IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v17y2020i1d10.1007_s10287-018-0305-1.html
   My bibliography  Save this article

Customer satisfaction: a mathematical framework for its analysis and its measurement

Author

Listed:
  • R. Ferrentino

    (University of Salerno)

  • C. Boniello

    (University of Salerno)

Abstract

The customer satisfaction, an important concept in the field of general marketing and in the management of firms, is the measure of the degree of customer satisfaction. More precisely, the customer satisfaction provides an assessment of the discrepancy between the perceived performance by the customer (i.e. all the sensations and impressions after use of a product or the fruition of a service) and the expectations (expectations and desires) of the same customer but also represents the company’s ability to anticipate and to manage the expectations of the customer, to satisfy its needs with competence and responsibility. The company resources, in fact, must be organized taking account of the demands of customers who represent a precious commodity for the company, even if their value does not appear in the financial statements, the fulcrum around which revolves the whole system business. To have satisfied customers is, therefore, fundamental for a company and, therefore, the customer satisfaction can be defined as a touchstone for the management of customer relationships, as a key to create the competitive advantage as of a company. In this article, the authors present some of the main processes and detection systems required for a scrupulous and reliable process of measuring of the customer satisfaction or better they present a mathematical framework to determine and to improve the customer satisfaction and to demonstrate how it has a great impact on corporate performance. In particular, the authors propose a model of structural equations with latent variables which is the most rigorous methodology currently available for the evaluations of the customer satisfaction and they hope that the paper, which at first sight has little in common with mathematics, is a very useful for stimulating research at the interface of mathematics and marketing and that it builds a link that can become beneficial for both disciplines involved.

Suggested Citation

  • R. Ferrentino & C. Boniello, 2020. "Customer satisfaction: a mathematical framework for its analysis and its measurement," Computational Management Science, Springer, vol. 17(1), pages 23-45, January.
  • Handle: RePEc:spr:comgts:v:17:y:2020:i:1:d:10.1007_s10287-018-0305-1
    DOI: 10.1007/s10287-018-0305-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10287-018-0305-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10287-018-0305-1?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. R. Ferrentino & M. T. Cuomo & C. Boniello, 2016. "On the customer lifetime value: a mathematical perspective," Computational Management Science, Springer, vol. 13(4), pages 521-539, October.
    2. Sunil Gupta & Valarie Zeithaml, 2006. "Customer Metrics and Their Impact on Financial Performance," Marketing Science, INFORMS, vol. 25(6), pages 718-739, 11-12.
    3. 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.
    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. Polo, Yolanda & Sese, F. Javier & Verhoef, Peter C., 2011. "The Effect of Pricing and Advertising on Customer Retention in a Liberalizing Market," Journal of Interactive Marketing, Elsevier, vol. 25(4), pages 201-214.
    2. R. Ferrentino & M. T. Cuomo & C. Boniello, 2016. "On the customer lifetime value: a mathematical perspective," Computational Management Science, Springer, vol. 13(4), pages 521-539, October.
    3. Cho, Jihoon & Aribarg, Anocha & Manchanda, Puneet, 2023. "Can firms benefit from integrating high-frequency survey measures with objective service quality data?," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 513-533.
    4. Venkatesh Shankar & Pablo Azar & Matthew Fuller, 2008. "—: A Multicategory Brand Equity Model and Its Application at Allstate," Marketing Science, INFORMS, vol. 27(4), pages 567-584, 07-08.
    5. Angulo-Ruiz, Fernando & Pergelova, Albena & Cheben, Juraj & Angulo-Altamirano, Eladio, 2016. "A cross-country study of marketing effectiveness in high-credence services," Journal of Business Research, Elsevier, vol. 69(9), pages 3636-3644.
    6. Jae-Woong Jeong & Heon-Hwi Lee & Hun Park, 2022. "A Study on the Effect of Knowledge Services on Organizational Performances Based on the Concept of Balanced Scorecards for the Sustainable Growth of Firms: Evidence from South Korea," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    7. Mahsa Samsami & Ralf Wagner, 2021. "Investment Decisions with Endogeneity: A Dirichlet Tree Analysis," JRFM, MDPI, vol. 14(7), pages 1-19, July.
    8. Martijn G. de Jong & Jan-Benedict E. M. Steenkamp & Bernard P. Veldkamp, 2009. "A Model for the Construction of Country-Specific Yet Internationally Comparable Short-Form Marketing Scales," Marketing Science, INFORMS, vol. 28(4), pages 674-689, 07-08.
    9. Mercedes Esteban-Bravo & Jose M. Vidal-Sanz & Gökhan Yildirim, 2014. "Valuing Customer Portfolios with Endogenous Mass and Direct Marketing Interventions Using a Stochastic Dynamic Programming Decomposition," Marketing Science, INFORMS, vol. 33(5), pages 621-640, September.
    10. Carlos Lamela-Orcasitas & Jesús García-Madariaga, 2023. "How to really quantify the economic value of customer information in corporate databases," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    11. Marion Debruyne & David J. Reibstein, 2005. "Competitor See, Competitor Do: Incumbent Entry in New Market Niches," Marketing Science, INFORMS, vol. 24(1), pages 55-66, December.
    12. Vardit Landsman & Moshe Givon, 2010. "The diffusion of a new service: Combining service consideration and brand choice," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 91-121, March.
    13. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2020. "How much do consumers know about the quality of products? Evidence from the diaper market," The Japanese Economic Review, Springer, vol. 71(4), pages 541-569, October.
    14. Yoshida, Masayuki, 2017. "Consumer experience quality: A review and extension of the sport management literature," Sport Management Review, Elsevier, vol. 20(5), pages 427-442.
    15. Govert Bijwaard, 2010. "Regularity in individual shopping trips: implications for duration models in marketing," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1931-1945.
    16. Antioco, Michael & Coussement, Kristof, 2018. "Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias," International Journal of Information Management, Elsevier, vol. 38(1), pages 301-310.
    17. Mercedes Esteban-Bravo & José Múgica & Jose Vidal-Sanz, 2005. "Optimal Duration of Magazine Promotions," Marketing Letters, Springer, vol. 16(2), pages 99-114, April.
    18. Fernando S. Machado & Rajiv K. Sinha, 2007. "Smoking Cessation: A Model of Planned vs. Actual Behavior for Time-Inconsistent Consumers," Marketing Science, INFORMS, vol. 26(6), pages 834-850, 11-12.
    19. Tomczyk, Przemysław & Doligalski, Tymoteusz & Zaborek, Piotr, 2016. "Does customer analysis affect firm performance? Quantitative evidence from the Polish insurance market," Journal of Business Research, Elsevier, vol. 69(9), pages 3652-3658.
    20. Zhang, Hao & Liang, Xiaoning & Wang, Shiquan, 2016. "Customer value anticipation, product innovativeness, and customer lifetime value: The moderating role of advertising strategy," Journal of Business Research, Elsevier, vol. 69(9), pages 3725-3730.

    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:comgts:v:17:y:2020:i:1:d:10.1007_s10287-018-0305-1. 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.