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The formation of unmanned aerial vehicle (UAV) swarm plays a critical role in numerous applications, such as unmanned agriculture, environmental monitoring and cooperative fencing. Meanwhile, the self-organized swarm model exhibits excellent performance in amorphous formation flight, and its collective motion pattern displays great potential in dense obstacle avoidance. The paper aims to realize the formation maintenance of UAVs while combining the advantage of the self-organized swarm model in avoiding dense obstacles. Thereby enhancing the flexibility, adaptability and safety of UAV swarms in dense and unpredictable scenarios.

In this paper, a self-organized formation (SOF) swarm model with a constrained coordination mechanism is proposed. A global information-based formation rule is designed to flexibly maintain the formation. A constraint coordination mechanism is designed to resolve the problem of constraint conflicts between formation rules and self-organized behavior rules. The model introduces a new obstacle avoidance rule to prevent deadlocks. Extensive experiments including simulations, real flights and comparative experiments are conducted to evaluate the performance of the model.

The simulation results show that SOF swarm enables the formation elastically to dense obstacles. Compared to the Vasarhelyi model, swarm performance metrics are improved. For example, the task completion time of SOF swarm is reduced by 16%, 28% and 39% across the three obstacle densities, and the order of SOF swarm is improved by 4%, 13% and 18%, respectively. The proposed model is also validated with a swarm of seven quadcopters that can successfully navigate and maintain formation in a real-world indoor environment with dense obstacles. Video at: https://youtu.be/V8hYgOHxWls.

The proposed formation rule is based on global information construction, which presents challenges in terms of communication overhead in distributed systems.

An SOF swarm model is proposed, which achieves formation maintenance by incorporating formation rule and constraint coordination mechanism and improves obstacle avoidance performance by introducing a new obstacle avoidance rule. After real UAVs verification, the model is feasible for practical deployment and provides a new solution to the formation flight and formation maintenance problems encountered in dense environments.

(1) The shear lag effect and its additional deflection contribution to composite beams based on spatial grid elements were presented. (2) A refined spatial grid element analysis method that can simultaneously obtain the internal forces, displacements and stresses of various parts of a composite beam.

A refined spatial grid element analysis method.

The proposed method can directly obtain the internal forces and displacements of the joints of the composite beam roof, floor and web.

To comprehensively comprehend the mechanical behavior of double-girder steel plate composite girder bridge structures and facilitate refined analysis, this paper introduces a refined spatial grid element analysis model applicable to both the global and local domains.

This study aims to explore the interaction of “contractual governance – relational governance – governmental governance” mechanisms and proposes hypotheses about the effects of megaproject governance on governance performance from both theoretical and practical perspectives.

In this paper, a megaproject governance model is developed to explain the relationship between governance mechanisms and governance performance. The model is based on related literature and explores the interactions between governance mechanisms and how they work to improve governance performance. The structural equation model (SEM) is adopted to explore the influence path on governance performance for megaprojects.

The results indicate that: (a) The findings highlight the positive role of project governance mechanisms on governance performance. (b) Contractual governance, relational governance, and governmental governance directly affect governance performance. In addition, contractual governance mediates governance performance through relational governance and governmental governance; governmental governance mediates governance performance through contractual governance and relational governance. (c) Contractual governance, relational governance, and governmental governance play a positive role in governance performance.

Governmental governance is added to project governance theory and the empirical research method is used to explore the interaction between contractual governance, relational governance, and governmental governance of megaprojects. The SEM is used to systematically explore the paths of megaproject governance mechanisms on governance performance, considering the interactive role of the “contractual governance - relational governance - governmental governance” and the mediating role.

The study reveals the impact path of multidimensional megaproject governance mechanisms on governance performance. In this paper, the empirical findings can help the project participants by providing a decision-making basis for good governance and references for the governments to promote the construction of a micro-institutional environment for megaprojects.

The contributions of this study are (1) to add an exploration of governmental governance to the existing project governance theory, and (2) to consider the interactions of the “contractual governance – relational governance – governmental governance” mechanisms, and (3) to explore their effects on governance performance, including direct and mediating effects. This study contributes to a comprehensive understanding of megaproject governance by considering governmental governance and the interactions of the three governance mechanisms. Understanding the impact of megaproject governance on governance performance could assist project stakeholders and provide decision guidance for good governance.

COVID-19 has forced audit firms to change the way they operate. One change has been to rely more on information technology (IT) and IT human capital to overcome COVID-19-related challenges. We refer to audit firms’ use of these two resources as audit firm informatization (AFI). It is important to understand whether AFI helps audit firms address challenges created by the pandemic. Thus, this study examines the impact of AFI on audit quality during the COVID-19 pandemic in China with a focus on IT human capital.

