Measuring the Impact of Inventory and Marketing on Production Smoothening in a Utility Sector: A Panel Data Approach

Utility sector is the foundation of economic growth that ensures energy security and industrial productivity along with influencing the living standards especially for the developing countries. The present study critically examines the progressing landscape of India’s utility sector, focusing on demand side drifts, executive challenges, financial performances and technological improvements. The study uses extensive panel data of 26 major firms of the utility sector listed in Bombay Stock Exchange (BSE) sectoral indices over the period of 10 years (2013-2023). The panel data analysis includes multiple linear regression modelling, random effect analysis and fixed effect regression models capture the heterogeneity in the data. The regression model indicates that change in cost of goods sold (proxy variable of demand), marketing expenses, profit before interest and tax (PBIT) and inventories are significantly impacting the change in cost of production (proxy variable for production). Between ordinary least square (OLS) and random effect, Breusch pagan test concluded that random effect is better approach which shows time invariability. After that Hausman test confirms that there is temporal dynamism present in data and hence the fixed effect prevails. The study provides valuable insights for optimizing production smoothening and hence the operational efficiency based on financial performance.