Examining the Antecedents of Continuous Usage Intention for Smart Self-Service Automated Kiosks in Bangkok

Authors

  • Kom Campiranon College of Innovation, Thammasat University, Thailand
  • Anderson Ngelambong Faculty of Hotel and Tourism Management, Universiti Teknologi MARA Cawangan Pulau Pinang, Malaysia
  • Dahlan Abdullah Faculty of Hotel and Tourism Management Universiti Teknologi MARA Cawangan Pulau Pinang, Malaysia

DOI:

https://doi.org/10.70730/tureview.v29i1.241255

Keywords:

Self-Service Technology, Self-Service Kiosk, Fast-Food Restaurant, Innovativeness

Abstract

The implementation of self-service automation technology is acknowledged as an essential strategy to enhance service quality and profitability in the fast-food industry. This study, informed by Cognitive Appraisal Theory, examines the factors influencing the continuing intention to use smart self-service automated kiosks among Thai young adults. Based on Partial Least Squares-Structural Equation Modeling, the study found substantial empirical evidence linking perceived responsiveness, customization, convenience, and innovativeness with attitudes toward smart self-service technologies, which then affect continuous usage intentions. Interestingly, perceived functionality, interface design, and payment security did not significantly influence attitudes toward smart self-service technologies. The current study enhances both theoretical and practical comprehension of the elements influencing prolonged technology utilization in the digital service domain. Theoretically, the findings highlight the essential importance of smart self-service technology (SST) features in maintaining user engagement with smart kiosks. This study offers significant implications for fast-food companies, highlighting the necessity to improve customer sentiment through dependable and intuitive kiosk interfaces. Subsequent study ought to investigate these links within diverse demographic contexts and employ longitudinal methodologies to track the progression of user behaviors.

Author Biography

Anderson Ngelambong, Faculty of Hotel and Tourism Management, Universiti Teknologi MARA Cawangan Pulau Pinang, Malaysia

He is the corresponding author of this paper.

References

Albert, D., Aschenbrenner, K. M., & Schmalhofer, F. (1989). Cognitive Choice Processes and the Attitude-Behavior Relation. In Springer Series in Social Psychology (pp. 61-99). https://doi.org/10.1007/978-1-4612-3504-0_3

Baba, N., Hanafiah, M. H., Shahril, A. M., & Zulkifly, M. I. (2023). Investigating customer acceptance, usage, trust, and perceived safety risk of self-ordering kiosk technology in Malaysian quick-service restaurants during COVID-19 pandemic. Journal of Hospitality and Tourism Technology, 14(3), 309-329. https://doi.org/10.1108/jhtt-08-2021-0226

Bandoophanit, T., & Pumprasert, S. (2022). The paradoxes of just-in-time system: an abductive analysis of a public food manufacturing and exporting company in Thailand. Management Research Review, 45(8), 1019-1043. https://doi.org/10.1108/mrr-04-2021-0262

Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588-606. https://doi.org/10.1037/0033-2909.88.3.588

Bryman, A. (2016). Social research methods. Oxford University Press.

Cheung, J. T. H., Lok, J., Gietel-Basten, S., & Koh, K. (2021). The food environments of fruit and

vegetable consumption in East and Southeast Asia: a systematic review. Nutrients, 13(1), 148. https://doi.org/10.3390/nu13010148

Chongvilaivan, A. (2020). Openness and inclusive growth in South-East Asia. In ANU Press eBooks (pp. 87-102). https://doi.org/10.22459/aigap.2020.05

Du, X., & Wang, H. W. a. M. (2018). McDonald’s performance and brand design in Chinese market. Proceedings of the 2nd International Conference on e-Education, e-Business and Information Management (EEIM 2018), (pp. 159-164) https://doi.org/10.23977/eeim.2018.029

Çon, M. E., & Bennett, R. (2024). Perspectives of young adults in the United Kingdom on fast food. Ziraat Mühendisliği, 380, 36-46. https://doi.org/10.33724/zm.1496351

