IoT-based Enhanced Decision-making and data mining for digital transformation of Tobacco Companies

Abstract

Abstract In recent years, the Internet of Things (IoT) has transformed various sectors, including the tobacco industry, by offering digital transformation opportunities. There is enormous potential for improving decision-making and commercial performance in the tobacco sector via integrating IoT-enabled digital transformation and data mining approaches. Tobacco businesses could achieve a competitive advantage in the market by using the features of IoT devices to improve internal processes, stimulate innovation, and provide a more satisfying consumer experience. However, this study aims to increase tobacco firms' market share, performance, core competitiveness, and digital transformation used to boost corporate performance. Data mining will be used to assess the cigarette industry's financial success after the digital revolution. The IoT's layered design helps cigarette companies increase production. Expanding manufacturing capacity in enterprises' production chains may boost productivity and yield at each IoT level. This meta-analysis examines the correlations between tobacco businesses' digital transformation and commercial success, focusing on four major dimensions: digital technology, digital strategy, digital capacity, and digital culture. This framework's functional links and contextual components are explored using IoT. The cigarette industry's success is tied to digital technology's four dimensions, with digital culture having the largest influence. The research uses an upgraded version of the Iterative Dichotomiser 3 (ID3) decision tree approach to assessing cigarette businesses' success after digital transformation. This work added attribute gain correction and information entropy calculations to the ID3 decision tree technique. Through IoT, the ID3 decision tree method's performance has been optimized. This study has shown robust data mining, great efficiency in the IoT, and high accuracy in categorizing varied data sets. Tobacco companies may increase their performance by increasing total competition capacity.