Black swan events such as the coronavirus (COVID-19) outbreak cause substantial supply chain disruption risks to modern companies. In today’s turbulent and complex business environment, supply chain resilience and robustness as two critical capabilities for firms to cope with disruptions have won substantial attention from both the academia and industry. Accordingly, this study intends to explore how digitalization helps build supply chain resilience and robustness. Adopting organizational information processing theory, it proposes the mediating effect of supply chain collaboration and the moderating effect of formal contracts. Using survey data of Chinese manufacturing firms, the study applied structural equation modelling to test the research model. Results show that digitalization has a direct effect on supply chain resilience, and supply chain collaboration can directly facilitate both resilience and robustness. Our study also indicates a complementary mediating effect of supply chain collaboration on the relationship between digitalization and supply chain resilience and an indirect-only mediation effect on the relationship between digitalization and supply chain robustness. Findings reveal the differential roles of digitalization as a technical factor and supply chain collaboration as an organizational factor in managing supply chain disruptions. Paradoxically, formal contracts enhance the relationship between digitalization and supply chain resilience but weaken the relationship between supply chain collaboration and supply chain resilience. The validation of moderating effects determines the boundary conditions of digitalization and supply chain collaboration and provides insights into governing supply chain partners’ behavior. Overall, this study enhances the understanding on how to build a resilient and robust supply chain.

Coupling analysis of passenger and train flows is an important approach in evaluating and optimizing the operation efficiency of large-scale urban rail transit (URT) systems. This study proposes a passenger–train interaction simulation approach to determine the coupling relationship between passenger and train flows. On the bases of time-varying origin–destination demand, train timetable, and network topology, the proposed approach can restore passenger behaviors in URT systems. Upstream priority, queuing process with first-in-first-serve principle, and capacity constraints are considered in the proposed simulation mechanism. This approach can also obtain each passenger’s complete travel chain, which can be used to analyze (including but not limited to) various indicators discussed in this research to effectively support train schedule optimization and capacity evaluation for urban rail managers. Lastly, the proposed model and its potential application are demonstrated via numerical experiments using real-world data from the Beijing URT system (i.e., rail network with the world’s highest passenger ridership).

Named entity recognition (NER) is essential in many natural language processing (NLP) tasks such as information extraction and document classification. A construction document usually contains critical named entities, and an effective NER method can provide a solid foundation for downstream applications to improve construction management efficiency. This study presents a NER method for Chinese construction documents based on conditional random field (CRF), including a corpus design pipeline and a CRF model. The corpus design pipeline identifies typical NER tasks in construction management, enables word-based tokenization, and controls the annotation consistency with a newly designed annotating specification. The CRF model engineers nine transformation features and seven classes of state features, covering the impacts of word position, part-of-speech (POS), and word/character states within the context. The F1-measure on a labeled construction data set is 87.9%. Furthermore, as more domain knowledge features are infused, the marginal performance improvement of including POS information will decrease, leading to a promising research direction of POS customization to improve NLP performance with limited data.

Digital technologies (DTs) can assist businesses in coping with supply chain (SC) disruptions caused by unpredictability, such as pandemics. However, the current knowledge of the relationship between DTs and supply chain resilience (SCR) is insufficient. This study draws on information processing theory to develop a serial mediation model to address this deficiency. We analyze a sample set consisting of 264 Chinese manufacturers. The empirical results reveal that digital supply chain platforms (DSCPs), as well as supply chain traceability (SCT) and supply chain agility (SCA), fully mediate the favorable association between DTs and SCR. Specifically, the four significant indirect paths indicated that firms can improve SCR only if they use DTs to directly or indirectly improve SCT and SCA (through DSCPs). Our study contributes to the literature on resilience by examining the possible mechanism of mediation through which DTs influence SCR. The findings also offer essential insights for firms to modify their digital strategies and thrive in a turbulent environment.

