Effectiveness of accrual basis accounting system in state budget and treasury system in TAM 3 framework

Ratih Kusumastuti*  -  Universitas Jambi, Indonesia
Derist Touriano  -  Universitas Adiwangsa Jambi, Indonesia
Sry Rosita  -  Universitas Jambi, Indonesia
Raja Sharah Fatricia  -  Lancaster University, United Kingdom

(*) Corresponding Author
DOI: 10.21580/jiafr.2022.4.1.10896

Purpose - This study establishes a basic theoretical model developed using Technology Acceptance Model (TAM 3) with several critical factors on the effectiveness of accrual basis accounting systems in the State Budget and the Treasury System.

Method - This basic research uses a causal model with primary data collected quantitatively and presented descriptively. The study population was users of the State Budget and Treasury System in the Regional Office V of Jambi Province using the convenience sampling method.

Result - The results of this study stated that all TAM variables were correlated with each other and TAM 3 variables were correlated with the effectiveness of the accrual-based accounting system in SPAN. It was proven that there was a significant relationship between all variables. However, the accrual-based accounting system in SPAN practically does not provide convenience and tends to have low intensity of use and low effectiveness.

Implication - The result of this research states that all variables of TAM are correlated to each other and TAM 3 variables are correlated to the effectiveness of accrual basis accounting system in SPAN.

Originality - This study focuses on the effectiveness of accrual basis accounting system in State Budget and Treasury System: migration of the Indonesian Islamic banking system of BSI.

