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A decision support system for service recovery in affective computing: an experimental investigation

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Abstract

With the development of information technology, information technology not only improves human’s living environments and the quality of life but also increases the productivity of industries. Information technology helps businesses to provide customers with quality services using existing resources and make the right and effective service decisions. Accordingly, businesses have to not only understand customer needs but also pay attention to customer emotions when they make service decisions. This study aims to build a service recovery decision support system by adopting affective computing, artificial neural networks and decision trees approaches. Three experiments are conducted to evaluate the feasibility and performance of the service recovery decision support system. The experiment results show that the service recovery decision support system can have the high performance of customer recognition. Meanwhile, customer emotion can be a clue to enable businesses to make the right service decisions in service recovery.

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Authors and Affiliations

  1. Department of Information Management, Tamkang University, New Taipei City, Taiwan

    Yen-Hao Hsieh & Szu-Chieh Chen

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  1. Yen-Hao Hsieh
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  2. Szu-Chieh Chen
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Correspondence to Yen-Hao Hsieh.

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Appendices

Appendix 1

See Tables 11, 12 and 13.

Table 11 Mapping table of service failures and ID
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Table 12 Mapping table of customer’s attributes and ID
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Table 13 Mapping table of service recovery measures and ID
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Appendix 2

See Table 14.

Table 14 Decision rules
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Hsieh, YH., Chen, SC. A decision support system for service recovery in affective computing: an experimental investigation. Knowl Inf Syst 62, 2225–2256 (2020). https://doi.org/10.1007/s10115-019-01419-1

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