Quality 4.0 is an emerging concept that has been increasingly appreciated because of the intensification of competition, continually changing customer requirements and technological evolution. It deals with aligning quality management practices with the emergent capabilities of Industry 4.0 to improve cost, time, and efficiency and increase product quality. This article aims to comprehensively review extant studies related to Quality 4.0 to uncover current research trends, distil key research topics, and identify areas for future research. Thus, 46 journal articles extracted from the Scopus database from 2017 to 2022 were collected and reviewed. A descriptive analysis was first performed according to the year-wise publication, sources of publication, and research methods. Then, the selected articles were analyzed and classified according to four research themes: Quality 4.0 concept, Quality 4.0 implementation, quality management in Quality 4.0, and Quality 4.0 model and application. By extracting the literature review findings, we identify the Quality 4.0 definitions and features, develop the quality curve theory, and highlight future research opportunities. This study supports practitioners, managers, and academicians in effectively recognizing and applying Quality 4.0 to enhance customer satisfaction, achieve innovation enterprise efficiency, and increase organizational competitiveness in the era of Industry 4.0.

With the development of the bike-sharing system (BSS) and the introduction of green and low carbon development, the environmental impacts of BSS had received increasing attention in recent years. However, the emissions from the rebalancing of BSS, where fossil-fueled vehicles are commonly used, are usually neglected, which goes against the idea of green travel in a sharing economy. Previous studies on the bike-sharing rebalancing problem (BRP), which is considered NP-hard, have mainly focused on algorithm innovation instead of improving the solution model, thereby hindering the application of many existing models in large-scale BRP. This study then proposes a method for optimizing the CO₂ emissions from BRP and takes the BSS of Beijing as a demonstration. We initially analyze the spatial and temporal characteristics of BSS, especially the flow between districts, and find that each district can be independently rebalanced. Afterward, we develop a rebalancing optimization model based on a partitioning strategy to avoid deciding the number of bikes being loaded or unloaded at each parking node. We then employ the tabu search algorithm to solve the model. Results show that (i) due to over launch and lack of planning in rebalancing, the BSS in Beijing shows great potential for optimization, such as by reducing the number of vehicle routes, CO₂ emissions, and unmet demands; (ii) the CO₂ emissions of BSS in Beijing can be reduced by 57.5% by forming balanced parking nodes at the end of the day and decreasing the repetition of vehicle routes and the loads of vehicles; and (iii) the launch amounts of bikes in specific districts, such as Shijingshan and Mentougou, should be increased.

The construction industry is a major contributor to environmental pollution. The effect of the construction industry on the environment may be mitigated using eco-friendly construction materials, such as biocomposites. Once developed, biocomposites may offer a viable alternative to the current materials in use. However, biocomposites are lagging in terms of adoption and eventual use in the construction industry. This article provides insights into the steps for biocomposites to become a product that is ready to use by the construction industry in a structural role. The development and the adoption of such a material is tackled with the use of two concepts, i.e., technology readiness level and roadmapping, and explored in a case study on the “liquid wood”. Furthermore, interviews in the construction industry are carried out to identify the industry’s take on biocomposites. A customized roadmap, which underlines a mostly nontechnical perspective concerning this material, has emerged. Additionally, the adoption and diffusion issues that the “liquid wood” may encounter are outlined and complemented with further recommendations.

Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber–physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.

During the COVID-19 pandemic, the current operating environment of pharmaceutical supply chain (PSC) has rapidly changed and faced increasing risks of disruption. The Internet of Things (IoT) and blockchain not only help enhance the efficiency of PSC operations in the information technology domain but also address complex related issues and improve the visibility, flexibility, and transparency of these operations. Although IoT and blockchain have been widely examined in the areas of supply chain and logistics management, further work on PSC is expected by the public to enhance its resilience. To respond to this call, this paper combines a literature review with semi-structured interviews to investigate the characteristics of PSC, the key aspects affecting PSC, and the challenges faced by PSC in the post-pandemic era. An IoT–blockchain-integrated hospital-side oriented PSC management model is also developed. This paper highlights how IoT and blockchain technology can enhance supply chain resilience and provides a reference on how PSC members can cope with the associated risks.

