SCIENCE ARTICLE
Factors Affecting the Acceptance of Mobile Technologies in SMEs: Evidence from Top Management Perspectives
 
More details
Hide details
1
business management, İstanbul Beykent University, Turkey
 
2
management information systems, İstanbul Galata University, Turkey
 
These authors had equal contribution to this work
 
 
Submission date: 2025-08-14
 
 
Final revision date: 2025-10-26
 
 
Acceptance date: 2025-11-06
 
 
Online publication date: 2026-01-09
 
 
Publication date: 2026-01-07
 
 
Corresponding author
Hasan Sadık Tatlı   

management information systems, İstanbul Galata University, Adres: Cihangir, Sıraselviler Cd. No:65, 34433 Bey, 34433, BEYOĞLU, Turkey
 
 
Management 2025;(2):487-522
 
KEYWORDS
JEL CLASSIFICATION CODES
O32
O33
L25
 
TOPICS
ABSTRACT
Research background and purpose:
The research aims to determine the factors affecting the adoption and use of mobile technologies by top managers. The research sample consists of top managers in SMEs.

Design/methodology/approach:
Data were obtained from SME managers in Turkey. Within the scope of the research, 204 survey data were collected from top managers in SMEs. SmartPLS 3 were used to analyze the data.

Findings:
It has been determined that factors such as usefulness, social impact, and self-efficacy positively affect the intention to use mobile technologies. In addition, behavioral intention had a significant and strong effect on actual usage. It has been determined that the intention to use mobile technolo-gies has a mediating role in the effect of factors on actual usage for mobile usage, social impact and technology self-efficacy. According to the findings, hedonic and mobile ease of use did not affect the behavioral intention of actual use, either directly or indirectly.

Value added and limitations:
The originality of this research lies in its integrated approach, combining the perspectives of top managers of Turkish SMEs with the UTAUT theoretical framework to explain their behavioral in-tentions toward adopting mobile technologies for business purposes. Therefore, the findings uniquely represent the adoption intentions of SME executives in Turkey.
REFERENCES (135)
1.
Ada, S., & Tatlı, H. S. (2013). Akıllı telefon kullanımını etkileyen faktörler üzerine bir araştırma [A study on the factors affecting smartphone usage]. In Proceedings of the XV. Akademik Bilişim Sempozyumu (Antalya, Turkey). http://ab.org.tr/ab13/bildiri/....
 
2.
Agárdi, I., & Alt, M. A. (2024). Do digital natives use mobile payment differently than digital immigrants? A comparative study between generation X and Z. Electronic Commerce Research, 24(3), 1463-1490. https://doi.org/10.1007/s10660....
 
3.
Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23. https://doi.org/10.1016/j.jret....
 
4.
Aini, Q., Manongga, D., Rahardja, U., Sembiring, I., & Li, Y. M. (2025). Understanding behavioral intention to use of air quality monitoring solutions with emphasis on technology readiness. International Journal of Human–Computer Interaction, 41(8), 5079-5099. https://doi.org/10.1080/104473....
 
5.
Ajzen, I, & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin 82(2), 261-277. https://doi.org/10.1037/h00764....
 
6.
Al-Adwan, A. S., Meet, R. K., Anand, S., Shukla, G. P., Alsharif, R., & Dabbaghia, M. (2025). Understanding continuous use intention of technology among higher education teachers in emerging economy: Evidence from integrated TAM, TPACK, and UTAUT model. Studies in Higher Education, 50(3), 505-524. https://doi.org/10.1080/030750....
 
7.
Alam, S. S., Ahmed, S., Kokash, H. A., Mahmud, M. S., & Sharnali, S. Z. (2024). Utility and hedonic perception-Customers’ intention towards using of QR codes in mobile payment of Generation Y and Generation Z. Electronic Commerce Research and Applications, 65, 101389. https://doi.org/10.1016/j.eler....
 
8.
Al-Azmi, M. T., Retnani, W. E. Y., Putra, J. A., & Afrianto, E. (2024). Analysis of user acceptance factors in kai access mobile application using the unified technology of acceptance and use of technology (UTAUT) method. LOREM: Computational Engineering and Computer Information Systems, 1(1), 36-47.
 
