An Emotional Agent Approach for Online Customer Satisfaction Surveys Analysis

  • Authors

    • Shahidatul Nadhirah Mansor
    • Salama A. Mostafa
    • Rozanawati Darman
    • Aida Mustapha
    • Mohammed Ahmed Jubair
    • Mustafa Hamid Hassan
    • Mazin Abed Mohammed
    2019-01-18
    https://doi.org/10.14419/ijet.v8i1.7.25981
  • Customer Satisfaction Survey (CSS), Software Agent, Emotional Agent (EA), Kentucky Fried Chicken (KFC) and Pizza Hut (PH).

  • Abstract

    A modern approach for ensuring quality in organizations and enterprises, as well as enhancing the development of a truly customer-focused management and culture, is through the Customer Satisfaction Survey (CSS). In this paper, an Emotional Agent (EA) possessing the BDI architecture for CSS is proposed. The EA is integrated into an Online Customer Satisfaction Surveys Analysis (OCSSA) System. The EA is used in analyzing the satisfaction of customer and express an emotion representation to the results via the graphical user interface. The emotional results are categorized into five emotional levels: Very Happy, Happy, Neutral, Sad and Very Sad; these cases are expressed through emoji icons. The implementation of the OCSSA is done through the use of object-oriented methodology. The system’s implementation includes Jade and Java agent platform. The testing of the OCSSA system has been carried out in Kentucky Fried Chicken (KFC) and Pizza Hut (PH) case studies. The test is specifically conducted in order to evaluate the satisfaction rate of customers that visit PH and KFC. The use of emotional agents is employed in analyzing the CSS. The system successfully performs 10 tests for each of the tested cases. Through the use of this system, the manager is able to obtain feedback about the services provided in a visualized and informative way.

     

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  • How to Cite

    Nadhirah Mansor, S., A. Mostafa, S., Darman, R., Mustapha, A., Ahmed Jubair, M., Hamid Hassan, M., & Abed Mohammed, M. (2019). An Emotional Agent Approach for Online Customer Satisfaction Surveys Analysis. International Journal of Engineering & Technology, 8(1.7), 227-233. https://doi.org/10.14419/ijet.v8i1.7.25981

    Received date: 2019-01-16

    Accepted date: 2019-01-16

    Published date: 2019-01-18