Evaluating the Accuracy of Neural Network Algorithms in Analyzing Consumer Purchase Patterns: The Impact of AI Technology on Environmental Performance in Pakistan's Shipbuilding Industry
DOI:
https://doi.org/10.62843/jrsr/2024.3a044Keywords:
Neural Network Algorithms, Shipbuilding, AI Technology, Environmental Performance, Eco-Design, Green Procurement, Waste Management, Energy EfficiencyAbstract
The objective of this research is to explore the neural network algorithms Approaches and AI technology on Environmental Performance: The Role of Green Procurement, Eco-Design, Waste Management, and Energy Efficiency in the Shipbuilding sector/Industry of Pakistan. A survey questionnaire was adopted to analyse the impact and the role of Green Procurement, Eco Design, Waste Management, and Energy Efficiency in the Shipbuilding Industry/sector of Pakistan. The respondents were reached through random convenient sampling. More than 300 responses were collected from the shipbuilding sector including supply chain members, technicians, supervisors, executives and managers. The study analyses the responses through the SMART PLS-04. The study finding has exposed that four neural network algorithm approaches in the supply chain Green Procurement (GP), Eco-Design (ED), Waste Management (WM) and Energy Efficiency (EE) have a positive impact on Environmental Performance (EP) in shipbuilding sector of Pakistan. The research is limited to the shipbuilding sector of Pakistan and there are only four approaches have been taken for this study. This research will help concerned managers in the shipbuilding sector of Pakistan to run their operations activities effectively by implementing GP, ED, WM, and EE approaches.
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