DATA ANALYTICS IN INFORMATION SHARING AND RESOURCE DEPENDENCY: ENHANCING ACCOUNTING SYSTEMS

Öz

In the context of advances in blockchain technologies, a growing number of organizations are prioritizing the strategic use of data analytics to achieve sustainable performance. The conversion of big data into a digital format, coupled with its cross-departmental sharing for a comprehensive assessment of market dynamics, has precipitated a heightened interdependence among departments. Therefore, necessitating a greater reliance on the information generated by accounting systems. This study reveals the interplay among the use of data analytics, digital information sharing, and the effectiveness of accounting systems, in the context of knowledge sharing theory, and resource dependency theory. The results indicate that the use of data analytics improves accounting system effectiveness by reinforcing digital information sharing and fostering interdepartmental interdependence.

Anahtar Kelimeler

• Knowledge-sharing theory
• use of data analytics
• interdependence
• sharing of digital information
• effectiveness of accounting information systems

Etik Beyan

This study has been prepared in accordance with the rules of scientific research and publication ethics. The research was approved by the Ethics Committee of Istanbul Gelişim University Rectorate with the decision numbered 2025-16-03 and dated 29.08.2025.

BİLGİ PAYLAŞIMI VE KAYNAK BAĞIMLILIĞI BAĞLAMINDA VERİ ANALİTİKLERİ: MUHASEBE SİSTEMLERİNİN GELİŞTİRİLMESİ

Öz

Blok zinciri teknolojisindeki gelişmeler bağlamında, giderek artan sayıda organizasyon sürdürülebilir performans elde etmek için veri analitiğinin stratejik kullanımına öncelik vermektedir. Büyük verinin dijital formata dönüştürülmesi ve piyasa dinamiklerinin kapsamlı bir şekilde değerlendirilmesi için departmanlar arası bilgi paylaşımı, departmanlar arasında artan bir karşılıklı bağımlılığı tetiklemiş ve dolayısıyla muhasebe sistemleri tarafından üretilen bilgilere daha fazla güvenilmesini zorunlu kılmıştır. Bu çalışma, bilgi paylaşımı teorisi ile kaynak bağımlılığı teorisi bağlamında veri analitiğinin kullanımı, dijital bilgi paylaşımı ve muhasebe sistemlerinin etkinliği arasındaki etkileşimi ortaya koymaktadır. Sonuçlar, veri analitiğinin kullanımının dijital bilgi paylaşımını güçlendirerek ve departmanlar arası bağımlılığı teşvik ettiğini ve muhasebe sisteminin etkinliğini artırdığını göstermektedir.

Anahtar Kelimeler

• Bilgi paylaşım teorisi
• veri analitiklerinin kullanımı
• karşılıklı bağımlılık
• dijital bilginin paylaşımı
• muhasebe bilgi sisteminin etkinliği

Etik Beyan

Bu çalışma, bilimsel araştırma ve yayın etiği kurallarına uygun olarak hazırlanmıştır. Araştırma, İstanbul Gelişim Üniversitesi Rektörlüğü Etik Kurulu'nun 29.08.2025 tarih ve 2025-16-03 sayılı kararıyla onaylanmıştır.

Kaynakça

1. Abdelhalim, A. M., & Hassan, M. (2025). Exploring the impact of big data analytics and risk management convergence on sustainability performance development: an accounting perspective. Discover Sustainability, 6(1), 175. https://doi.org/10.1007/s43621-025-00866-x
2. Albergaria, M., & Jabbour, C. J. C. (2020). The role of big data analytics capabilities (BDAC) in understanding the challenges of service information and operations management in the sharing economy: Evidence of peer effects in libraries. International Journal of Information Management, 51, 102023. https://doi.org/10.1016/j.ijinfomgt.2019.10.008
3. Al-Okaily, M. (2025). Attitudes toward the adoption of accounting analytics technology in the digital transformation landscape. Journal of Accounting & Organizational Change, 21(3), 593–613. https://doi.org/10.1108/jaoc-04-2024-0127
4. Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44. https://doi.org/10.1016/j.accinf.2017.03.003
5. Ardito, L., Scuotto, V., Del Giudice, M., & Petruzzelli, A. M. (2019). A bibliometric analysis of research on Big Data analytics for business and management. Management Decision, 57(8), 1993–2009. https://doi.org/10.1108/md-07-2018-0754
6. Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. https://doi.org/10.2307/3150783
7. Aryani, A. T. D., & Rosyid, A. (2025). Online learning engagement and operational accounting competencies: the moderating role of digital literacy. Education and Information Technologies, 1–23. https://doi.org/10.1007/s10639-025-13517-5
8. Bailey, D. E., Leonardi, P. M., & Chong, J. (2010). Minding the gaps: Understanding technology interdependence and coordination in knowledge work. Organization Science, 21(3), 713–730. https://doi.org/10.1287/orsc.1090.0473