Fan, J., Shao, M., Li, Y., & Huang, X. (2018). Understanding users’ attitude toward mobile paymentuse. Industrial Management & Data Systems, 118(3), 524-540. https://doi.org/10.1108/imds-06-2017-0268

Fernando, E., Surjandy, S., Meyliana, M., Wijadja, H. A., Hidayat, D., Kusumaningtyas, A. W., & Heryatno, R. (2020). Factors influencing the intention to use technology services to implement Self-Service technology Case study: Situation Pandemic COVID-19. Advances in Science Technology and Engineering Systems Journal, 5(5), 342-347. https://doi.org/10.25046/aj050542

Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015-1033. https://doi.org/10.1108/jeim-10-2018-0237

Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: a comparison of four procedures. Internet Research, 29(3), 430-447. https://doi.org/10.1108/intr-12-2017-0515

Furuzawa, S., & Kiminami, L. (2017). Changes in the international specialization of food manufacturing industry in East Asia. Asia-Pacific Journal of Regional Science, 1(2), 359-378. https://doi.org/10.1007/s41685-017-0035-3

Ghazali, H., & Roslan, N. (2021). Why should I stay? Prediction on factors influence employee intention to stay in fast food restaurants in Malaysia. International Journal of Academic Research in Business and Social Sciences, 11(10). https://doi.org/10.6007/ijarbss/

v11-i10/10906

Grand View Research (2025). Fast Food & Quick Service Restaurant Market Summary. Retrieved September 10, 2025, from https://www.grandviewresearch.com/industry-analysis/fastfood-quick-service-restaurants-market

Gustafson, C. M., Cimiotti, J. P., Vong, G., Hertzberg, V., & Song, M. (2025). Age Classifications of Young Adults with Chronic Illness: A scoping review. Nursing Forum, 2025(1). https://doi.org/10.1155/nuf/5592882

Habib, A., Irfan, M., & Shahzad, M. (2022). Modeling the enablers of online consumer engagement and platform preference in online food delivery platforms during COVID-19. Future Business Journal, 8(1). https://doi.org/10.1186/s43093-022-00119-7

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) using R. In Classroom companion:business. https://doi.org/10.1007/978-3-030-80519-7

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). In DigitalCommons - Kennesaw State University (Kennesaw State University). https://digitalcommons.kennesaw.edu/facbooks2014/39

Han, J., Moon, H., Oh, Y., Chang, J. Y., & Ham, S. (2020). Impacts of menu information quality and nutrition information quality on technology acceptance characteristics and behaviors toward fast food restaurants’ kiosk. Nutrition Research and Practice, 14(2), 167. https://doi.org/10.4162/nrp.2020.14.2.167

Haque, R. U., Khan, R. H., Shihavuddin, A. S. M., Syeed, M. M. M., & Uddin, M. F. (2022). Lightweight and parameter-optimized real-time food calorie estimation from images using CNN-Based approach. Applied Sciences, 12(19), 9733. https://doi.org/10.3390/app12199733

Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116(1), 2-20. https://doi.org/10.1108/imds-09-2015-0382

Henseler, J., Ringle, C. M., & Sarstedt, M. (2014). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8

Herzberg, F. (2015). Motivation-Hygiene Theory. In Organizational Behavior 1 (pp. 61-74). Routledge

Innerhofer, J., Nasta, L., & Zehrer, A. (2022). Antecedents of labor shortage in the rural hospitality industry: a comparative study of employees and employers. Journal of Hospitality and Tourism Insights, 7(1), 28-55. https://doi.org/10.1108/jhti-04-2022-0125

Jain, N. R. K., Liu-Lastres, B., & Wen, H. (2021). Does robotic service improve restaurant consumer experiences? An application of the value-co-creation framework. Journal of Foodservice Business Research, 26(1), 78-96. https://doi.org/10.1080/15378020.2021.1991682

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

Kaushik, A. K., & Rahman, Z. (2015). An alternative model of self-service retail technology adoption. Journal of Services Marketing, 29(5), 406-420. https://doi.org/10.1108/jsm-08-2014-0276

Keawchuer, S., Piriyodom, A., & Ruangsan, N. (2022). Content Marketing Factors For Infographic Design Impacting Food Delivery Service Users In Bangkok. Journal of Pharmaceutical Negative Results, 13(9), 3002-3011. https://doi.org/10.47750/pnr.2022.13.S09.373

Nasser Ali M, & Shah, K. A. M. (2022). Factors influencing consumer’s intention to use self service technology in retail. Global Business and Management Research: An International Journal, 14(3), 1044-1052.