We use a mixed-methods approach. First, we perform multivariate regression analyses on archival data. Specifically, we investigate the relationship between IT human capital and audit quality and the two mechanisms (i.e. improved efficiency and reduced audit risk) underlying the relationship. We also investigate how this relationship is moderated by features of clients, audit firms and individual auditors. Then we use interviews to corroborate the results of our regression analyses.

Our analyses of archival data show that IT human capital positively affects audit quality through improved efficiency and reduced audit risk and that this positive impact is more pronounced for clients in non-manufacturing industries, those with a more opaque information environment, audit firms with greater industry coverage and individual auditors with less experience. Our interview data indicate that audit firms with more advanced AFI and a higher level of IT human capital in particular are less disrupted by the pandemic and are better able to use IT to address challenges associated with COVID-19. Furthermore, the results confirm that improved efficiency and reduced audit risk are the mechanisms through which AFI enhances audit quality. Finally, we identify issues associated with the use of IT.

This study is the first to investigate how IT human capital (and by extension AFI) influences audit quality in the context of the COVID-19 pandemic. Our findings should be of interest to practitioners and setters of auditing standards.

This study aims to assess the mediating and driving roles of knowledge cooperation in the effectiveness of G60 Sci-tech Innovation Corridor (G60 STIC) for regional collaborative innovation within the knowledge economy context. Furthermore, it focuses on whether knowledge cooperation is more effective than resource cooperation in terms of spatial spillover and its mediating effects on collaborative innovation.

This study employs multiple statistical and econometric approaches, including social cooperation network, Super-DEA, spatial difference-in-difference model (SDID) and mediating effect model, to measure the effectiveness of knowledge cooperation and resource cooperation paths within the framework of the G60 STIC on regional collaborative innovation in the Yangtze River Delta region (YRD) from 2002 to 2022.

First, the knowledge cooperation networks validate the strengthening of collaborative innovation is primarily centred on provincial cities and leading manufacturing locales, with smaller cities radiating outwards from these centres. The knowledge cooperation network was generally stronger than the resource cooperation network. Second, the G60 STIC significantly enhances collaborative innovation efficiency by intensifying knowledge, resource and interactive cooperation networks. Third, within the context of the knowledge economy, knowledge cooperation presents a stronger spillover and mediating effect in stimulating collaborative innovation than resource cooperation.

This study clarifies the existence of a knowledge cooperation network and its mediating role in stimulating the effectiveness of strategic, innovative platforms on collaborative innovation. This further verifies the stronger role of the knowledge cooperation than the resource cooperation, which serves as a vital element in promoting strategic innovative platforms to optimise collaborative innovation.

The increasing unexpected contingencies make resilience indispensable for project teams. Drawn on input–process–outcome (IPO) framework, this study aims to investigate how and when team mindfulness (i.e. input) fosters team resilience (i.e. outcome) via team formalization and team improvisation (i.e. process) under boundary conditions of the shared mental model.

By conducting a three-wave research design, this paper collects 312 questionaries from the Chinese construction industry. The proposed hypotheses were tested by hierarchical regression analysis and structural equation modeling.

The results confirm that team mindfulness exerts a positive effect on team resilience. The positive relationship is mediated by team formalization and team improvisation. In addition, the shared mental model serves as a buffering moderator between team mindfulness and team resilience via team improvisation.

This study suggests managers take appropriate interventions of mindfulness to foster team resilience. Making explicit procedures for risk management and taking improvisational action appropriately are also key processes for addressing crises.

This study enriches the literature on the positive prediction effect of team mindfulness on team resilience. Combining team formalization with team improvisation, this study provides new alternatives for the process variables in the IPO framework. Furthermore, this paper reveals the “dark side” of the shared mental model on the relationship between team mindfulness and team resilience.

The construction industry has experienced an irreversible digital transformation to smart construction. Many countries have published supporting policies to encourage the development of smart construction. However, there is no universally valid approach. This paper thus aims to evaluate smart construction policies issued by 24 pilot cities in China and identify applicable policy tools and their impact.

This paper collected 33 governmental documents on smart construction through the official websites in China. Different policy tools were classified into supply-side, demand-side and environment-side categories. The supporting policies of smart construction development in pilot cities were quantitatively evaluated by using a policy modeling consistency index (PMC-index) model.

