Wei Wang, Yongyong He, Yang Li, Bin Wei, Yutong Hu and Jianbin Luo
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Keywords
Zhen Li, Yutong Jin, Wenjing Li, Qingfeng Meng and Xin Hu
The impacts of COVID-19 on construction projects have attracted much attention in the construction management research community. Nevertheless, a systematic review of these…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Practical implications
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.
Originality/value
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.
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Xixian Peng, Jiaqi Ren and Yutong Guo
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Jiangjun Wan, Yuxin Zhao, Miaojie Chen, Xi Zhu, Qingyu Lu, Yuwei Huang, Yutong Zhao, Chengyan Zhang, Wei Zhu and Jinxiu Yang
The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are…
Abstract
Purpose
The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.
Design/methodology/approach
In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.
Findings
In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.
Originality/value
This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.
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Xue Chen, Zhaohua Zhang and Yutong Yang
The purpose of this paper is to explore the distribution of local thermal sensitivity of human body heating and the local preferred heating temperature, and the influence of this…
Abstract
Purpose
The purpose of this paper is to explore the distribution of local thermal sensitivity of human body heating and the local preferred heating temperature, and the influence of this sensitive division on thermal response when heating human body in cold environment.
Design/methodology/approach
Eight subjects were invited to use carbon fiber heating patches in an environment of 5 and RH 50%, and eight body parts were selected to explore the heating sensitivity. By measuring the skin temperature and evaluating the subjective thermal sensation and thermal comfort, the thermal sensitivity of local body segments and the influence of single-zone and double-zone heating on human thermal response were explored.
Findings
The sensitivity of local heating on overall thermal sensation (OTS) was foot > back > chest > abdomen > waist > elbow > hand > knee. Both single-zone and double-zone heating can improve the OTS, but double-zone heating can reach thermal neutrality and thermal comfort. In order to prevent the high temperature of heating patches from damaging human body, the local skin temperature should be monitored in the design of local heating clothing, and 39.6 should be taken as the upper limit of local skin temperature.
Originality/value
The results provide a theoretical basis for the selection of heating position in local electric heating clothing (EHC) and the design of intelligent temperature adjustment heating clothing, improve the performance of local EHC and reduce energy consumption.
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Keywords
Zidan Tian, Ting Wang, Kaiwen Jiang, Qinghua He, Yutong Xue and Xiaoyan Chen
Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were…
Abstract
Purpose
Recent studies suggested that owner dynamic capabilities (ODCs) enabling public owners of megaprojects to activate, orchestrate and reorganize resources to uncertainties were beneficial to improving the project resilience of megaprojects. However, most of them pay insufficient attention to the specific context of long cycles and deep uncertainty in megaprojects, neglecting the causal complexity that different dimensions of ODCs and learning mechanisms interact with each other in terms of enhancing project resilience. Therefore, this study aims to systematically unveil the complex causality among ODCs, learning mechanisms and project resilience of megaprojects.
Design/methodology/approach
This study introduces a configurational perspective to explore how multi-dimensional ODCs combine to improve project resilience in megaprojects along with different organizational learning mechanisms and learning orientations. Based on 330 ODC events in 19 construction megaprojects, a multi-temporal crisp-set qualitative comparative analysis method is adopted to extract configurations of ODCs for project resilience improvement and unveil their evolution features over the whole megaproject lifecycle.
Findings
Six configurations are identified for improving project resilience in megaprojects, including cognition-dominant, cognition-deficient, transformation-dominant, innovation-driven, value-co-creation and exploitative-transformation configurations. The results also indicate that distinct megaproject stages appeal to corresponding ODC configurations for project resilience improvement under unique uncertain contexts.
Originality/value
This study not only makes theoretical contributions to the literature on dynamic capability and project resilience in the megaproject management field but also provides useful practical guidance for public owners of megaprojects to better utilize ODCs for project resilience improvement.
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Xingmin Liu, Tongsheng Zhu, Yutong Xue, Ziqiang Huang and Yun Le
Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Huijie Cui, Yutong Li and Shangkun Liang
This study aimed to analyze the impact of enterprise digital transformation on bank loan contracting from 2007 to 2021.
Abstract
Purpose
This study aimed to analyze the impact of enterprise digital transformation on bank loan contracting from 2007 to 2021.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Yanchao Sun, Jiayu Li, Hongde Qin and Yutong Du
Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Binghai Zhou, Qi Yi, Xiujuan Li and Yutong Zhu
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.