9.
Alderete, M. V. (2017). Mobile broadband: a key enabling technology for entrepreneurship?. Journal of Small Business Management, 55(2), 254-269. https://doi.org/10.1111/jsbm.1....
 
10.
Alhalafi, N., & Veeraraghavan, P. (2023). Exploring the challenges and issues in adopting cybersecurity in Saudi smart cities: Conceptualization of the cybersecurity-based UTAUT model. Smart Cities, 6(3), 1523-1544. https://doi.org/10.3390/smartc....
 
11.
Ali, I., & Warraich, N. F. (2024). Use and acceptance of technology with academic and digital libraries context: A meta-analysis of UTAUT model and future direction. Journal of Librarianship and Information Science, 56(4), 965-977. https://doi.org/10.1177/096100....
 
12.
Ali, R. A., & Arshad, M. R. M. (2016). Understanding intention to use mobile learning: A perspective of the extended unified theory of acceptance and use of technology. International Journal of Advanced and Applied Sciences (IJAAS), 3(7), 81-88. http://dx.doi.org/10.21833/ija....
 
13.
Almahri, F. A. A. J., & Saleh, N. I. M. (2025). Insights into technology acceptance: A concise review of key theories and models. Innovative and Intelligent Digital Technologies; Towards an Increased Efficiency: Volume 2, 797-807. https://doi.org/10.1007/978-3-....
 
14.
Alowayr, A. (2022). Determinants of mobile learning adoption: Extending the unified theory of acceptance and use of technology (UTAUT). The International Journal of Information and Learning Technology, 39(1), 1-12. https://doi.org/10.1108/IJILT-....
 
15.
Al-Rahmi, A. M., Al-Rahmi, W. M., Alturki, U., Aldraiweesh, A., Almutairy, S., & Al-Adwan, A. S. (2022). Acceptance of mobile technologies and M-learning by university students: An empirical investigation in higher education. Education and Information Technologies, 27(6), 7805-7826. https://doi.org/10.1007/s10639....
 
16.
Alshammari, S. H., & Babu, E. (2025). The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT. Scientific Reports, 15(1), 7169. https://doi.org/10.1038/s41598....
 
17.
Alzghoul, A., Khaddam, A. A., Abousweilem, F., Irtaimeh, H. J., & Alshaar, Q. (2024). How business intelligence capability impacts decision-making speed, comprehensiveness, and firm performance. Information Development, 40(2), 220-233. https://doi.org/10.1177/026666....
 
18.
An, S., Eck, T., & Yim, H. (2023). Understanding consumers’ acceptance intention to use mobile food delivery applications through an extended technology acceptance model. Sustainability, 15(1), 832. https://doi.org/10.3390/su1501....
 
19.
Ar. A. A. & İskender H. (2005). Türkiye’de Kobi’ler ve Kobi’lerde planlama, uygulama ve denetim [SMEs in Turkey and planning, implementation and control in SMEs]. Mevzuat Dergisi, 87(5). Aslan, M. (2021). Örgüt yapısının tekrar incelenmesi [Organizational structure revisited]. Business & Management Studies: An International Journal, 9(1), 282–294. https://doi.org/10.15295/bmij.....
 
20.
Balocco, R., Mogre, R., & Toletti, G. (2009). Mobile internet and SMEs: A focus on the adoption. Industrial Management & Data Systems, 109(2), 245-261. https://doi.org/10.1108/026355....
 
21.
Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122-147. https://doi.org/10.1037/0003-0....
 
22.
Basarir-Ozel, B., & Mardikyan, S. (2017). Factors affecting E-commerce adoption: A case of Turkey. The International Journal of Management Science and Information Technology (IJMSIT), (23), 1-11.
 
23.
Çakır, İ. & Kazançoğlu, İ. (2020). Sanal market alışverişi yapma niyetinde genişletilmiş teknoloji kabul modeli bileşenleri ile risk algılarının etkisi [The effect of risk perceptions on the intention to online grocery shopping with extended technology acceptance model components]. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 18, 305–326. https://doi.org/10.18026/cbaya....
 
24.
Carpenter, M. A., Geletkanycz, M. A., & Sanders Gerard, Wm. (2004). Upper echelons research revisited: Antecedents, elements, and consequences of top management team composition. Journal of Management, 30(6), 749-778. https://doi.org/10.1016/j.jm.2....
 
