دانلود مقاله پیوند بین صنعت 4.0 و مدیریت زنجیره تامین سبز
خلاصه
1. مقدمه
2. بررسی ادبیات
3. روش تحقیق
4. نتایج و تجزیه و تحلیل
5. یافته ها
6. نتیجه گیری و پیامدها
بیانیه مشارکت نویسنده CRediT
اعلامیه منافع رقابتی
تصدیق
منابع
Abstract
1. Introduction
2. Literature review
3. Research methodology
4. Results and analysis
5. Findings
6. Conclusion and implications
CRediT authorship contribution statement
Declaration of Competing Interest
Acknowledgement
References
چکیده
این مقاله ارتباط بین دو پارادایم - صنعت 4.0 و مدیریت زنجیره تامین سبز (GSCM) را پس از یک مطالعه تجربی انجام شده در صنعت خودرو نشان می‌دهد. 243 پاسخ از متخصصان زنجیره تامین خودرو از اروپا (از جمله بریتانیا) برای آزمایش فرضیه‌های توسعه‌یافته استفاده می‌شود. یک رویکرد یکپارچه و دو مرحله‌ای که مدل‌سازی ساختاری تفسیری و مدل‌سازی معادلات ساختاری را ترکیب می‌کند، یک ساختار سلسله مراتبی چند سطحی برای ایجاد پیوند بین فناوری‌های صنعت 4.0، شیوه‌های زنجیره تامین سبز (GSC) و عملکرد GSC ایجاد می‌کند. این مطالعه اثر غیرمستقیم فن‌آوری‌های صنعت 4.0 را از طریق شیوه‌های GSC بر عملکرد GSC نشان داد. و این پیوند قوی‌تر از تأثیر مستقیم صنعت 4.0 و شیوه‌های GSC در زنجیره تأمین خودرو است. زنجیره‌های تامین آینده باید بر روی هدایت و اتصال فناوری‌هایی مانند اینترنت اشیا (IoT)، سیستم‌های فیزیکی سایبری (CPS) و بلاک چین برای اجرای موثر شیوه‌های GSC تمرکز کنند. شیوه‌های GSC، عمدتاً لجستیک معکوس و خرید سبز، به شدت تحت تأثیر فناوری‌های مخرب هستند و برای بهبود عملکرد GSC حیاتی هستند. شناسایی و پیوند فناوری‌های کلیدی صنعت 4.0 با شیوه‌های GSC به سازمان‌ها در اتخاذ تصمیم‌های مبتنی بر شواهد برای بهبود عملکرد پایداری سود می‌رساند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
The paper evidence the link between two paradigms - Industry 4.0 and Green Supply Chain Management (GSCM) following an empirical study conducted in the automotive industry. 243 responses from the automotive supply chain professionals from Europe (including the UK) are used to test the developed hypotheses. An integrated, two-stage approach combining interpretive structural modelling and structural equation modelling develops a multi-level hierarchical structure for establishing the link between Industry 4.0 technologies, Green Supply Chain (GSC) practices and GSC performance. The study evidenced an indirect effect of Industry 4.0 technologies through GSC practices on GSC performance; and this link is found to be stronger than the direct effect of Industry 4.0 and GSC practices in the automotive supply chains. Future supply chains should focus on driving and linking technologies such as the Internet of Things (IoT), Cyber-Physical Systems (CPS) and Blockchain for effective implementation of GSC practices. GSC practices, mainly reverse logistics and green purchasing, are highly influenced by disruptive technologies and are critical for leading improvement in GSC performance. Identifying and linking key Industry 4.0 technologies with GSC practices will benefit organizations in making evidence-informed decisions for improved sustainability performance.
Introduction
The main aim of Industry 4.0 is to make manufacturing operations/systems efficient, autonomous, and sustainable (Koh et al., 2019). Industry 4.0 is the latest industry transformation, attempting to build smart systems by integrating physical objects with digital technologies (Dalenogare et al., 2018, Fatorachian and Kazemi, 2021). Internet of Things (IoT), Cyber-Physical Systems (CPS), Big Data Analytics (BDA), Additive Manufacturing (AM) and Cloud Computing (CC) are some of the technologies of Industry 4.0. These Industry 4.0 capabilities provide higher productivity and flexibility, but they also help drive the organisations' sustainability goals (Schroeder et al., 2019, Felsberger et al., 2020; Kamble et al., 2020).
Regarding the economic dimension of sustainability, Industry 4.0 technologies can reduce set-up times, lead times, labour and material cost, increase production and design flexibility, and enhance productivity and customization (Wang et al., 2017). In case of the environmental dimension, the reduced energy and resource consumption leads to reduction of waste or Co2 emission across production and supply chain processes (Sarkis and Zhu, 2018). In case of the social dimension, smart factories and manufacturing support employee health and safety by improving working conditions, which results in higher employee satisfaction and motivation (Müller et al., 2018). These benefits highlight growing relationships between Industry 4.0 technologies and sustainability (Liu et al., 2020). However, except a few sporadic studies (such as Li et al., 2020, Bai et al., 2020), this relationship is not well investigated due to the lack of robust evidence (Kamble et al., 2018, de Sousa Jabbour et al., 2018).
Conclusion and implications
Discussion
The paper aimed to assess and evidence the link between Industry 4.0 and GSC practices and how they influence GSC performance in the automotive supply chain following an empirical study. The scarce literature surrounding the relationship between two paradigms - Industry 4.0 and GSCM was the motivation for study. While attempting to address the defined research question, the study found that the implementation of Industry 4.0 technologies will positively impact the implementation of GSC practices in automotive supply chains. Furthermore, Industry 4.0 technologies will also positively improve GSC performance metrics and, therefore, provide evidence that the technologies of Industry 4.0 will assist organizations in transitioning towards sustainable development (Bonilla et al., 2018, Stock et al., 2018). Moreover, it is also apparent that the impact of Industry 4.0 on GSC practices will indirectly lead to an improvement in the green performance of automotive supply chains, which supports the findings made by Kamble et al. (2020).
The study employed an integrated, two-stage approach by combining ISM and SEM methods to provide multiple findings. First, following the ISM method, a multi-level structural relationship among the key Industry 4.0 technologies and GSC practices for improving GSC performance was built. The ten-level hierarchical structure revealed that IoT and CPS are the most significant factors compared to other Industry 4.0 technologies influencing GSC practices. Later, MICMAC analysis supported in developing a driving and dependence power matrix. Within GSC practices, it was found that RL carried the highest driving power, strongly influencing GP and SCEC (Cluster II in Fig. 4). In linking factors, although CC, ME and BC carry the same level of dependence power on other high-level Industry 4.0 technologies, BC carries the highest driving power for linking Industry 4.0 technologies with GSC practices and other SC processes (Cluster III in Fig. 4).