Main Article Content

Abstract

Decentralised school finance depends on the capacity and commitment of the staff responsible for administering funds. This study examines whether fund-manager capacity and organisational commitment mediate the association between budgetary participation and performance, and whether information and communication technology (ICT) use strengthens these pathways. A Google Forms survey, distributed through school principals to designated BOS fund-management personnel in Tangerang Regency, Indonesia, yielded 400 usable records relating to the 2025 BOSP funding cycle, covering Stage I (January–June) and Stage II (July–December). Partial least squares structural equation modelling with 10,000 bootstrap resamples showed positive direct and indirect associations. Budgetary participation was associated with performance directly (β = 0.153) and through capacity (β = 0.114, 95% BCa confidence interval [0.072, 0.167]) and commitment (β = 0.057, [0.029, 0.092]). ICT strengthened both first-stage relationships; the moderated mediation indices were 0.061 [0.034, 0.096] and 0.028 [0.013, 0.053], respectively. The model explained 39.7% of performance variance, with blindfolding Q² = 0.253. Supplementary regressions with individual covariates retained the principal associations. The findings connect participative budgeting to staff development and motivation in school-grant administration and suggest that meaningful involvement, applied financial training, and usable digital workflows should be considered together. The cross-sectional design, perceptual measures, aggregate control specification, and mixed fit diagnostics qualify the conclusions.

Keywords

Budgetary Participation BOS Funds School Financial Management ICT Use Organisational Commitment

Article Details

How to Cite
Bagus, B. C. S. (2026). Budgetary Participation and BOS Fund Manager Performance in Digitally Enabled School Finance. Economics and Digital Business Review, 8(1), 164–185. https://doi.org/10.37531/ecotal.v8i1.4208

References

  1. Alhasnawi, M. Y., Mohd Said, R., Alshdaifat, S. M., Elorabi, K. A., Al-Hasnawi, M. H., & Khudhair, A. H. (2024). How does budget participation affect managerial performance in the higher education sector? A mediated-moderated model. Asian Journal of Accounting Research, 9(4), 325–339. https://doi.org/10.1108/AJAR-12-2023-0405
  2. Bandur, A. (2012). School-based management developments and partnership: Evidence from Indonesia. International Journal of Educational Development, 32(2), 316–328. https://doi.org/10.1016/j.ijedudev.2011.05.007
  3. Bandur, A. (2018). Stakeholders’ responses to school-based management in Indonesia. International Journal of Educational Management, 32(6), 1082–1098. https://doi.org/10.1108/IJEM-08-2017-0191
  4. Barrera-Osorio, F., Fasih, T., Patrinos, H. A., & Santibáñez, L. (2009). Decentralized decision-making in schools: The theory and evidence on school-based management. World Bank. https://doi.org/10.1596/978-0-8213-7969-1
  5. Blanco-Encomienda, F. J., & Al Jasimee, K. H. (2026). Predicting the performance of industrial enterprises through ICT-enabled processes: The interplay of staff capacity and organizational commitment. Business Process Management Journal, 32(8), 1–27. https://doi.org/10.1108/BPMJ-06-2025-0912
  6. Brownell, P., & McInnes, M. (1986). Budgetary participation, motivation, and managerial performance. The Accounting Review, 61(4), 587–600.
  7. Chenhall, R. H. (2003). Management control systems design within its organizational context: Findings from contingency-based research and directions for the future. Accounting, Organizations and Society, 28(2–3), 127–168. https://doi.org/10.1016/S0361-3682(01)00027-7
  8. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. https://doi.org/10.2307/2393553
  9. Deci, E. L., Olafsen, A. H., & Ryan, R. M. (2017). Self-determination theory in work organizations: The state of a science. Annual Review of Organizational Psychology and Organizational Behavior, 4, 19–43. https://doi.org/10.1146/annurev-orgpsych-032516-113108
  10. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
  11. 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/10.2307/3151312
  12. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  13. Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50(1), 1–22. https://doi.org/10.1080/00273171.2014.962683
  14. He, L., & Ismail, K. (2023). Do staff capacity and performance-based budgeting improve organisational performance? Empirical evidence from Chinese public universities. Humanities and Social Sciences Communications, 10, Article 29. https://doi.org/10.1057/s41599-023-01523-2
  15. 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/s11747-014-0403-8
  16. Long, J. S., & Ervin, L. H. (2000). Using heteroscedasticity consistent standard errors in the linear regression model. The American Statistician, 54(3), 217–224. https://doi.org/10.1080/00031305.2000.10474549
  17. Maiga, A. S., Nilsson, A., & Jacobs, F. A. (2014). Assessing the impact of budgetary participation on budgetary outcomes: The role of information technology for enhanced communication and activity-based costing. Journal of Management Control, 25(1), 5–32. https://doi.org/10.1007/s00187-014-0191-9
  18. Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322. https://doi.org/10.2307/25148636
  19. Meyer, J. P., & Allen, N. J. (1991). A three-component conceptualization of organizational commitment. Human Resource Management Review, 1(1), 61–89. https://doi.org/10.1016/1053-4822(91)90011-Z
  20. Milani, K. (1975). The relationship of participation in budget-setting to industrial supervisor performance and attitudes: A field study. The Accounting Review, 50(2), 274–284.
  21. Ministry of Primary and Secondary Education of the Republic of Indonesia. (2025). Regulation of the Minister of Primary and Secondary Education Number 8 of 2025 concerning technical guidelines for the management of operational assistance funds for educational units. https://jdih.kemendikdasmen.go.id/sjdih/siperpu/dokumen/salinan/Permendikdasmen_No_8_Tahun_2025_ttg_Juknis_Pengelolaan_Dana_Bantuan_Operasional_Satuan_Pendidikan.pdf
  22. Nitzl, C., Roldán, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial Management & Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
  23. Nouri, H., & Parker, R. J. (1998). The relationship between budget participation and job performance: The roles of budget adequacy and organizational commitment. Accounting, Organizations and Society, 23(5–6), 467–483. https://doi.org/10.1016/S0361-3682(97)00036-6
  24. Otley, D. (2016). The contingency theory of management accounting and control: 1980–2014. Management Accounting Research, 31, 45–62. https://doi.org/10.1016/j.mar.2016.02.001
  25. Parker, R. J., & Kyj, L. (2006). Vertical information sharing in the budgeting process. Accounting, Organizations and Society, 31(1), 27–45. https://doi.org/10.1016/j.aos.2004.07.005
  26. Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  27. Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227. https://doi.org/10.1080/00273170701341316
  28. Riketta, M. (2002). Attitudinal organizational commitment and job performance: A meta-analysis. Journal of Organizational Behavior, 23(3), 257–266. https://doi.org/10.1002/job.141
  29. Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3 [Computer software]. SmartPLS GmbH. https://www.smartpls.com
  30. Shields, J. F., & Shields, M. D. (1998). Antecedents of participative budgeting. Accounting, Organizations and Society, 23(1), 49–76. https://doi.org/10.1016/S0361-3682(97)00014-7
  31. Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., 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
  32. Winata, L., & Mia, L. (2005). Information technology and the performance effect of managers’ participation in budgeting: Evidence from the hotel industry. International Journal of Hospitality Management, 24(1), 21–39. https://doi.org/10.1016/j.ijhm.2004.04.006