Accounting Information Systems (AIS) play a critical role in enhancing organizational efficiency and decision-making processes. Understanding the factors that influence AIS adoption is essential for organizations aiming to optimize their technological capabilities.
Objective
The objective of this study is to identify the key factors influencing employees’ behavioral intentions to use Accounting Information Systems (AIS) and to examine how these intentions affect their actual use behavior.
Methods
Employing a survey methodology, the research collected data on key variables. The survey, adapted from validated instruments, was distributed to a sample of 366 employees across public and private sector organizations in Saudi Arabia. SEM was used to analyze the complex relationships among these variables.
Results
The results indicate that performance expectancy, effort expectancy, social influence, and facilitating conditions all have direct and positive impacts on the behavioral intention to use AIS. Additionally, Behavioral Intention positively influences AIS Use Behavior.
Conclusions
The findings confirm the UTAUT model’s relevance in Saudi Arabia, emphasizing the influence of cultural factors and Vision 2030 on technology adoption. The study highlights the importance of perceived usefulness, ease of use, social support, and organizational systems in promoting AIS adoption, offering valuable insights for both theory and practice in technology management.
AlsyoufAIshakAK. Understanding EHRs continuance intention to use from the perspectives of UTAUT: practice environment moderating effect and top management support as predictor variables. Int J Electron Healthc2018; 10(1–2): 24–59. DOI: 10.1504/IJEH.2018.092175.
2.
Karaman AksentijevićNJežićZZaninovićPA. The effects of information and communication technology (ICT) use on human development A macroeconomic approach. Economies2021; 9(3): 1–12. DOI: 10.3390/economies9030128.
3.
BuntinMBBurkeMFHoaglinMC, et al.The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Aff2011; 30(3): 464–471. DOI: 10.1377/hlthaff.2011.0178.
4.
AlshirahMLutfiAAlshirahA, et al.Influences of the environmental factors on the intention to adopt cloud based accounting information system among SMEs in Jordan. Accounting2021; 7(3): 645–654. DOI: 10.5267/j.ac.2020.12.013.
5.
AlaminAYeohWWarrenM, et al.An empirical study of factors influencing accounting information systems adoption. In: Paper presented at the twenty-third European conference on information systems, Münster, Germany, May 26-29, 2015, pp. 1–11. https://aisel.aisnet.org/ecis2015_cr/3
6.
AlmaiahMAAl-KhasawnehA. Investigating the main determinants of mobile cloud computing adoption in university campus. Educ Inf Technol2020; 25(4): 3087–3107. DOI: 10.1007/s10639-020-10120-8.
7.
BhattacherjeeALinCP. A unified model of IT continuance: three complementary perspectives and crossover effects. Eur J Inf Syst2015; 24(4): 364–373. DOI: 10.1057/ejis.2013.36.
8.
VenkateshVThongJYChanFK, et al.Extending the two‐stage information systems continuance model: incorporating UTAUT predictors and the role of context. Inf Syst J2011; 21(6): 527–555. DOI: 10.1111/j.13652575.2011.00373.x.
9.
BhattacherjeeAPremkumarG. Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Q2004; 28(2): 229–254. DOI: 10.2307/25148634.
10.
TamCSantosDOliveiraT. Exploring the influential factors of continuance intention to use mobile Apps: extending the expectation confirmation model. Inf Syst Front2020; 22: 243–257. DOI: 10.1007/s10796-018-9864-5.
11.
AlmaiahMAHajjejFLutfiA, et al.A conceptual framework for determining quality requirements for mobile learning applications using Delphi Method. Electronics2022; 11(5): 788. DOI: 10.3390/electronics11050788.
12.
BoonstraABroekhuisM. Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC Health Serv Res2010; 10: 1–17.
13.
LiaoCPalviaPChenJL. Information technology adoption behavior life cycle: toward a Technology Continuance Theory (TCT). Int J Inf Manag2009; 29(4): 309–320. DOI: 10.1016/j.ijinfomgt.2009.03.004.
14.
OweisK. The effect of management quality of accounting information system outputs on customers satisfaction in Saudi Arabia commercial banks. Accounting2022; 8(3): 277–286. DOI: 10.5267/j.ac.2021.12.002.
15.
LutfiA. Factors influencing the continuance intention to use accounting information system in Jordanian SMEs from the perspectives of UTAUT: top management support and self-efficacy as predictor factors. Economies2022; 10(4): 1–17. DOI: 10.3390/economies10040075.
16.