9. Bedford, D. S. (2020). Conceptual and empirical issues in understanding management control combinations. Accounting, Organizations and Society, 86, 101187. https://doi.org/10.1016/j.aos.2020.101187
10. Beersma, B., Homan, A. C., Van Kleef, G. A., & De Dreu, C. K. W. (2013). Outcome interdependence shapes the effects of prevention focus on team processes and performance. Organizational Behavior and Human Decision Processes, 121(2), 194–203. https://doi.org/10.1016/j.obhdp.2013.02.003
11. Bevan, D., Kipka, C., Sita Nirmala Kumaraswamy, K., & Chitale, C. M. (2012). Collaborative knowledge sharing strategy to enhance organizational learning. Journal of Management Development, 31(3), 308–322. https://doi.org/10.1108/02621711211208934
12. Bose, S., Dey, S. K., & Bhattacharjee, S. (2023). Big data, data analytics and artificial intelligence in accounting: An overview. Handbook of Big Data Research Methods, 32–51. https://doi.org/10.4337/9781800888555.00007
13. Cheng, J. L. C. (1983). Interdependence and coordination in organizations: A role-system analysis. Academy of Management Journal, 26(1), 156–162. https://doi.org/10.2307/256142
14. Chenhall, R. H., & Morris, D. (1986). The impact of structure, environment, and interdependence on the perceived usefulness of management accounting systems. Accounting Review, 16–35. https://doi.org/10.2308/tar-4490476
15. Chin, W. W. (2009). How to write up and report PLS analyses. In Handbook of partial least squares: Concepts, methods and applications (pp. 655–690). Springer. https://doi.org/10.1007/978-3-540-32827-8_29
16. Choi, J. W. (2020). Studying “and”: A perspective on studying the interdependence between management control practices. Accounting, Organizations and Society, 86, 101188. https://doi.org/10.1016/j.aos.2020.101188
17. Cockrell, R. C., Stone, D. N., & Wier, B. (2018). Accounting for professional accountants’ dysfunctional knowledge sharing: A self-determination theory perspective. Journal of Information Systems, 32(1), 45–65. https://doi.org/10.2308/isys-51677
18. Coman, D. M., Ionescu, C. A., Duică, A., Coman, M. D., Uzlau, M. C., Stanescu, S. G., & State, V. (2022). Digitization of accounting: the premise of the paradigm shift of role of the professional accountant. Applied Sciences, 12(7), 3359. https://doi.org/10.3390/app12073359
19. Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. https://doi.org/10.1287/mnsc.32.5.554
20. De Mauro, A., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122–135. https://doi.org/10.1108/LR-06-2015-0061
21. De Silva, P., Gunarathne, N., & Kumar, S. (2025). Exploring the impact of digital knowledge, integration and performance on sustainable accounting, reporting and assurance. Meditari Accountancy Research, 33(2), 497–552. https://doi.org/10.1108/medar-02-2024-2383
22. Deng, H., Duan, S. X., & Wibowo, S. (2023). Digital technology driven knowledge sharing for job performance. Journal of Knowledge Management, 27(2), 404–425. https://doi.org/10.1108/jkm-08-2021-0637
23. Duh, R.-R., Knechel, W. R., & Lin, C.-C. (2020). The effects of audit firms’ knowledge sharing on audit quality and efficiency. Auditing: A Journal of Practice & Theory, 39(2), 51–79. https://doi.org/10.2308/ajpt-52597
24. 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
25. Franke, F., & Hiebl, M. R. W. (2023). Big data and decision quality: the role of management accountants’ data analytics skills. International Journal of Accounting & Information Management, 31(1), 93–127. https://doi.org/10.1108/ijaim-12-2021-0246
26. Gerdin, J. (2005). The impact of departmental interdependencies and management accounting system use on subunit performance. European Accounting Review, 14(2), 297–327. https://doi.org/10.1080/09638180500043485
27. Grabner, I., Klein, A., & Speckbacher, G. (2022). Managing the trade-off between autonomy and task interdependence in creative teams: The role of organizational-level cultural control. Accounting, Organizations and Society, 101, 101347. https://doi.org/10.1016/j.aos.2022.101347
28. Hair, J. F. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). sage.
29. Hassan, H., & Maelah, R. (2021). Management accounting information usefulness, digital inclusion and performance of SMEs. International Conference on Business and Technology, 125–143. https://doi.org/10.1007/978-3-031-08084-5_11
30. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford publications.
31. Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405–431. https://doi.org/10.1108/IMR-09-2014-0304
32. Hung, S. Y., Tsai, J. C. A., Chen, K., Chen, C., & Yeh, T. T. (2024). Tacit knowledge sharing in information systems development projects: social interdependence and regulatory focus perspectives. Information Technology & People, 37(4), 1449-1477. https://doi.org/10.1108/itp-08-2022-0587
33. Jassem, S. (2024). Artificial Intelligence in Accounting Practices in the Industry 5.0 Era from a Dynamic Capabilities Perspective: Role of Strategic Foresight, Agility, and Flexibility. In Opportunities and Risks in AI for Business Development: Volume 1 (pp. 149–160). Springer. https://doi.org/10.1007/978-3-031-65203-5_14
34. Jiang, H., Luo, Y., Xia, J., Hitt, M., & Shen, J. (2023). Resource dependence theory in international business: Progress and prospects. Global strategy journal, 13(1), 3-57. https://doi.org/10.1002/gsj.1467
35. Jiang, L. (2024). The use of blockchain technology in enterprise financial accounting information sharing. Plos One, 19(2), e0298210. https://doi.org/10.1371/journal.pone.0298210
36. Kembro, J., Näslund, D., & Olhager, J. (2017). Information sharing across multiple supply chain tiers: A Delphi study on antecedents. International Journal of Production Economics, 193, 77–86. https://doi.org/10.1016/j.ijpe.2017.06.032
37. Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking. Accounting, Auditing & Accountability Journal, 35(9), 109–135. https://doi.org/10.1108/aaaj-09-2020-4934
38. Li, Y., & Juma’h, A. H. (2022). The Effect of Technological and Task Considerations on Auditors’ Acceptance of Blockchain Technology. Journal of Information Systems, 36(3), 129–151. https://doi.org/10.2308/isys-2020-022
39. Lin, H.-F. (2007). Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions. Journal of Information Science, 33(2), 135–149. https://doi.org/10.1177/0165551506068174
40. Mia, L., & Goyal, M. (1991). Span of control, task interdependence and usefulness of MAS information in not‐for‐profit government organizations. Financial Accountability & Management, 7(4), 249–266.
41. Mukherjee, A., Sharma, U., & Liu, J. (2025). Big data analytics role in shaping the work of accounting function and accounting professionals. Journal of Accounting & Organizational Change, 21(7), 272-306. https://doi.org/10.1108/jaoc-08-2024-0255
42. Müller, O., Fay, M., & Vom Brocke, J. (2018). The effect of big data and analytics on firm performance: An econometric analysis considering industry characteristics. Journal of Management Information Systems, 35(2), 488–509. https://doi.org/10.1080/07421222.2018.1451955
43. Nguyen, T.-M., Siri, N. S., & Malik, A. (2022). Multilevel influences on individual knowledge sharing behaviours: the moderating effects of knowledge sharing opportunity and collectivism. Journal of Knowledge Management, 26(1), 70–87. https://doi.org/10.1108/jkm-01-2021-0009
44. Nicolaou, A. I. (2000). A contingency model of perceived effectiveness in accounting information systems: Organizational coordination and control effects. International Journal of Accounting Information Systems, 1(2), 91–105. https://doi.org/10.1016/s1467-0895(00)00006-3
45. Nielsen, S. (2015). The impact of business analytics on management accounting. Available at SSRN 2616363.
46. Öztürk, O. & Bağış, M. (2025). Bridging resource dependence theory and resource-based view: a theoretical synthesis. Management Decision. 64(6), 2175-2205. https://doi.org/10.1108/MD-05-2024-1071
47. Pugliese, A., Minichilli, A., & Zattoni, A. (2014). Integrating agency and resource dependence theory: Firm profitability, industry regulation, and board task performance. Journal of Business Research, 67(6), 1189–1200. https://doi.org/10.1016/j.jbusres.2013.05.003
48. Puranam, P., Raveendran, M., & Knudsen, T. (2012). Organization design: The epistemic interdependence perspective. Academy of Management Review, 37(3), 419–440. https://doi.org/10.5465/amr.2010.0535
