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This study aimed to analyze the impact of enterprise digital transformation on bank loan contracting from 2007 to 2021.

This study used an empirical approach to examine the impact of digital transformation on bank loan interest rates and the possible mechanisms. The digital transformation data of firms were obtained by Python, and the bank loan contracting information of Chinese listed firms was hand-collected from the notes of the annual report.

The results show that digital transformation can significantly reduce the bank loan interest rate and show heterogeneity in the nature of property rights, industry type and firm size. The above results remain significant after conducting a series of robustness tests. Channel tests suggest that digital transformation can promote total factor productivity, improve firms’ information environment and reduce the risk of financial distress, thus helping them reduce their loan interest rate. In addition, banks’ digital transformation can also affect the link between enterprise digital transformation and bank loan interest rates.

First, this paper deeply investigates the relationship between enterprise digital transformation and bank loan contracting, and the mechanisms behind it which expands the research on economic consequences of digitalization. Developing digitalization society has been a top priority in China as it is an urgent task to survive in the competitive global economic environment as a developing country. Second, in developed countries, the evidence relating to bank loan contracting is plentiful. However, the Chinese studies are still very limited as it has no database like Dealscan in US.

Green technology innovation is the organic combination of green development and innovation driven. It is also a powerful guarantee for shaping sustainable competitive advantages of manufacturing enterprises. To explore what kind of executive incentive contracts can truly stimulate green technology innovation, this study aims to distinguish the equity incentive and reputation incentive, upon their contractual elements characteristics and green governance effects, and then put forward suggestions for green technology innovation accordingly.

This study establishes an evaluation model and uses empirical methods to test. Concretely, using data from A-share listed manufacturing companies for the period from 2007 to 2020, this study compares and analyzes the impact of equity and reputation incentive on green technology innovation and explores the relationship between internal green business behavior and external green in depth.

This study finds that reputation incentives focus on long-term and non-utilitarian orientation, which can promote green technology innovation in enterprises. While equity incentives, linked to performance indicators, have a inhibitory effect on green technology innovation. Internal and external institutional factors such as energy conservation measures, the “three wastes” management system, and environmental recognition play the regulatory role in the relationship between incentive contracts and green technology innovation.

Those findings validate and expand the efficient contracting hypothesis and the rent extraction hypothesis from the perspective of green technology innovation and provide useful implications for the design of green governance systems in manufacturing enterprises.

Corporate governance, privatisation.

Masters level programmes, with particular focus on corporate governance, privatisation, and organizational development.

Yutong Bus is a real and highly publicized case in China. It is a listed company carved out from a state-owned enterprise (SOE), Yutong Group. Later the management successfully bought out Yutong Group and thus indirectly controlled the company. The deal transformed Yutong Group from a SOE to a private company. The management was innovative in pushing through the management buy-out (MBO), but politically, it created a public outcry about the loss of state-owned assets. The key issue here is the selection of state owned enterprises suitable for privatization and, more importantly, the determination of selling price. In China “the market for corporate control is still lagging behind” (Shanghai Stock Exchange).

Students would be expected to gain an understanding of recent economic reform in China, Corporate Governance in the Chinese context and wider issues associated with privatization and MBOs.

Teaching note.

The impacts of COVID-19 on construction projects have attracted much attention in the construction management research community. Nevertheless, a systematic review of these studies is still lacking. The purpose of this paper is to systematically analyze the impacts of COVID-19 on the different stages of a project life-cycle, and comprehensively sort out the epidemic response measures adopted by project participants. In addition, the study also attempts to explore the challenges and opportunities faced by project management practitioners under the context of COVID-19.

This study comprehensively demonstrates the systematic review process of COVID-19 related research in the construction industry, systematically summarizes the research status of the impact of COVID-19 on construction projects, and defines the strategies to deal with COVID-19 in project management; and through the visualization research, determines the current key research topics and future research trends.

This study identifies 11 construction activities in the project management life cycle that are affected by COVID-19 and finds that the COVID-19 epidemic has the greatest impact on construction workers, construction standards, construction contracts and construction performance. The study further summarizes the six main epidemic countermeasures and mitigation measures taken within the construction industry following the arrival of the epidemic. In addition, the results of this study identify opportunities and future trends in intelligent construction technology, rapid manufacturing engineering and project management in the construction industry in the post-epidemic era through literature results, which also provide ideas for related research.

COVID-19 has brought severe challenges to society. It is of great significance for the future sustainable development of the construction industry to identify the impact of COVID-19 on all phases of the project and to promote the development of coping strategies by project stakeholders.

First of all, there is little study comprehensively reviewing the impacts of COVID-19 on the different stages of construction projects and the strategies to deal with the negative impacts. In addition, from a life cycle perspective, the used articles in this study were grouped into different categories based on project stages. This promotes an integrated and comprehensive understanding of historical studies. Moreover, on the basis of a comprehensive review, this paper puts forward future research directions to promote the sustainable development of the construction sector.

Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation, nonlinear model uncertainties and external ocean current disturbances. The containment errors can be limited to a small neighborhood of zero in finite time by employing control strategy. The control strategy can keep errors within a certain range between the trajectory followed by AUVs and their intended targets. This can mitigate the issues of collisions and disruptions in communication which may arise from AUVs being in close proximity or excessively distant from each other.

The tracking errors are constrained. Based on the directed communication topology, a cooperative formation control algorithm for multi-AUV systems with constrained errors is designed. By using the saturation function, state observers are designed to estimate the AUV’s velocity in six degrees of freedom. A new virtual control algorithm is designed through combining backstepping technique and the tan-type barrier Lyapunov function. Neural networks are used to estimate and compensate for the nonlinear model uncertainties and external ocean current disturbances. A neural network adaptive law is designed.

The containment errors can be limited to a small neighborhood of zero in finite time so that follower AUVs can arrive at the convex hull consisting of leader AUVs within finite time. The validity of the results is indicated by simulations.

The state observers are designed to approximate the speed of the AUV and improve the accuracy of the control method. The anti-saturation function and neural network adaptive law are designed to deal with input saturation and general disturbances, respectively. It can ensure the safety and reliability of the multiple AUV systems.

The purpose of this study is to investigate the inner flow field characteristics of groove textures in thrust bearings. Cavitation and vortex are studied simultaneously to enrich the theories of surface texture.

Navier–Stokes equations are solved using computational fluid dynamics. The MIXTURE model is adopted to study the gas–liquid mixture flow under the cavitation condition.

Re number, the depth ratio as well as the area ratio of the groove texture and the bottom shape are all influencing factors of the inner flow field characteristics. When cavitation region and vortex region occupy the bottom of the groove texture, these do not overlap because of the pressure gradient. The positive pressure gradient in the non-cavitation region introduces nonlinearity into the velocity profiles, which affects the load-carrying capacity and friction.

Cavitation and vortex are studied simultaneously only in this study. The characteristics of the textured thrust bearing can be analyzed and explained with the combined effect of cavitation and vortex.

This paper aims to investigate a multi-objective electric vehicle’s (EV’s) synergetic scheduling problem in the automotive industry, where a synergetic delivery mechanism to coordinate multiple EVs is proposed to fulfill part feeding tasks.

A chaotic reference-guided multi-objective evolutionary algorithm based on self-adaptive local search (CRMSL) is constructed to deal with the problem. The proposed CRMSL benefits from the combination of reference vectors guided evolutionary algorithm (RVEA) and chaotic search. A novel directional rank sorting procedure and a self-adaptive energy-efficient local search strategy are then incorporated into the framework of the CRMSL to obtain satisfactory computational performance.

The involvement of the chaotic search and self-adaptive energy-efficient local search strategy contributes to obtaining a stronger global and local search capability. The computational results demonstrate that the CRMSL achieves better performance than the other two well-known benchmark algorithms in terms of four performance metrics, which is inspiring for future researches on energy-efficient co-scheduling topics in manufacturing industries.

This research fully considers the cooperation and coordination of handling devices to reduce energy consumption, and an improved multi-objective evolutionary algorithm is creatively applied to solve the proposed engineering problem.

E-commerce live streaming (ELS) has become a new and important shopping channel. Although previous studies have provided insightful findings on how to engage consumers in ELS, limited effort has been made to explore the role of factors of live streaming rooms. Based on the literature on space perception and the retail environment, this study aims to develop a theoretical model to examine how perceived distance and perceived depth affect consumers' affective and cognitive perceptions and then further impact product attitude in ELS.

This study collected 414 valid survey responses to test the proposed research model. Survey data were analyzed using partial least squares (PLS)-structural equation modeling. The PLS Multi-Group analysis (PLS-MGA) was used to test the consistency of the research model across different product types and watching durations.

The results suggest that environmental factors of a live streaming room (i.e. perceived distance and perceived depth) can impact consumers' attitudes toward the product in the live streaming via both cognitive and affective routes. These effects keep consistent across different product types and watching durations.

The paper focuses on the environmental perspective, which is unexplored in previous literature on ELS. It highlights the importance of the space design of live streaming rooms.

Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

The study aims to figure out the impact of supply chain planning (SCP) on innovation performance (IP), the mediating role of agreement on supply chain vision and goals (ASCVG), and the moderated effect of information technology (IT) use with buyers and suppliers.

Based on 265 pieces of data collected from global manufacturing companies, the authors tested the proposed hypothesis through regression analyses. Meanwhile, the plug-in of statistical software SPSS, PROCESS (Model 4 and 14) was used to examine the mediation and moderated mediation models.

The results reveal that ASCVG partially mediates the effect of SCP on IP. Furthermore, the indirect influence of SCP on IP is stronger when the extent of IT use with buyers is higher, while this indirect effect is not moderated by IT use with suppliers.

In this study, the authors investigated the combined effect of SCP, ASCVG, and IT use with external partners on IP, which provides theoretical and practical insights into the ways that manufacturing firms effectively use the SCP, ASCVG and IT use with external partners to heighten IP.