Authors :
Ramsha Siddiqui; Ahmed Erfan Nahian; Nirban Bhowmick; Saad Mirza
Volume/Issue :
Volume 11 - 2026, Issue 6 - June
Google Scholar :
https://tinyurl.com/3h6cbcs9
Scribd :
https://tinyurl.com/3jxrnrs8
DOI :
https://doi.org/10.38124/ijisrt/26jun1181
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
Reliable enterprise Decision-Support Systems (DSS) require integrated mechanisms for auditability, transparent
reporting, and performance measurement to ensure accountability and high-quality decision-making. However, existing
approaches often separate audit functions from performance monitoring, resulting in fragmented governance and reduced
operational visibility. To address this limitation, this study proposes an integrated Auditability and Performance Monitoring
Framework for enterprise DSS environments. The framework unifies structured reporting workflows, transaction
traceability, KPI-based performance evaluation, and validation procedures within a single architecture. A Decision-Support
Reliability Index (DSRI) is introduced to quantitatively assess overall system effectiveness by integrating key governance
and operational performance indicators. The framework is evaluated using five enterprise-inspired benchmark scenarios
supplemented by sensitivity analysis. Experimental results demonstrate consistent improvements in reporting reliability,
process transparency, compliance efficiency, and operational performance across all scenarios. Even under high-complexity
conditions, the framework maintains stable DSRI values, indicating strong robustness and scalability. The findings confirm
that integrating auditability with performance monitoring significantly enhances governance quality and decision-support
effectiveness in modern enterprise systems.
Keywords :
Enterprise Decision-Support Systems (DSS), Auditability, Performance Monitoring, Data Governance, Reporting Reliability, KPI Analytics, Transaction Traceability, Decision-Support Reliability Index (DSRI).
References :
- Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2020). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 38, 100466. https://doi.org/10.1016/j.accinf.2020.100466
- Al-Okaily, M., Al-Okaily, A., Teoh, A. P., & Al-Debei, M. M. (2023). Digital transformation and firm performance: The role of enterprise information systems and governance mechanisms. Information Systems Frontiers, 25(4), 1357–1375. https://doi.org/10.1007/s10796-021-10196-0
- Jans, M., Alles, M. G., & Vasarhelyi, M. A. (2021). A field study on the use of process mining of event logs as an analytical procedure in auditing. The Accounting Review, 96(2), 287–314. https://doi.org/10.2308/TAR-2018-0170
- Alles, M. G., Kogan, A., & Vasarhelyi, M. A. (2021). Putting continuous auditing theory into practice: Lessons from two pilot implementations. Journal of Information Systems, 35(1), 1–20. https://doi.org/10.2308/ISYS-19-013
- Rezaee, Z., Elam, R., & Sharbatoghlie, A. (2021). Continuous auditing: Building automated audit capabilities in organizations. Managerial Auditing Journal, 36(7), 885–905. https://doi.org/10.1108/MAJ-07-2020-2746
- Raji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., & Barnes, P. (2020). Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 33–44. https://doi.org/10.1145/3351095.3372873
- Faccia, A., Mosteanu, N. R., Cavaliere, L. P. L., & Mataruna-Dos-Santos, L. J. (2023). Electronic auditing and digital transformation in accounting information systems. Systems, 11(6), 290. https://doi.org/10.3390/systems11060290
- Chiarini, A., Silvestri, B., & Ruggieri, M. (2022). Performance measurement systems and digital transformation: A systematic literature review. Business Process Management Journal, 28(5/6), 1321–1346. https://doi.org/10.1108/BPMJ-01-2022-0018
- Hasan, E. (2025). Machine learning-based KPI forecasting for finance and operations teams. IJSRED - International Journal of Scientific Research and Engineering Development, 8(6), 2139–2149. https://doi.org/10.5281/zenodo.17926746
- Alsurayyi, A. I., & Alsughayer, S. A. (2021). The relationship between corporate governance and firm performance: The effect of internal audit and enterprise resource planning (ERP). Open Journal of Accounting, 10(2), 56–76. https://doi.org/10.4236/ojacct.2021.102006
