Developing a smart system with Industry 4.0 for customer dissatisfaction

This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables hoteliers to interact with customers by understanding what they like/dislike from their behaviors via data analysis. Therefore, this system helps hoteliers to enhance service quality by predicting service issues.

The system, named the dissatisfaction identification system (DIS), is developed. A total of 127 service items were examined by a hotel manager who preset the threshold values for the measurement of service quality. A big data set for the questionnaire survey is statistically generated by a pseudorandom number generator and 10,000 mock data sets are taken as input for comparison.

The results indicated that 36 out of 127 service items are identified as service issues for the participating hotel. Examples include customer code number 01d, “Space of parking lot is adequate” in the safety management category, and number 05a, “A hotel's service time meets my needs” in the front office service category. The items identified require improvement action plans for preventing customer dissatisfaction.

This paper offers a new perspective paper emphasizing customer dissatisfaction using a big data-driven technology system. The DIS, prevention system, is developed to aid hotels by enhancing their relationships with customers using a data-driven approach.