The shape and features of the service robot impact customer satisfaction

Abstract

The topic is discussed on how the shape and features of service robots affect customer satisfaction. The main objective of the study is to determine the degree of influence of robotic services on customer experience and which customer segments prefer robotic services (SR). From there, this study will make recommendations to help service businesses and consultants in the F&B industry have more information to increase customer satisfaction; this is also a reference example for future research to develop and find out more limitations that have not been mentioned. The research process of the topic is carried out with 2 main phases: secondary data research and quantitative research. (1) Secondary data research method: The author's group has discussed and consulted from many sources including documents and research articles of different domestic and foreign authors with topics related to the topic. to robot service like: “The Value of Service Robots from the Hotel Guest’s Perspective: A Mixed-Method Approach” (Igrid Y. Lin, Anna S. Mattila, 2021); “The antecedents and consequences of memorable brand experience: Human baristas versus robot baristas” (Jinsoo Hwang, Ja Young (Jacey) Choe, Heather Markham Kim, Jinkyung Jenny Kim, 2021); “How to enhance hotel guests’ acceptance and experience of smart hotel technology: An examination of visiting intentions” (Huijun Yang, Hanqun Song, Catherine Cheung, Jieqi Guan, 2021). From there, find out research models, research hypotheses, and design survey questionnaires from previous research papers. (2) Quantitative research method: The authors design a questionnaire in the form of a survey with the aim of testing the reliability, through the value of the scales with a level of 1-5. (dissatisfied – very satisfied) using Cronbach's alpha reliability method. The group conducted an online survey of subjects who knew about SR or had used it with 470 survey questionnaires, collected 435 survey questionnaires, of which 304 questionnaires met the survey requirements. suggest. The authors used the SmartPLS4 tool to screen and statistic the level of customer satisfaction or dissatisfaction about SR.