Cited by 29Technology Adoption and User BehaviourAI in Service InteractionsHealth, Technology, Consumer Behavior

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

Open access
Seo, Kyung Hwa·2020·Sustainability

Abstract

This study presents fundamental data on the technology acceptance of kiosks in QSR (Quick Service Restaurants) and the marketing plans for efficient management performance. In this paper, the combined concept model was established through the acceptance literature, and an expanded UTAUT2 (Unified Theory of Acceptance and Use of Technology) model was then presented by empirical analysis. This study was evaluated by 303 customers with experience using QSR kiosks. The results show that the seven factors suggested by the UTAUT2 and trust have a positive direct and indirect effect on behavioral intention. In addition, this study confirmed the significant influence relationship between the variables in UTAUT2. It was also found that facilitating conditions and price value have a significant positive effect on trust. Lastly, trust has a significant positive effect on performance expectancy and behavioral intentions. As a result, this research demonstrates an extended and integrated UTAUT2 by verifying the relationship between basic UTAUT2 and trust. The limitations of this study and recommendations for future research are also discussed.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/su12218790

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Appropriate use of kiosk-based service technology is associated with greater perceived flexibility and trust among quick-service restaurant customers.

    “Seo (2020) similarly found that the appropriate use of kiosk -based service technology was associated with greater perceived flexibility and trust among quick-service restaurant customers.”

    From Restaurant Service Quality in Relation to Customer Satisfaction (2026) · cites this paper as Seo, 2020

    The Discussion of Results (section 5.1; page unavailable) reports that conditions facilitating kiosk use have a significant positive effect on quick-service restaurant customers’ trust. It does not report greater perceived flexibility among customers or test whether ‘appropriate use’ increases both flexibility and trust; flexibility appears in the title as workplace flexibility. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • The comparatively low technology score reflects an uneven rollout of digital touchpoints rather than a low customer priority.

    “Seo (2020) similarly found that appropriately implemented technology adoption strengthens customers' sense of convenience and trust, which together with the elevated variability observed here suggests that the comparatively low technology score reflects an uneven rollout of digital touchpoints rather than a low customer priority.”

    From Restaurant Service Quality in Relation to Customer Satisfaction (2026) · cites this paper as Seo (2020)