A smart society is an advanced form of society following agricultural society, industrial society, and information society, with digital data processing system as its main carrier. However, the governance of a smart society still faces many challenges. In view of this problem, first, this research constructs a smart society governance modernization strategy. Second, the innovation mode of a society governance mechanism driven by digital technology is proposed, including the precise intellectual control of a digital twin, the intelligent ubiquitous sensing of the Internet of Things, the empowerment remodeling of a blockchain and the livelihood service of artificial intelligence. Third, this study systematically explores the practice of smart society governance modernization from the aspects of basic information platform construction, evaluation system construction, application demonstration of epidemic prevention and control driven by big data, support of spatial intelligence and artificial intelligence technology for people’s livelihood, smart campus, public resources, and data governance application demonstration to provide theoretical guidance for promoting digital technology innovation in the process of the governance of a smart society.

The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.

Building an effective resilient supply chain system (RSCS) is critical and necessary to reduce the risk of supply chain disruptions in unexpected scenarios such as COVID-19 pandemic and trade wars. To overcome the impact of insufficient raw material supply on the supply chain in mass disruption scenarios, this study proposes a novel RSCS considering product design changes (PDC). An RSCS domain model is first developed from the perspective of PDC based on a general conceptual framework, i.e., function-context-behavior-principle-state-structure (FCBPSS), which can portray complex systems under unpredictable situations. Specifically, the interaction among the structure, state and behavior of the infrastructure system and substance system is captured, and then a quantitative analysis of the change impact process is presented to evaluate the resilience of both the product and supply chain. Next, a case study is conducted to demonstrate the PDC strategy and to validate the feasibility and effectiveness of the RSCS domain model. The results show that the restructured RSCS based on the proposed strategy and model can remedy the huge losses caused by the unavailability of raw materials.

The adverse impact of the outbreak of COVID-19 has reduced ports’ operational efficiency. In addition, ports and inland logistics providers are generally independent of each other and difficult to work together, which leads to time loss. Thus, as the core player, ports can integrate with inland logistics providers to improve the efficiency and resilience of maritime supply chains. This study examines the strategic options of two competing maritime supply chains consisting of ports and inland logistics providers. We investigate the impact of cooperation between ports and inland logistics providers and government regulation on the maritime supply chain by comparing members’ optimal pricing and overall social welfare under centralized, decentralized, and hybrid scenarios. Results indicate that the hybrid scenario is an equilibrium strategy for maritime supply chain, although this strategy is not optimal for governments seeking to improve supply chain resilience and maximize social welfare. Furthermore, observations show that through government economic intervention, both seaborne supplies can be incentivized to adopt an integrated strategy, and business and society can achieve a win–win situation.

Although China’s construction machinery thrives to meet the needs of construction, a number of challenges still remain to be overcome, such as lack of thorough knowledge of regional disparities and several limitations in terms of carbon emissions and economic development. Meanwhile, a low-carbon economy was proposed and implemented in China. This research aims to investigate the differences in industrial agglomeration of construction machineries and further explore the relationship between industrial agglomeration and low-carbon economy. On this basis, spatiotemporal analysis was performed to evaluate the levels of industrial agglomeration in different regions based on the situations of China’s construction machinery industry. Furthermore, this study explored the interaction between industrial agglomeration and low-carbon economy utilizing the coupling coordination analysis method. Results showed that the coupling coordination of the two subsystems was extremely unbalanced in 2006, and it maintained an increasing trend, reaching a relatively high level in 2018. Finally, suggestions, such as establishing a policy guarantee system and implementing variable policies in different regions, were proposed to provide guidelines for the government decision-making and promote the sustainable development of China’s construction machinery industry.

Cloud warehousing service (CWS) has emerged as a promising third-party logistics service paradigm driven by the widespread use of e-commerce. The current CWS billing method is typically based on a fixed rate in a coarse-grained manner. This method cannot reflect the true service value under the fluctuating e-commerce logistics demand and is not conducive to CWS resilience management. Accordingly, a floating mechanism can be considered to introduce more flexible billing. A CWS provider lacks sufficient credibility to implement floating mechanisms because it has vested interests in terms of fictitious demand. To address this concern, this report proposes a blockchain-enabled floating billing management system as an overall solution for CWS providers to enhance the security, credibility, and transparency of CWS. A one-sided Vickrey–Clarke–Groves (O-VCG) auction mechanism model is designed as the underlying floating billing mechanism to reflect the real-time market value of fine-grained CWS resources. A blockchain-based floating billing prototype system is built as an experimental environment. Our results show that the O-VCG mechanism can effectively reflect the real-time market value of CWSs and increase the revenue of CWS providers. When the supply of CWS providers remains unchanged, allocation efficiency increases when demand increases. By analyzing the performance of the O-VCG auction and comparing it with that of the fixed-rate billing model, the proposed mechanism has more advantages. Moreover, our work provides novel managerial insights for CWS market stakeholders in terms of practical applications.

