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Article
Publication date: 2 September 2022

Sara Abhari, Alireza Jalali and Mastura Jaafar

This study investigated the linkage between customers’ acceptance (CA) level and smart service competencies in the food sector across Penang, Malaysia. This research aims to…

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Abstract

Purpose

This study investigated the linkage between customers’ acceptance (CA) level and smart service competencies in the food sector across Penang, Malaysia. This research aims to develop a vision of how smart technology may transform the business model in hospitality industry to create value.

Design/methodology/approach

In this study, the level of CA of the smart restaurant is proposed as the dependent variable, while the perceived security (PS), perceived ease of use (PEOU) and perceived enjoyment (PE) are proposed as independent variables (IVs). The quantitative approach and simple random sampling method were adopted in this study. Data were collected from 150 respondents by distributing 225 survey questionnaires to restaurant customers across Penang, Malaysia. The data were analysed by the reliability test, factor analysis and multiple regression analysis using SPSS 23.0 software

Findings

The study outcomes indicated that PE and PEOU emerged as the most significant predictors for CA of smart services in restuarants in Penang. The smart services provide customers to experience enjoyable dining services with accurate and user-friendly service delivery.

Originality/value

This study may serve as a guideline for food and beverage (F&B) business owners and restaurant operators with an industrial standard to adopt smart services in restaurants and their progression to develop the intention to use such a novel technology. This research is one of the few attempts that have looked into the influences of hedonic, comfortable and security value on customers’ acceptance level of smart restaurant services.

Details

Arab Gulf Journal of Scientific Research, vol. 40 no. 3
Type: Research Article
ISSN: 1985-9899

Keywords

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

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Only Open Access

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