Implementation of Machine Learning in Supply Chain Management process for Sustainable Development by Multiple Regression Analysis Approach (MRAA)

Abstract

In the digital technology environment, business enterprises are focusing in enhancing the precision on marketing efforts so as to remain more competitive and enhance profit margins. The application of Machine Learning, Deep Learning, Data analytics in supply chain management (SCM) is getting more popular due to the growing consumer demand and organisation are identifying various ways in order to lower the cost of transportation of goods from one location to another. Through the enhancement in theology across SCM process, the data is highly critical for analysing the location and movement of the networks so as to reduce the overall cost involvement in the goods and services. The supply chain process is highly interconnected through physical flow of goods from raw materials to finished goods, hence there are more volume of data and financial flow across the supply chain. Therefore, it is highly important in analysing the increasing complexity in supply chain and also to understand the implementation of ML in enhancing the SCM process for sustainable development and growth among the various companies. The study is an empirical investigation on the key factors influencing the design and implementation of ML in the SCM process by major companies located in India for achieving sustainable development. A total of 132 respondents were chosen and closed ended questionnaire were distributed to them, based on the data collected the researchers performed detailed statistical analysis like Correlation analysis, Multiple regression analysis using SPSS package.

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