Multi-Factor Cost Adjustment for Enhanced Export-Oriented Production Capacity in Manufacturing Firms

Abstract

Many manufacturing firms face considerable difficulties in building export capacity and selling their products in international markets. These firms often struggle with unpredictable cost changes, logistical problems along the supply chain, and rising labor expenses that could threaten the competitive edge of manufacturing operations. As there is also a clear absence of practical export models tailored to the unique needs of industrial firms, our study aims to offer a more holistic approach to assessing the impact of cost components on enhancing export-oriented production capacity (EOPC), a perspective not comprehensively provided by the comparative advantage theory, the Heckscher–Ohlin model, or the resource-based theory. While offering a comprehensive analysis of cost components in production, we argue that adjusting the resources, managing the costs, and enhancing production efficiency can significantly improve the EOPC of the manufacturing firms. Using primary data collected from 200 manufacturing firms in Oman during the period 2012–2016, multiple regression analysis followed by descriptive statistical analysis together with a correlation matrix indicates strong positive relationships between the EOPC and factors such as the raw material cost (RMC), labor wages (LW), labor force (LF), and R&D costs (RND). Multicollinearity assessment shows VIF values below the threshold, suggesting reliable estimates. Interaction terms and market conditions were integrated into the model, enhancing its predictive accuracy. Preliminary multiple regression analysis confirms the significant impact of the RMC, LW, LF, and R&D on the EOPC, while highlighting the importance of market conditions in moderating these effects. The model’s adjusted R2 value indicates a strong fit, showing that the independent variables account for a substantial proportion of the variance in the EOPC. Each variable’s importance is reflected in its coefficient, while p-values assess the statistical significance, highlighting which factors are crucial for enhancing export capabilities. Specifically, low p-values for cost components, labor force size, and wages confirm their significant influence, and varying market conditions further modulate these effects, demonstrating the accurate interplay between internal and external factors. Adjustments in cost components under varying market scenarios were analyzed, indicating optimal strategies for increasing the EOPC. Of the five scenarios proposed to distribute the cost either among some variables while keeping others constant or among all the factors, the best-case scenario adjusted all variables together, resulting in a 20% increment in exports. We conclude with some practical and policy implications for governments to support industries in accessing cheap resources through tax reductions on imported raw materials and efficient supply chains, while promoting innovation, technology adoption, and R&D investment at the firm level.