- Pudjono, A. N. S., Setyadi, D., & Purwanto, A. (2025). Advancing local governance: A systematic review of performance management systems. Cogent Social Sciences, 11(1), 2442545. https://doi.org/10.1080/23311886.2024.2442545
- Akter, T. (2026, March 30). Design and implementation of intelligent KPI-based decision support systems for data-driven operations management in U.S. enterprises. SSRN. https://doi.org/10.2139/ssrn.6496239
- Svanberg, J., Heikkilä, M., & Yigitbasioglu, O. (2022). Corporate governance performance ratings with machine learning. Intelligent Systems in Accounting, Finance and Management, 29(3), 168–183. https://doi.org/10.1002/isaf.1525
- Alkaraan, F., Albitar, K., Hussainey, K., & Venkatesh, V. G. (2023). Corporate transformation toward Industry 4.0 and financial performance: The influence of strategic management accounting and governance mechanisms. Technological Forecasting and Social Change, 187, 122199. https://doi.org/10.1016/j.techfore.2022.122199
- Moll, J., & Yigitbasioglu, O. (2022). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. British Accounting Review, 54(1), 101051. https://doi.org/10.1016/j.bar.2021.101051
- Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2021). Big data in accounting: An overview. Accounting Horizons, 35(3), 191–205. https://doi.org/10.2308/HORIZONS-19-121
- Teittinen, H., Pellinen, J., & Järvenpää, M. (2022). ERP systems and management control: New perspectives for organizational performance measurement. Management Accounting Research, 55, 100789. https://doi.org/10.1016/j.mar.2021.100789
- Akhter, T. (2025, October 6). Algorithmic internal controls for SMEs using MIS event logs. TechRxiv. https://doi.org/10.36227/techrxiv.175978941.15848264.v1
- Akhter, T., Alimozzaman, D. M., Hasan, E., & Islam, R. (2025, October). Explainable predictive analytics for healthcare decision support. International Journal of Sciences and Innovation Engineering, 2(10), 921–938. https://doi.org/10.70849/IJSCI02102025105
- Hasan, E. (2025). Big Data-Driven Business Process Optimization: Enhancing Decision-Making Through Predictive Analytics. TechRxiv. October 07, 2025. 10.36227/techrxiv.175987736.61988942/v1
- Al Sany, S. M. A., Rahman, M., & Haque, S. (2025). ERP–MIS Integration for Intelligent Apparel Production Planning. World Journal of Advanced Engineering Technology and Sciences, 17(1), 145–156. https://doi.org/10.30574/wjaets.2025.17.1.1387
- Islam, R. (2026). AI-Integrated Management Information Systems for Manufacturing and Supply Chain Risk Mitigation. Zenodo. https://doi.org/10.5281/zenodo.18349501
- Mirza, S. B., Islam, M. A., Tariq, F., & Shaik, M. H. (2026). Diagnostic analytics for enterprise reporting platforms. Saudi Journal of Engineering and Technology, 11(4), 247–256. https://doi.org/10.36348/sjet.2026.v11i04.009
- Barua, P. (2026). Business intelligence dashboards for operational performance monitoring in enterprise data systems [Manuscript submitted for publication]. Zenodo. https://doi.org/10.5281/zenodo.20120659
- Chokder, R. (2026). Data analytics and dashboard reporting for customer relationship management and sales performance monitoring [Manuscript submitted for publication]. Zenodo. https://doi.org/10.5281/zenodo.20135662
- Sharmin, M., Rahman, M. A., Rohman, H., & Tumpa, S. A. (2026). Business operations monitoring through integrated management information systems. International Journal of Science and Research Archive, 19(3), 309–324. https://doi.org/10.30574/ijsra.2026.19.3.1097
- Alam, M. J., Khayyam, F., Junaid, E., & Ahmed, M. (2026). Intelligent regulatory monitoring and audit trail information systems for enterprise risk and compliance management. International Journal of Science and Research Archive, 19(3), 283–295. https://doi.org/10.30574/ijsra.2026.19.3.1165
- Mim, M., & Akter, M. (2026, January 28). Integration of business intelligence dashboards in administrative decision making. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.6402899
- Rahman, M., Alam, M. S., Al Sany, S. M. A., & Nahar, S. (2026, February 24). Enterprise AI driven data management framework for cross industry decision intelligence and operational optimization. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.6330258
- Nahar, S., Rahman, M., Alam, M. S., & Al Sany, S. M. A. (2026). Intelligent data governance and ethical AI framework for enterprise information systems. Zenodo. https://doi.org/10.5281/zenodo.18839122
