Determinants of Information Technology Investment Expenditure

Authors

  • Josua Panatap Soehaditama Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia
  • Adler Haymans Manurung Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia
  • Nera Marinda Machdar Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia
  • Wastam Wahyu Hidayat Universitas Bhayangkara Jakarta Raya, Jakarta, Indonesia

DOI:

https://doi.org/10.38035/gijea.v3i4.1108

Keywords:

IT Cost, Leadership, Efficiency, Bank Size, Resource-Base View, Dynamic Capabilities

Abstract

Amid globalization, financial deregulation, and market volatility, banks aggressively adapt to maintain long-term competitive advantages. While digital transformation is non-negotiable, heavy capital allocations for Information Technology (IT) often face the "productivity paradox," where extensive spending does not automatically translate into immediate efficiency or output returns. Objective: This study aims to analyze the critical internal and external determinants of IT Investment Expenditure in the Indonesian banking industry. Methodology: Drawing upon the Resource-Based View (RBV) and Dynamic Capabilities Theory, this study utilizes panel data from commercial banks listed on the Indonesia Stock Exchange (IDX) and registered with the Financial Services Authority (OJK) from 2010 to 2023. The empirical framework corrects prior model discrepancies by formally treating Bank Risk as an independent control variable. Model selection was rigorously evaluated using the Chow, Hausman, and Lagrange Multiplier (LM) tests, validating the Fixed Effect Model (FEM) as the most robust specification. Results: The empirical findings demonstrate that Leadership and Efficiency (BOPO) have a statistically significant positive impact on IT Investment Expenditure. Conversely, Bank Size exhibits a statistically significant negative effect. Client-Based variables, Bank Risk (NPL), and the COVID-19 pandemic dummy do not show a statistically significant direct impact on IT expenditures. Conclusion: The findings suggest that smaller banking institutions bear a disproportionately higher financial burden relative to their asset size to keep pace with technological changes, whereas larger banks successfully exploit structural economies of scale in their IT infrastructure deployment.

References

Ackermann, J., Yeung, M. A., & Van Bommel, E. (2007). Better It Management for Banks. The Mckinsey Quarterly, 1–7.

Adigwe, C. S., Abalaka, A., Olaniyi, O. O., Adebiyi, O. O., & Oladoyinbo, T. O. (2023). Critical Analysis of Innovative Leadership Through Effective Data Analytics: Exploring Trends in Business Analysis, Finance, Marketing, and Information Technology. Asian Journal of Economics, Business and Accounting, 23(22). https://doi.org/10.9734/Ajeba/2023/V23i221165

Alsamhi, M. H., Al-Ofairi, F. A., Najib H.S., Farhan, Al-ahdal, W. M., and A. Siddiqu (2022), Impact of Covid-19 on firms’ performance:

Empirical evidence from India, Cogent Business & Management, 9:1, 2044593, DOI: 10.1080/23311975.2022.2044593

Andrayani, I., & Dewi, A. F. (2014). Pengaruh IT Spending Terhadap Kinerja Perusahaan Telekomunikasi Yang Terdaftar Di Bursa Efek Seluruh Asia Tenggara Pada Tahun 2009-2012. Modus. https://doi.org/10.24002/Modus.V26i2.581

Banker, R. D., Hu, N., Pavlou, P. A., & Luftman, J. (2011). CIO Reporting Structure, Strategic Positioning, and Firm Performance. Mis Quarterly, 487–504. https://doi.org/10.2307/23044053

Beccalli, E. (2007). It and European Bank Performance. Springer. https://doi.org/10.1057/9780230591981

Biorn, E. (2017). Econometrics of Panel Data: Methods and Applications. Oxford University Press.

Chen, Y., Liang, L., Yang, F., & Zhu, J. (2006). Evaluation of Information Technology Investment: A Data Envelopment Analysis Approach. Computers & Operations Research, 33(5), 1368–1379. https://doi.org/10.1016/J.Cor.2004.09.021

Ciotti, M., Ciccozzi, M., Terrinoni, A., Jiang, W. C., Wang, C. B. and S. Bernardini (2020): The COVID-19 pandemic, Critical Reviews in Clinical Laboratory Sciences, DOI: 10.1080/10408363.2020.1783198

Daryanto, W. M., Rizki, M. I. and Mahardika (2021), Financial Performance Analysis of Construction Company before and during COVID-19 Pandemic in Indonesia, International Journal of Business, Economics and Law, Vol. 24, Issue 4, pp. 99 – 108

Dorfman, R., Samuelson, P. A., & Solow, R. M. (1987). Linear Programming and Economic Analysis. Courier Corporation.

Firmansyah, I. (2019). Pengaruh Kepemimpinan, Realisasi Anggaran, Reinventing Government Dan Pengendalian Internal Pemerintah Terhadap Kinerja Operasional. Malaysian Journal of Social Sciences and Humanities (Mjssh), 4(3), 192–207.

Ginsberg, A., & Venkatraman, N. (1992). Investing in New Information Technology: The Role of Competitive Posture and Issue Diagnosis. Strategic Management Journal, 13(S1), 37–53. https://doi.org/10.1002/Smj.4250131005

Gotcheva, N., Watts, G., & Oedewald, P. (2013). Developing Smart and Safe Organizations: An Evolutionary Approach. International Journal of Organizational Analysis, 21(1), 83–97. https://doi.org/10.1108/19348831311322551

Greene, W. H. (2008); Econometric Analysis; Pearson – Prentice Hall.

