Thin-film-transistor liquid-crystal displays (TFT-LCDs) have gained popularity due to their widespread use in the production of televisions, laptops, and iPads. TFT-LCD firms’ activities that build relationships with suppliers and customers contribute to the emergence of supply networks. A firm’s ability to identify risks, however, is complicated, as TFT-LCD supply networks are becoming increasingly global, complex, and interconnected. The extant research on the topological structure of TFT-LCD supply networks is limited, and the risks identified rely on untested assumptions about the topological structure of such networks. To fill these gaps, this study examines the topological structure and COVID-19 related risk propagation in TFT-LCD supply networks from a dynamic perspective. First, the evolution of the topological structure of TFT-LCD supply networks from 2015 to 2020 is explored by constructing a weighted and undirected supply network. Second, the hidden risky sources in TFT-LCD supply networks are revealed by the proposed risk propagation model. The results show that TFT-LCD supply networks are characterised by a ‘hub and spoke’ feature and an explicit shift from geographical to global cooperation. Additionally, a ‘robust-yet-fragile’ configuration in these supply networks is uncovered, and the hidden risky sources in the main TFT-LCD manufacturers and suppliers and in interfirm cooperations are revealed. These findings will help managers reduce the vulnerability of TFT-LCD supply networks to disruptions and construct more robust and resilient networks.

A cyber-physical supply network is composed of an undirected cyber supply network and a directed physical supply network. Such interdependence among firms increases efficiency but creates more vulnerabilities. The adverse effects of any failure can be amplified and propagated throughout the network. This paper aimed at investigating the robustness of the cyber-physical supply network against cascading failures. Considering that the cascading failure is triggered by overloading in the cyber supply network and is provoked by underload in the physical supply network, a realistic cascading model for cyber-physical supply networks is proposed. We conducted a numerical simulation under cyber node and physical node failure with varying parameters. The simulation results demonstrated that there are critical thresholds for both firm’s capacities, which can determine whether capacity expansion is helpful; there is also a cascade window for network load distribution, which can determine the cascading failures occurrence and scale. Our work may be beneficial for developing cascade control and defense strategies in cyber-physical supply networks.

Enterprises in low-carbon supply chains have been exploring blockchain technology in order to make carbon data transparent. However, there is still some opaque information in the market, such as the value-added service efficiency. How do supply chain members make decisions between information sharing and blockchain adoption? This study considers blockchain adoption and information sharing in a low-carbon supply chain with a single manufacturer and a single retailer. The retailer has private information about value-added services and decides how to share it with the manufacturer. We examine six combined strategies comprised of blockchain scenarios and information sharing formats (no sharing, voluntary sharing, and mandatory sharing). The results indicate that supply chain members prefer blockchain technology under no sharing and voluntary sharing. Under mandatory sharing, supply chain members have incentives to participate in blockchain when the value-added service efficiency exceeds a threshold value. While the manufacturer prefers to obtain the value-added service information, the retailer decides to share information depending on the value-added service efficiency. Besides, supply chain members’ attitude toward the sharing contract also depends on the value-added service efficiency.

In the logistics sector, price competition is no longer the only form of horizontal competition between logistics service integrators; instead, it frequently takes the form of service efficiency competition among chains. Facing fierce market competition, vertical resource integration gradually becomes the trend in logistics industry integration. Using the inverse derivation method and comparative analysis, this study examines the relationship between the overall profit of its chain and that of the rival chain under service efficiency competition with or without the integration strategy. Furthermore, it builds two parallel competition logistics service supply chain models based on the inter-chain Nash competition and Stackelberg game of the chain members. The study results demonstrate that when the cost per unit of service efficiency is fixed, the greater the intensity of competition between chains, the more managers should tend to choose an integration strategy to maximize their profits. More interestingly, we find that the optimal integration decision of the supply chain is independent of the competitive intensity when the cost required to improve the unit service efficiency is extremely high.

The production and sales of electric vehicle lithium-ion batteries (EV LIB) have experienced rapid growth in the past decade, resulting in an extensive and intricate supply chain network (SCN). The SCNs orchestrated by different focal firms are interdependent due to the joint suppliers and customers. This interdependence, coupled with geographical segmentation, introduces vulnerability to the global EV LIB SCN. Focal firms need management insights from the multiplexity of the global EV LIB SCN to address the potential vulnerability. This investigation utilizes the empirical data regarding the supplier–buyer relationships of the top six EV LIB manufacturers in 2020 to construct the multilayered EV LIB SCN. Then, a focal firm-specific analysis is conducted to explore the multiplexity of the global EV LIB SCN, including identifying the influential firms, measuring the structure of SCNs led by different focal firms, and distinguishing the dependence and discrepancies of different focal firms’ SCNs. Furthermore, an SCN vulnerability (SCNV) index was designed to assess the vulnerability of such a multilayered SCN in two disruption scenarios, i.e., single-country blockade and intercountry blockade. The structural analysis can assist focal firms in allocating vulnerability-coping resources more effectively. Besides, the assessment of SCNV can assist managers in identifying potential risk sources beyond their own SCNs.