SalehMMJawabrehOAbu-EkerEF. Factors of applying creative accounting and its impact on the quality of financial statements in Jordanian hotels, sustainable practices. Journal of Sustainable Finance & Investment2023; 13(1): 499–515. DOI: 10.1080/20430795.2021.1962662.
17.
SitungkirANapitupuluIH. The quality of management accounting information system is the key to increasing user satisfaction of information systems: evidence of state owned enterprises (SOE's) in Indonesia. Quality-Access to Success2019; 20(173): 145–150.
18.
Al-MamaryYHSSiddiquiMAAbdalraheemSG, et al.Factors impacting Saudi students’ intention to adopt learning management systems using the TPB and UTAUT integrated model. Journal of Science and Technology Policy Management2024; 15(5): 1110–1141. DOI: 10.1108/JSTPM-04-2022-0068.
19.
ThongJYYapCS. Information systems effectiveness: a user satisfaction approach. Inf Process Manag1996; 32(5): 601–610. DOI: 10.1016/0306-4573(96)00004-0.
20.
LutfiA. Factors affecting the success of accounting information system from the lens of DeLone and McLean IS model. International Journal of Information Management Data Insights2023; 3(2): 1–10. DOI: 10.1016/j.jjimei.2023.100202.
21.
IdrisKMMohamadR. AIS usage factors and impact among Jordanian SMEs: the moderating effect of environmental uncertainty. Journal of Advanced Research in Business and Management Studies2017; 6(1): 24–38.
22.
MareiA. The effect of e-procurement on financial performance: moderating the role of competitive pressure. 10 5267/j uscm2022; 10(3): 855–866. DOI: 10.5267/j.uscm.2022.3.009.
23.
DaoudL. Predictors and consequences of using accounting information system among companies in Jordan: the moderating role of resistance to change. J Southwest Jiaot Univ2023; 58(4). DOI: 10.35741/issn.0258-2724.58.4.85.
24.
FatimaSIshtiaqMJavedA. Impact of accounting information system on corporate governance: evidence from Pakistani textile sector. International Journal of Law and Management2021; 63(4): 431–442. DOI: 10.1108/IJLMA-07-2020-0212.
25.
AlmagrashiAMujalliAKhanT, et al.Factors determining internal auditors’ behavioral intention to use computer-assisted auditing techniques: an extension of the UTAUT model and an empirical study. Futur Bus J2023; 9(1): 74. DOI: 10.1186/s43093-023-00231-2.
26.
AlomairAFarleyAYangHH. The impact of IFRS adoption on the value relevance of accounting information in Saudi Arabia. Account Finance2022; 62(2): 2839–2878. DOI: 10.1111/acfi.12902.
27.
Al-GhamdiSAbu-AlfaAAlotaibiT, et al.Chronic kidney disease management in the Middle East and Africa: concerns, challenges, and novel approaches. Int J Nephrol Renovasc Dis2023; 16: 103–112. DOI: 10.2147/IJNRD.S363133.
28.
AlsughayerS. Role of ERP systems in management accounting in SMEs in Saudi Arabia. J Account Organ Change2024; ahead-of-print. DOI: 10.1108/JAOC-11-2022-0176.
29.
VenkateshVMorrisMGDavisGB, et al.User acceptance of information technology: toward a unified view. MIS Q2003; 27(3): 425–478. DOI: 10.2307/30036540.
30.
DavisFD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q1989; 13(3): 319–340. DOI: 10.2307/249008.
31.
VenkateshVDavisFD. A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag Sci2000; 46(2): 186–204. DOI: 10.1287/mnsc.46.2.186.11926.
32.
DadayanLFerroE. When technology meets the mind: a comparative study of the technology acceptance model. In: International conference on electronic government 2005. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 137–144. DOI: 10.1007/11545156_13.
33.
DwivediYKRanaNPChenH, et al., 2011. A meta-analysis of the unified theory of acceptance and use of technology (UTAUT). In: Governance and sustainability in information systems. Managing the transfer and diffusion of IT: IFIP WG 8.6 international working conference, Hamburg, Germany, September 22-24, 2011, pp. 155–170. Springer Berlin Heidelberg. DOI: 10.1007/978-3-642-24148-2_10.
34.
AbdALIdrisKMMohamadR. The influence of technological, organizational and environmental factors on accounting information system usage among Jordanian small and medium-sized enterprises. Int J Econ Financ Issues2016; 6(7): 240–248.
35.
JambulingamM. Behavioural intention to adopt mobile technology among tertiary students. World Appl Sci J2013; 22(9): 1262–1271. DOI: 10.5829/idosi.wasj.2013.22.09.2748.
