INTEGRATING IOT AND BIG DATA ANALYTICS FOR ENHANCED SUPPLY CHAIN PERFORMANCE IN INDUSTRIAL ENGINEERING SECTORS: A CROSS-MARKET STUDY

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Abstract

Integrating the Internet of Things (IoT) and big data analytics revolutionizes supply chain management across industrial engineering sectors, offering unprecedented opportunities for enhancing efficiency, responsiveness, and competitive advantage. This study employs a qualitative research design, leveraging expert interviews to explore the multifaceted impact of these technologies on supply chain performance. Findings underscore the critical importance of strategic alignment, leadership support, and a clear focus on business objectives for successful technology implementation. Enhanced real-time visibility, improved decision-making, and operational efficiency are identified as consistent benefits across sectors. However, the specific outcomes and applications vary according to industry-specific challenges and priorities. Despite the rich insights gained, the study acknowledges the limitations inherent in its qualitative approach. It suggests avenues for future research, including quantitative analyses and deeper dives into sector-specific implementations. This research contributes to a better understanding of how IoT and big data analytics can be effectively integrated into supply chains, providing a foundation for organizations seeking to navigate the complexities of digital transformation in an interconnected global marketplace.
整合物联网和大数据分析,提高工业工程行业的供应链绩效:跨市场研究
物联网(IoT)与大数据分析的结合彻底改变了工业工程领域的供应链管理,为提高效率、响应速度和竞争优势提供了前所未有的机遇。本研究采用定性研究设计,利用专家访谈来探讨这些技术对供应链绩效的多方面影响。研究结果强调了战略调整、领导支持和明确业务目标对于成功实施技术的至关重要性。增强实时可视性、改善决策和提高运营效率被认为是各行业的一致优势。不过,具体成果和应用因行业的特定挑战和优先事项而异。尽管获得了丰富的见解,但本研究承认其定性方法存在固有的局限性。它提出了未来研究的途径,包括定量分析和深入研究特定行业的实施情况。本研究有助于更好地理解如何将物联网和大数据分析有效地整合到供应链中,为企业在互联互通的全球市场中应对复杂的数字化转型奠定基础。
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