- Islam, R. (2025). AI and big data for predictive analytics in pharmaceutical quality assurance.. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5564319
- Al Sany, S. M. A. (2025). The role of data analytics in optimizing budget allocation and financial efficiency in startups. IJSRED – International Journal of Scientific Research and Engineering Development, 8(5), 2287–2297. https://doi.org/10.5281/zenodo.17536325
- Rahman M. (2025). Design and Implementation of a Data-Driven Financial Risk Management System for U.S. SMEs Using Federated Learning and Privacy-Preserving AI Techniques. In IJSRED - International Journal of Scientific Research and Engineering Development (Vol. 8, Number 6, pp. 1041–1052). https://doi.org/10.5281/zenodo.17769869
- Rahman, T. (2026). Financial Risk Intelligence: Real-Time Fraud Detection and Threat Monitoring. Zenodo. https://doi.org/10.5281/zenodo.18176490
- Rashid, M. F. (2026). Management information systems enabled ethical and sustainable apparel sourcing: Supplier compliance and traceability scorecard dashboard. Zenodo. https://doi.org/10.5281/zenodo.19441584
- Ahmed, M. (2026, March 16). Operational risk management in international apparel manufacturing networks. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.6560164
- Alam, M. J. (2026, March 11). Digital compliance management systems for regulatory documentation and risk monitoring in organizational operations. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.6410539
- Alam, M. J. (n.d.). Policy monitoring platforms for institutional governance and organizational accountability. Social Science Research Network. https://doi.org/10.2139/ssrn.6416238
- Alam, M. J. (2026). Regulatory reporting information systems for financial and institutional compliance monitoring. Preprints.org. https://doi.org/10.20944/preprints202603.1198.v1
- Khayyam, F. (2026). Scalable trust and auditability for generative AI in enterprise CRM platforms: A framework and reference architecture. Zenodo. https://doi.org/10.5281/zenodo.19607181
- Mim, M. M. A., Sharif, M. M., Rahman, F., & Nahar, S. (2026). AI-powered decision support systems for sustainable organizations. International Journal of Scientific Research and Engineering Development (IJSRED), 9(1), 423–434. https://doi.org/10.5281/zenodo.18454996
- Khayyam, F. (2026). Design and implementation of generative artificial intelligence-driven automation for enterprise customer relationship management decision support systems. Global Journal of Engineering and Technology Advances, 27(2), 164–177. https://doi.org/10.30574/gjeta.2026.27.2.0089
- Dukkipati, S. S. N. C. (2026, February 9). Design and implementation of scalable AI-driven conversational systems for enterprise-level feedback intelligence and decision support. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6263818
- Mirza, S. B. (2026). Predictive Reliability Engineering for Cloud Scale Business Intelligence Platforms through Anomaly Detection Capacity Optimization and Proactive Support Automation. Zenodo. https://doi.org/10.5281/zenodo.19474845
- Alam, M. J. (2026). Information systems for legal documentation management and policy analysis in institutional governance. Figshare. https://doi.org/10.6084/m9.figshare.31717873
- Alam, M. J. (2026). Digital contract lifecycle management systems for corporate governance and regulatory oversight. Zenodo. https://doi.org/10.5281/zenodo.19007705
- Alam, M. J. (2026). Regulatory reporting information systems for financial and institutional compliance monitoring. Preprints.org. https://doi.org/10.20944/preprints202603.1198.v1
- Akter, T. (2026). AI-driven workforce productivity optimization in U.S. service organizations using KPI-based predictive analytics. Zenodo. https://doi.org/10.5281/zenodo.19311795
- Bhuiyan, M. I. H. (2026). AI-driven customer complaint analytics for systemic risk reduction and consumer protection in the U.S. banking sector. Zenodo. https://doi.org/10.5281/zenodo.19344701
- Islam, R. (2026). Data-driven sales performance evaluation using business analytics. Zenodo. https://doi.org/10.5281/zenodo.19371191
- Hossain, M. I. (2026). Enabled digitalization of container vessel navigation and U.S. port operations using real-time AIS and operational data for shipping and supply chain optimization. Zenodo. https://doi.org/10.5281/zenodo.19441203