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 56

  1. Swimberghe, 2014, Drivers of customer relationships in quick-service restaurants: The role of corporate social responsibility, Cornell Hosp. Q., 55, 354, 10.1177/1938965513519008 · DOI
  2. Kaushik, 2015, Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents, Tour. Manag. Perspect., 16, 278
  3. Kim, 2013, Factors influencing customer acceptance of kiosks at quick service restaurants, J. Hosp. Tour. Technol., 4, 40
  4. Baba, 2020, Self-ordering kiosk usage and post-purchase behaviour in quick service restaurant, J. Tour. Hosp. Culin. Arts, 12, 360
  5. Harrington, 2013, QSR choice: Key restaurant attributes and the roles of gender, age and dining frequency, J. Qual. Assur. Hosp. Tour., 14, 81, 10.1080/1528008X.2013.749380 · DOI
  6. Bitner, 2000, Technology infusion in service encounters, J. Acad. Mark. Sci., 28, 138, 10.1177/0092070300281013 · DOI
  7. Kimes, 2008, The role of technology in restaurant revenue management, Cornell Hosp. Q., 49, 297, 10.1177/1938965508322768 · DOI
  8. Venkatesh, 2003, User acceptance of information technology: Toward a unified view MIS quarterly, Manag. Inf. Syst., 27, 425, 10.2307/30036540 · DOI · Paper page
  9. Venkatesh, 2012, Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology, MIS Q., 36, 157, 10.2307/41410412 · DOI · Paper page
  10. Khalizadeh, 2017, Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry, Comput. Hum. Behav., 70, 460, 10.1016/j.chb.2017.01.001 · DOI
  11. Okumus, 2018, Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants, Int. J. Hosp. Manag., 72, 67, 10.1016/j.ijhm.2018.01.001 · DOI
  12. Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., and Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. Sustainability, 11. · DOI
  13. Han, 2020, Impacts of menu information quality and nutrition information quality on technology acceptance characteristics and behaviors toward fast food restaurants’ kiosk, Nutr. Res. Pract., 14, 167, 10.4162/nrp.2020.14.2.167 · DOI
  14. Dixon, 2007, Customer preference for restaurant technology innovations, Corenll Hosp. Rep., 9, 6
  15. Faullant, 2008, Consumer acceptance of internet banking: The influence of internet trust, Int. J. Bank Mark., 26, 483, 10.1108/02652320810913855 · DOI · Paper page
  16. Belanche, 2012, Integrating trust and personal values into the Technology Acceptance Model: The case of e-government services adoption Integración de la confianza y los valores personales en el Modelo de Adoción Tecnológica: El caso de la adopción de la administración electrónica, Cuad. Econ. Dir. Empresa., 15, 192
  17. Pavlou, 2003, Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, Int. J. Electron. Commer., 7, 69
  18. Baabdullah, 2014, Adopting an extended UTAUT2 to predict consumer adoption of M-technologies In Saudi Arabia, UK Acad. Inf. Syst. Conf. Proc., 5, 1
  19. Slade, 2015, Modeling consumers’ adoption intentions of remote mobile payments in the United Kingdom: Extending UTAUT with innovativeness, risk, and trust, Psychol. Mark., 32, 860, 10.1002/mar.20823 · DOI · Paper page
  20. Singh, 2017, How long tail and trust affect online shopping behavior: An extension to UTAUT2 framework, Pac. Asia J. Assoc. Inf. Syst., 9, 1
  21. Ponte, 2015, Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents, Tour. Manag., 47, 286, 10.1016/j.tourman.2014.10.009 · DOI · Paper page
  22. Lee, 2013, Effects of trust and perceived risk on user acceptance of a new technology service, Soc. Behav. Personal., 41, 587, 10.2224/sbp.2013.41.4.587 · DOI
  23. Chen, 2012, The influence of perceived value and trust on online buying intention, J. Comput., 7, 1655, 10.4304/jcp.7.7.1655-1662 · DOI
  24. McKnight, 2002, Developing and validating trust measures for e-commerce: An integrative typology, Inf. Syst. Res., 13, 334, 10.1287/isre.13.3.334.81 · DOI · Paper page
  25. Cheng, D., Liu, G., Qian, C., and Song, Y.F. (2009, January 12–15). Customer Acceptance of Internet Banking: Integrating Trust and Quality with UTAUT Model. Proceedings of the IEEE International Conference on Service Operations and Logistics, and Informatics, Beijing, China.
  26. Baabdullah, 2018, Consumer adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The role of social influence, hedonic motivation and trust, Technol. Soc., 53, 91, 10.1016/j.techsoc.2018.01.004 · DOI
  27. Alalwan, 2017, Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust, Int. J. Inf. Manag., 37, 99, 10.1016/j.ijinfomgt.2017.01.002 · DOI
  28. Alalwan, 2018, Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk, J. Retail. Consum. Serv., 40, 125, 10.1016/j.jretconser.2017.08.026 · DOI · Paper page
  29. Alalwan, 2020, Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse, Int. J. Inf. Manag., 50, 28, 10.1016/j.ijinfomgt.2019.04.008 · DOI
  30. Herrero, 2017, Explaining the adoption of social networks sites for sharing user-generated content: A revision of the UTAUT2, Comput. Hum. Behav., 71, 209, 10.1016/j.chb.2017.02.007 · DOI
