IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v17y1998i1p45-65.html
   My bibliography  Save this article

A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction

Author

Listed:
  • Ruth N. Bolton

    (The Maryland Business School, University of Maryland, 3467 Van Munching Hall, College Park, Maryland 20742)

Abstract

Many service organizations have embraced relationship marketing with its focus on maximizing customer lifetime value. Recently, there has been considerable controversy about whether there is a link between customer satisfaction and retention. This research question is important to researchers who are attempting to understand how customers' assessments of services influence their subsequent behavior. However, it is equally vital to managers who require a better understanding of the relationship between satisfaction and the duration of the provider-customer relationship to identify specific actions that can increase retention and profitability in the long run. Since there is very little empirical evidence regarding this research question, this study develops and estimates a dynamic model of the duration of provider-customer relationship that focuses on the role of customer satisfaction. This article models the duration of the customer's relationship with an organization that delivers a continuously provided service, such as utilities, financial services, and telecommunications. In the model, the duration of the provider-customer relationship is postulated to depend on the customer's subjective expected value of the relationship, which he/she updates according to an anchoring and adjustment process. It is hypothesized that cumulative satisfaction serves as an anchor that is updated with new information obtained during service experiences. The model is estimated as a left-truncated, proportional hazards regression with cross-sectional and time series data describing cellular customers perceptions and behavior over a 22-month period. The results indicate that customer satisfaction ratings elicited prior to any decision to cancel or stay loyal to the provider are positively related to the duration of the relationship. The strength of the relationship between duration times and satisfaction levels depends on the length of customers' prior experience with the organization. Customers who have many months' experience with the organization weigh prior cumulative satisfaction more heavily and new information (relatively) less heavily. The duration of the service provider-customer relationship also depends on whether customers experienced service transactions or failures. The effects of perceived losses arising from transactions or service failures on duration times are directly weighed by prior satisfaction, creating contrast and assimilation effects. How can service organizations develop longer relationships with customers? Since customers weigh prior cumulative satisfaction heavily, organizations should focus on customers in the early stages of the relationship—if customers' experiences are not satisfactory, the relationship is likely to be very short. There is considerable heterogeneity across customers because some customers have a higher utility for the service than others. However, certain types of service encounters are potential relationship “landmines” because customers are highly sensitive to the costs/losses arising from interactions with service organizations and insensitive to the benefits/gains. Thus, incidence and quality of service encounters can be early indicators of whether an organization's relationship with a customer is flourishing or in jeopardy. Unfortunately, organizations with good prior service levels will suffer more when customers perceive that they have suffered a loss arising from a service encounter—due to the existence of contrast effects. However, experienced customers are less sensitive to such losses because they tend to weigh prior satisfaction levels heavily. By modeling the duration of the provider-customer relationship, it is possible to predict the revenue impact of service improvements in the same manner as other resource allocation decisions. The calculations in this article show that changes in customer satisfaction can have important financial implications for the organization because lifetime revenues from an individual customer depend on the duration of his/her relationship, as well as the dollar amount of his/her purchases across billing cycles. Satisfaction levels explain a substantial portion of explained variance in the durations of service provider-customer relationships across customers, comparable to the effect of price. Consequently, it is a popular misconception that organizations that focus on customer satisfaction are failing to manage customer retention. Rather, this article suggests that service organizations should be proactive and learn from customers they defect by understanding their current satisfaction levels. Managers and researchers may have underestimated the importance of the link between customer satisfaction and retention because the relationship between satisfaction and duration times is very complex and difficult to detect without advanced statistical techniques.

Suggested Citation

  • Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
  • Handle: RePEc:inm:ormksc:v:17:y:1998:i:1:p:45-65
    DOI: 10.1287/mksc.17.1.45
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.17.1.45
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.17.1.45?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
    ---><---