25.
Chahal, J., & Rani, N. (2022). Exploring the acceptance for e-learning among higher education students in India: combining technology acceptance model with external variables. Journal of Computing in Higher Education, 34(3), 844-867. https://doi.org/10.1007/s12528....
 
26.
Chang, S. H. Chou, C. H. & Yang, J. M. (2010). The literature review of technology acceptance model: A study of the bibliometric distributions, PACIS 2010 Proceedings 158, 1635.
 
27.
Chen, J., Wang, T., Fang, Z., & Wang, H. (2023). Research on elderly users’ intentions to accept wearable devices based on the improved UTAUT model. Frontiers in Public Health, 10, 1035398. https://doi.org/10.3389/fpubh.....
 
28.
Chen, K. Chen, J. V. & Yen, D. C. (2011). Dimensions of self-efficacy in the study of smart phone acceptance. Computer Standards and Interfaces, 33(4), 422-431. https://doi.org/10.1016/j.csi.....
 
29.
Chun, H. Lee, H. & Kim, D. (2012). The integrated model of smartphone adoption: Hedonic and utilitarian value perceptions of smartphones among Korean college students. Cyberpsychology, Behavior, and Social Networking, 15(9), 473-479. https://doi.org/10.1089/cyber.....
 
30.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
 
31.
Çolak, H., & Kağnıcıoğlu, C. H. (2018, May 24–25). Identification of prominent criteria in the selection of new generation smartphones: An application in Anadolu University (pp. 442–448). 4th Global Business Research Congress, İstanbul. http://doi.org/10.17261/Pressa....
 
32.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688.
 
33.
Coşkun, B. (2023). KOBİ’lerde modern yönetim tekniklerinin uygulanması: Van Organize Sanayi Bölgesi örneği [Implementation of modern management techniques in SMEs: The case of Van Organized Industrial Zone] [Unpublished master’s thesis]. Bartın University.
 
34.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance. MIS Quarterly, 13(3), 319- 340. https://doi.org/10.2307/249008.
 
35.
Davis, F.D. Bagozzi, R.P. & Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two. Management Science, 35(8), 982- 1001. https://doi.org/10.1287/mnsc.3....
 
36.
Deng, Y., & Liu, H. (2025). To overcome test anxiety in online assessment: unpacking the mediator roles of techno competencies, teacher support, self-efficacy, and autonomy. BMC Psychology, 13(1), 192. https://doi.org/10.1186/s40359....
 
37.
Dinh, C. M., & Park, S. (2024). How to increase consumer intention to use Chatbots? An empirical analysis of hedonic and utilitarian motivations on social presence and the moderating effects of fear across generations. Electronic Commerce Research, 24(4), 2427-2467. https://doi.org/10.1007/s10660....
 
38.
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719-734. https://doi.org/10.1007/s10796....
 
39.
Efendi, B., Ekasari, S., Sani, I., Wakhidah, E. N., & Munizu, M. (2024). Analysis of the influence of behavioral intention, perceived ease of use and perceived usefulness on actual usage of digital wallet customers. JEMSI (Jurnal Ekonomi, Manajemen, dan Akuntansi), 10(1), 209-214. https://doi.org/10.35870/jemsi....
 
40.
Erdoğan, G. (2023). Mobil alışveriş uygulamalarında algılanan faydanın öncülü ve sonuçları [Antecedent and consequences of perceived usefulness in mobile shopping applications]. Gazi İktisat ve İşletme Dergisi, 9(2), 162-177. https://doi.org/10.30855/gjeb.....
 
41.
Eze, S. C., Chinedu-Eze, V. C., Bello, A. O., Inegbedion, H., Nwanji, T., & Asamu, F. (2019). Mobile marketing technology adoption in service SMEs: A multi-perspective framework. Journal of Science and Technology Policy Management, 10(3), 569-596. https://doi.org/10.1108/JSTPM-....
 
42.
Ezeudoka, B. C., & Fan, M. (2024). Determinants of behavioral intentions to use an E-Pharmacy service: Insights from TAM theory and the moderating influence of technological literacy. Research in Social and Administrative Pharmacy, 20(7), 605-617. https://doi.org/10.1016/j.saph....
 