Keywords: TAM 3; effectiveness; accrual basis accounting; BSI system

  1. Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. MIS Quarterly, 16(2), 227. https://doi.org/10.2307/249577
  2. Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  3. Alalwan, A. A., Dwivedi, Y. K., Rana, N. P. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan. Journal of Enterprise Information Management, 29(1), 118–139. https://doi.org/10.1108/JEIM-04-2015-0035
  4. Althunibat, A., Alrawashdeh, T. A., & Muhairat, M. (2014). The Acceptance of Using M-Government Services in Jordan. Journal of Theoretical and Applied Information Technology, 63(3), 733–740.
  5. Anouze, A. L. M., & Alamro, A. S. (2019). Factors affecting intention to use e-banking in Jordan. International Journal of Bank Marketing, 38(1), 86–112.
  6. Arnott, D., Lizama, F., & Song, Y. (2017). Patterns of business intelligence systems use in organizations. Decision Support Systems, 97, 58–68. https://doi.org/10.1016/j.dss.2017.03.005
  7. Augusty, F. (2011). Metode Penelitian Manajemen: Pedoman Penelitian untuk Penulisan Skripsi, Tesis dan Disertasi Ilmu Manajemen. Badan Penerbit Universitas Diponegoro.
  8. Awuku, E. T. (2020). Awuku, E. T. (2020). Is Downward Accountability Essential? Facets of Accountability Dimensions in Non-Governmental Organisation with Lessons from Ghana. International Journal for Research in Applied Science and Engineering Technology, 8(6), 2056–2061.
  9. Awwaliyah, N., Agriyanto, R., & Farida, D. (2019). The effect of regional original income and balance funding on regional government financial performance. Journal of Islamic Accounting and Finance Research, 1(1), 25–46. 10.21580/jiafr.2019.1.1.3745
  10. Barker, R., & Teixeira, A. (2018). Gaps in the IFRS conceptual framework. Accounting in Europe, 15(2), 153–166.
  11. Carter, L., & Bélanger, F. (2005). The utilization of e-government services: citizen trust, innovation and acceptance factors. Information Systems Journal, 15(1), 5–25.
  12. Carter, L., Weerakkody, V., Phillips, B., & Dwivedi, Y. K. (2016). Citizen Adoption of e-government Services: Exploring citizen perceptions of online services in the United States and United Kingdom. Information Systems Management, 33(2), 124–140.
  13. Cartwright, E. (2018). Behavioral Economics (3rd Editio). Routledge. https://doi.org/10.4324/9781315105079
  14. Chen, C.-C., & Tsai, J.-L. (2019). Determinants of behavioral intention to use the Personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628–638.
  15. Chen, L., & Aklikokou, A. K. (2020). Determinants of E-government adoption: testing the mediating effects of perceived usefulness and perceived ease of use. International Journal of Public Administration, 43(10), 43(10), 850–865.
  16. Conteh, S., & Hamidah, H. (2021). Audit Expectation GAP in The Public Sector of The Gambia. The Indonesian Accounting Review, 11(2), 127–141.
  17. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
  18. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
  19. Dehghani, M. (2018). Exploring the motivational factors on continuous usage intention of smartwatches among actual users. Behaviour & Information Technology, 37(2), 145–158.
  20. Farzin, M., Sadeghi, M., Yahyayi Kharkeshi, F., Ruholahpur, H., & Fattahi, M. (2020). Extending UTAUT2 in M-banking adoption and actual use behavior: Does WOM communication matter? Asian Journal of Economics and Banking, 5(2), 136–157.
  21. Gupta, M., Cazzanti, L., & Srivastava, S. (2005). Minimum expected risk probability estimates for nonparametric neighborhood classifiers. Statistical Signal Processing, 631–636.
  22. 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/S2212-5671(16)00079-4
  23. Hamstra, M. R., Van Yperen, N. W., Wisse, B., & Sassenberg, K. (2014). On the perceived effectiveness of transfor- mational–transactional leadership: The role of encouraged strategies and followers’ regulatory focus. European Journal of Social Psychology, 44(March), 643–656.
  24. Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 58(5), 1159–1197.
  25. Hansen, J. M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197–206.
  26. Hariguna, T., Lai, M.-T., Hung, C.-W., & Chen, S.-C. (2017). Understanding information system quality on public e-government service intention : an empirical study. International Journal of Innovation and Sustainable Development, 11(2–3), 271–290.
  27. Islami, X., Mulolli, E., & Mustafa, N. (2018). Using Management by Objectives as a performance appraisal tool for employee satisfaction. Future Business Journal, 4(1), 4(1), 94–108.
  28. Jacobs, M. D. F. (2008). A review of capital budgeting practices (No. 8-160). International Monetary Fund. (No. 8–160).
  29. Karahanna, E., & Straub, D. W. (1999). The psychological origins of perceived usefulness and ease-of-use. Information & Management, 35, 237–250.
  30. Keszey, T. (2017). Information Systems in Transition Economies : Does Ownership Matter ? Information Systems Management, 34(1), 65–84. https://doi.org/10.1080/10580530.2017.1254456
  31. Khan, H. U., & Alshare, K. (2015). Factors influence consumers ’ adoption of mobile payment devices in Qatar. International Journal of Mobile Communications, 13(6), 670–689. https://doi.org/10.1504/IJMC.2015.072100
  32. Kozunova, G. L., Voronin, N. A., Venediktov, V. V., & Stroganova, T. A. (2019). Learning with reinforcement: the role of immediate feedback and the internal model of the situation. Neuroscience and Behavioral Physiology, 49(9), 1150–1158.
  33. Kromann, L., & Sørensen, A. (2019). Automation, performance and international competition: a firm-level comparison of process innovation. Economic Policy, 34(100), 691–722.
  34. Kumar Jha, J., & Varkkey, B. (2018). Are you a cistern or a channel? Exploring factors triggering knowledge-hiding behavior at the workplace: evidence from the Indian R&D professionals. Journal of Knowledge Management, 22(4), 824–849.
  35. Latan, H., & Ghozali, I. (2014). Partial Least Squares: Konsep, Teknik dan Aplikasi WarpPLS 4.0. BP Universitas Diponegoro.
  36. Leone, A. J., Minutti-Meza, M., & Wasley, C. E. (2019). Influential observations and inference in accounting research. The Accounting Review, 94(6), 337–364.
  37. Lule, I., Omwansa, T. K., & Waema, T. M. (2012). Application of technology acceptance model (TAM) in m-banking adoption in Kenya. International Journal of Computing and ICT Research, 6(1), 31–43.
