AN ANALYSIS OF FACTORS INFLUENCING CUSTOMERS’ ACCEPTANCE OF SMART RESTAURANTS IN JAKARTA, INDONESIA.

Authors

  • Daniel Yuwono a:1:{s:5:"en_US";s:83:"Program Doktoral Ilmu Ekonomi, Fakultas Ekonomi dan Bisnis, Universitas Trisakti. ";}
  • Sophan Supandi
  • Sarfilianty Anggiani

DOI:

https://doi.org/10.20527/jwmthemanagementinsightjournal.v12i2.286

Keywords:

smart service, technology accepted model (TAM), smart restaurant, perceived of price

Abstract

Technology is becoming an essential element of business operations, and the restaurant industry is no exception. With the support of technology, smart restaurants have emerged in the food and beverage industry. This study investigates the linkage between customers’ acceptance (CA) level and smart service competencies in the Food and Beverage sector across Jakarta, as part of the technology acceptance model (TAM). The study applies a quantitative approach and convenience sampling technique to draw the samples. The data were gathered from 117 respondents and structural equation modeling was used to analyze data.  Smart PLS (Partial Least Square) was used for the tool analysis. The results of this study indicate that the CA of smart restaurants was influenced by perceived of enjoyment (PE), perceived ease of use (PEOU), and perceived of price (PV). However, perceived of security (PS) does not relate to CA.

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References

Abhari, S., Jalali, A., & Jaafar, M. (2022). Determinants influencing customers’ acceptance of smart restaurants in Penang, Malaysia. Arab Gulf Journal of Scientific Research, 40(3), 264–279. https://doi.org/10.1108/AGJSR-06-2022-0081

Aguilar, E., Remeseiro, B., Bolaños, M., & Radeva, P. (2017). Grab, Pay and Eat: Semantic Food Detection for Smart Restaurants. http://arxiv.org/abs/1711.05128

Bapat, D., & Khandelwal, R. (2023). Antecedents and consequences of consumer hope for digital payment apps services. Journal of Services Marketing, 37(1), 110–127. https://doi.org/10.1108/JSM-12-2021-0456

Ivkov, M., Blešić, I., Simat, K., Demirović, D., Božić, S., Stefanović, V., Professor, A., Simat student, K., Demirović, D. M., & Professor, F. (2016). INNOVATIONS IN THE RESTAURANT INDUSTRY-AN EXPLORATORY STUDY 11186). In INNOVATIONS IN THE RESTAURANT INDUSTRY-AN EXPLORATORY STUDY Economics of Agriculture (Vol. 63).

Kabadayi, S., Ali, F., Choi, H., Joosten, H., & Lu, C. (2019). Smart service experience in hospitality and tourism services: A conceptualization and future research agenda. Journal of Service Management, 30(3), 326–348. https://doi.org/10.1108/JOSM-11-2018-0377

Khatri, I. (2019). Information Technology in Tourism & Hospitality Industry: A Review of Ten Years’ Publications. Journal of Tourism & Hospitality Educa On, 9, 74–87.

Lai, P. C. (2017). Security as an Extension to TAM Model: Consumers’ Intention to Use a Single Platform E-Payment. Asia-Pacific Journal of Management Research and Innovation, 13(3–4), 110–119. https://doi.org/10.1177/2319510x18776405

Neuhofer, B., Buhalis, D., & Ladkin, A. (2015). Smart technologies for personalized experiences: a case study in the hospitality domain. Electronic Markets, 25(3), 243–254. https://doi.org/10.1007/s12525-015-0182-1

Stewart, H., & Jürjens, J. (2018). Data security and consumer trust in FinTech innovation in Germany. Information and Computer Security, 26(1), 109–128. https://doi.org/10.1108/ICS-06-2017-0039

Trang, S., Mandrella, M., Marrone, M., & Kolbe, L. M. (2022). Co-creating business value through IT-business operational alignment in inter-organisational relationships: empirical evidence from regional networks. European Journal of Information Systems, 31(2). https://doi.org/10.1080/0960085X.2020.1869914

Umap, S., Surode, S., Kshirsagar, P., Binekar, M., & Nagpal, N. (2018). Smart Menu Ordering System in Restaurant. 7(4), 207–212. www.ijsrst.com

Venkatesh, V., Walton, S. M., & Thong, J. Y. L. (n.d.). Quarterly Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1. http://about.jstor.org/terms

Yang, H., Lee, H., & Zo, H. (2017). User acceptance of smart home services: An extension of the theory of planned behavior. Industrial Management and Data Systems, 117(1), 68–89. https://doi.org/10.1108/IMDS-01-2016-0017

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Published

2024-06-27

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