The COVID-19 outbreak has caused uncertainty risk surges, increased sustainable supply chain vulnerabilities, and challenges to sustainable supply chain resilience (SSCR) management. Therefore, improving SSCR is necessary to alleviate vulnerabilities, and SSCR management must generate large capital investments. However, the economic downturn brought about by the COVID-19 epidemic has made some companies have limited budgets that can be used to improve SSCR. Therefore, the design of resilience solutions needs to fully consider the constraints of budgetary costs. Most of the existing related literature only discusses optimal resilience solutions under certain cost constraints, so such resilience solutions cannot be applied to most enterprises. In this study, we set the cost constraint as a variable quantity, using resilience efficiency and customer satisfaction as indicators, to determine the changing laws of optimal resilience strategies when cost constraints change. These rules can be applied to enterprises with different budgeted costs. Our findings suggest that companies should prioritize sacrificing resilience measures (RMs) related to adaptive capacity when budget costs gradually decline, and RMs related to absorptive capacity are indispensable at all budget levels. Furthermore, the pursuit of environmental and social sustainability cannot be abandoned, no matter how limited the flexible budget may be.

In the post-pandemic era, food supply chains and firms therein are facing unprecedented severe challenges, because once infection is detected, numerous products must be recalled or abandoned, and both suppliers and retailers in the supply chain suffer enormous loss. To survive under the pandemic, retailers have adopted different sourcing strategies, such as contingent sourcing, which, in turn, affect the upstream suppliers and hence the resilience of the whole supply chain. With the rapid development of digital technologies, retailers nowadays can utilize blockchain as a reliable and efficient way to reduce product risk and hence advance the resilience of food supply chains by improving product traceability and inspection accuracy, and making sourcing transparent. In this paper, we develop a game-theoretic model to investigate the interrelation between the retailer’s decisions on blockchain adoption and sourcing strategies. We consider that a retailer originally orders from a risky supplier while conducting an imperfect inspection to detect infected products before selling. The retailer may speculatively keep on ordering from the risky supplier or adopt contingent sourcing by ordering from an alternative safe supplier. The retailer also has an option to implement blockchain to improve the inspection accuracy and product traceability. We derive the optimal retail prices under different sourcing strategies with and without blockchain adoption and then analyze the incentives for sourcing strategy and blockchain adoption. Then, we identify the conditions of an all-win situation for food retailer, supplier, supply chain resilience, and consumers with/without government subsidy. Finally, we extend to consider the situation that some consumers have health-safety concerns and preferences for blockchain adoption.

Logistics networks (LNs) are essential for the transportation and distribution of goods or services from suppliers to consumers. However, LNs with complex structures are more vulnerable to disruptions due to natural disasters and accidents. To address the LN post-disruption response strategy optimization problem, this study proposes a novel two-stage stochastic programming model with robust delivery time constraints. The proposed model jointly optimizes the new-line-opening and rerouting decisions in the face of uncertain transport demands and transportation times. To enhance the robustness of the response strategy obtained, the conditional value at risk (CVaR) criterion is utilized to reduce the operational risk, and robust constraints based on the scenario-based uncertainty sets are proposed to guarantee the delivery time requirement. An equivalent tractable mixed-integer linear programming reformulation is further derived by linearizing the CVaR objective function and dualizing the infinite number of robust constraints into finite ones. A case study based on the practical operations of the JD LN is conducted to validate the practical significance of the proposed model. A comparison with the rerouting strategy and two benchmark models demonstrates the superiority of the proposed model in terms of operational cost, delivery time, and loading rate.