- Islam, M. A., Tariq, F., Shaik, M. H., & Mirza, S. B. (2026). Identity-centric security models for enterprise web systems. Saudi Journal of Engineering and Technology, 11(4), 237–246. https://doi.org/10.36348/sjet.2026.v11i04.008
- Akter, T., Afroje, S., Chokder, R., & Bhuiyan, M. I. H. (2026). Workforce productivity measurement models for service-oriented organizations. Saudi Journal of Engineering and Technology, 11(4), 257–265. https://doi.org/10.36348/sjet.2026.v11i04.010
- Bhuiyan, M. I. H., Akter, T., Afroje, S., & Chokder, R. (2026). Operational risk indicators derived from customer interaction data in digital banking platforms. Saudi Journal of Engineering and Technology, 11(4), 266–275. https://doi.org/10.36348/sjet.2026.v11i04.011
- Alam, M. J. (2026). Digital evidence management systems for legal case documentation and investigation records. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.6416718
- Akter, T. (2026, March 30). Design and implementation of intelligent KPI-based decision support systems for data-driven operations management in U.S. enterprises. SSRN. https://doi.org/10.2139/ssrn.6496239
- Khayyam, F. (2026, April 17). Enterprise scale privacy preserving data fabric architecture for multi tenant AI driven customer relationship management platforms. SSRN. SSRN https://doi.org/10.2139/ssrn.6597358
- Dukkipati, S. S. N. C. (2026, May 7). Design and performance evaluation of event-driven microservices for large-scale enterprise data processing. SSRN. https://doi.org/10.2139/ssrn.6730598
- Sharmin, M. (2026). Information system–based project coordination and process improvement in service organizations. Zenodo. https://doi.org/10.5281/zenodo.20382574
- Afroje, S. (2026, June 6). Information system integration for credit card operations and banking service efficiency [Preprint]. Zenodo. https://doi.org/10.5281/zenodo.20508756
- Siddiki, A. (2026, May 9). Intelligent event-driven middleware architecture for scalable financial service integration using Kafka and distributed microservices. SSRN. https://doi.org/10.2139/ssrn.6737940
- Dukkipati, S. S. N. C., Junaid, E., Siddiki, A., & Khayyam, F. (2026). Scalable cloud-native microservices architecture for enterprise AI platforms: Reliability, security, and real-time distributed processing frameworks. International Journal of Science and Research Archive, 19(3), 296–308. https://doi.org/10.30574/ijsra.2026.19.3.1110
- Rahman, M. A., Rohman, H., Tumpa, S. A., & Sharmin, M. (2026). Network monitoring frameworks for enterprise IT infrastructure. Global Journal of Engineering and Technology Advances, 27(3), 064–079. https://doi.org/10.30574/gjeta.2026.27.3.0118
- Chokder, R., Bhuiyan, M. I. H., Akter, T., & Afroje, S. (2026). Enterprise data integration for customer relationship and sales performance monitoring. Scholars Journal of Engineering and Technology, 14(7), 413–421. https://doi.org/10.36347/sjet.2026.v14i07.005
- Hossain, M. I., Rashid, M. F., Barua, P., & Joy, S. H. A. K. (2026). Traceability and compliance monitoring systems in global apparel supply chains. Saudi Journal of Engineering and Technology, 11(7), 644–654. https://doi.org/10.36348/sjet.2026.v11i07.001
- Barua, P., Joy, S. H. A. K., Hossain, M. I., & Rashid, M. F. (2026). Enterprise supply chain performance dashboards for logistics decision support. Global Journal of Engineering and Technology Advances, 28(1), 044–060. https://doi.org/10.30574/gjeta.2026.28.1.0126
- Nahian, A. E., Bhowmick, N., Mirza, S., & Siddiqui, R. (2026). Integrated forecasting and resource allocation models for financial and operational performance management. Saudi Journal of Business and Management Studies, 11(8), 261–270. https://doi.org/10.36348/sjbms.2026.v11i08.001
- Bhowmick, N., Mirza, S., Siddiqui, R., & Nahian, A. E. (2026). Enterprise workflow efficiency assessment through process analytics and performance measurement frameworks. International Journal of Science and Research Archive, 20(2), 58–70. https://doi.org/10.30574/ijsra.2026.20.2.1428
- Akter, E. (September 15, 2025). Sustainable Waste and Water Management Strategies for Urban Civil Infrastructure. Available at SSRN: https://ssrn.com/abstract=5490686 or http://dx.doi.org/10.2139/ssrn.5490686