Kim, M., & Qu, H. (2013). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225-245. https://doi.org/10.1108/ijchm-09-2012-0165

Kincaid, C. S., & Baloglu, S. (2005). An exploratory study on the impact of Self-Service Technology on restaurant operations. Journal of Foodservice Business Research, 8(3), 55-65. https://doi.org/10.1300/j369v08n03_05

King, C., & Du, J. (2022). Profiting from growth: Trade, investment and the ASEAN-China technology gap. Applied Economics Letters, 30(13), 1763-1771. https://doi.org/10.1080/13504851.2022.2082365

Kim, M., Kim, Y., & Lee, G. (2023). Effect of situational factors (control, convenience, time pressure, and order complexity) on customers’ self-service technology choices. Journal of Hospitality Marketing & Management, 32(5), 649-669. https://doi.org/10.1080/19368623.2023.2195398

Kock, F., Berbekova, A., & Assaf, A. G. (2021). Understanding and managing the threat of common method bias: Detection, prevention and control. Tourism Management, 86, 104330. https://doi.org/10.1016/j.tourman.2021.104330

Kock, N. (2015). Common method bias in PLS-SEM. International Journal of e-Collaboration, 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101

Langove, N., Masood, K., & Iqbal, A. (2022). Turnover intention: A case of employee working in the fast food industry of Quetta. Academic Journal of Social Sciences (AJSS ), 6(3), 089-103. https://doi.org/10.54692/ajss.2022.06031814

Lin, J. C., & Chang, H. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality, 21(4), 424-444. https://doi.org/10.1108/09604521111146289

Lu, S., & Ahn, J. (2023). An integrated model for understanding the role of self-service technology attributes and customers’ demographic characteristics in the restaurant service context. Journal of Foodservice Business Research, 28(5), 1063-1086. https://doi.org/10.1080/15378020.2023.2279002

Liu, Y., Li, C., McCabe, S., & Xu, H. (2019). How small things affect the big picture? International Journal of Contemporary Hospitality Management, 31(7), 2994-3014. https://doi.org/10.1108/ijchm-10-2017-0655

Malhotra, N. K., & Dash, S. (2016). Marketing research: An applied orientation (7th ed.). Pearson.

Mason, M. C., Zamparo, G., & Pauluzzo, R. (2023). Amidst technology, environment and human touch. Understanding elderly customers in the bank retail sector. International Journal of Bank Marketing, 41(3), 572-600. https://doi.org/10.1108/ijbm-06-2022-0256

Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), 50-64. https://doi.org/10.1509/jmkg.64.3.50.18024

Mondor Intelligence (2025). Thailand Foodservice market size. Retrieved September 10, 2025, from https://www.mordorintelligence.com/industry-reports/thailand-foodservice-market

Okumus, B., Ozturk, A. B., & Bilgihan, A. (2021). Generation Y’s dining out behavior. International Hospitality Review, 35(1), 41-56. https://doi.org/10.1108/ihr-07-2020-0023

Park, S., Lehto, X., & Lehto, M. (2020). Self-service technology kiosk design for restaurants: An QFD application. International Journal of Hospitality Management, 92, 102757. https://doi.org/10.1016/j.ijhm.2020.102757

Pingali, P. (2006). Westernization of Asian diets and the transformation of food systems: Implications for research and policy. Food Policy, 32(3), 281-298. https://doi.org/10.1016/j.foodpol.2006.08.001