43.
Faqih, K. M. (2022). Factors influencing the behavioral intention to adopt a technological innovation from a developing country context: The case of mobile augmented reality games. Technology in Society, 69, 101958. https://doi.org/10.1016/j.tech....
 
44.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
 
45.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224....
 
46.
Ghose, P., Bhuiyan, M. R. I., Hasan, M. N., Rakib, S. H., & Mani, L. (2025). Mediated and moderating variables between behavioral intentions and actual usages of fintech in the USA and Bangladesh through the extended UTAUT model. International Journal of Innovative Research and Scientific Studies, 8(2), 113-125. https://doi.org/10.53894/ijirs....
 
47.
Giovannini, S., Xu, Y., & Thomas, J. (2015). Luxury fashion consumption and Generation Y consumers: Self, brand consciousness, and consumption motivations. Journal of Fashion Marketing and Management, 19(1), 22-40. https://doi.org/10.1108/JFMM-0....
 
48.
Graham, J. R., Harvey, C. R., & Puri, M. (2015). Capital allocation and delegation of decision-making authority within firms. Journal of Financial Economics, 115(3), 449-470. https://doi.org/10.1016/j.jfin....
 
49.
Grant, C. A., Wallace, L. M., & Spurgeon, P. C. (2013). An exploration of the psychological factors affecting remote e‐worker’s job effectiveness, well‐being and work‐life balance. Employee Relations, 35(5), 527-546. https://doi.org/10.1108/ER-08-....
 
50.
Gu, J. C., Lee, S. C., & Suh, Y. H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616. https://doi.org/10.1016/j.eswa....
 
51.
Gulacti, S. (2020). Finansal teknoloji kullanıcılarını etkileyen faktörlerin teknoloji kabul modeli ile belirlenmesi [Determining the factors affecting financial technology users using technology acceptance model]. (Master’s thesis), Gümüşhane University.
 
52.
Guriting, P., & Oly Ndubisi, N. (2006). Borneo online banking: evaluating customer perceptions and behavioural intention. Management Research News, 29(1/2), 6-15. https://doi.org/10.1108/014091....
 
53.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2017). Multivariate Data Analysis (7th edition). Pearson.
 
54.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage Publications.
 
55.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2019). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.
 
56.
Hambrick, D. C. & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9(2),193-206. https://doi.org/10.2307/258434.
 
57.
Hambrick, D. C. (1995). Fragmentation and the other problems Ceos have with their top management teams. California Management Review, 37(3), 110-127. https://doi.org/10.2307/411658.
 
58.
Hameed, I., Akram, U., Khan, Y., Khan, N. R., & Hameed, I. (2024). Exploring consumer mobile payment innovations: An investigation into the relationship between coping theory factors, individual motivations, social impact and word of mouth. Journal of Retailing and Consumer Services, 77, 103687. https://doi.org/10.1016/j.jret....
 
59.
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The effects of perceived usefulness and perceived ease of use on continuance intention to use e-government. Procedia Economics and Finance, 35, 644-649. https://doi.org/10.1016/S2212-....
 
60.
Han, M. C. (2019). Instant messaging chat bot: your new best friend? In Smart marketing with the internet of things. IGI Global, 164-184.
 
61.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). 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....
 
62.
Hess, T. J., McNab, A. L., & Basoglu, K. A. (2014). Reliability generalization of perceived ease of use, perceived usefulness, and behavioral intentions. MIS Quarterly, 38(1), 1-28.
 
63.
Hossain, M., Hossain, A., & Manik, M. H. (2024). Assessment of Customers’ Satisfaction in Mobile Banking Services: The Mediating Role of Ease of Use. Transnational Business and Management, 2(2), 43-64. https://doi.org/10.33182/tbm.v....
 
64.
Hwang, C., Jin, B., Song, L., & Feng, J. (2024). Factors influencing older adults’ intention to use virtual fitting room technology during the COVID-19 pandemic. Journal of Fashion Marketing and Management: An International Journal, 28(3), 444-459. https://doi.org/10.1108/JFMM-1....
 
65.
Jha, A. & Saha, D. (2022). Mobile broadband for inclusive connectivity: What deters the high-capacity deployment of 4G-LTE innovation in India?. Inf Syst Front 24, 1305–1329. https://doi.org/10.1007/s10796....
 
