The Adoption of Restaurant-Based E-Service

Mozeik, Celeste K.; Beldona, Srikanth; Çobanoğlu, Cihan; Poorani, Ali A.

doi:10.1080/15378020903158525

Cited by 21 publications

(21 citation statements)

References 26 publications

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“…Furthermore, it also provides an insight into the customers' needs and wants which may be essential for restaurant operators in order to provide better services to customers. This evidence is in line with Mozeik et al (2009) confirmed that the adoption of e-services in restaurants namely the conventional computing devices and mobile computing devices were driven by perceived usefulness and perceived ease of use. In the light of these findings, several recommendations will be made which may be useful for restaurant operators and other related authorities.…”

Section: Discussionsupporting

confidence: 86%

“…Users will use m-payment systems when they find the system to be useful for their transaction needs or financial issues. Mozeik et al (2009) found and concluded that the adoption of e-services in restaurants namely the conventional computing devices (i.e., desktop and laptop computers) was driven by perceived usefulness. Cooper (1997) identifies "ease of use" as one of the three important characteristics from the customer's perspective for adoption of innovative service.…”

Section: Perceived Usefulnessmentioning

confidence: 99%

“…Cooper (1997) identifies "ease of use" as one of the three important characteristics from the customer's perspective for adoption of innovative service. The adoption of e-services in restaurants such as mobile computing devices (i.e., BlackBerry Smartphones, Palm Pilots) was driven by perceived ease of use confirmed by Mozeik et al (2009).…”

Section: Perceived Usefulnessmentioning

confidence: 99%

See 2 more Smart Citations

Diagnosing TAM Using Factor Analysis

Zahari

Othman

2018

AjBeS

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Factor analysis using Principal Axis Factoring (PAF) extraction method and oblique rotation conducted to confirm the factor structure and unidimensionality of the constructs by extending the Technology Acceptance Model (TAM). This study examines responsiveness towards the actual usage of Malaysia’s “Touch ‘n Go” smart card amongst restaurant customers. Results discovered that two factors extracted from the three core determinants of customer responsiveness, in which dimensions such as awareness, brand Image, attitude and actual usage of the smart card remained due to the significant factor loadings. Replication of this factor analysis through further research is significant to customize the research framework.Keywords: technology acceptance model, responsiveness, smart card, restaurantseISSN 2398-4295 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. http://dx.doi.org/10.21834/ajbes.v3i11.101

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Section: Discussionsupporting

confidence: 86%

Section: Perceived Usefulnessmentioning

confidence: 99%

Section: Perceived Usefulnessmentioning

confidence: 99%

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Diagnosing TAM Using Factor Analysis

Zahari

Othman

2018

AjBeS

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“…These experiences will be improved in the smart restaurant, whereas the understanding of smart restaurant services has progressed along with the evaluation of technological capability (Mozeik, Beldona, Cobanoglu, & Poorani, 2009). On the other word, while there is an increasing amount of using smart technology, the appropriate technology implement in the restaurant can help to increase business revenue.…”

Section: Customers' Acceptance Level Of Smart Restaurantmentioning

confidence: 99%

Customers’ Acceptance Level Of Smart Restaurant Services In Penang

Lim¹,

Jaafar²,

Jalali³

et al. 2019

The European Proceedings of Multidisciplinary Sciences

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Nowadays, the world is changing rapidly, with innovative technology, a new set of challenges need to be considered and addressed. The discussions about using technology in restaurants and food service sector only cover some of the main topics such as information system management and integration, automation, data analytics, and guest-facing technology. However, despite the positive prospects of smart technology in the hospitality industries, they have not been adopted widely in Food and Beverage (F&B) sectors in some Asian or Middle Eastern countries. This study aims to investigate the core motivations for adopting smart restaurant services in developing countries such as Malaysia. The purpose of this study is to explore the relationship between the predictors' variables such as perceived cost, perceived enjoyment, novelty, and customers' acceptance level of smart restaurant services as a dependent variable. A research framework is developed based on the extended Technology Acceptance Model (TAM) and Diffusion of Innovation Theory (DOI). The quantitative research approach was applied to the empirical part of this study to test the conceptual model. Therefore, to achieve this purpose, a survey was conducted in Penang, Malaysia. The data was collected from 150 respondents and analysed by SPSS statistical software. The research results indicate that perceived enjoyment (PE) is the most significant predictor in customers' acceptance of a smart restaurant which is followed by perceived cost (PC). However, Implications of the findings is relevant and helpful to both academia and F&B operators along with future research opportunities with an industrial standard for restaurant entrepreneurs.

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“…The user will tolerate some difficulty in using technology as long as it seems to be useful. However, the implementation is more likely to fail if the user does not find utility from its use (Mozeik et al 2009). Wang et al (2012) found that a customer has a positive attitude toward a self-service technology if it is perceived to be easy to use, controllable, and useful.…”

Section: Utility As Intrinsic Customer Value In Technologiesmentioning

confidence: 99%

Understanding Customer Value in Technology-Enabled Services: A Numerical Taxonomy Based on Usage and Utility

2015

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U se of technologies in service encounters can enhance service delivery and increase customer satisfaction in services.Our research develops a numerical taxonomy that provides a deeper understanding of usage and value of customerfacing technology-based innovations in the U.S. restaurant industry. In this study, utility is a proxy for intrinsic customer value. Usage was estimated by past visits to restaurants and utility was calculated by using a specific type of discrete choice experiment known as Best-Worst (or max-diff) experiment. We offer insights for service strategy technology choices and customer value in service delivery systems research and practice. Furthermore, we advance service science by discussing the inherent management pitfalls of failing to distinguish between technology usage and utility in services.

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The Adoption of Restaurant-Based E-Service

Cited by 21 publications

References 26 publications

Diagnosing TAM Using Factor Analysis

Diagnosing TAM Using Factor Analysis

Customers’ Acceptance Level Of Smart Restaurant Services In Penang

Understanding Customer Value in Technology-Enabled Services: A Numerical Taxonomy Based on Usage and Utility

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