Prayogo, A., Diza, T., Prasetyaningtyas, S. W., & Maharani, A. (2020). A qualitative study exploring the effects of job analysis and organizational culture toward job satisfaction in a coffee shop. Open Journal of Business and Management, 08(06), 2687-2695. https://doi.org/10.4236/ojbm.2020.86166

Ringle, C. M., Wende, S., & Becker, J.M. (2024). SmartPLS. Retrieved September 10, 2025, from https://www.smartpls.com

Ro, Y., & Kwon, B. (2024). Does user burden matter?: Age Differences in user Behavior of Self- Service Technology. International Journal of Human-Computer Interaction, 41(10), 6047-6066. https://doi.org/10.1080/10447318.2024.2375085

Sahi, G. K., & Gupta, S. (2013). Predicting customers’ behavioral intentions toward ATM services.

Journal of Indian Business Research, 5(4), 251-270. https://doi.org/10.1108/jibr-10-2012-0085

Samengon, H., Ishak, F. a. C., Karim, M. S. A., Ghazali, H., & Arshad, M. M. (2023). Investigating Motivations for Customers to use Interactive Self-service Technology in Fast-food Restaurant. International Journal of Academic Research in Business and Social Sciences, 13(2). https://doi.org/10.6007/ijarbss/v13-i2/16200

Santiago, J., Borges-Tiago, M. T., & Tiago, F. (2023). Embracing RAISA in restaurants: Exploring customer attitudes toward robot adoption. Technological Forecasting and Social Change, 199, 123047. https://doi.org/10.1016/j.techfore.2023.123047

Saravanakumar, S., & Narayanan, M. B. (2018). The Service Automation and Robotics in Hospitality Industry, A Study on Business Implications. International Journal of Mechanical and Production Engineering Research and Development, 8(6), 91-100. https://doi.

org/10.24247/ijmperddec201810

Saunders, M. N. K., Lewis, P., & Thornhill, A. (2019). Research methods for business students. Pearson Higher Ed.

Seo, K. H. (2020). A study on the application of kiosk service as the workplace Flexibility: The Determinants of expanded technology adoption and trust of quick service restaurant customers. Sustainability, 12(21), 8790. https://doi.org/10.3390/su12218790

Shawon, M. S. R., Jahan, E., Rouf, R. R., & Hossain, F. B. (2022). Psychological distress and unhealthy dietary behaviours among adolescents aged 12-15 years in nine South-East Asian countries: a secondary analysis of the Global School-Based Health Survey data.

British Journal of Nutrition, 129(7), 1242-1251. https://doi.org/10.1017/s0007114522002306

Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322-2347. https://doi.org/10.1108/ejm-02-2019-0189

Singh, S., & Sagar, R. (2021). A critical look at online survey or questionnaire-based research studies during COVID-19. Asian Journal of Psychiatry, 65, 102850. https://doi.org/10.1016/j.ajp.2021.102850

Song, H., Yang, H., & Sthapit, E. (2023). Robotic service quality, authenticity, and revisit intention to restaurants in China: extending cognitive appraisal theory. International Journal of Contemporary Hospitality Management, 37(5), 1497-1515. https://doi.org/10.1108/

ijchm-11-2022-1396

Spohrer, R., Larson, M., Maurin, C., Laillou, A., Capanzana, M., & Garrett, G. S. (2013). The growing importance of staple foods and condiments used as ingredients in the food industry and implications for Large-Scale Food Fortification programs in Southeast Asia.

Food and Nutrition Bulletin, 34(2_suppl1), S50-S61. https://doi.org/10.1177/15648265130342s107

Ting, H., Memon, M. A., Thurasamy, R., & Cheah, J. (2025). Snowball sampling: A review and guidelines for survey research. Asian Journal of Business Research, 15(1), 1-15. https://doi.org/10.14707/ajbr.250186

Veas-González, I., Carrión-Bósquez, N. G., Serrano-Malebran, J., Veneros-Alquinta, D., García-Umaña, A., & Campusano-Campusano, M. (2024). Exploring the moderating effect of brand image on the relationship between customer satisfaction and repurchase

intentions in the fast-food industry. British Food Journal, 126(7), 2714-2731. https://doi.org/10.1108/bfj-01-2024-0077

