Digital supply chain transformation: The role of smart technologies on operational performance in manufacturing industry

IF 4.9 Q1 BUSINESS

International Journal of Engineering Business Management Pub Date : 2024-03-21 DOI:10.1177/18479790241234986

Khai Loon Lee, Chi Xin Teong, Haitham M Alzoubi, Muhammad Turki Alshurideh, Mounir El Khatib, Shehadeh Mofleh Al-Gharaibeh

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引用次数: 0

Abstract

This study aims to investigate the impact of digital supply chains and smart technology on the operational performance of the manufacturing industry. Due to the lack of knowledge and guidance in this area, the adoption of smart technology throughout the supply chain is limited, leading to poor operational performance. Therefore, the purpose of this study is to investigate how smart technology and digital supply chain transformation can improve operational performance. To test hypotheses and accomplish study goals, the Resource-Based View (RBV) theory was combined with a quantitative research strategy. The study population of companies was obtained from a manufacturing directory, and a minimum sample size of 107 companies was determined using G*Power. Additionally, 600 online surveys were sent to the manufacturing companies, resulting in a response rate of 17.83%. Data analysis was conducted using Smart-PLS 4.0 software, and eight of the 10 hypotheses were supported. The findings showed that smart technologies completely mediate the link between digital transformation and relationship performance, emphasizing the need for manufacturing organizations to focus on incorporating smart technology into their supply chain to enhance operational performance. The study concludes by presenting theoretical and practical implications, limitations, and recommendations.

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数字化供应链转型：智能技术对制造业运营绩效的作用

本研究旨在探讨数字化供应链和智能技术对制造业运营绩效的影响。由于缺乏这方面的知识和指导，整个供应链对智能技术的采用有限，导致运营绩效不佳。因此，本研究旨在探讨智能技术和数字化供应链转型如何提高运营绩效。为了检验假设并实现研究目标，本研究将资源观（RBV）理论与定量研究策略相结合。研究的公司群体来自制造业目录，并使用 G*Power 确定了 107 家公司的最小样本量。此外，还向制造企业发送了 600 份在线调查问卷，回复率为 17.83%。使用 Smart-PLS 4.0 软件进行了数据分析，结果支持了 10 项假设中的 8 项。研究结果表明，智能技术完全调解了数字化转型与关系绩效之间的联系，这强调了制造企业需要重视将智能技术融入供应链，以提高运营绩效。研究最后提出了理论和实践意义、局限性和建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Engineering Business Management BUSINESS-

CiteScore

7.50

自引率

6.10%

发文量

审稿时长

15 weeks

期刊介绍： The International Journal of Engineering Business Management (IJEBM) is an international, peer-reviewed, open access scientific journal that aims to promote an integrated and multidisciplinary approach to engineering, business and management. The journal focuses on issues related to the design, development and implementation of new methodologies and technologies that contribute to strategic and operational improvements of organizations within the contemporary global business environment. IJEBM encourages a systematic and holistic view in order to ensure an integrated and economically, socially and environmentally friendly approach to management of new technologies in business. It aims to be a world-class research platform for academics, managers, and professionals to publish scholarly research in the global arena. All submitted articles considered suitable for the International Journal of Engineering Business Management are subjected to rigorous peer review to ensure the highest levels of quality. The review process is carried out as quickly as possible to minimize any delays in the online publication of articles. Topics of interest include, but are not limited to: -Competitive product design and innovation -Operations and manufacturing strategy -Knowledge management and knowledge innovation -Information and decision support systems -Radio Frequency Identification -Wireless Sensor Networks -Industrial engineering for business improvement -Logistics engineering and transportation -Modeling and simulation of industrial and business systems -Quality management and Six Sigma -Automation of industrial processes and systems -Manufacturing performance and productivity measurement -Supply Chain Management and the virtual enterprise network -Environmental, legal and social aspects -Technology Capital and Financial Modelling -Engineering Economics and Investment Theory -Behavioural, Social and Political factors in Engineering