The Impact of Digital Twins on Local Industry Symbiosis Networks in Light of the Uncertainty Caused by the Public Crisis

The Impact of Digital Twins on Local Industry Symbiosis Networks in Light of the Uncertainty Caused by the Public Crisis

Ziyue Chen (Norwegian University of Science and Technology, Norway) and Lizhen Huang (Norwegian Univeristy of Science and Technology, Norway)
DOI: 10.4018/IJISSCM.20220101
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Abstract

Digital twins provide a solution for information-sharing between enterprises, thereby alleviating uncertainties in the supply chain. In light of the public crisis caused by COVID-19, the authors suggest a signal game model for a two-stage supply chain with two suppliers and two manufacturers. Based on the model, the impact of the digital twin platform on the profits of the local industrial symbiosis network is analyzed. The results show that the uncertainty of supply and demand caused by the public crisis has led to fluctuations in profits and profit volatility. Under this influence, suppliers are willing to participate in information-sharing on the digital twin platform, but manufacturers are less willing to participate. Moreover, application of the digital twin platform in information-sharing is conducive to maintaining and promoting the smooth operation of the industrial chain under these conditions of uncertainty.
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Introduction

The industrial symbiosis (IS) network refers to the long-term cooperative symbiosis formed by the transfer and exchange of material, energy, knowledge, and human and technological resources between companies within a region. The network aims to obtain both environmental and competitive benefits (Wang, Mishima, & Adachi, 2021). The enterprise-level IS network and hybrid network, including IS and traditional modes of manufacturing, are newer endeavours in Norway. However, COVID-19 has caused economic turmoil worldwide since the beginning of 2020. Except for some basic industries (i.e., medical, public security, food retailing, etc.), most industries have suffered a severe shock. Thus, Norway is experiencing has its highest unemployment rate since World War II.

COVID-19 has brought uncertainty to the manufacturing industry and production process due to uncertain supplies, transportation disruption, and indeterminate demand (Shrivastava, Ernst, & Krishnamoorthy, 2019). In addition, many companies on the IS network have not established a fixed mode of information communication and transaction. When dealing with shocks like COVID-19, difficulties in information sharing and communication lead to greater challenges than faced by companies in the traditional supply chain. First, the material supply is highly uncertain. It is impossible to order recycled materials or predict their output because recycled materials are not a mainstream product of the suppliers. The output of recycled materials depends on the output of mainstream products (Liao & Li, 2016). Greater instability of mainstream product supply chains during COVID-19 makes their supply on the symbiosis network more unstable. Second, the costs and environmental impacts of production plans based on renewable materials must be evaluated. Availability of recycled materials is low and quality is unstable. Compared with traditional methods like landfills and incineration, the renewable remanufacturing processes may lead to unexpectedly high production costs, which cause more environmental pollution (Prosman & Sacchi, 2018). However, during COVID-19, communication between companies was restricted and could not be assessed in due time.

To solve this uncertain challenge, more information sharing between enterprises on the network is necessary (Chan, Liu, & Szeto, 2017; Kiil et al., 2019). Digital Twins (DT), as an important technology for the realization of Industry 4.0, can combine the Internet of things (IoT), artificial intelligence (AI), machine learning, and software analysis with spatial network diagrams to create real-time digital simulation models. These models are updated and changed as the physical copy changes (Zhang et al., 2019). As an emerging solution for data integration and real-time processing to realize intelligent production, the DT platforms have the advantages of real-time data transmission, data analysis, and information visualization (Qi & Tao, 2018). This provides a potential solution for information communication of enterprises on the current IS network. However, there is limited research on the impact of the DT platform on the IS networks.

The authors of this study analyse the impact of the DT-based vertical information sharing between enterprises in the local IS network under a public crisis represented by COVID-19. It aims to illustrate the economic impact of the DT platform’s information-sharing function on the IS supply network. First, the authors establish a signal game model framework to describe a mixed IS network composed of two suppliers and two manufacturers. Second, based on the scenario analysis, the authors model three scenarios in which two manufacturing companies agree or disagree to share demand information with suppliers through the DT platform. Based on the solution of the models, the authors compare the consequences of these decisions and discover the influence of the platform on the amount and stability of enterprise profits.

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