66.
Joa, C. Y., & Magsamen-Conrad, K. (2022). Social influence and UTAUT in predicting digital immigrants’ technology use. Behaviour & Information Technology, 41(8), 1620-1638. https://doi.org/10.1080/014492....
 
67.
Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212.https://doi.org/10.1016/j.tech....
 
68.
Kim, B., & Han, I. (2009). What drives the adoption of mobile data services? An approach from a value perspective. Journal of Information Technology, 24, 35-45. https://doi.org/10.1057/jit.20....
 
69.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (IJEC), 11(4), 1-10.
 
70.
Lamba, M. (2014). Karar vermeyi etkileyen yapısal faktörler bakımından yönetim ve organizasyon teorilerinin incelenmesi [Study of the management and organization theories in terms of the structural factors affecting decision-making], KMÜ Sosyal ve Ekonomik Araştırmalar Dergisi 16(27), 8-18.
 
71.
Lau, M. M., Lam, A. Y., & Cheung, R. (2016). Examining the factors influencing purchase intention of smartphones in Hong Kong. Contemporary Management Research, 12(2), 213-224, https://doi.org/10.7903/cmr.13....
 
72.
Lew, S. Tan, G. W. H. Loh, X. M. Hew, J. J. & Ooi, K. B. (2020). The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model. Technology in Society, 101430. https://doi.org/10.1016/j.tech....
 
73.
Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. https://doi.org/10.1108/106622....
 
74.
Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies, 26(6), 6629-6649. https://doi.org/10.1007/s10639....
 
75.
Marikyan, D. & Papagiannidis, S. (2023). Unified theory of acceptance and use of technology: A review. TheoryHub Book.
 
76.
Menon, D., & Shilpa, K. (2023). Chatting with ChatGPT: Analyzing the factors influencing users’ intention to use the Open AI’s ChatGPT using the UTAUT model. Heliyon, 9(11). https://doi.org/10.1016/j.heli....
 
77.
Muhanguzi, S., & Kyobe, M. (2014). Aligning work practices, mobile technology and strategy for performance improvement: the case of SMEs in Uganda. The Electronic Journal of Information Systems in Developing Countries, 60(1), 1-22. https://doi.org/10.1002/j.1681....
 
78.
Natalia, O., & Tesniwati, R. (2021). The effect of perception of trust, perception of ease of use, perception of benefits, perception of risk and perception of service quality on interest in using mobile banking bank independent in Bekasi City. International Journal of Science, Technology & Management, 2(5), 1722-1730. https://doi.org/10.46729/ijstm....
 
79.
Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8-22. https://doi.org/10.1016/j.jret....
 
80.
Nayati Utami, H., Siti Astuti, E., Maulani Ramadhan, H., Trialih, R., & Alief Aprilian, Y. (2019). The interests of small-and medium-sized enterprises (SMEs) actor in using mobile commerce in effort to expand business network. Journal of Science and Technology Policy Management, 10(3), 493-508. https://doi.org/10.1108/JSTPM-....
 
81.
Nikolopoulou, K.; Gialamas, V.; Lavidas, K. (2020). Acceptance of mobile phone by university students for their studies: An investigation applying UTAUT2 model. Educ. Inf. Technol. 25, 4139–4155, https://doi.org/10.1007/s10639....
 
82.
Noerman, T., Riyadi, Yuliaji, E. S., & Natasha, C. A. M. (2025). The impacts of social influence and hedonic motivation on experience and continuance intention of using AI in SMEs’ HRM. Cogent Business & Management, 12(1), 2542422. https://doi.org/10.1080/233119....
 
83.
North, K., Aramburu, N., & Lorenzo, O. J. (2020). Promoting digitally enabled growth in SMEs: A framework proposal. Journal of Enterprise Information Management, 33(1), 238-262. https://doi.org/10.1108/JEIM-0....
 
84.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
 
85.
Nuryyev, G., Wang, Y. P., Achyldurdyyeva, J., Jaw, B. S., Yeh, Y. S., Lin, H. T., & Wu, L. F. (2020). Blockchain technology adoption behavior and sustainability of the business in tourism and hospitality SMEs: An empirical study. Sustainability, 12(3), 1256. https://doi.org/10.3390/su1203....
 
