Description
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.
Recommended Citation
Chen, Szu-Chieh; Chuang, Yi-Chun; and Hsieh, Yen-Hao, "Applying Affective Computing to Design a Decision Support System for Service Recovery" (2015). AMCIS 2015 Proceedings. 1.
https://aisel.aisnet.org/amcis2015/IntelSys/GeneralPresentations/1
Applying Affective Computing to Design a Decision Support System for Service Recovery
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.