicate that (i) it is interesting to consider complainants since they represent a typical and rather active customer segment, (ii) furthermore, it is beneficiary to invest in complaint handling, since these investments are likely to influence customers’ future behavior and (iii) survival forests are a helpful tool to investigate the impact of complaint handling on future customer behavior, since its components provide evidence of changing effects over time.

Suggested Citation

  • B. Larivière & D. Van Den Poel, 2005. "Investigating the post-complaint period by means of survival analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/299, Ghent University, Faculty of Economics and Business Administration.
    • Handle: RePEc:rug:rugwps:05/299
    as

    Download full text from publisher

    File URL: http://wps-feb.ugent.be/Papers/wp_05_299.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. B. Larivière & D. Van Den Poel, 2004. "Investigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial services," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/223, Ghent University, Faculty of Economics and Business Administration.
    2. Bougie, J.R.G. & Pieters, R. & Zeelenberg, M., 2003. "Angry customers don't come back, they get back : The experience and behavioral implications of anger and dissatisfaction in services," Other publications TiSEM 1708fb71-fd68-41d9-b870-e, Tilburg University, School of Economics and Management.
    3. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    4. Martin R. Young & Wayne S. DeSarbo & Vicki G. Morwitz, 1998. "The Stochastic Modeling of Purchase Intentions and Behavior," Management Science, INFORMS, vol. 44(2), pages 188-202, February.
    5. Maxham, James III, 2001. "Service recovery's influence on consumer satisfaction, positive word-of-mouth, and purchase intentions," Journal of Business Research, Elsevier, vol. 54(1), pages 11-24, October.
    6. Kumar, Dhananjay & Westberg, Ulf, 1997. "Maintenance scheduling under age replacement policy using proportional hazards model and TTT-plotting," European Journal of Operational Research, Elsevier, vol. 99(3), pages 507-515, June.
    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. Mathieu Béal & William Sabadie & Yany Grégoire, 2019. "The effects of relationship length on customer profitability after a service recovery," Marketing Letters, Springer, vol. 30(3), pages 293-305, December.
    2. Jens Hogreve & Nicola Bilstein & Leonhard Mandl, 2017. "Unveiling the recovery time zone of tolerance: when time matters in service recovery," Journal of the Academy of Marketing Science, Springer, vol. 45(6), pages 866-883, November.

    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. K. Coussement & D. Van Den Poel, 2008. "Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 08/527, Ghent University, Faculty of Economics and Business Administration.
    2. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    3. Kalamas, Maria & Laroche, Michel & Makdessian, Lucy, 2008. "Reaching the boiling point: Consumers' negative affective reactions to firm-attributed service failures," Journal of Business Research, Elsevier, vol. 61(8), pages 813-824, August.
    4. Valentina Sommovigo & Ilaria Setti & Piergiorgio Argentero, 2019. "The Role of Service Providers’ Resilience in Buffering the Negative Impact of Customer Incivility on Service Recovery Performance," Sustainability, MDPI, vol. 11(1), pages 1-22, January.
    5. Prinzie, Anita & Van den Poel, Dirk, 2006. "Investigating purchasing-sequence patterns for financial services using Markov, MTD and MTDg models," European Journal of Operational Research, Elsevier, vol. 170(3), pages 710-734, May.
    6. A. Prinzie & D. Van Den Poel, 2005. "Incorporating sequential information into traditional classification models by using an element/position- sensitive SAM," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/292, Ghent University, Faculty of Economics and Business Administration.
    7. Jens Hogreve & Nicola Bilstein & Leonhard Mandl, 2017. "Unveiling the recovery time zone of tolerance: when time matters in service recovery," Journal of the Academy of Marketing Science, Springer, vol. 45(6), pages 866-883, November.
    8. B. Larivière & D. Van Den Poel, 2004. "Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/282, Ghent University, Faculty of Economics and Business Administration.
    9. Arora, Swapan Deep & Chakraborty, Anirban, 2021. "Intellectual structure of consumer complaining behavior (CCB) research: A bibliometric analysis," Journal of Business Research, Elsevier, vol. 122(C), pages 60-74.
    10. M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
    11. Bastian Popp & Herbert Woratschek, 2017. "Consumer–brand identification revisited: An integrative framework of brand identification, customer satisfaction, and price image and their role for brand loyalty and word of mouth," Journal of Brand Management, Palgrave Macmillan, vol. 24(3), pages 250-270, May.
    12. Garaus, Marion & Wagner, Udo, 2016. "Retail shopper confusion: Conceptualization, scale development, and consequences," Journal of Business Research, Elsevier, vol. 69(9), pages 3459-3467.
    13. Zhou, Yuanyuan & Tsang, Alex S.L. & Huang, Minxue & Zhou, Nan, 2014. "Does delaying service-failure resolution ever make sense?," Journal of Business Research, Elsevier, vol. 67(2), pages 159-166.
    14. Heyes, Anthony & Kapur, Sandeep, 2012. "Angry customers, e-word-of-mouth and incentives for quality provision," Journal of Economic Behavior & Organization, Elsevier, vol. 84(3), pages 813-828.
    15. Yen-Chun Chou & Howard Hao-Chun Chuang, 2018. "A predictive investigation of first-time customer retention in online reservation services," Service Business, Springer;Pan-Pacific Business Association, vol. 12(4), pages 685-699, December.
    16. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
    17. Huang, Wen-Hsien & Shen, George C. & Liang, Che-Ling, 2019. "The effect of threshold free shipping policies on online shoppers' willingness to pay for shipping," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 105-112.
    18. Slãvescu Ecaterina Oana & Panait Iulian, 2012. "Improving Customer Churn Models as one of Customer Relationship Management Business Solutions for the Telecommunication Industry," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 1156-1160, May.
    19. Gómez Fernández, Juan F. & Márquez, Adolfo Crespo & López-Campos, Mónica A., 2016. "Customer-oriented risk assessment in network utilities," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 72-83.
    20. Fennell, Patrick B. & Coleman, Joshua T. & Kuo, Andrew, 2020. "The moderating role of donation quantifiers on price fairness judgments," Journal of Business Research, Elsevier, vol. 110(C), pages 464-473.

    More about this item

    Keywords

    Data mining; customer relationship management; consumer complaint behavior; actual customer behavior; proportionality; survival forests.;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:rug:rugwps:05/299. 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: Nathalie Verhaeghe (email available below). General contact details of provider: https://edirc.repec.org/data/ferugbe.html .

    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.