86.
Oanh, N. (2021, 20 Ekim). The 7 best mobile CRM software: Reviews and comparison. https://www.appvizer.com/magaz....
 
87.
OECD (2024). SME Digitalisation to manage shocks and transitions: 2024 OECD D4SME survey.
 
88.
OECD SME and Entrepreneurship Papers, No. 62, OECD Publishing, Paris, https://doi.org/10.1787/eb4ec9....
 
89.
Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33-46. https://doi.org/10.1016/j.eswa....
 
90.
Oye, N. D., A. Iahad, N., & Ab. Rahim, N. (2014). The history of UTAUT model and its impact on ICT acceptance and usage by academicians. Education and Information Technologies, 19(1), 251-270. https://doi.org/10.1007/s10639....
 
91.
Ozer, E. Y. (2023). Muhasebe bilgi sisteminin işletme yönetim kararları üzerindeki etkileri: TRC3 bölgesindeki KOBİlere yönelik bir araştırma [Effects of accounting information system on business management decisions: A research for SMEs in TRC3 region]. (PHD thesis), Hasan Kalyoncu University, Turkey.
 
92.
Papakostas, C., Troussas, C., Krouska, A., & Sgouropoulou, C. (2023). Exploring users’ behavioral intention to adopt mobile augmented reality in education through an extended technology acceptance model. International Journal of Human–Computer Interaction, 39(6), 1294-1302. https://doi.org/10.1080/104473....
 
93.
Parhamnia, F. (2022). Investigating mobile acceptance in academic library services based on Unified Theory of Acceptance and Use of Technology Model (UTAUT-2). The Journal of Academic Librarianship, 48(5), 102570. https://doi.org/10.1016/j.acal....
 
94.
Park, Y., & Chen, J. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349-1365. https://doi.org/10.1108/026355....
 
95.
Pentina, I., Koh, A. C., & Le, T. T. (2012). Adoption of social networks marketing by SMEs: Exploring the role of social impacts and experience in technology acceptance. International Journal of Internet Marketing and Advertising, 7(1), 65-82. https://doi.org/10.1504/IJIMA.....
 
96.
Qu, K., & Wu, X. (2024). ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments. Education and Information Technologies, 29(15), 19471-19503. https://doi.org/10.1007/s10639....
 
97.
Rahayu, F. S., Nastiti, P., & Arthajanvian, T. (2025). The role of hedonic motivation in influencing TikTok use and how it relates to generation z characteristics. Advances in Human‐Computer Interaction, 2025(1), 5971465. https://doi.org/10.1155/ahci/5....
 
98.
Ramli, A. A. R., Safaria, S., & Rizki, M. N. (2024). Analysis of using behavior on the GoHalalGo application: UTAUT model approach. Formosa Journal of Sustainable Research, 3(4), 755-770. https://doi.org/10.55927/fjsr.....
 
99.
Rejali, S., Aghabayk, K., Esmaeli, S., & Shiwakoti, N. (2023). Comparison of technology acceptance model, theory of planned behavior, and unified theory of acceptance and use of technology to assess a priori acceptance of fully automated vehicles. Transportation Research Part A: Policy and Practice, 168, 103565. https://doi.org/10.1016/j.tra.....
 
100.
Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. SmartPLS GmbH, Boenningstedt. Journal of Service Science and Management, 10(3), 32-49.
 
101.
Salimon, M. G., Kareem, O., Mokhtar, S. S. M., Aliyu, O. A., Bamgbade, J. A., & Adeleke, A. Q. (2023). Malaysian SMEs m-commerce adoption: TAM 3, UTAUT 2 and TOE approach. Journal of Science and Technology Policy Management, 14(1), 98-126. https://doi.org/10.1108/JSTPM-....
 
102.
Seethamraju, R., Diatha, K. S., & Garg, S. (2018). Intention to use a mobile-based information technology solution for tuberculosis treatment monitoring–applying a UTAUT model. Information Systems Frontiers, 20, 163-181. https://doi.org/10.1007/s10796....
 
