Inventory dynamics in process industries: An empirical investigation

Process industry firms have thrived in recent decades, but changes in the markets are currently putting both growth and profitability at risk. In this context, inventory management is increasingly viewed as an essential lever for creating a sustainable competitive advantage. Despite this, many firms struggle to implement best practices because of industry-specific constraints. This research explores how seven fundamental characteristics of process industries drive inventory performance. We empirically investigate four process industries and four peer industries, using financial accounting, credit rating, stock market and trading data and implement a seemingly unrelated regression (SUR) equations model. Our results show that capital intensity, capital costs, transportation costs, delivery time, price volatility, demand uncertainty and gross margin directly affect a company's degree of freedom in terms of inventory management and illustrate that inventory management in process industries follows different dynamics. This study enhances the understanding of inventory drivers and gives practitioners a tool to guide future improvement efforts.