49. Raguseo, E., & Vitari, C. (2018). Investments in big data analytics and firm performance: an empirical investigation of direct and mediating effects. International Journal of Production Research, 56(15), 5206–5221. https://doi.org/10.1080/00207543.2018.1427900
50. Raveendran, M., Silvestri, L., & Gulati, R. (2020). The role of interdependence in the micro-foundations of organization design: task, goal, and knowledge interdependence. Academy of Management Annals, 14(2), 828–868. https://doi.org/10.5465/annals.2018.0015
51. Razak, N. A., Pangil, F., Zin, M. L. M., Yunus, N. A. M., & Asnawi, N. H. (2016). Theories of knowledge sharing behavior in business strategy. Procedia Economics and Finance, 37, 545–553. https://doi.org/10.1016/S2212-5671(16)30163-0
52. Rialti, R., Zollo, L., Ferraris, A., & Alon, I. (2019). Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model. Technological Forecasting and Social Change, 149, 119781. https://doi.org/10.1016/j.techfore.2019.119781
53. Saleh, I., Abu Afifa, M., Alkhawaja, A., & Marei, Y. (2023). Big data analytics and sustainability accounting and reporting: Evidence from Canada. Conference on Sustainability and Cutting-Edge Business Technologies, 313–321. https://doi.org/10.1007/978-3-031-42463-2_29
54. Seddon, P., & Yip, S.-K. (1992). An empirical evaluation of user information satisfaction (UIS) measures for use with general ledger accounting software. Journal of Information Systems, 6(1). https://doi.org/10.2308/jis-9504251920
55. Spraakman, G., Sanchez-Rodriguez, C., & Tuck-Riggs, C. A. (2021). Data analytics by management accountants. Qualitative Research in Accounting & Management, 18(1), 127–147. https://doi.org/10.1108/qram-11-2019-0122
56. Tan, K. H., Ji, G., Lim, C. P., & Tseng, M.-L. (2017). Using big data to make better decisions in the digital economy. In International Journal of Production Research 55(17), 4998–5000. https://doi.org/10.1080/00207543.2017.1331051
57. Theodorakopoulos, L., Thanasas, G., & Halkiopoulos, C. (2024). Implications of big data in accounting: Challenges and opportunities. Emerging Science Journal, 8(3), 1201–1214. https://doi.org/10.28991/esj-2024-08-03-024
58. Trinh, H. T. (2026). An SME approach to data analytics by management accountants in the transition economy of Vietnam. Journal of Science and Technology Policy Management, 17(3), 547-568. https://doi.org/10.1108/jstpm-12-2023-0222
59. Trivellas, P., Akrivouli, Z., Tsifora, E., & Tsoutsa, P. (2015). The impact of knowledge sharing culture on job satisfaction in accounting firms. The mediating effect of general competencies. Procedia Economics and Finance, 19, 238–247. https://doi.org/10.1016/S2212-5671(15)00025-8
60. Tuan, N. M., Hung, N. Q., & Hang, N. T. (2021). Digital transformation in the business: a solution for developing cash accounting information systems and digitizing documents. VNUHCM Journal of Science and Technology Development, 24(2), 1975–1987. https://doi.org/10.32508/stdj.v24i2.2526
61. Vera‐Mun˜ oz, S. C., Ho, J. L., & Chow, C. W. (2006). Enhancing knowledge sharing in public accounting firms. Accounting Horizons, 20(2), 133–155. https://doi.org/10.2308/acch.2006.20.2.133
62. Vitari, C., & Raguseo, E. (2020). Big data analytics business value and firm performance: linking with environmental context. International Journal of Production Research, 58(18), 5456–5476. https://doi.org/10.1080/00207543.2019.1660822
63. Voss, U., & Brettel, M. (2014). The effectiveness of management control in small firms: Perspectives from resource dependence theory. Journal of Small Business Management, 52(3), 569–587. https://doi.org/10.1111/jsbm.12050
64. Weigel, C., & Hiebl, M. R. W. (2023). Accountants and small businesses: toward a resource-based view. Journal of Accounting & Organizational Change, 19(5), 642–666. https://doi.org/10.1108/jaoc-03-2022-0044
65. Widén-Wulff, G., & Ginman, M. (2004). Explaining knowledge sharing in organizations through the dimensions of social capital. Journal of Information Science, 30(5), 448–458. https://doi.org/10.1177/0165551504046997
66. Xu, X., & He, Y. (2024). Blockchain application in modern logistics information sharing: A review and case study analysis. Production Planning & Control, 35(9), 886–900. https://doi.org/10.1080/09537287.2022.2058997