103.
Shahzad, M. F., Xu, S., & Baheer, R. (2024). Assessing the factors influencing the intention to use information and communication technology implementation and acceptance in China’s education sector. Humanities and Social Sciences Communications, 11(1), 1-15. https://doi.org/10.1057/s41599....
 
104.
Shanmugam, A. Savarimuthu, M. T. & Wen, T. C. (2014). Factors affecting Malaysian behavioral intention to use mobile banking with mediating effects of attitude. Academic Research International, 5(2), 236-253.
 
105.
Shao, C., Nah, S., Makady, H., & McNealy, J. (2025). Understanding user attitudes towards AI-enabled technologies: An integrated model of Self-Efficacy, TAM, and AI Ethics. International Journal of Human–Computer Interaction, 41(5), 3053-3065. https://doi.org/10.1080/104473....
 
106.
Sharma, S., Singh, G., & Pratt, S. (2025). Applying a technology acceptance model to understand digital-free tourism. Tourism Recreation Research, 50(2), 229-246. https://doi.org/10.1080/025082....
 
107.
Sharma, S., Virani, S., Saini, J. R., & Rautela, S. (2025). Determinants of adoption of virtual reality as a teaching aid in higher education: the mediating role of hedonic motivation. Journal of Applied Research in Higher Education. ahead-of-print https://doi.org/10.1108/JARHE-....
 
108.
Soomro, S.A. & Habeeb, Y.O. (2025). Impact of perceived ease of use on impulsive buying behaviour through mobile commerce with hedonic and utilitarian effects. Asia-Pacific Journal of Business Administration, 17(3), 796-813. https://doi.org/10.1108/APJBA-....
 
109.
Stocchi, L., Pourazad, N., Michaelidou, N., Tanusondjaja, A., & Harrigan, P. (2022). Marketing research on Mobile apps: past, present and future. Journal of the Academy of Marketing Science, 1-31. https://doi.org/10.1007/s11747....
 
110.
Tanos, M., Man, N., & Nawi, N. (2024). Perceived ease of use, perceived usefulness, and intention to use e-commerce platforms by agribusiness owners in Malaysia: A review. International Journal of Academic Research in Business and Social Sciences, 14(2), 666-678. http://dx.doi.org/10.6007/IJAR....
 
111.
Tarhini, A., Alalwan, A. A., Shammout, A. B., & Al-Badi, A. (2019). An analysis of the factors affecting mobile commerce adoption in developing countries: Towards an integrated model. Review of International Business and Strategy, 29(3), 157-179. http://dx.doi.org/10.1108/RIBS....
 
112.
Tatli H. S., Bıyıkbeyi T., Gençer Çelik, G, & Öngel, G. (2024). Paperless technologies in universities: Examination in terms of unified theory of acceptance and use of technology (UTAUT). Sustainability 16(7), 2692. https://doi.org/10.3390/su1607....
 
113.
Taufique, K. M. R., Sabbir, M. M., Quinton, S., & Andaleeb, S. S. (2024). The different impact of utilitarian and hedonic attributes on web-based retail shopping behaviour through the lens of extended technology acceptance model. International Journal of Retail & Distribution Management, 52(4), 443-460. https://doi.org/10.1108/IJRDM-....
 
114.
Tomas, F. & Immerzeel, J. (2025). Chatbots in eyewitness interviews: perceived usefulness and ease of use drive intent to use conversational agent. Journal of Criminal Psychology, Vol. ahead-ofprint, https://doi.org/10.1108/JCP-11....
 
115.
Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of a computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement, 54(3), 813-821. https://doi.org/10.1177/001316....
 
116.
TÜİK, (2023, 22 Aralık). Küçük ve orta büyüklükteki girişim istatistikleri [Statistics of small and medium-sized enterprises], 2022. 4 Nisan 2023 TÜİK (tuik.gov.tr).
 
117.
Unal, E., & Uzun, A. M. (2021). Understanding university students’ behavioral intention to use Edmodo through the lens of an extended technology acceptance model. British Journal of Educational Technology, 52(2), 619-637. https://doi.org/10.1111/bjet.1....
 