Veeramootoo, N., Nunkoo, R., & Dwivedi, Y. K. (2018). What determines success of an e-government service? Validation of an integrative model of e-filing continuance usage. Government Information Quarterly, 35(2), 161-174. https://doi.org/10.1016/j.giq.2018.03.004

Wang, K. (2017). Food Safety and Contract Edamame: The geopolitics of the vegetable trade in East Asia. Geographical Review, 108(2), 274-295. https://doi.org/10.1111/gere.12254

Weijters, B., Rangarajan, D., Falk, T., & Schillewaert, N. (2007). Determinants and outcomes of customers’ use of Self-Service Technology in a retail setting. Journal of Service Research, 10(1), 3-21. https://doi.org/10.1177/1094670507302990

Windasari, N. A., Kusumawati, N., Larasati, N., & Amelia, R. P. (2022). Digital-only banking experience: Insights from gen Y and gen Z. Journal of Innovation & Knowledge, 7(2), 100170. https://doi.org/10.1016/j.jik.2022.100170

Wong, I. A., Huang, J., & Lin, Z. (2024). Understanding smart service failure: The case of smart restaurants. International Journal of Hospitality Management, 119, 103714. https://doi.org/10.1016/j.ijhm.2024.103714

Wu, C., & Wu, P. (2018). Investigating user continuance intention toward library self-service technology. Library Hi Tech, 37(3), 401-417. https://doi.org/10.1108/lht-02-2018-0025

Xiao, A., Yang, S., & Iqbal, Q. (2018). Factors Affecting Purchase Intentions in Generation Y: An Empirical Evidence from Fast Food Industry in Malaysia. Administrative Sciences, 9(1), 4. https://doi.org/10.3390/admsci9010004

Yang, S., Liu, K., Gai, J., & He, X. (2022). Transformation to industrial artificial intelligence and workers’ mental health: evidence from China. Frontiers in Public Health, 10, 881827. https://doi.org/10.3389/fpubh.2022.881827

Yoon, C. (2023). Technology adoption and jobs: The effects of self-service kiosks in restaurants on labor outcomes. Technology in Society, 74, 102336. https://doi.org/10.1016/j.techsoc.2023.102336

Yum, M. S. (2021). Evaluation of urban interactive kiosks centered on interface ergonomy and user experience. Ergonomi, 4(1), 35-46. https://doi.org/10.33439/ergonomi.871755

Zaitouni, M., & Murphy, K. S. (2023). Self-Service Technologies (SST) in the U.S. Restaurant industry: An evaluation of consumer perceived value, satisfaction, and continuance intentions. Journal of Foodservice Business Research, 28(2), 245-276. https://doi.org/1

1080/15378020.2023.2229582

Zhang, N., Chen, J., Liu, Z., & Zhang, J. (2013). Public Information System Interface Design Research. In Lecture notes in computer science (pp. 247-259). https://doi.org/10.1007/978-3-642-40483-2_17

Shahril, Z., Zulkafly, H. A., Ismail, N. S., & Sharif, N. U. N. M. (2021). Customer satisfaction towards Self-Service Kiosks for Quick Service Restaurants (QSRs) in Klang Valley. International Journal of Academic Research in Business and Social Sciences, 11(13). https://doi.

org/10.6007/ijarbss/v11-i13/8502

Van Donge, J. K., Henley, D., & Lewis, P. (2012). Tracking development in South-East Asia and Sub-Saharan Africa: The primacy of policy. Development Policy Review, 30(s1). https://doi.org/10.1111/j.1467-7679.2012.00563.x

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2026-06-26

How to Cite

Campiranon, K., Ngelambong, A., & Abdullah, D. (2026). Examining the Antecedents of Continuous Usage Intention for Smart Self-Service Automated Kiosks in Bangkok. Thammasat Review, 29(1), 116–149. https://doi.org/10.70730/tureview.v29i1.241255