PurposeThe purchase is becoming a more difficult cum tactical decision that affects the cost factor, quality factor, time factor and responsive factor of the buy and maintains them. The purpose of this study is to investigate the effect of inventory management (IM) practices on operational efficiencies (OEs) in Indian steel manufacturing firms.Design/methodology/approachThe study is based on a quantitative research design that has collected information from 321 key officials of Indian steel manufacturing firms. The analyses are carried out with the use of statistical techniques such as confirmatory factor analysis and structural equation modeling (SEM).FindingsThe paper finds that inventory management (IE) has a considerable impact on the OE of steel manufacturing firms in India. The manufacturing industry must highlight the significance of inventory management practice (IMP) for enhancing firm efficiencies in a volatile environment with the help of management teams. Understanding the impact of IE practices on firms’ OE would be helpful for company shareholders and investors.Practical implicationsThe paper suggests the manufacturing industry to emphasize the role of inventory management practices to have better productivity of the firm. This research focuses on the relationship between IMP and OE.Social implicationsEffective and efficient use of inventory will be helpful in reducing the overall cost of production and reduced costs to customers.Originality/valueCompanies require resources to attain a long-term competitive edge. Also, as a consequence, the research is compatible with resource-based view (RBV) theory.

Purpose This study aims to identify the impact of commercial issues (CIs), financial issues (FIs) and corporate affairs (CAs) on operational excellence (OE) of the mining industry. Design/methodology/approach A purposive sample of size 321 was collected from Indian mining executives with more than ten years of exposure to the mining field. Factors are identified and confirmed with the use of confirmatory factor analysis. The structural equation modeling technique was then applied to understand the unique as well as the complex relationships between FI, CI, CA and OE. Findings The results indicate that all three issues, CI, FI and CA, have an influence on OE in the Indian mining industry. Among the variables of the issues considered in this study, marketing products and size and quality of products (from CI); scale of economies (from FI); risk management (from CA); and transportation and machine operation (from OE) are the highest influencing variables. Research limitations/implications This study has its limitations in sampling, the timing of sample collection and their mode. The samples were collected from only massively deposited large mines. Practical implications Business managers of the mining industry will be more vigilant and aware of those indirect variables such as marketing products, size and quality of products, scale of economies and risk management, which can influence OE apart from major influencing variables such as transportation and machine operations and production scheduling. Originality/value To the best of the authors’ knowledge, this is the first study in the mining industry to evaluate the impact of these three issues on OE. The originality of this research lies in testing the CI, FI and CA of the mining industry with OE, which is completely new to this field.

The mineral industry environment is an interlinked chain of activities. Identification of major activities of the mineral industry, termed as critical success factors (CSFs), and their relationship structure will be approachable, productive and efficiency-oriented for the industry to manage. The aim of the article is to develop a relationship structure consisting of CSFs influencing the mineral industry. Sixteen such operational influencing CSFs are identified through a broad literature review and subsequent dialogues held with mineral-field experts. The interpretive structural modelling (ISM) approach is applied for analysing CSFs and finding a relationship structure. The study is carried out in Odisha, Chhattisgarh and Jharkhand, mineral-rich states of India. Identification of CSFs and their relationship is carried out in nine phases sequentially to arrive at the latent structure. This is the only study to develop relationships of CSFs for any mineral industry in India. The findings of the study will provide insights on the relationship structure of CSFs of the mineral industry’s operation and be helpful for improvements in addressing operational difficulties for corporates, as well as academics. Among the 16 CSFs identified, ‘training and skill level’, ‘infrastructure’ and ‘political influence’ have the maximum driving force and are the least dependent. The projected model is helpful in understanding the relationship among CSFs and the business operation as a whole.

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