118.
Ünalan, M. Yapraklı, T. Ş. & Kaçer, Z. (2019). Mobil alışveriş uygulamalarının kullanımını etkileyen faktörler ve bu faktörlerin memnuniyet ve kullanma niyeti üzerindeki etkisi [Factors influencing the usage of mobile shopping applications and the impact of these factors on satisfaction and intention to use]. Akademi Sosyal Bilimler Dergisi, 6(17), 391-408.
 
119.
Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5), 960-991. https://doi.org/10.1108/IJBM-0....
 
120.
Uzkurt, C., Ekmekcioglu, E. B., Ceyhan, S., & Hatiboglu, M. B. (2024). Digital technology use of SMEs during the COVID-19 pandemic in Turkey: Mobile applications’ role on motivation and job performance. Kybernetes, 53(4), 1354-1373. https://doi.org/10.1108/K-08-2....
 
121.
Van Akkeren, J., & Harker, D. (2002). Mobile data technologies and SME adoption and Diffusion: an empirical study of barriers and facilitators. Australasian Journal of Information Systems, 9(2). https://doi.org/10.3127/ajis.v....
 
122.
Varga, J. (2021). Defining the economic role and benefits of micro, small and medium-sized enterprises in the 21st century with a systematic review of the literature. Acta Polytechnica Hungarica, 18(11), 209-228.
 
123.
Venkatesh, V. Morris, M. G. Davis, G. B. & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/300365....
 
124.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.4....
 
125.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/414104....
 
126.
Wang, H., Tao, D., Yu, N., & Qu, X. (2020). Understanding consumer acceptance of healthcare wearable devices: An integrated model of UTAUT and TTF. International Journal of Medical Informatics, 139, 104156. https://doi.org/10.1016/j.ijme....
 
127.
Wilson, N., Keni, K., & Tan, P. H. P. (2021). The role of perceived usefulness and perceived ease-ofuse toward satisfaction and trust which influence computer consumers’ loyalty in China. Gadjah Mada International Journal of Business, 23(3), 262-294. https://doi.org/10.22146/gamai....
 
128.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. https://doi.org/10.1016/j.im.2....
 
129.
Yanit, M., & Wan, F. (2023). Right agent, wrong level of hedonism: How high (vs low) hedonic values in AI-performed tasks lead to decreased perceptions of humanlikeness, warmth, and less consumer support. Computers in Human Behavior, 147, 107870. https://doi.org/10.1016/j.chb.....
 
130.
Yawised, K., Apasrawirote, D., Chatrangsan, M., & Muneesawang, P. (2025). Extending UTAUT-2 towards acceptance by SMEs of the mobile application platform “Tripper Notifier Application”. Journal of Science and Technology Policy Management. ahead-of-print https://doi.org/10.1108/jstpm-....
 
131.
Yenilmez, B. (2024). Türkiye’deki KOBİ’lerin blockchain teknolojisine adaptasyonu ile ilgili görüşleri [Views of SMEs in Turkey on adaptation to blockchain technology]. Üçüncü Sektör Sosyal Ekonomi Dergisi, 59(2), 993–1007. https://doi.org/10.15659/3.sek....
 
132.
Yörük, T. ve Özçetin, S. (2021). Çevrimiçi öğrenmeye yönelik özyeterlik ölçeğinin Türkçeye uyarlanması [Adaptation of online learning self-efficacy scale into Turkish]. Kahramanmaraş Sütçü İmam Üniversitesi Sosyal Bilimler Dergisi, 18 (3), 1640-1657. https://doi.org/10.33437/ksusb....
 
133.
Yunior, M. C., & Augustine, Y. (2024). The influence of social impact, relative advantage, user satisfaction on cloud-based e-learning with behavioral intention as a mediating variable. Technium Soc. Sci. J., 56(1), 36-50. https://doi.org/10.47577/tssj.....
 
134.
Zeynel, E. (2024). Örgütsel davranış açısından öznel iyi oluşun önemi. Örgütsel Davranış Araştırmaları, 196-206.
 
135.
Zubir, M. H. H., & Abdul Latip, M. S. (2024). Factors affecting citizens’ intention to use e-government services: assessing the mediating effect of perceived usefulness and ease of use. Transforming Government: People, Process and Policy, 18(3), 384-399. https://doi.org/10.1108/TG-04-....
 
eISSN:2299-193X
ISSN:1429-9321 (1997-2019)
Journals System - logo
Scroll to top