36.
VenkateshVZhangX. Unified theory of acceptance and use of technology: US vs. China. J Global Inf Technol Manag2010; 13(1): 5–27. DOI: 10.1080/1097198X.2010.10856507.
37.
KumarSKarAKIlavarasanPV. Applications of text mining in services management: a systematic literature review. International Journal of Information Management Data Insights2021; 1(1): 1–14. DOI: 10.1016/j.jjimei.2021.100008.
38.
ThompsonRLHigginsCAHowellJM. Personal computing: toward a conceptual model of utilization. MIS Q1991; 15(1): 125–143. DOI: 10.2307/249443.
39.
HofkirchnerWKreowskiHJ. Digital Humanism: how to shape digitalisation in the age of global challenges?InProceedings2022; 81(1): 1–6. DOI: 10.3390/proceedings2022081004.
40.
KarahannaEStraubDWChervanyNL. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q1999; 23(2): 183–213. DOI: 10.2307/249751.
41.
Ramírez-CorreaPRondán-CataluñaFJArenas-GaitánJ, et al.Analysing the acceptation of online games in mobile devices: an application of UTAUT2. J Retailing Consum Serv2019; 50: 85–93. DOI: 10.1016/j.jretconser.2019.04.018.
42.
AlshehriAJ RutterMSmithS. The effects of UTAUT and usability qualities on students’ use of learning management systems in Saudi tertiary education. JITE: Research2020; 19: 891–930. DOI: 10.28945/4659.
43.
ZulhermanZAmirullohGPurnomoA, et al.Development of android-based millealab virtual reality media in natural science learning. J Pendidik Sains Indones2021; 9(1): 1–10.
44.
AlrawadMLutfiAAlyatamaS, et al.Perception of occupational and environmental risks and hazards among mineworkers: a psychometric paradigm approach. Int J Environ Res Public Health2022; 19(6): 1–12. DOI: 10.3390/ijerph19063371.
45.
AjzenI. The Theory of planned behavior. Organ Behav Hum Decis Process1991; 50: 179–211.
46.
MulhemAAAlmaiahMA. A conceptual model to investigate the role of mobile game applications in education during the COVID-19 pandemic. Electronics2021; 10(17): 179–211. DOI: 10.3390/electronics10172106.
47.
ParkHLeeMAhnJM. Bottom‐up solutions in a time of crisis: the case of Covid‐19 in South Korea. R&D Management2021; 51(2): 211–222. DOI: 10.1111/radm.12449.
48.
CavusNMohammedYBYakubuMN. Determinants of learning management systems during COVID-19 pandemic for sustainable education. Sustainability2021; 13(9): 5189. DOI: 10.3390/su13095189.
49.
SaadAMMohamadMBTsongCK. Behavioural intention of lecturers towards mobile learning and the moderating effect of digital literacy in saudi arabian universities. Int Trans J Eng Manag Appl Sci Technol2021; 12(1): 1–9. DOI: 10.14456/ITJEMAST.2021.2.
50.
WangYSLiaoYW. Assessing eGovernment systems success: a validation of the DeLone and McLean model of information systems success. Govern Inf Q2008; 25(4): 717–733. DOI: 10.1016/j.giq.2007.06.002.
51.
AlshammariR. The current use of mobile devices among students and faculty in EFL teaching in a Saudi Arabian context. Turkish Online Journal of Educational Technology-TOJET2020; 19(2): 34–51.
52.
AlharbiF. Associations between social learning environments and students' reading comprehension skills: an analysis of PISA's Saudi Arabia dataset. J Educ Elearn Res2021; 9(1): 1–7.
53.
AlsyoufALutfiAAlsubahiN, et al.The use of a technology acceptance model (TAM) to predict patients’ usage of a personal health record system: the role of security, privacy, and usability. Int J Environ Res Public Health2023; 20(2): 1–24. DOI: 10.3390/ijerph20021347.
54.
AwangZ. Structural equation modeling using AMOS graphic. Shah Alam: Penerbit Universiti Teknologi MARA, 2012.
55.
Al-MamaryYHShamsuddinA. Testing of the technology acceptance model in context of Yemen. Mediterr J Soc Sci2015; 6(4): 268–273. DOI: 10.5901/mjss.2015.v6n4s1p268.
56.
ThomranMAlshallaqiMAl-MamaryYH, et al.The key enablers of competitive advantage formation in small and medium enterprises: the case of the Ha’il region. Front Psychol2022; 13: 1–15. DOI: 10.3389/fpsyg.2022.1030405.