Supply-type and environment-type policy instruments were used more frequently than demand-type policies in 24 pilot cities. Most of the 24 pilot cities had an evaluation of PMC-index over 8, realizing the consistency of smart construction policies. Eight pilot cities had an evaluation of PMC-index of 6–7.99, realizing acceptable consistency. Only Foshan City has an evaluation of PMC-index below 4, which may reflect a poor consistency of policy implementation. The paper proposes consistencies of smart construction policies of 24 pilot cities and valid policy instruments, including the presale of commercial residential buildings, additional bonus points in the tendering process and cooperating with multiple departments when promoting smart construction.

This paper contributes to expanding policy evaluation studies in the smart construction field and provides concrete suggestions for policymakers to formulate more effective and specific policies and strategies for the development of smart construction.

This study aims to replace petroleum-based lubricating oils with sustainable biomaterials, addressing issues associated with existing alternatives, such as poor performance, high cost and limited availability.

The transformation of agricultural waste cardanol, a nonedible vegetable oil that is abundantly available, into green cardanyl acetate (CA) biolubricating ester oil. The potential of CA as a base stock for lubricants is validated by assessing its lubrication performance.

CA exhibited a higher viscosity index, flash point and thermal stability than commercially available mineral-based (CTL3, coal-to-liquid) and synthetic (PAO2, poly-alpha-olefin) lubricant base stocks. Moreover, CA exhibits excellent anticorrosivity properties as well as PAO2 and CTL3. The tribological properties of CA were evaluated, and the results show that CA exhibits a smaller average wear scar diameter (WSD) of 0.54 mm than that of PAO2 (0.85 mm) and CTL3 (0.90 mm). In extreme pressure tests, acylated CA demonstrated the highest last nonseizure load capacity at 510 N, outperforming commercial CTL3 (491 N) and PAO2 (412 N). All results demonstrate that CA displays an excellent series of base stock properties.

The novelty of this work lies in the utilization of renewable agricultural waste, cashew nut shell liquid, to produce a high-value biolubricant as an alternative to commercial fossil-based lubricants. The renewable nature, low cost, and large-scale availability of raw materials pave a new path for the production and application of biolubricants, showcasing the immense potential of converting agricultural waste into high-value products.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0064/

Low-carbon city policies (LCCP) are crucial environmental regulatory frameworks driving China’s transition toward a low-carbon economy. This study investigated the impact of LCCP on enterprise digital transformation (EDT).

This study employed a staggered difference-in-differences model for Chinese listed companies from 2007 to 2021. It also used a cross-sectional model for further analysis.

We found that the implementation of LCCP can promote EDT. This impact was more pronounced among enterprises with greater media attention in high-energy-consumption industries and well-developed economic areas.

This study has practical implications for the LCCP, as it evaluates the consequences of macro-level LCCP on micro-level corporate economic consequences. It provides an important reference for developing countries to implement LCCP and promote green industry upgrading.

This study broadens the impact of the LCCP, providing valuable insights into substantiating carbon neutrality goals and fostering the influencing factors of EDT.

As the complex influencing factors for financing decisions and limited information at the early project stage often render inappropriate financing mode and scheme (FMS) selection in the large-scale urban rail transit (URT) field, this study aims to identify the multiple influencing factors and establish a revised case-based reasoning (CBR) model by drawing on experience in historical URT projects to provide support for effective FMS decisions.

Our research proposes a two-phase, five-step CBR model for FMS decisions. We first establish a case database containing 116 large-scale URT projects and a multi-attribute FMS indicator system. Meanwhile, grey relational analysis (GRA), the entropy-revised G1 method and the time decay function have been employed to precisely revise the simple CBR model for selecting high-similarity cases. Then, the revised CBR model is verified by nine large-scale URT projects and a demonstration project to prove its decision accuracy and effectiveness.

We construct a similarity case indicator system of large-scale URT projects with 11 indicators across three attributes, in which local government fiscal pressure is considered the most influential indicator for FMS decision-making. Through the verification with typical URT projects, the accuracy of our revised CBR model can reach 89%. The identified high-similarity cases have been confirmed to be effective for recommending appropriate financing schemes matched with a specific financing mode.

This is the first study employing the CBR model, an artificial intelligence approach that simulates human cognition by learning from similar past experiences and cases to enhance the accuracy and reliability of FMS decisions. Based on the characteristics of the URT projects, we revise the CBR model in the case retrieval process to achieve a higher accuracy. The revised CBR model utilizes expert experience and historical information to provide a valuable auxiliary tool for guiding the relevant government departments in making systematic decisions at the early project stage with limited and ambiguous project information.