Skip to main content
SpringerLink
Log in

A Bayesian Based System for Evaluating Customer Satisfaction in an Online Store

  • Conference paper
  • First Online:
Intelligent Systems and Applications (IntelliSys 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 869))

Included in the following conference series:

Abstract

This research presents a method of developing Bayesian Network models of complex systems using data sourced from open survey. The process of collection and conversion of random survey information into probability forms are shown with emphasis on integrating expert knowledge and respondents’ responses into a Bayesian system model. Random survey questionnaires were administered to customers of an online store to capture their responses about factors that make for efficient product delivery and quality website design. The responses and other known factors that influence online customer satisfaction formed the structures on which the system is modeled, thus formalizing a method of building Bayesian Network models from open survey. Customer satisfaction which is a key performance indicator in businesses is evaluated. Results of simulation showed that Bayesian Networks can be applied in developing models for complex system which can effectively serve as management tool for inference and prediction that can aid decision making.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ali, T., Asi, O., Selim, Z., Omer, F.D.: Universal structure modelling approach to customer satisfaction index. Indus. Manage. Data Syst. 113(7), 932–949 (2013)

    Google Scholar 

  2. Anna, H.: Customer Satisfaction Survey Case Study: omenamies. Bachelor’s Thesis International Business, Tampereen University of Applied Sciences (2014)

    Google Scholar 

  3. Chakraboty, S., Mengersen, K., Fidge, C., Ma, L., Lassen, D. A Bayesian network-based customer satisfaction model: a tool for management decisions in railway transport. Decis. Anal. J. 3, 4 (2016)

    Google Scholar 

  4. Cheng, H., Fang, G.: Fuzzy evaluating customer satisfaction of jet fuel companies. ICICIS 2011, part 1, CCIS 134, pp 368–373. Springer, Berlin, Heidelberg (2011)

    Google Scholar 

  5. Chen, X., Yu, L., Tan, M., Guan, Q.: A new evaluation model of customer satisfaction index. In: Proceedings of the Ninth International Conference on Management Science and Engineering Management. Adv. Intell. Syst. Comput. 362. Springer, Berlin, Heidelberg (2015)

    Google Scholar 

  6. Cronin, J.J., Taylor, S.A.: Measuring service quality: a re-examination and extension. J. Mark. 56(3), 55–68 (1992)

    Article  Google Scholar 

  7. Culiberg, B.: Identifying service quality dimensions as antecedents to customer satisfaction in retail banking. Econ. Bus. Rev. 12(3), 151–166 (2010)

    Google Scholar 

  8. Death, G., Fabricius, K.E.: Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81(11), 3178–3192 (2000)

    Article  Google Scholar 

  9. Denham, R., Falk, M., Mengersen, K.: The Bayesian conditional independence model for measurement error: applications in ecology. Environ. Ecol. Stat. 18, 239–255 (2011)

    Article  MathSciNet  Google Scholar 

  10. Dogan, I.: Analysis of facility location model using Bayesian networks. Exp. Syst. Appl. 39(1), 1092–1104 (2012)

    Article  Google Scholar 

  11. Drosos, D., Tsotsolas, Ν., Chalikias, M.: Evaluating Customer Satisfaction: the Case of the Mobile Telephony Industry in Greece. CIT&DS 2015, CCIS 535, 249–267. Springer International Publishing, Switzerland (2015)

    Google Scholar 

  12. Hackl, P., Westlund, A.H.: On structural equation modelling for customer satisfaction measurement. Total Qual. Manag. 11(4–6), 820–825 (2000)

    Article  Google Scholar 

  13. Heaton J.: Bayesian networks for predictive modeling Society for actuaries. Forecast. Futurism (7) (2013)

    Google Scholar 

  14. Hsieh, J.C.-F., Cramb, S.M., McGree, J.M., Baade, P.D., Dunn, N.A., Mengersen, K.L.: Bayesian spatial analysis for the evaluation of breast cancer detection methods. Aust N. Z. J. Stat. 55(4), 351–367 (2013)

    Article  MathSciNet  Google Scholar 

  15. Iberahim, H., Mohd, T.N.K., Mohd, A.A.S., Saharuddin, H.: Customer satisfaction on reliability and responsiveness of self service technology for retail banking services. Procedia Econ. Finance 37, 13–20 (2016)

    Article  Google Scholar 

  16. Jiang, H., Zhang, Y.: An investigation of service quality, customer satisfaction and loyalty in China’s airline market. J. Air Transp. Manage. 57, 80–88 (2016)

    Article  Google Scholar 

  17. Johnson, S., Fielding, F., Hamilton, G., Mengersen, K.: An integrated Bayesian network approach to lyngbya majuscula bloom initiation. Mar. Environ. Res. 69(1), 27–37 (2010)

    Article  Google Scholar 

  18. Justus, M.M., Henry, P.G., Gongera, E.G.: An evaluation of E-banking services on customer satisfaction: case of National Bank of Kenya. Eur. J. Bus. Manage. 6(22) (2014). ISSN 2222-1905 (Paper), ISSN 2222-2839