  38. Lund, M., & Nielsen, C. (2018). The concept of business model scalability. Journal of Business Models, 6(1), 6(1), 1–18.
  39. Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191. https://doi.org/10.1287/isre.2.3.173
  40. Megarani, N., Warno, & Fauzi, M. (2019). The effect of tax planning, company value, and leverage on income smoothing practices in companies listed on Jakarta Islamic Index. Journal of Islamic Accounting and Finance Research, 1(1), 139–162.
  41. Moqbel, M. A., & Bartelt, V. L. (2016). Consumer Acceptance of Personal Cloud: Integrating Trust and Risk with the Technology Acceptance Model. AIS Transactions on Replication Research, 2(1), 1–5.
  42. Mutahar, A. M., Daud, N. M., Thurasamy, R., Isaac, O., & Abdulsalam, R. (2018). The mediating of perceived usefulness and perceived ease of use: the case of mobile banking in Yemen. International Journal of Technology Diffusion (IJTD), 9(2), 21–40.
  43. Namahoot, K. ., & Laohavichien, T. (2018). Assessing the intentions to use internet banking: The role of perceived risk and trust as mediating factors. International Journal of Bank Marketing, 36(2), 256–276. https://doi.org/10.1108/IJBM-11-2016-0159 Marketing.
  44. Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61(August), 404–414. https://doi.org/10.1016/j.chb.2016.03.030
  45. Olola, O. A. (2019). Effects of international public sector accounting standards on financial accountability in Nigeria public sector. European Journal of Accounting, Auditing and Finance Research, 7(3), 41–54.
  46. Pittig, A. (2019). Incentive-based extinction of safety behaviors: Positive outcomes competing with aversive outcomes trigger fear-opposite action to prevent protection from fear extinction. Behaviour Research and Therapy, 121(103463), 1–10.
  47. Rahi, S., Ghani, M., Alnaser, F., & Ngah, A. (2018). Investigating the role of unified theory of acceptance and use of technology (UTAUT) in internet banking adoption context. Management Science Letters, 8(3), 173-186.
  48. Rikhardsson, P., Rohde, C., Christensen, L., & Batt, C. E. (2021). Management controls and crisis: evidence from the banking sector. Accounting, Auditing & Accountability Journal, 34(4), 757–785.
  49. Riyanto. (2016). Standar Akuntansi Pemerintah (SAP) Berbasis Akrual pada Badan Layanan Umum menurut Peraturan Menteri Keuangan Terbaru. https://bppk.kemenkeu.go.id/id/publikasi/artikel/150-artikel-keuangan-umum/22944-standar-akuntansi-pemerintah-sap-berbasis-akrual-pada-badan-layanan-umum-menurut-peraturan-menteri-keuangan-terbaru
  50. Sharma, G., Shakya, S., & Kharel, P. (2014). Technology acceptance perspectives on user satisfaction and trust of e-government adoption. Journal of Applied Sciences, 14(9), 860–872.
  51. Shaw, H., Ellis, D. A., & Ziegler, F. V. (2018). The Technology Integration Model (TIM). Predicting the continued use of technology. Computers in Human Behavior, 83, 83, 204–214.
  52. Shet, S. V., Poddar, T., Samuel, F. W., & Dwivedi, Y. K. (2021). Examining the determinants of successful adoption of data analytics in human resource management–A framework for implications. Journal of Business Research, 131, 311–326.
  53. Shropshire, J., Warkentin, M., & Sharma, S. (2015). Personality, attitudes, and intentions: Predicting initial adoption of information security behavior. Computers and Security, 49, 177–191. https://doi.org/10.1016/j.cose.2015.01.002
  54. Singh, S., & Srivastava, R. K. (2018). Predicting the intention to use mobile banking in India. International Journal of Bank Marketing, 36(2), 357–378.
  55. Steers, R. M. (2014). Organizational Effectiveness (Erlangga).
  56. Straub, D., & Karahanna, E. (2017). Measuring System Usage : Implications for IS Theory Testing. Management Science, 41(8), 1328–1342. https://doi.org/10.1287/mnsc.41.8.1328
  57. Strickland, J. C., & Johnson, M. W. (2021). Rejecting impulsivity as a psychological construct: A theoretical, empirical, and sociocultural argument. Psychological Review, 128(2), 336–361.
  58. Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management and Data Systems, 116(3), 508–525. https://doi.org/10.1108/IMDS-05-2015-0195
  59. Thorndike, B. Y. E. L. (1933). A theory of the action of the after-effects of a connection upon it. Psychological Review, 40(5), 434–439.
  60. Valenzuela, S., Halpern, D., Katz, J. E., & Miranda, J. P. (2019). The paradox of participation versus misinformation: Social media, political engagement, and the spread of misinformation. Digital Journalism, 7(6), 802–823.
  61. 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., 35(2), 161–174.
  62. Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
  63. Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204. http://pubsonline.informs.org/doi/abs/10.1287/mnsc.46.2.186.11926
  64. Waemustafa, W., & Abdullah, A. (2016). Mode of Islamic Bank Financing: Does Effectiveness of Shariah Supervisory Board Matter? Australian Journal of Basic and Applied Sciences, 9(37), 458–465.
  65. Wang, D. H., Chen, P., Yu, T. H., & Hsiao, C. (2015). The effects of corporate social responsibility on brand equity and fi rm performance. Journal of Business Research, 68(11), 2232–2236. https://doi.org/10.1016/j.jbusres.2015.06.003
  66. Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2015). Understanding SaaS adoption from the perspective of organizational users: A tripod readiness model. Computers in Human Behavior, 45, 254–264. https://doi.org/10.1016/j.chb.2014.12.022
  67. Yusup, M., Hardiyana, A., & Sidharta, I. (2015). User Acceptance Model on E-Billing Adoption : A Study of Tax Payment by Government Agencies. Asia Pacific Journal of Multidisciplinary Research, 3(4), 150–157.
  68. Zelmiyanti, R. (2015). Perkembangan akuntansi berbasis akrual pada sektor pemerintah di indonesia. Jurnal Riset Akuntansi Dan Komputerisasi Akuntansi, 6(1), 68–72.
  69. Zhu, Y., Zhang, J. H., Au, W., & Yates, G. (2020). University students’ online learning attitudes and continuous intention to undertake online courses: A self-regulated learning perspective. Educational Technology Research and Development, 68(3), 1485–1519.

Journal of Islamic Accounting and Finance Research
Published by Department of Sharia Accounting, Faculty of Islamic Economics and Business, Universitas Islam Negeri Walisongo Semarang, Indonesia
Jl Prof. Dr. Hamka Kampus III Ngaliyan Semarang 50185
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ISSN: 2715-0429 (Print)
ISSN: 2714-8122 (Online)

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