- Karim, M. A., Zaman, M. T. U., Nabil, S. H., & Joarder, M. M. I. (2025, October 6). AI-enabled smart energy meters with DC-DC converter integration for electric vehicle charging systems. TechRxiv. https://doi.org/10.36227/techrxiv.175978935.59813154/v1
- Rahman, M., Razaq, A., Hossain, M. T., & Zaman, M. T. U. (2025). Machine learning approaches for predictive maintenance in IoT devices. World Journal of Advanced Engineering Technology and Sciences, 17(1), 157–170. https://doi.org/10.30574/wjaets.2025.17.1.1388
- Rahman M.. (October 15, 2025) Integrating IoT and MIS for Last-Mile Connectivity in Residential Broadband Services. TechRxiv. DOI: 10.36227/techrxiv.176054689.95468219/v1
- Islam, R. (2025, October 15). Integration of IIoT and MIS for smart pharmaceutical manufacturing . TechRxiv. https://doi.org/10.36227/techrxiv.176049811.10002169
- Rahman, M. (2025, October 15). IoT-enabled smart charging systems for electric vehicles. TechRxiv. https://doi.org/10.36227/techrxiv.176049766.60280824/v1
- Alam, MS (2025, October 21). AI-driven sustainable manufacturing for resource optimization. TechRxiv. https://doi.org/10.36227/techrxiv.176107759.92503137/v1
- Al Morshed, S. A., Hossain, M. I., Tajik, M. A., & Abdullah, M. S. (2026). Risk-informed construction delivery for resilient public infrastructure under geotechnical and environmental uncertainty. Saudi Journal of Engineering and Technology, 11(8), 698–706. https://doi.org/10.36348/sjet.2026.v11i08.002
- Chokder, R. (2026). ERP-based data integration framework for business operations and managerial decision support. SSRN. https://doi.org/10.2139/ssrn.7186578
- Junaid, A. (2026). Performance optimization of 5G NR networks through mobility management and carrier aggregation configuration. SSRN. https://doi.org/10.2139/ssrn.7202280
- Khalid, M. A. (2026). Structural design and optimization of industrial steel structures for process and power plant facilities. SSRN. https://doi.org/10.2139/ssrn.7205750
- Rohman, H. (2026). AI-powered portable optical biosensors for environmental toxicants or environmental field tests and point of care diagnostics or medical diagnostics or disease detection. SSRN. https://doi.org/10.2139/ssrn.7205318
- Mirza, S., Nahian, A. E., Bhowmick, N., & Siddiqui, R. (2026). Inventory resilience and demand variability modeling for multi-sector organizational operations. Global Journal of Engineering and Technology Advances, 28(2), 015–027. https://doi.org/10.30574/gjeta.2026.28.2.0164
- Hossain, M. I., Tajik, M. A., Abdullah, M. S., & Al Morshed, S. A. (2026). Lifecycle performance governance for smart buildings and critical infrastructure in sustainable urban systems. International Journal of Science and Research Archive, 20(2), 119–131. https://doi.org/10.30574/ijsra.2026.20.2.1545
Reliable enterprise Decision-Support Systems (DSS) require integrated mechanisms for auditability, transparent
reporting, and performance measurement to ensure accountability and high-quality decision-making. However, existing
approaches often separate audit functions from performance monitoring, resulting in fragmented governance and reduced
operational visibility. To address this limitation, this study proposes an integrated Auditability and Performance Monitoring
Framework for enterprise DSS environments. The framework unifies structured reporting workflows, transaction
traceability, KPI-based performance evaluation, and validation procedures within a single architecture. A Decision-Support
Reliability Index (DSRI) is introduced to quantitatively assess overall system effectiveness by integrating key governance
and operational performance indicators. The framework is evaluated using five enterprise-inspired benchmark scenarios
supplemented by sensitivity analysis. Experimental results demonstrate consistent improvements in reporting reliability,
process transparency, compliance efficiency, and operational performance across all scenarios. Even under high-complexity
conditions, the framework maintains stable DSRI values, indicating strong robustness and scalability. The findings confirm
that integrating auditability with performance monitoring significantly enhances governance quality and decision-support
effectiveness in modern enterprise systems.
Keywords :
Enterprise Decision-Support Systems (DSS), Auditability, Performance Monitoring, Data Governance, Reporting Reliability, KPI Analytics, Transaction Traceability, Decision-Support Reliability Index (DSRI).