In the Industry 4.0 era, disruptive technologies such as big data analytics, blockchain, Internet-of-Things, and additive manufacturing have become major forces driving supply chain transformation. Under such circumstances, particular attention should be attached to balancing resilience and efficiency of the supply chain, especially in the presence of more turbulence. In this study, we first summarize the conflicts between supply chain efficiency and supply chain resilience regarding practices and objectives. Then, we discuss the positive effects of disruptive technologies in improving resilience and efficiency. Afterwards, we propose a research agenda that covers both the influence mechanism and trade-off mechanism of these technologies in terms of resilience and efficiency.

Given the aging society, an increase in social demand, information- and communication technology-driven culture, and government policy support emerges to enable the development of the socialized care services system for the aged (SCSSA). The development of the SCSSA would be a significant step toward addressing China’s aging population. However, the construction of the SCSSA challenges the theories and methods of traditional elderly care service system construction. Specifically, the implementation path for such elderly care service policies is unclear, the necessary technological support is insufficient, and the mechanism for integrating intelligent information technology remains underexplored. Thus, this paper focuses on the needs of the elderly, grounded in the context of the changing elderly care service policies in China, and proposes a research paradigm that integrates system construction and support measure embedding. We then construct the original SCSSA, which includes “material + spirit + medical treatment + healthcare” and propose a method of optimization and iteration. Finally, we build the research framework of systematic support measures from the perspectives of policy reconstruction, institutional embeddedness, and technical support. Our work provides theoretical support and practical guidance for the construction and dynamic optimization of the SCSSA, thus making a significant contribution that will help China effectively cope with its aging society.

Omnichannel retailing strategies are widely used in practice and have been extensively studied in recent years, but few studies have explored omnichannel retailing operations in response to supply disruption in the post-pandemic era. To fill this gap, this study explores whether the adoption of omnichannel fulfillment options (i.e., ship-from-store and ship-to-store options) can mitigate the risk of supply disruption in a supply chain where a retailer orders products from a reliable supplier and a risky supplier, respectively. Under the omnichannel retailing strategy, the retailer’s order quantity from the risky supplier may increase or decrease while that from the reliable supplier may increase. Interestingly, it is possible to achieve a win–win–win outcome when the supply disruption risk is high and the market share of the channel offered by the risky supplier is low. Moreover, the entire supply chain benefits from the omnichannel retailing strategy even if it faces a high level of disruption risk.

Indoor environment has significant impacts on human health as people spend 90% of their time indoors. The COVID-19 pandemic and the increased public health awareness have further elevated the urgency for cultivating and maintaining a healthy indoor environment. The advancement in emerging digital twin technologies including building information modeling (BIM), Internet of Things (IoT), data analytics, and smart control have led to new opportunities for building design and operation. Despite the numerous studies on developing methods for creating digital twins and enabling new functionalities and services in smart building management, very few have focused on the health of indoor environment. There is a critical need for understanding and envisaging how digital twin paradigms can be geared towards healthy indoor environment. Therefore, this study reviews the techniques for developing digital twins and discusses how the techniques can be customized to contribute to public health. Specifically, the current applications of BIM, IoT sensing, data analytics, and smart building control technologies for building digital twins are reviewed, and the knowledge gaps and limitations are discussed to guide future research for improving environmental and occupant health. Moreover, this paper elaborates a vision for future research on integrated digital twins for a healthy indoor environment with special considerations of the above four emerging techniques and issues. This review contributes to the body of knowledge by advocating for the consideration of health in digital twin modeling and smart building services and presenting the research roadmap for digital twin-enabled healthy indoor environment.

Disruptive technologies provide a new paradigm for supply chain risk management and bring opportunities and challenges for the improvement of supply chain resilience (SCRes). This study summarizes the application cases of some disruptive technologies in the SCRes and analyzes the benefits and damages brought by disruptive technologies to the SCRes. The results show that disruptive technologies can provide the supply chain with flexibility, visibility, agility, and other capabilities at various stages of risk management. Hence, technology advancements greatly increase the level of the SCRes. Although disruptive technologies undermine the construction of SCRes, these damages can be eliminated through technology iteration or other disruptive technologies. Furthermore, disruptive technologies will provide better stability for the SCRes. The study also makes several suggestions for the use of disruptive technologies in the construction of the SCRes.