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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Reshmi, S., Balakrishnan, K.: Empowering chatbots with business intelligence by big data integration. Int. J. Adv. Res. Comput. Sci. 9, 627 (2018)
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)
Chung, M., Ko, E., Joung, H., Kim, S.J.: Chatbot e-service and customer satisfaction regarding luxury brands. J. Bus. Res. (2018)
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)
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)
Manusama, B., Elliot, B., Magnus Revang, A.M.: Market guide for virtual customer assistants (2019)
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)
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
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)
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)
Gerbing, D.W., Anderson, J.C.: An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Mark. Res. 25, 186–192 (1988)
Rossmann, A.: Digital maturity: conceptualization and measurement model. In: Proceedings of the 39th International Conference in Information Systems, San Francisco (2018)
Guest, G., Bunce, A., Johnson, L.: How many interviews are enough? An experiment with data saturation and variability. Field methods. 18, 59–82 (2006)
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)
Rossiter, J.R.: The C-OAR-SE procedure for scale development in marketing. Int. J. Res. Mark. 19, 305–335 (2002)
Diamantopoulos, A.: The C-OAR-SE procedure for scale development in marketing: a comment. Int. J. Res. Mark. 22, 1–9 (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-51057-2_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51056-5
Online ISBN: 978-3-030-51057-2
eBook Packages: EngineeringEngineering (R0)