Gujarati, D. N., (2003), Basic Econometrics; 4th eds.; McGraw Hill.

Hamdani, H., Wahyuni, N., Amin, A., & Sulfitra, S. (2018). Analisis Faktor-Faktor Yang Mempengaruhi Kinerja Keuangan Bank Umum Syariah Yang Terdaftar Di Bursa Efek Indonesia (Bei) (Periode 2014-2016). Jurnal Emt Kita, 2(2), 62–73. https://doi.org/10.35870/Emt.V2i2.55

Hannan, T. H., & McDowell, J. M. (1984). The Determinants of Technology Adoption: The Case of the Banking Firm. The RAND Journal of Economics, 15(3), 328–335. https://doi.org/10.2307/2555441

Judge, G. G., R. C. Hill, W. E. Griffiths, and H. Lutkepohl (1982), Introduction to the Theory and Practice of Econometrics; John Wiley & Sons, New York.

Khallaf, A., Omran, M. A., & Zakaria, T. (2017). Explaining The Inconsistent Results of The Impact of Information Technology Investments on Firm Performance: A Longitudinal Analysis. Journal of Accounting & Organizational Change, 13(3), 359–380. https://doi.org/10.1108/Jaoc-11-2015-0086

Lullah, N., Taswan, T., & Waruwu, P. (2020). Pengaruh Kecukupan Modal, Loan To Deposit Ratio, Konsentrasi Kepemilikan Dan Ukuran Bank Terhadap Kinerja Bank Umum. Dinamika Akuntansi Keuangan Dan Perbankan, 9(1), 79–90.

Madanchian, M., & Taherdoost, H. (2019). Assessment of Leadership Effectiveness Dimensions in Small & Medium Enterprises (Smes). Procedía Manufacturing, 32, 1035–1042. https://doi.org/10.1016/J.Promfg.2019.02.318

Manurung, A.H. (2024a). Corporate Finance: Indonesia’s Case. Jakarta: PT. Adler Manurung Press.

Manurung, A.H. (2024b). Regression and Extension: Cross-Section and Time Series Data. Jakarta: PT. Adler Manurung Press.

Manurung, A.H. (2024c). Variabel Moderasi dan Variabel Mediasi dalam Model Jakarta: PT. Adler Manurung Press.

Martínez, A. B., De andrés, J., & García, J. (2014). Determinants of The Web Accessibility of European Banks. Information Processing & Management, 50(1), 69–86. https://doi.org/10.1016/J.Ipm.2013.08.001

Mumin, Y. A., Ustarz, Y., & Yakubu, I. (2014). Automated Teller Machine (Atm) Operation Features and Usage in Ghana: Implications for Managerial Decisions. Journal of Business Administration and Education, 5(2), 137–157.

Ngo, H.T. and Duong, H.N. (2024), "Covid-19 pandemic and firm performance: evidence on industry differentials and impacting channels", International Journal of Social Economics, Vol. 51 No. 4, pp. 569-583.

Ou, C. S., Yen, D. C., & Hung, C. S. (2009). Determinants of information technology investments: The case of ATM in an emerging economy. Advances in Accounting, 25(2), 278-283.

Roach, S. (1994). Lessons of The Productivity Paradox. Computerworld, 19.

Shaharuddin, S. N. H., Mahmud, R., Azhari,N. K. M., and W. Perwitasari (2021), Company Performance during Covid-19: Impact of leverage, liquidity and cash flows, AcE-Bs2021, 9th Asian Conference on Environment-Behaviour Studies, Perdana Kota Bharu, Kelantan, Malaysia, 28-29 Jul 2021, E-BPJ, 6(17), Aug 2021 (pp.11-16)

Shen, H., Fu, M., Pan, H., Yu, Z., and Y. Chen (2020). The Impact of the COVID-19 Pandemic on Firm Performance, Emerging Markets Finance and Trade, 56(10), 2213–2230.

Shih, E., Kraemer, K. L., & Dedrick, J. (2007). Research note—determinants of country-level investment in information technology. Management science, 53(3), 521-528.

Sollosy, M. D., & Weible, R. J. (2020). Does An Information Technology Investment Contribute To Company Performance: A Further Examination of The Productivity Paradox. https://doi.org/10.30845/Ijbht.V10n1p2

Sul, Donggyu (2019), Panel Data Econometrics: Common Factor Analysis for Empirical Researchers; Routledge.

Turner, J. (1983). Organizational Performance, Size, and The Use of Data Processing Resources.

Shevlin, R. (2019). How Much Do Banks Spend on Technology? (Hint: It Would Weigh 670 Tons in $100 Bills). Forbes, April, 1.

Wooldridge, J. M. (2002); Econometric Analysis of Cross Section and Panel Data; the MIT Press, Cambridge – England.

Published

2026-07-09

How to Cite

Soehaditama, J. P., Manurung, A. H., Machdar, N. M., & Hidayat, W. W. (2026). Determinants of Information Technology Investment Expenditure. Greenation International Journal of Economics and Accounting, 3(4), 821–830. https://doi.org/10.38035/gijea.v3i4.1108