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International Journal of Academic Research in Accounting, Finance and Management Sciences

Open Access Journal

ISSN: 2225-8329

When Information is not Enough: Replenishment Uncertainty and the Value of Decision Information Use in SME Inventory Management

Nurziana Mohd Atan, Mutilah Mohamad, Ahmad Amru Mohamad Zaid

http://dx.doi.org/10.6007/IJARAFMS/v16-i4/29283

Open access

This study examines whether replenishment decision uncertainty (RDU) conditions the association between decision information use (DIU) and perceived replenishment decision effectiveness (RDE) in small and medium-sized enterprises (SMEs). Grounded in Organisational Information Processing Theory, a survey of 360 SME respondents in Selangor, Malaysia, using purposive sampling in October 2026 was analysed through standardised composite-score regression, heteroskedasticity-consistent inference and 2,500-resample percentile bootstrap intervals. DIU was positively associated with RDE at mean uncertainty (? = 0.371), and the DIU × RDU interaction was positive (? = 0.115; 95% bootstrap CI [0.017, 0.206]). Adding the interaction increased explained variance from 0.137 to 0.151 (?R² = 0.014). Conditional DIU slopes were 0.256, 0.371 and 0.485 at low, average and high uncertainty. However, the RDU measure exhibited limited measurement quality (Cronbach’s ? = 0.662; composite reliability = 0.683; average variance extracted = 0.433). The findings offer a cautious, decision-specific illustration of uncertainty as a statistical boundary condition rather than proof of causal inventory-performance gains. Further measurement refinement and independent operational outcomes are important for corroboration.

Abdellatif, M. A. M., Abubakar, A. M., Elayan, M. B. H., & Hayajneh, J. A. M. (2024). Business analytics capabilities and decision quality: The mediating roles of decision speed and comprehensiveness. Information Systems Management, 41(1), 91–108. https://doi.org/10.1080/10580530.2023.2179704
Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political Analysis, 14(1), 63–82. https://doi.org/10.1093/pan/mpi014
Cao, G., Duan, Y., & Li, G. (2015). Linking business analytics to decision making effectiveness: A path model analysis. IEEE Transactions on Engineering Management, 62(3), 384–395. https://doi.org/10.1109/TEM.2015.2441875
DeHoratius, N., & Raman, A. (2008). Inventory record inaccuracy: An empirical analysis. Management Science, 54(4), 627–641. https://doi.org/10.1287/mnsc.1070.0789
Galbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4(3), 28–36. https://doi.org/10.1287/inte.4.3.28
Jonsson, P., & Myrelid, P. (2016). Supply chain information utilisation: Conceptualisation and antecedents. International Journal of Operations & Production Management, 36(12), 1769–1799. https://doi.org/10.1108/IJOPM-11-2014-0554
Lem, K. W. (2024). Data analytics strategy and internal information quality. Contemporary Accounting Research, 41(2), 1376–1410. https://doi.org/10.1111/1911-3846.12942
Li, S., & Lin, B. (2006). Accessing information sharing and information quality in supply chain management. Decision Support Systems, 42(3), 1641–1656. https://doi.org/10.1016/j.dss.2006.02.011
Nordin, M. S., Hussin, A. R. C., & Zaid, A. A. M. (2025). Key components for evaluating paid digital advertising (PDA) performance for SMEs in Malaysia. International Journal of Academic Research in Business and Social Sciences, 15(12), 1806–1813. https://doi.org/10.6007/IJARBSS/v15-i12/27302
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
Raj, A., Kumar, R. R., Narayanan, S., Kirca, A. H., & Jeyaraj, A. (2025). Analytics capability, supply chain capabilities, and operational performance: A meta-analytic investigation. Journal of Operations Management, 71(6), 786–805. https://doi.org/10.1002/joom.1376
Rashid, A., Rasheed, R., Ngah, A. H., Jayaratne, M. D. R. P., Rahi, S., & Tunio, M. N. (2024). Role of information processing and digital supply chain in supply chain resilience through supply chain risk management. Journal of Global Operations and Strategic Sourcing, 17(2), 429–447. https://doi.org/10.1108/JGOSS-12-2023-0106
Saha, E., & Rathore, P. (2024). The impact of healthcare 4.0 technologies on healthcare supply chain performance: Extending the organizational information processing theory. Technological Forecasting and Social Change, 201, Article 123256. https://doi.org/10.1016/j.techfore.2024.123256
Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107–120. https://doi.org/10.1007/s11336-008-9101-0
Teerasoponpong, S., & Sopadang, A. (2022). Decision support system for adaptive sourcing and inventory management in small- and medium-sized enterprises. Robotics and Computer-Integrated Manufacturing, 73, Article 102226. https://doi.org/10.1016/j.rcim.2021.102226
Tiwari, M., Bryde, D. J., Stavropoulou, F., Dubey, R., Kumari, S., & Foropon, C. (2024). Modelling supply chain visibility, digital technologies, environmental dynamism and healthcare supply chain resilience: An organisation information processing theory perspective. Transportation Research Part E: Logistics and Transportation Review, 188, Article 103613. https://doi.org/10.1016/j.tre.2024.103613
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099
Zaid, A. A. M., & Hussin, A. R. C. (2024). From ink to insight: A methodology review of questionnaire design and validation for crowdfunding in social media. International Journal of Academic Research in Business and Social Sciences, 14(1), 1156–1171. https://doi.org/10.6007/IJARBSS/v14-i1/20530

Atan, N. M., Mohamad, M., & Zaid, A. A. M. (2026). When Information is not Enough: Replenishment Uncertainty and the Value of Decision Information Use in SME Inventory Management. International Journal of Academic Research in Accounting, Finance and Management Sciences, 16(4), 470–480.