The Role of Inventory Management in Improving Supply Chain Efficiency: An Illustrative Empirical Study of Manufacturing and Distribution Firms

Author

Adoni Aravind Babu Yadav, Dr RV Srinivas

Abstract

 This article explores the role of inventory management in enhancing supply chain efficiency in manufacturing, logistics, wholesale and retail organizations. A fictional cross-sectional dataset of 120 respondents (warehouse personnel, production managers, supply chain managers, inventory managers and others) who received a 20-item questionnaire was analysed to demonstrate a complete research process including problem identification, literature review, objectives and hypotheses, methodology, statistical analysis, results and recommendations. The descriptive statistics, Cronbach’s alpha, a Chi-square test of independence, one-way ANOVA (with a Kruskal-Wallis robustness test), and Spearman’s correlation were used. Respondents viewed inventory management positively: 70.0% believed it contributes to supply chain efficiency to a great or very great extent (mean 3.96 on a five-point Likert scale), and 70.0-82.5% agreed that inventory management practice benefits costs, service and coordination. However, the results of the inferential statistical analysis did not reveal significant effects. The use of a computerized inventory management system was not related to high perceived supply chain efficiency (χ²=0.169, df=1, p=0.681), and the mean perceived supply chain efficiency scores did not differ significantly between low, medium and high inventory-management-practice groups (F(2, 117)=2.854, p=0.062; η²=0.047), although the medium group had the highest mean score. Due to very low Cronbach’s Alpha (α=0.12), the benefit items were analysed individually. Since the data were fictional, the current article discusses the analytical process and provides recommendations. Thus, the current study highlights the importance of integrated inventory management policies, accurate stock records, and collaborative approaches with suppliers supported by technology.

Keywords

Inventory Management; Supply Chain Efficiency; Demand Forecasting; Inventory Control; Warehouse Management; ERP; Manufacturing and Distribution; ANOVA; Chi-Square.

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References

Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032–1048.

Choi, T.-M., Wallace, S. W., & Wang, Y. (2018). Big data analytics in operations management. Production and Operations Management, 27(10), 1868–1883.

DeHoratius, N., & Raman, A. (2008). Inventory record inaccuracy: An empirical analysis. Management Science, 54(4), 627–641.

Eroglu, C., & Hofer, C. (2011). Lean, leaner, too lean? The inventory–performance link revisited. Journal of Operations Management, 29(4), 356–369.

Gaur, V., Fisher, M. L., & Raman, A. (2005). An econometric analysis of inventory turnover performance in retail services. Management Science, 51(2), 181–194. https://doi.org/10.1287/mnsc.1040.0298

Harris, F. W. (1913). How many parts to make at once. Factory, The Magazine of Management, 10(2), 135–136, 152.

Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546–558. https://doi.org/10.1287/mnsc.43.4.546

Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1–25.

Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502–517. https://doi.org/10.1016/j.jbusres.2020.09.009

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