    Google Scholar 

  19. Kenett, R.S., Salini, S.: Modern analysis of customer satisfaction surveys: comparison of models and integrated analysis. Appl. Stoch. Models Bus. Ind. 27(5), 465–475 (2011)

    Article  MathSciNet  Google Scholar 

  20. Kotler, V., Armstrong, G., Wong, V., Saunders, J.: Principles of Marketing, 4th edn. Prentice Hall. www.pearsoned.co.uk/kotler (2008)

  21. Liu, X., Zeng, X., Xu, Y., Koehl, L.: A fuzzy model of customer satisfaction index in e-commerce. Math. Comput. Simul. 77(2008), 512–521 (2008)

    Article  MathSciNet  Google Scholar 

  22. Mashinchi, R., Selamat, A., Ibrahim, S., Krejcar, O., Penhaker, M.: Evaluating Customer satisfaction: linguistics reasoning by fuzzy artificial neural networks. In: New Trends in Intelligent Information and Database Systems Studies in Computational Intelligence, vol. 598. Springer, Berlin, Heidelberg (2015)

    Google Scholar 

  23. Medina, L.A., Jankovic, M., Kremer, G.E.O., Yannou, B.: An investigation of critical factors in medical device development through Bayesian networks. Exp. Syst. Appl. 40(17), 7034–7045 (2013)

    Article  Google Scholar 

  24. Miranda, M.D., Sassi, R.J.: Using Sentiment Analysis to Assess customer satisfaction in an Online Job Search Company, vol. 183, pp. 17–27. BIS 2014 Workshops, LNBIP. Springer International Publishing, Switzerland (2014)

    Google Scholar 

  25. Nadkarni, S., Shenoy, P.: A causal mapping approach to constructing Bayesian networks. Dec. Support Syst. 38(2), 259–81 (2004)

    Article  Google Scholar 

  26. Ozatac, N., Saner, T., Zeynep, S.S.: Customer satisfaction in the banking sector: the case of North Cyprus. Procedia Econ. Finan. 39(2016), 870–878 (2016)

    Article  Google Scholar 

  27. Perucca, G., Salini, S.: Travellers’ satisfaction with railway transport: a Bayesian network approach. Qual. Technol. Quant. Manag. 11(1), 71–84 (2014)

    Article  Google Scholar 

  28. Rahim, H., Amjad, A.N., Yomna, K.H.: Service quality and customer satisfaction of a UAE-based airline: an empirical investigation. J. Air Transp. Manage. 2014, 1–9 (2014)

    Google Scholar 

  29. Rubogora, F.: Service quality and customer satisfaction in selected banks in Rwanda. J. Bus. Fin. Aff. 6, 246 (2017)

    Google Scholar 

  30. Saket, S., Singh, A., Khanduga, D.: Fuzzy-Vikor analysis for customer performance index of civil domestic airline industry in India. Manage. Sci. Lett. 5(2015), 301–310 (2015)

    Article  Google Scholar 

  31. Salini, S., Kenett, R.S.: Bayesian networks of customer satisfaction survey data. Appl. Stat. 36(11), 1177–1189 (2009)

    Article  MathSciNet  Google Scholar 

  32. Shahraki, A.R.: Evaluation of customer satisfaction about bank service quality. Int. J. Ind. Math. 6(2) (2014). ISSN 2008-5621, Article ID IJIM-00420

    Google Scholar 

  33. Tseng, K.C., Pu, I.T.: A novel integrated model to increase customer satisfaction. J. Ind. Prod. Eng. 30(6), 373–380 (2013)

    Google Scholar 

  34. Wu, M.Y., Tseng, L.H.: Customer satisfaction and loyalty in an online shop: an experiential marketing perspective. Int. J. Bus. Manage. 10(1), 2015 (2015)

    Google Scholar 

  35. Zefinescu, C., Mostafa, A.R., Vesna, P., Mihai, M.: Measuring the economic performance in decision making process in the contemporary economies. Procedia Econ. Finan. 22, 380–387 (2015)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Edo University Iyamho, Iyamho-Uzairue, Nigeria

    Acheme David Ijegwa & Japheth Bunakiye Richard

  2. Department of Computer Science, Federal University of Agriculture, Abeokuta, Nigeria

    Vincent Rebecca Olufunke & Olusegun Folorunso

Authors
  1. Acheme David Ijegwa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vincent Rebecca Olufunke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Olusegun Folorunso
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Japheth Bunakiye Richard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Acheme David Ijegwa .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, UK

    Rahul Bhatia

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ijegwa, A.D., Olufunke, V.R., Folorunso, O., Richard, J.B. (2019). A Bayesian Based System for Evaluating Customer Satisfaction in an Online Store. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_78

Download citation

Publish with us

Policies and ethics

Search

Navigation