Data Science Insights
Vol. 2 No. 1 (2024): Journal of Data Science Insights

Customer Satisfaction Towards Onsite Restaurant Interactive Self-Service Technology (ORISST)

Por Eng Choo (Unknown)
Fadhilah Mat Yamin (Unknown)
Wan Ishak, Wan Hussain (Unknown)



Article Info

Publish Date
29 Feb 2024

Abstract

A recent development in the restaurant industry is the use of on-site restaurant interactive self-service technology (ORISST) by some operators who are moving away from traditional service methods. ORISST allows customers to manage dining services independently through interfaces such as self-service kiosks or tabletop tablets. However, the gap in understanding customer satisfaction regarding ORISST is notable as there is a lack of technology-related research in the restaurant industry. The research objectives of this study is to investigate the significant relationship between the four dimensions of SSTQUAL (functionality, design, enjoyment, customization) and customer satisfaction in using ORISST. In this study, quantitative research was conducted. Data was collected via google form from 293 STML students at UUM who had experience using ORISST. The findings of this study show that functionality, design and enjoyment have a significant positive relationship with customer satisfaction in using ORISST, with functionality being the most significant determinant. In contrast, customization has no significant relationship with customer satisfaction in using ORISST. All these findings may provide valuable suggestions to restaurant operators on how to properly implement ORISST to improve their business performance and attract more customers. This study has broadened the understanding of customer satisfaction towards ORISST which has yet to be fully explored.

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Journal Info

Abbrev

jdsi

Publisher

Subject

Computer Science & IT Engineering

Description

Data Science Insights, with ISSN 3031-1268 (Online) published by PT Visi Media Network is a journal that publishes Focus & Scope research articles, which include Data Science and Machine Learning; Data Science and AI; Blockchain and Advance Data Science; Cloud computing and Big Data; Business ...