Unleashing the power of cloud adoption and artificial intelligence in optimizing resilience and sustainable manufacturing supply chain in the USA

IF 7.3 2区 工程技术 Q1 ENGINEERING, INDUSTRIAL Journal of Manufacturing Technology Management Pub Date : 2024-07-01 DOI:10.1108/jmtm-02-2024-0080
Aamir Rashid, Rizwana Rasheed, Abdul Hafaz Ngah, Noor Aina Amirah
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Abstract

Purpose

Recent disruptions have sparked concern about building a resilient and sustainable manufacturing supply chain. While artificial intelligence (AI) strengthens resilience, research is needed to understand how cloud adoption can foster integration, collaboration, adaptation and sustainable manufacturing. Therefore, this study aimed to unleash the power of cloud adoption and AI in optimizing resilience and sustainable performance through collaboration and adaptive capabilities at manufacturing firms.

Design/methodology/approach

This research followed a deductive approach and employed a quantitative method with a survey technique to collect data from its target population. The study used stratified random sampling with a sample size of 1,279 participants working in diverse manufacturing industries across California, Texas and New York.

Findings

This research investigated how companies can make their manufacturing supply chains more resilient and sustainable. The findings revealed that integrating the manufacturing supply chains can foster collaboration and enhance adaptability, leading to better performance (hypotheses H1-H7, except H5). Additionally, utilizing artificial intelligence helps improve adaptability, further strengthening resilience and sustainability (H8-H11). Interestingly, the study found that internal integration alone does not significantly impact collaboration (H5). This suggests that external factors are more critical in fostering collaboration within the manufacturing supply chain during disruptions.

Originality/value

This study dives into the complex world of interconnected factors (formative constructs in higher order) influencing manufacturing supply chains. Using advanced modeling techniques, it highlights the powerful impact of cloud-based integration. Cloud-based integration and artificial intelligence unlock significant improvements for manufacturers and decision-makers by enabling information processes and dynamic capability theory.

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释放云技术和人工智能的力量,优化美国制造业供应链的复原力和可持续性
目的最近的破坏性事件引发了人们对建立弹性和可持续制造供应链的关注。虽然人工智能(AI)能增强复原力,但仍需开展研究,以了解云技术的应用如何促进集成、协作、适应和可持续制造。因此,本研究旨在通过制造业企业的协作和适应能力,释放云技术和人工智能在优化弹性和可持续绩效方面的力量。研究采用分层随机抽样法,样本量为 1 279 名参与者,他们分别在加利福尼亚州、得克萨斯州和纽约州从事不同的制造业。研究结果本研究调查了企业如何使其制造业供应链更具弹性和可持续性。研究结果表明,整合制造业供应链可以促进协作,增强适应性,从而提高绩效(假设 H1-H7,H5 除外)。此外,利用人工智能有助于提高适应性,进一步增强复原力和可持续性(H8-H11)。有趣的是,研究发现,仅靠内部整合并不会对协作产生显著影响(H5)。原创性/价值本研究深入探讨了影响制造供应链的相互关联因素(高阶形成性构造)的复杂世界。它利用先进的建模技术,强调了基于云的集成的强大影响。基于云的集成和人工智能通过启用信息流程和动态能力理论,为制造商和决策者带来了重大改进。
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来源期刊
Journal of Manufacturing Technology Management
Journal of Manufacturing Technology Management Engineering-Control and Systems Engineering
CiteScore
16.30
自引率
7.90%
发文量
45
期刊介绍: The Journal of Manufacturing Technology Management (JMTM) aspires to be the premier destination for impactful manufacturing-related research. JMTM provides comprehensive international coverage of topics pertaining to the management of manufacturing technology, focusing on bridging theoretical advancements with practical applications to enhance manufacturing practices. JMTM seeks articles grounded in empirical evidence, such as surveys, case studies, and action research, to ensure relevance and applicability. All submissions should include a thorough literature review to contextualize the study within the field and clearly demonstrate how the research contributes significantly and originally by comparing and contrasting its findings with existing knowledge. Articles should directly address management of manufacturing technology and offer insights with broad applicability.
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