    References listed on IDEAS

    as
    1. Oliver, Richard L. & Winer, Russell S., 1987. "A framework for the formation and structure of consumer expectations: Review and propositions," Journal of Economic Psychology, Elsevier, vol. 8(4), pages 469-499, December.
    2. Claes Fornell & Birger Wernerfelt, 1988. "A Model for Customer Complaint Management," Marketing Science, INFORMS, vol. 7(3), pages 287-298.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    5. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    6. Eugene W. Anderson & Claes Fornell & Roland T. Rust, 1997. "Customer Satisfaction, Productivity, and Profitability: Differences Between Goods and Services," Marketing Science, INFORMS, vol. 16(2), pages 129-145.
    7. Kristiaan Helsen & David C. Schmittlein, 1993. "Analyzing Duration Times in Marketing: Evidence for the Effectiveness of Hazard Rate Models," Marketing Science, INFORMS, vol. 12(4), pages 395-414.
    8. Gilly, Mary C & Gelb, Betsy D, 1982. "Post-Purchase Consumer Processes and the Complaining Consumer," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 323-328, December.
    9. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762, October.
    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. Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
    2. Arnold, Mark J. & Reynolds, Kristy E. & Ponder, Nicole & Lueg, Jason E., 2005. "Customer delight in a retail context: investigating delightful and terrible shopping experiences," Journal of Business Research, Elsevier, vol. 58(8), pages 1132-1145, August.
    3. Gürtler, Marc & Hartmann, Nora, 2003. "Behavioral dividend policy," Working Papers FW04V1, Technische Universität Braunschweig, Institute of Finance.
    4. Jonathan D. Bohlmann & José Antonio Rosa & Ruth N. Bolton & William J. Qualls, 2006. "The Effect of Group Interactions on Satisfaction Judgments: Satisfaction Escalation," Marketing Science, INFORMS, vol. 25(4), pages 301-321, July.
    5. Dong, Songting & Ding, Min & Grewal, Rajdeep & Zhao, Ping, 2011. "Functional forms of the satisfaction–loyalty relationship," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 38-50.
    6. McQuilken, Lisa, 2010. "The influence of failure severity and employee effort on service recovery in a service guarantee context," Australasian marketing journal, Elsevier, vol. 18(4), pages 214-221.
    7. Mathies, Christine & Gudergan, Siegfried P., 2011. "The role of fairness in modelling customer choice," Australasian marketing journal, Elsevier, vol. 19(1), pages 22-29.
    8. Rust, Roland T. & Metters, Richard, 1996. "Mathematical models of service," European Journal of Operational Research, Elsevier, vol. 91(3), pages 427-439, June.
    9. Kirchler, Erich & Holzl, Erik, 2006. "Twenty-five years of the Journal of Economic Psychology (1981-2005): A report on the development of an interdisciplinary field of research," Journal of Economic Psychology, Elsevier, vol. 27(6), pages 793-804, December.
    10. Jin, Liyin & He, Yanqun & Song, Haiyan, 2012. "Service customization: To upgrade or to downgrade? An investigation of how option framing affects tourists’ choice of package-tour services," Tourism Management, Elsevier, vol. 33(2), pages 266-275.
    11. Bolton, R.N. & Lemo, K.N. & Verhoef, P.C., 2002. "The Theoretical Underpinnings of Customer Asset Management," ERIM Report Series Research in Management ERS-2002-80-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Bélyácz, Iván & Kovács, Kármen, 2018. "A birtoklási hatás megnyilvánulásának háttere és következményei. A kilátáselmélet alkalmazása fogyasztási döntésekre [Background and consequences of the endowment effect. Applying prospect theory t," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(4), pages 382-401.
    13. Kim, Joonkyung & Zhao, Min & Soman, Dilip, 2023. "Converging vs diverging: The effect of visual representation of goal structure on financial decisions," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 362-377.
    14. Kristien Werck & Bruno Heyndels & Benny Geys, 2008. "The impact of ‘central places’ on spatial spending patterns: evidence from Flemish local government cultural expenditures," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 32(1), pages 35-58, March.
    15. James K. Hammitt, 2020. "Valuing mortality risk in the time of COVID-19," Journal of Risk and Uncertainty, Springer, vol. 61(2), pages 129-154, October.
    16. Justin S. Skillman & Michael J. Vernarelli, 2016. "Framing effects on bidding behavior in experimental first-price sealed-bid money auctions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(4), pages 391-400, July.
    17. Karle, Heiko & Schumacher, Heiner & Vølund, Rune, 2023. "Consumer loss aversion and scale-dependent psychological switching costs," Games and Economic Behavior, Elsevier, vol. 138(C), pages 214-237.
    18. Duncan Luce, R., 1997. "Associative joint receipts," Mathematical Social Sciences, Elsevier, vol. 34(1), pages 51-74, August.
    19. Uri Gneezy & Jan Potters, 1997. "An Experiment on Risk Taking and Evaluation Periods," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 631-645.
    20. Cristiano Codagnone & Giuseppe Alessandro Veltri & Francesco Bogliacino & Francisco Lupiáñez-Villanueva & George Gaskell & Andriy Ivchenko & Pietro Ortoleva & Francesco Mureddu, 2016. "Labels as nudges? An experimental study of car eco-labels," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 33(3), pages 403-432, December.

    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:inm:ormksc:v:17:y:1998:i:1:p:45-65. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.