57.
AlshammariMMAl-MamaryYHAbubakarAA. Revolutionizing education: unleashing the power of social media in Saudi Arabian public universities. Humanit Soc Sci Commun2024; 11(1): 1–2. DOI: 10.1057/s41599-024-03313-w.
58.
AlquhaifAAbdulrabMRashedRQ, et al.From traditional to tech-savvy: an empirical investigation of students’ actual use of LMS in Saudi universities. Int J Adv Appl Sci2023; 10(6): 137–149. DOI: 10.21833/ijaas.2023.06.017.
59.
Al-MamaryYHAlfalahAAShamsuddinA, et al.Artificial intelligence powering education: ChatGPT's impact on students’ academic performance through the lens of technology-to-performance chain theory. J Appl Res High Educ2024; 1–17. DOI: 10.1108/JARHE-04-2024-0179.
60.
Al-MamaryYH. Understanding the use of learning management systems by undergraduate university students using the UTAUT model: credible evidence from Saudi Arabia. International Journal of Information Management Data Insights2022; 2(2): 1–11. DOI: 10.1016/j.jjimei.2022.100092.
61.
AlghamdiAMAlsuhaymiDSAlghamdiFA, et al.University students’ behavioral intention and gender differences toward the acceptance of shifting regular field training courses to e-training courses. Educ Inf Technol2022; 27: 451–468. DOI: 10.1007/s10639-021-10701-1.
62.
CatherineNGeofreyKMMoyaMB, et al.Effort expectancy, performance expectancy, social influence and facilitating conditions as predictors of behavioural intentions to use ATMs with fingerprint authentication in Ugandan banks. Global J Comput Sci Technol2017; 17(5): 5–23.
63.
AlmaiahMAAlamriMMAl-RahmiW. Applying the UTAUT model to explain the students’ acceptance of mobile learning system in higher education. IEEE Access2019; 7: 174673–174686. DOI: 10.1109/ACCESS.2019.2957206.
64.
SairSADanishRQ. Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and social sciences (PJCSS)2018; 12(2): 501–520.
65.
RazaSAQaziWKhanKA, et al.Social isolation and acceptance of the learning management system (LMS) in the time of COVID-19 pandemic: an expansion of the UTAUT model. J Educ Comput Res2021; 59(2): 183–208. DOI: 10.1177/0735633120960421.
66.
BervellBNyagormePArkorfulV. LMS-enabled blended learning use intentions among distance education tutors: examining the mediation role of attitude based on technology-related stimulus-response theoretical framework. Contemporary Educational Technology2020; 12(2): 1–21. DOI: 10.30935/cedtech/8317.
67.
AlharbiAFAljojoNZainolA, et al.Identification of critical factors affecting the student’s acceptance of learning management system (LMS) in Saudi Arabia. Int J Innov2020; 9(2): 353–388. DOI: 10.5585/iji.v9i2.19652.
68.
AbbadMM. Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Educ Inf Technol2021; 26(6): 7205–7224. DOI: 10.1007/s10639-021-10573-5.
69.
AlsaaidAAbd RazakN. The blackboard learning management system: an intention usage among lecturers at a Saudi Arabia public universities. PalArch’s Journal of Archaeology of Egypt/Egyptology2020; 17(6): 9753–9764.
70.
AswaniRIlavarasanPVKarAK, et al.Adoption of public WiFi using UTAUT2: an exploration in an emerging economy. Proc Comput Sci2018; 132: 297–306. DOI: 10.1016/j.procs.2018.05.180.
71.
RajehMTAbduljabbarFHAlqahtaniSM, et al.Students’ satisfaction and continued intention toward e-learning: a theory-based study. Med Educ Online2021; 26(1): 1–8. DOI: 10.1080/10872981.2021.1961348.
72.
RamanADonYKhalidR, et al.Usage of learning management system (Moodle) among postgraduate students: UTAUT model. Asian Soc Sci2014; 10(14): 186–192. DOI: 10.5539/ass.v10n14p186.
73.
AlshammariSH. The influence of technical support, perceived self-efficacy, and instructional design on students’ use of learning management systems. Turk Online J Dist Educ2020; 21(3): 112–141. DOI: 10.17718/tojde.762034.
74.
AlshehriARutterMJSmithS. An implementation of the UTAUT model for understanding students’ perceptions of learning management systems: a study within tertiary institutions in Saudi Arabia. Int J Dist Educ Technol2019; 17(3): 1–24. DOI: 10.4018/IJDET.2019070101.
