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The Impact of Chatbots on Customer Service Performance

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Advances in the Human Side of Service Engineering (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1208))

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Abstract

The advent of chatbots in customer service solutions received increasing attention by research and practice throughout the last years. However, the relevant dimensions and features for service quality and service performance for chatbots remain quite unclear. Therefore, this research develops and tests a conceptual model for customer service quality and customer service performance in the context of chatbots. Additionally, the impact of the developed service dimensions on different customer relationship metrics is measured across different service channels (hotline versus chatbots). Findings of six independent studies indicate a strong main effect of the conceptualized service dimensions on customer satisfaction, service costs, intention to service reusage, word-of-mouth, and customer loyalty. However, different service dimensions are relevant for chatbots compared to a traditional service hotline.

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References

  1. Reshmi, S., Balakrishnan, K.: Empowering chatbots with business intelligence by big data integration. Int. J. Adv. Res. Comput. Sci. 9, 627 (2018)

    Article  Google Scholar 

  2. Przegalinska, A., Ciechanowski, L., Stroz, A., Gloor, P., Mazurek, G.: In bot we trust: a new methodology of chatbot performance measures. Bus. Horiz. 62, 785–797 (2019)

    Article  Google Scholar 

  3. Chung, M., Ko, E., Joung, H., Kim, S.J.: Chatbot e-service and customer satisfaction regarding luxury brands. J. Bus. Res. (2018)

    Google Scholar 

  4. Nordheim, C.B., Følstad, A., Bjørkli, C.A.: An initial model of trust in chatbots for customer service—findings from a questionnaire study. Interact. Comput. 31, 317–335 (2019)

    Article  Google Scholar 

  5. Balasudarsun, N.L., Sathish, M., Gowtham, K.: Optimal ways for companies to use Facebook messenger chatbot as a marketing communication channel. Asian J. Bus. Res. 8, 1 (2018)

    Article  Google Scholar 

  6. Manusama, B., Elliot, B., Magnus Revang, A.M.: Market guide for virtual customer assistants (2019)

    Google Scholar 

  7. Trivedi, J.: Examining the customer experience of using banking chatbots and its impact on brand love: the moderating role of perceived risk. J. Internet Commer. 18, 91 (2019)

    Article  Google Scholar 

  8. Sugathan, P., Rossmann, A., Ranjan, K.R.: Toward a conceptualization of perceived complaint handling quality in social media and traditional service channels. Eur. J. Mark. 52, 973–1006 (2018). https://doi.org/10.1108/EJM-04-2016-0228

    Article  Google Scholar 

  9. Orsingher, C., Valentini, S., de Angelis, M.: A meta-analysis of satisfaction with complaint handling in services. J. Acad. Mark. Sci. 38, 169–186 (2010)

    Article  Google Scholar 

  10. Homburg, C., Fürst, A.: How organizational complaint handling drives customer loyalty: an analysis of the mechanistic and the organic approach. J. Mark. 69, 95–114 (2005)

    Google Scholar 

  11. Gerbing, D.W., Anderson, J.C.: An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Mark. Res. 25, 186–192 (1988)

    Article  Google Scholar 

  12. Rossmann, A.: Digital maturity: conceptualization and measurement model. In: Proceedings of the 39th International Conference in Information Systems, San Francisco (2018)

    Google Scholar 

  13. Guest, G., Bunce, A., Johnson, L.: How many interviews are enough? An experiment with data saturation and variability. Field methods. 18, 59–82 (2006)

    Article  Google Scholar 

  14. Smyth, J.D., Dillman, D.A., Christian, L.M., McBride, M.: Open-ended questions in web surveys: can increasing the size of answer boxes and providing extra verbal instructions improve response quality? Public Opin. Q. 73, 325–337 (2009)

    Article  Google Scholar 

  15. Rossiter, J.R.: The C-OAR-SE procedure for scale development in marketing. Int. J. Res. Mark. 19, 305–335 (2002)

    Article  Google Scholar 

  16. Diamantopoulos, A.: The C-OAR-SE procedure for scale development in marketing: a comment. Int. J. Res. Mark. 22, 1–9 (2005)

    Article  Google Scholar 

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Correspondence to Alexander Rossmann .

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Rossmann, A., Zimmermann, A., Hertweck, D. (2020). The Impact of Chatbots on Customer Service Performance. In: Spohrer, J., Leitner, C. (eds) Advances in the Human Side of Service Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1208. Springer, Cham. https://doi.org/10.1007/978-3-030-51057-2_33

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  • DOI: https://doi.org/10.1007/978-3-030-51057-2_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51056-5

  • Online ISBN: 978-3-030-51057-2

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