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This paper aims to investigate the relationship among emotional intelligence (EI), conflict management styles (CMSs) and innovation performance, and test the mediating effects of various types of CMSs. Innovation is playing a more and more critical role in the survival and development of companies. EI is assumed to be an antecedent of employees’ innovation performance. Conflict is an inevitable phenomenon in organizations, and different CMSs have different impacts on individual performance.

Research data were obtained from 159 employees in the construction industry in China. SPSS 19.0 was used to test and verify the hypotheses concerning the relationship among EI, CMSs and innovation performance. The authors also conducted a 500-times bootstrapping to verify the mediating roles of different CMSs.

Results indicate that EI is positively and significantly associated with integrating, compromising and dominating styles, as well as innovation performance in the construction industry. In addition, the integrating style has a significantly positive relationship with innovation performance. This research also confirms the mediating effect of integrating style on the relationship between EI and innovation performance.

The authors recommend that managers, especially in the construction industry, who are willing to maintain high levels of innovation performance of employees can provide EI training programs. In addition, to improve innovation performance, companies should provide employees with appropriate training emphasizing the importance of conflict management strategies, especially the integrating style.

Limited research has focused on the antecedents of conflict management strategies or the relationship between EI and innovation performance. A framework integrating EI, CMSs and innovation performance is put forward and empirical evidence of the relationship between EI and employees’ innovation performance is provided. This research helps to have a better understanding of the relationship between EI and innovation performance by introducing the integrating style as a mediating variable.

Making the right bid/no-bid decision is critical to the success and development of construction contracting enterprises. Decision makers’ personal characteristics, such as risk perception and propensity, have great impact on bid/no-bid decisions, which is the major concern of this research. The purpose of this paper is to explore the relationship among decision makers’ risk perception, risk propensity, and their bid/no-bid decision making of construction projects, as well as the factors influencing the risk perception and propensity.

In total, four hypotheses were proposed based on an extensive literature review. Experimental questionnaires were distributed to employees working in Chinese construction contracting enterprises with knowledge of construction bidding, and 134 valid questionnaires were obtained. Multivariate statistical analysis through SPSS 19.0 was used to analyze the acquired data.

Data analysis shows that in the context of international construction contracting: risk perception has a negative influence on bid/no-bid decision making; while risk propensity produces a positive influence and the probability and magnitude of potential gain or loss both have significant impacts on risk perception, and the probability plays a more important role.

This research studied the bid/no-bid decision making of construction projects from the new perspectives of risk perception and risk propensity of the decision makers.

Selecting a proper project delivery system is one of the critical issues for the success of a project. This paper discusses the application of project delivery systems in China and the existing project delivery system selection methods, analyzes project objectives and indicators influencing the selection of project delivery systems, and aims at finding an appropriate method to select project delivery systems.

A survey was conducted by postal questionnaire and Multivariate Statistical Analysis was applied to analyze the project data. A robust model was developed to analyze the selection of project delivery systems.

The results of survey and analysis show that design‐bid‐build (DBB)/project management (DBB+PM), design‐build (DB)/engineering, procurement and construction (EPC)/Turnkey, multi‐stage DB/EPC and EP+C are commonly used in China. The differences between DBB and DBB+PM, and differences between DB/EPC and Turnkey in China are not significant. Weights of project objectives in each project delivery system and the ranking of indicators influencing the selection of project delivery systems are acquired.

Analysis was conducted with a robust model instead of traditional model in consideration of efficiency. This research may assist owners in Mainland China in selecting project delivery systems, improve project performance, and encourage efficiency in project delivery process.

The purpose of this paper is to investigate the mechanism how the platform obtains and uses undisclosed information to determine individual borrowers’ credit score and to examine the effectiveness of credit scoring in predicting default. The motivation stems from the fact that there is little evidence about the role of P2P platform, which has been positioned as a kind of information intermediary.

Using a sample of 5,176 unsecured P2P loans having expired before December 31, 2015 on Renrendai.com and an approach of two-stage regression, the paper first estimates the undisclosed information embedded in credit score by regressing credit score on four types of public information about a borrower’s creditworthiness. Then, the authors use a Logit regression to examine the role of the excess information in predicting the default probability.

The certification information provided by the platform is the most important determinant for a borrower’s credit score and the undisclosed information embedded in credit score can predict the loan performance better than the public information of posted listings. Moreover, the predictive ability of the undisclosed information is better for high-risk borrowers than for low-risk ones.

Providing a credit score for each individual is a way for P2P platforms to play an information intermediary role. More evidence about whether or how a platform plays its role are worthy to be exploited by investigating a platform’s operating policies in detail and doing cross-platform comparative studies.

The results about the effect of various types of information on loan performance can provide an insightful guidance for P2P platforms to optimize their mechanism on information disclosure and credit scoring.

The existing literature mainly focuses on the effects of information voluntarily disclosed by borrowers and the behaviors of investors on P2P lending outcomes. The paper highlights the information intermediary role played by the platform and presents empirical evidence that credit scoring for individual borrowers is a way for P2P platforms to promote the direct lending for individual.