  31. Chaouali, 2016, The interplay of counter-conformity motivation, social influence, and trust in customers’ intention to adopt Internet banking services: The case of an emerging country, J. Retail. Consum. Serv., 28, 209, 10.1016/j.jretconser.2015.10.007 · DOI
  32. Lee, S.W., Sung, H.J., and Jeon, H.M. (2019). Determinants of continuous intention on food delivary apps: Extending UTAUT2 with information quality. Sustainability, 11. · DOI
  33. Bouwman, 2014, Revising TAM for hedonic location-based social networks: The influence of TAM, perceived enjoyment, innovativeness and extraversion, Int. J. Web Based Commun., 10, 188, 10.1504/IJWBC.2014.060355 · DOI
  34. Oliveira, 2014, Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM, Int. J. Inf. Manag., 34, 689, 10.1016/j.ijinfomgt.2014.06.004 · DOI · Paper page
  35. Brown, 2005, Model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle, MIS Q., 29, 399, 10.2307/25148690 · DOI
  36. Kulviewat, 2007, Toward a unified theory of consumer acceptance technology, Psychol. Mark., 24, 1059, 10.1002/mar.20196 · DOI
  37. Alalwan, 2015, Consumer adoption of Internet banking in Jordan: Examining the role of hedonic motivation, habit, self-efficacy and trust, J. Financ. Serv. Mark., 20, 145, 10.1057/fsm.2015.5 · DOI
  38. Shaw, 2019, The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value, Int. J. Inf. Manag., 45, 44, 10.1016/j.ijinfomgt.2018.10.024 · DOI
  39. Dodds, 1991, Effects of price, brand, and store information on buyer’s product evaluations, J. Mark. Res., 26, 307
  40. Singh, 2017, Understanding Jordanian Consumers’ online purchase intentions: Integrating trust to the UTAUT2 framework, Int. J. Appl. Eng. Res., 12, 10258
  41. Basak, 2015, Examining the factors affecting PDA acceptance among physicians: An extended technology acceptance model, J. Healthc. Eng., 6, 399, 10.1260/2040-2295.6.3.399 · DOI
  42. Featherman, 2010, Reducing online privacy risk to facilitate e-service adoption: The influence of perceived ease of use and corporate credibility, J. Serv. Mark., 24, 219, 10.1108/08876041011040622 · DOI
  43. Kim, 2014, Travelers’ behavioral intention toward hotel self-service kiosks usage, Int. J. Contemp. Hosp. Manag., 26, 225, 10.1108/IJCHM-09-2012-0165 · DOI
  44. Teo, 2011, An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modelling approach, Comput. Educ., 57, 1645, 10.1016/j.compedu.2011.03.002 · DOI
  45. Tamilmani, 2019, The battle of brain vs. heart: A literature review and meta-analysis of “hedonic motivation” use in UTAUT2, Int. J. Inf. Manag., 46, 222, 10.1016/j.ijinfomgt.2019.01.008 · DOI
  46. Gefen, 2003, Trust and TAM in online shopping: An integrated model, MIS Q., 27, 51, 10.2307/30036519 · DOI · Paper page
  47. Kumar, 2019, Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students, Educ. Inf. Technol., 24, 1793, 10.1007/s10639-018-09858-z · DOI
  48. Sharma, 2020, Consumer perceived value, involvement, trust, susceptibility to interpersonal influence, and intention to participate in online group buying, J. Retail. Consum. Serv., 52, 1, 10.1016/j.jretconser.2019.101946 · DOI
  49. Chinomona, 2013, The impact of product quality on perceived value, trust and students’ intention to purchase electronic gadgets, Mediterr. J. Soc. Sci., 4, 463
  50. Foon, 2011, Internet banking adoption in Kuala Lumpur: An application of UTAUT model, Int. J. Bus. Manag., 6, 161
  51. Zhou, 2010, Integrating TTF and UTAUT to explain mobilebanking user adoption, Comput. Hum. Behav., 26, 760, 10.1016/j.chb.2010.01.013 · DOI · Paper page
  52. Hair, J., Black, W.C., Babin, B.J., and Anderson, R.E. (2010). Multivariate Data Analysis, Pearson Education International. [7th ed.].
  53. Bagozzi, 1988, On the evaluation of structural equation models, J. Acad. Mark. Sci., 16, 74, 10.1007/BF02723327 · DOI · Paper page
  54. Formell, 1981, Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res., 18, 39, 10.1177/002224378101800104 · DOI · Paper page
  55. Raman, 2013, Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 model, Int. Educ. Stud., 6, 157, 10.5539/ies.v6n7p157 · DOI
  56. Gefen, 2000, E-commerce: The role of familiarity and trust, Omega, 28, 725, 10.1016/S0305-0483(00)00021-9 · DOI · Paper page

Cited by

Sorted by citations

Authors
Seo, K. H.
Affiliations
Ulsan College (KR)
Corresponding author
Seo, Kyung Hwa
Venue
Sustainability
Publisher
MDPI AG
Published
2020-10-22
Volume
12
Issue
21
Pages
8790
ISSN
2071-1050 (ISSN-L)
OpenAlex
W3093555342
Cited by
29
References
7
Citations by year
2026: 5 · 2025: 6 · 2024: 6 · 2023: 5 · 2022: 5 · 2021: 2
FWCI
2.98
Type
journal article
Language
en
Open access
Locations
  • Sustainability (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
fast food restaurants, technology acceptance, UTAUT2, trust, behavioral intention, performance expectancy, facilitating conditions, price value, work flexibility

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review