Economic Triggers and Strategic Use of Blended Automation in Semi-Automatic Corrugated Box Manufacturing MSMEs: A Managerial Economics Framework Based on Cobb-Douglas Production Function

Abstract

Financial decisions are very important, especially in Micro, Small and Medium Enterprises (MSMEs) when cost of production outweighs the profits. The increased production leads to inefficiency in operations and reduction in expected quality even when highly trained manpower manages the operations. This leads to loss of profit margins. Increased manpower may also not enhance the profit margins. This is the moment when human led functions must be automated. Further, the shortages in availability of trained manpower and MSMEs being feebly or semi-automated, is aggravating the problem of operational inefficiency. Furthermore, non-availability of funds makes it difficult for MSMEs to afford complete automation. Automation is frequently perceived as a necessary response; however premature or excessive automation often results in financial stress and underutilized capacity. This paper proposes a framework that is economically grounded and adopts selective automation called blended automation combined with parameter sensing, data-based monitoring supported by managerial interventions. This paper uses firm level data of a feebly automated corrugated-box manufacturing firm and used Ordinary Least Square (OLS) and Three-stage Least Squares (3SLS) to estimate the Cobb-Douglas production function.  Estimated output elasticities is used to derive marginal productivity and marginal revenue-marginal cost conditions. This indicates that input material is the predominantly drives the production output while labor and capital input exhibit reducing marginal productivity. The study points out the economic trigger moment at which targeted automation becomes economically justified. This framework aims to provide digitized decision-making tool for MSME firm owners thereby contributing to automation efforts in resource-constrained manufacturing environments in the country.