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Cited by 13

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Inventory management and performance of manufacturing firms

Panigrahi, Rashmi Ranjan, Jena, Duryodhan, Tandon, Deepak, Meher, Jamini Ranjan, Mishra, Padma Charan, Sahoo, Ansuman·2021·International Journal of Value Chain Management

Abstract

Inventory management practices (IMP) are prevalent in managing and controlling inventory in an organisation. The study aims to measure the performance of steel manufacturing firms by determining the effect of distribution turnover and inventory automation over competitive strength and operational efficiencies. From the extant literature, it is evident that the above relationship is very limited in the Indian context. Data were collected from five selected manufacturing firms from the state of Odisha, India. Respondents of the study are some key officials, viz. operations manager, production manager, purchase manager and warehouse manager from various manufacturing firms. As per the need of the study, various statistical tools such as correlation, multiple regression, confirmatory factor analysis and Kolmogorov-Smirnov test were used. The outcome of the study concludes that IMP has significant impact on firm performance and also contributes to the existing body of knowledge by helping inventory management practitioners of manufacturing industry.

Overview

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Crossref · 10.1504/ijvcm.2021.116400

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Metadata

Authors
Panigrahi, R. R., Jena, D., Tandon, D., Meher, J. R., Mishra, P. C., & Sahoo, A.
Venue
International Journal of Value Chain Management
Published
2021
Volume
12
Issue
2
Pages
149
ISSN
  • 1741-5357
  • 1741-5365
Cited by
13
References
0
Language
en

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This page
CoChat. (2026). Citation check: Inventory management and performance of manufacturing firms. https://app.cochat.ai/papers/10.1504/ijvcm.2021.116400
The paper
Panigrahi, R. R., Jena, D., Tandon, D., Meher, J. R., Mishra, P. C., & Sahoo, A. (2021). Inventory management and performance of manufacturing firms. International Journal of Value Chain Management. https://doi.org/10.1504/ijvcm.2021.116400

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.