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Optimizing IoT and Big data Embedded Smart Supply Chains for Sustainable Performance

Optimizing IoT and Big data Embedded Smart Supply Chains for Sustainable Performance

Journal
Impact Score 4.62

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Special Issue Information

Submission Deadline: 31-12-2021
Journal Impact Score: 4.62
Journal Name: Computers and Industrial Engineering
Publisher: Computers and Industrial Engineering

Special Issue Call for Papers


Optimizing IoT and Big data Embedded Smart Supply Chains for Sustainable Performance



Aims and Scope:



The demand for a sustainable and resilient supply chain increases to satisfy customers’ indefinite requirements (Manavalan & Jayakrishna, 2019). Industry 4.0 primarily indicates the vision of optimal industrial production and sustainable & smart supply chain management (Raj et al., 2020; Nakayama et al., 2020). The first three industrial revolutions are only limited to shop floor level, but industry 4.0 is a sophisticated concept evolving through engineering’s support (Napoleone et al., 2020). Based on the recent reviews, manufacturing companies should focus on sustainable development and implement innovations like the “Internet of things (IoT) and Big data” to optimize smart and resilient supply chains for sustainable performance and industry 4.0. Industry 4.0 brings the revolution of sustainable & digital supply chain through the latest technologies (Bueno et al., 2020; Koot et al., 2021)



Supply chain management changes have become necessary because there are many problems with the supply chain, like forecasting issues, maintaining traditional inventory, the delay during distribution, very slow digital transformation, counterfeit consumer goods, excessive carbon gas emission, toxic waste, etc. Those problems can only be solved by optimizing the contemporary technology embedded supply chain. Optimization model in IoT & big data embedded supply chain can minimize the environmental risk (Hampton et al., 2013). IoT is based on the network of physical objects with remote sensors and software to connect and exchange data with other devices over the internet (Vatankhah Barenji et al., 2020). Big data is an extensive and complex data set, and its potential is far beyond the capacity of a conventional database system (Kar and Dwivedi, 2020). These technologies lead towards agility, productivity, sustainability, visibility, interoperability, accuracy, provenance, lower cost, time planning, waste minimization, information exchange, coordination of chain, collaborative decision-making, better business outcomes, and new business opportunities by deepening customer relationships and boosting product development (Mishra et al., 2016; Ben-Daya et al., 2019).



The utilization of big data and IoT in the company can make the supply chain sustainable and robust. A supply chain with IoT & Big data technologies can achieve GPS, weather reports, forecasting, the best schedule for the best possible route, and demand management. With these advents, the enterprise can get the advantage of lower cost, significant performance, and quick delivery. Designers can transform customers’ demands into product features with big data analytics (Qi and Tao, 2018). Data scientists have split the big data analysis into 4Vs: Large Volume, Velocity, Variety, and Veracity (Nguyen et al., 2018). According to International Data Corporation’s (IDC) prediction, Big data will grow at the rate of 13.2 % compound annual growth and expects $274.3 billion worldwide big data analytics (BDA) revenue by 2022. The bigger and complex data will become more stringent and challenging to manage & analyze and execute for business insights.



The company can start up the full potential of data from inside and outside of the enterprise. Big data and predictive analytics models can help logistics and supply chain managers meet internal requirements and make necessary changes in the supply chain network (Waller et al., 2013). Transparent information exchange between customers and suppliers is inevitable to adopt industry 4.0 (Sung, 2018; Zonta et al., 2020). Control on the temperature in cold supply chains can be made possible through time temperature-indicator (TTI) with IoT. Moreover, IoT’s latest supply chain applications are reported to optimize RFID tracking technology, which requires organized, systematic, assimilated approaches to utilize GPS systems and digital technologies for sustainable manufacturing & supply chain (De Vass et al., 2018).



This special issue aims to leverage global capabilities by using the internet and complex data management, better link into the enterprise and Business-to-Business (B2B) system, smart processing and decision-making, higher safety and security, improved maintenance and reduced down-time, improved traceability of resources and products. The use of IoT and Big data in manufacturing, logistics, and supply chain is the promising domain of research that has a tremendous potential to raise productivity and sustainability. This special issue’s primary goal is to provide scholars and experts an opportunity to share the most recent advances in sustainable and resilient supply chains embedded with IoT and Big data. We invite original evidence-based research papers.



Topics of interest include, but not limited to:




Authors should submit a cover letter and a manuscript by December 31, 2021, via the Journal’s online submission site.



Editorial Information



Guest Editors:




References


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