Adoption of Business Analytics as a Data-Driven Approach to Process Optimizations in Mechanical Manufacturing Companies' Operational Performance: Moderating role of Mechanical Technology Utilization
Muhammad Awais Bhatti, Anvar Absamatov
King Faisal University Termez State University
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摘要与影响
The study objective was to test the adoption of business analytics as a data-driven approach to process optimizations in mechanical manufacturing companies' operational performance. The study also tested the moderating role of mechanical technology utilization. Data was collected from 320 employees of mechanical production manufacturing companies and analyzed using Structural Equation Modeling (SEM) with Smart PLS 4. The results showed that data acquisition and tool acquisition have positive and significant influence on the adoption of business analytics. Furthermore, perceived ease of use and perceived usefulness also positively and significantly influence adoption of business analytics. Adoption of business analytics also had a positive and significant influence on operational performance. Furthermore, mechanical technology utilization also positively moderates between adoption of business analytics and operational performance. The study with its specific findings strengthens the technology adoption theories by showing that data acquisition, tool acquisition, perceived ease of use, and perceived usefulness collectively drive business analytics adoption. They also extended operational performance theory by confirming that analytics adoption improves operational performance. Additionally, the moderating effect of mechanical technology utilization offers new theoretical insight into how digital mechanical integration enhances performance relationships. Furthermore, managers should invest in proper data and tool acquisition to support successful analytics adoption. Training employees to enhance ease of use and understanding of analytics tools will further increase adoption levels. Organizations should integrate mechanical technologies with analytics systems to maximize operational performance. These insights help mechanical firms design effective digital transformation and performance improvement strategies.
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经济 / 管理Big Data and Business Intelligence
Digital Transformation in Industry · AI and HR Technologies
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