THE APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE SUPPLY CHAINS OF TEXTILE INDUSTRIES
The need to wear the latest fashion ware, be in style, and look modern isn’t just limited to a few regions, but people all over the world have the same demands in this regard. With globalization taking over the world by storm, the awareness and knowledge in people of fashion and good clothing have taken an even stronger grip. In such circumstances, the textile and garment manufacturing companies have a huge demand to meet and for that to be overcome they must increase their production capacities, enhance their processes and work on their efficiencies. Global firms are making great use of Artificial intelligence and its various tools and branches to better their processes. This research explores how artificial intelligence is beneficial for organizations and goes on to establish significant relationships between artificial intelligence with demand forecast, decision making, and product deliveries. The study is based on the textile sector of Pakistan. The methodology used in this research is a quantitative model and for data collection, a questionnaire was formed and distributed to over 100 employees working in various textile and garment manufacturing companies across Pakistan. The data collected was then analyzed using SPSS and several tests were performed. Furthermore, regression analysis was also performed. A reliability test was also done to see how the scale items under each variable were interrelated and consistent with each other. The results of the test reveal that all the variables had a positive Cronbach alpha value, stating the scale items are consistent and most of them were above 0.7 which shows the consistency is strong. The correlation test results show that artificial intelligence is very much related to all the dependent variables and lastly, the regression tests also prove that Artificial intelligence has a very significant influence on decision making, demand forecasting, and product deliveries of textile firms.
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