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.

The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap has become a policy issue considering ever-increasing factors and their influence on this relation. Most existing studies have explored this interaction from a general perspective, or for developed countries. This paper explores time-series analysis of the dynamic variables and their inter-related influence in both the short and long run on the relationship between modern logistic industry and economic growth—a more specific perspective, particularly for developing countries. Accordingly, we exemplify our analysis by employing the vector autoregression (VAR) model to the most updated time series data of investment in the logistics industry and the economic growth of Pakistan from 1990 to 2018. The empirical findings endorse the previous studies’ outcomes and recognize the importance of sustainable economic development concerning continuously improving the logistics industry. However, a unidirectional relation is observed that economic growth leads to developing the logistics industry—economic growth exerts a significant demand-pull effect on Pakistan’s logistics. It implies that logistic industrial development is comparatively quicker in the geographical areas where economic growth is higher than those areas where economic growth is low. To conclude this study’s findings, logistics industry reforms should prioritize the selected geographical areas in improving the economy that would lead to the modern logistics industry’s development. As the model adopts Pakistan’s context, the overall statistical analysis can be generalized to other developing economies. These results would be of particular interest to strategy makers working in developing countries and help them design and develop modern transportation and logistics, coupled with interlinked technological factors, which would attract investment in the logistics industry for sustainable economic development.

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.

Purpose: The aim of this paper is to provide methods to find the emission source and estimate the amount of waste gas emissions in the electricity coal supply chain, establish the model of the environmental impact (burden) in the electricity coal supply chain, detect the critical factor which causes significant environmental impact, and then identify the key control direction and reduce amount of environmental pollution in the electricity coal supply chain. Design/methodology/approach: In this context, life cycle inventory and life cycle assessment of China’s electricity coal were established in three difference stages: coal mining, coal transportation, and coal burning. Then the outcomes were analyzed with the aim to reduce waste gases emissions’ environmental impact in the electricity coal supply chain from the perspective of sensitivity analysis. Findings: The results and conclusion are as follow: (1) In terms of total waste gas emissions in electricity coal supply chain, CO₂ is emitted in the greatest quantity, accounting for 98-99 wt% of the total waste gas emissions. The vast majority of the CO₂, greater than 93%, is emitted from the power plant when the coal is combusted. (2) Other than CO₂, the main waste gas is CH₄, SO₂ and so on. CH₄ is mainly emitted from Coal Bed Methane (CBM), so the option is to consider capturing some of the CH4 from underground mines for an alternative use. SO₂ is mainly emitted from power plant when the coal is combusted. (3) The environmental burden of coal burning subsystem is greatest, followed by the coal mining subsystem, and finally the coal transportation subsystem. Improving the coal-burning efficiency of coal-fired power plant in electricity coal supply chain is the most effective way to reduce the environmental impact of waste gas emissions. (4) Of the three subsystems examined (coal mining, coal transportation, and coal burning), transportation requires the fewest resources and has the lowest waste gas emissions. However, the energy consumption for this subsystem is significant (excluding the mine mouth case), and transportation distance is found to have a substantial effect on the oil consumption and non-coal energy consumption. (5) In electricity coal supply chain, the biggest environmental impact of waste gas emissions is GWP, followed by EP, AP, POCP and ODP, and regional impact is greater than the global impact. Practical implications: The model and methodology established in this paper could be used for environmental impact assessment of waste gas emissions in electricity coal supply chain and sensitivity analysis in China, and it could supply reference and example for similar researches. The data information on life cycle inventory, impact assessment and sensitivity analysis could supply theory and data reference for waste gas emissions control in electricity coal supply chain. Originality/value: To the best of our knowledge, this is the first time to study the environmental influence of electricity coal supply chain by employing a LCA approach from life cycle of electricity coal.

The e-commerce platforms have facilitated the information flow of cross-border supply chain (CBSC) and attracted a wide range of companies and individuals to participate in cross-border businesses. The tax costs associated with cross-border commodity flow have received unprecedented attention. However, there is a lack of common platforms between international tax planners and CBSC optimizers, and the impact of various tax policies on CBSC operations is still unclear. To fill this gap, this study presents a literature review to elaborate on the interface between taxes and CBSC operations. First, a literature collection approach is constructed, and 71 pertinent publications are identified. Then, a four-dimensional categorization consisting of supply chain themes, research methodologies, tax types, and illustration types was designed to classify and summarize the research content of the selected articles. The results show that (1) there are six main supply chain-related themes, i.e., the supply chain network, the distribution channel structure, product quantity and quality, production outsourcing, the procurement mode, and supply chain emissions, that are significantly affected by taxes. (2) Four types of taxes, including the corporate income tax (CIT), tariffs, environmental taxes and the value-added tax (VAT), have obvious impacts on CBSC operations. (3) Four mainstream methodologies, i.e., mathematical models, empirical models, conceptual models and simulation models, have been applied to explore the tax effects in CBSC modeling. (4) The tax-saving opportunities in CBSC operations mainly come from the following five areas: CIT rate gaps in different regions, special tax regulations such as the tax cross-credit principle and arm’s length principle, regional trade agreements (RTAs), preferential tax policies and export VAT rebate policy. Finally, this research provides a framework to analyze the trade-offs between taxes and traditional CBSC modeling factors. The results can support enterprises in CBSC in dealing with the complex international tax policies.

The modern logistics industry in relation to economic growth and carbon emission has opened new strategic perspectives. Recent research work have analyzed such complex interference from a broad perspective. However, analyzing this overlap needs comprehensive insight into the logistics industry while simultaneously estimating its short-run and long-run effects from regional aspects due to continue-evolving factors and their impact on it. This paper competently analyzes logistics industry components in connection with economic prosperity, energy consumption, trade development, and carbon emission from a more specific regional perspective of a developing country. Methodologically, an autoregressive distributive lag model (ARDL) is employed using correlative evaluation of the dynamic factors and their interactive impact in short and long run on this relation, based on time-series data of Pakistan from 1990 to 2019. The study results endorse the previous studies’ outcomes by recognizing that an increase in carbon emission depends on trade development, energy usage, economic development, and the logistics industry’s various components except for air logistics. However, study results show a unidirectional long-run causality directing from economic development, logistics industry, energy utilization, and trade development to carbon emission. Moreover, these results reveal that this emission is the leading factor to introduce stringent emission standards that further overlap with regional demographics trends, i.e., carbon emission implications. These findings imply that economic development applies a substantial demand-pull impact on national logistics, i.e., regional economic development directs to the growth of the logistics industry in the corresponding region. Consequently, high-income geographical regions have higher long-run risk concerning contemporary developmental activities of the logistics industry when adhering to carbon emission standards. Particularly, the influence of upcoming emission standards must be prioritized when planning the future returns of contemporary research and development activities of the logistics industry in a given geographic area, such as CPEC. Given Pakistan’s perspective, the proposed empirical analysis can be exampled to other developing countries. This analysis may facilitate the design and development of strategies for upcoming financial funding in the modern logistics industry to seek its sustainable development-goals in developing economies.