This study aims to present a comprehensive knowledge mapping and an in-depth analysis of plastic and sustainability research to understand better global trends and directions in this field that emerged between 1995 and 2022.

This study presents a visual analysis of 1933 research articles listed in the Web of Science (WoS) databases between the years 1995 and 2022 related to plastic and sustainability. The knowledge mapping based on CiteSpace and VOSviewer presents the current research status, which contains the analysis of the collaboration network, co-citation network, references with citation bursts and keyword analysis.

The results reveal that China and the USA are the most prominent countries in exploring the notion of sustainability and plastic. The Chinese Academy of Science is the most prominent institution. Chai Qiang, Friedrich Daniel, Sahajwalla Veena and Ok Yong Sik are the most prolific authors in this field. Furthermore, circular economy, bioplastic, sustainable development, polyester and bioplastics are the highly discussed issues in recent years. Not surprisingly, COVID-19 is the latest topic of discussion started in 2021 due to its negative impact on plastic pollution and the challenges it posed to sustainability.

This study is among the pioneers to shed light on the current research status of plastic and sustainability using the bibliometric method and the newest data. This study also suggests that collaborations between scholars and institutions require to be enhanced for better management of plastic pollution and to contribute to sustainable development.

As a key part of the algae removal equipment in the middle route of South-to-North Water Diversion Project, the static analysis and dynamic analysis are carried out for the structural characteristics of the frame. The paper aims to discuss this issue.

First, the model is constructed for analysis. Second, finite element analysis are carried out. And finally, test designed is used for the construction.

The optimization scheme that minimizes the quality under the condition of satisfying the allowable stress is found, and the quality is reduced by 6.88 percent.

The paper is based on the occurrence of seasonal algae in the main channel of the Middle Route of the South-to-North Water Diversion Project, an automatic algae-removing equipment was designed.

This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster popularity moderates social interaction-oriented content's effect on the two different behaviors in live-streaming commerce.

A research model was proposed and empirically tested using a panel data set collected from 537 live streams via Douyin (the Chinese version of TikTok), one of the most popular live broadcast platforms in China. A fixed-effects negative binomial regression model was used to examine the proposed research model.

This study's results show that social interaction-oriented content in broadcasters' live speech has an inverted U-shaped relationship with broadcast viewers' purchasing behavior and shares a positive linear relationship with viewers' gift-giving behavior. Furthermore, broadcaster popularity significantly moderates the effect of social interaction-oriented content on viewers' purchasing and gift-giving behaviors.

This research enriches the literature on live-streaming commerce by investigating how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' product-purchasing and gift-giving behaviors from the perspective of broadcast viewers' attention. Moreover, this study provides some practical guidelines for developing live speech content in the live-streaming commerce context.

Livelihood recovery is a top priority to sustain resettled communities. The purpose of this paper is to assess livelihood vulnerability of those displaced and resettled in the aftermath of the 2008 Wenchuan earthquake, China, based on a newly constructed locational adjustable framework.

The study takes two resettlement villages in Sichuan Province as case study areas. Face-to-face surveys using a structured questionnaire and semi-structured in-depth interviews were conducted to collect primary data in 2012-2013.

The findings show that distant resettlement of people post the Wenchuan earthquake has resulted in an increased livelihood vulnerability within resettlers and that they face more hazards post-resettlement when compared to host residents in the resettlement areas.

The indicators considered for the livelihood vulnerability index (LVI) are only a subset that represents typical factors applicable in the context of rural settings of China. The LVI may vary if more indicators are incorporated or coefficients obtained using different methods.

Highlights should be placed on livelihood assets and hazards to livelihood of the displaced people. During the transition period there is a pressing need for greater efforts to enhance migrants’ employment skills and assist them to restore viable livelihood activities.

This paper constructs a locational adjustable framework for analyzing and assessing livelihood vulnerability of disaster-induced resettlers from three aspects: livelihood hazards, livelihood assets and coping strategies.

The paper attempts to construct a novel multi-objective grey hierarchical group consensus approach to deal with the group consensus problems consisting of hierarchical relationship and non-cooperative behaviors among decision makers (DMs).

To deal with these group consensus problems consisting of hierarchical relationship and non-cooperative behaviors among DMs non-cooperative behavior in uncertain information systems, considering the influence of coordination cost and the degree of group consensus, based on the idea of grey situation decision-making, the authors establish a multi-objective grey hierarchical group consensus model, and design different invalid decision elimination rules for decision-making groups of different sizes, and use a case verifies the effectiveness and feasibility of the model.

With the continuous improvement of the coordination cost budget, the degree of consensus of all departments and the overall consensus tend to be stable, and will no longer change with the increase of the coordination cost budget. The cost required by each department is basically consistent with the response trend of the cost required to coordinate the overall situation to the pre-set lower limit of group consensus.

The proposed approach can succeed in identifying DMs' information, and mine the DMs' information and help make a relatively more scientific decision.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.