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The aim of this study is to examine when and why employee creative behavior leads to unethical pro-organizational behavior (UPB). Drawing on research on moral licensing, we argue that the relationship between employee creative behavior and UPB is indirectly mediated by moral licence.

The data were collected from 214 employees and their immediate supervisors, and the theoretical hypotheses were tested by correlation and a hierarchical regression analysis.

We found that: (1) employee creative behavior is positively correlated with their moral credentials and moral credits; (2) it supported the mediating role of moral credentials between creative behavior and UPB but did not support the relationship between creative behavior and UPB through moral credits and (3) the indirect relationship between creative behavior and UPB is strengthened through moral credentials when perceptions of organizational valuing of creativity are high.

This study responds to calls from researchers to explore more detrimental outcomes of creativity, and we extend existing research by empirically showing that creativity can promote some unethical pro-organizational behavior. We also contribute to explore the mediated role of moral licensing and the moderated role of the perceived organizational valuing of creativity to explain the creative behavior–UPB relationship.

Blockchain technology (BCT) is considered a promising tool to improve the productivity of construction project management. Existing research has studied its potential costs and benefits for the construction industry. However, the potential costs and benefits of BCT failed to be compared as actual costs and benefits of specific applications for stakeholders. To fill this gap, this study seeks to analyze the cost-effectiveness of BCT-based applications in construction project management.

This study is conducted with a customized systematic literature review based on transaction cost theory to enable qualitative comparison. With a deliberately designed structure confining extraneous variables, the costs and benefits of BCT-based applications are identified and compared. The inherent dependent relations of processes and the evolution relations of functions are identified. The cost-effectiveness of blockchain adoption is then analyzed.

Seven functions and six challenges are identified within five processes. The result suggests all identified functions are cost-effective except for manual instruction (coding smart contracts manually). The smart contracts require explicit definition and logic to be effective. However, the construction projects essentially require the institution to be flexible due to unpredictability. The adoption of smart contracts and corresponding additional requirements can increase the transaction cost of bounded rationality.

As manual instruction is fundamental to realize other functions, and its advanced substitute relies on its broad adoption, its cost-effectiveness must be improved for applications to be acceptable to stakeholders. The establishment of a universal smart contract model and a universal, legitimate and efficient database structure are recommended to minimize the cost and maximize the effect of applications.

This study contributes to the knowledge by providing a comprehensive analysis of BCT adoption’s cost-effectiveness in construction project management. The adopted review structure can be extended to analyze the qualitative benefits and challenges of management automation in the early stages.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.

Platform-based enterprises, as micro-entities in the platform economy, have the potential to effectively promote the low-carbon development of both supply and demand sides in the supply chain. Therefore, this paper aims to provide a multi-criteria decision-making method in a probabilistic hesitant fuzzy environment to assist platform-type companies in selecting cooperative suppliers for carbon reduction in green supply chains.

This paper combines the advantages of probabilistic hesitant fuzzy sets (PHFS) to address uncertainty issues and proposes an improved multi-criteria decision-making method called PHFS-DNMEREC-MABAC for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Within this decision-making method, we enhance the standardization process of both the DNMEREC and MABAC methods by directly standardizing probabilistic hesitant fuzzy elements. Additionally, a probability splitting algorithm is introduced to handle probabilistic hesitant fuzzy elements of varying lengths, mitigating information bias that traditional approaches tend to introduce when adding values based on risk preferences.

In this paper, we apply the proposed method to a case study involving the selection of carbon emission reduction collaboration suppliers for Tmall Mart and compare it with the latest existing decision-making methods. The results demonstrate the applicability of the proposed method and the effectiveness of the introduced probability splitting algorithm in avoiding information bias.

Firstly, this paper proposes a new multi-criteria decision making method for aiding platform-based enterprises in selecting carbon emission reduction collaboration suppliers in green supply chains. Secondly, in this method, we provided a new standard method to process probability hesitant fuzzy decision making information. Finally, the probability splitting algorithm was introduced to avoid information bias in the process of dealing with inconsistent lengths of probabilistic hesitant fuzzy elements.

Because of the multiple design elements and complicated relationship among design elements of complex products design, it is tough for designers to systematically and dynamically express and manage the complex products design process.

To solve these problems, a supernetwork model of complex products design is constructed and analyzed in this paper. First, the design elements (customer demands, design agents, product structures, design tasks and design resources) are identified and analyzed, then the sub-network of design elements are built. Based on this, a supernetwork model of complex products design is constructed with the analysis of the relationship among sub-networks. Second, some typical and physical characteristics (robustness, vulnerability, degree and betweenness) of the supernetwork were calculated to analyze the performance of supernetwork and the features of complex product design process.

The design process of a wind turbine is studied as a case to illustrate the approach in this paper. The supernetwork can provide more information about collaborative design process of wind turbine than traditional models. Moreover, it can help managers and designers to manage the collaborative design process and improve collaborative design efficiency of wind turbine.

The authors find a new method (complex network or supernetwork) to describe and analyze complex mechanical product design.

Despite the knowledge transfer in project contexts which has been extensively studied by scholars, the study on inter-organizational knowledge transfer in international construction projects is still scattered and unsystematic. This research aims to explore the key factors influencing inter-organizational knowledge transfer of international construction projects and analyze how these factors interact to create a synthetic framework that enhances the effectiveness of knowledge transfer (EKT).

At first, eight factors influencing inter-organizational knowledge transfer within international construction projects were identified, which were from the four dimensions of subject, relationship, channel and context, namely cultural distance, connection strength, organizational climate, intercultural competence, information technology capability, transmit willingness, receive willingness and richness of transfer channels. Then, a conceptual model was developed and 13 hypotheses were formulated, which were derived from a literature review and in-depth survey. After that, data from 353 respondents were collected and analyzed, and the hypotheses were tested by structural equation modeling analysis and bootstrapping test.

The results suggest that cultural distance hinders transfer willingness, which further affects EKT. Connection strength affects EKT by positively influencing transfer willingness and channel. Besides, organizational climate and intercultural competence positively influence transfer willingness and further affect EKT, while information technology capability affects the richness of transfer channels.

This research gives a thorough examination of the determinants influencing inter-organizational knowledge transfer of international construction projects, thus formulating available approaches that project managers and personnel can employ to effectively facilitate EKT.

This study aims to investigate the critical success factors of digital transformation in the construction industry and identify whether the respondents' profiles influence their perceptions of critical success factors for digital transformation.

To achieve the objectives, a literature review was first conducted based on technology-organization-environment (TOE) framework. Then a questionnaire survey was carried out. A total of 86 people were surveyed in this study, mainly from the construction industry. At the level of data processing, SPSS was used for analysis. Among the main tests used were the Shapiro–Wilk test, reliability analysis, mean rank analysis, Kruskal–Wallis test and Mann–Whitney U test.

The study identified 15 critical success factors of digital transformation and found the three most important factors of digital transformation. Furthermore, respondents with different years of experience, enterprises with different sizes and different years made no difference in the perception of factors. Respondents' different occupations and types of enterprises created a bias in the perception of factors for digital transformation.

Firstly, the small sample size of the questionnaire limits the reference value of data analysis for certain groups. In addition, this study focuses broadly on construction enterprises without specifically examining different types of enterprises, thus lacking depth in its findings.

This study establishes a connection between TOE theory and the construction industry through an extensive literature review, identifying relevant factors and providing a reference for future research.

The study's results would enrich the research on digital transformation in the construction industry and provide a reference for the digital transformation of construction enterprises.

Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

In the process of group decision-making, there may be multilayer subjects. In other words, members of the decision-making group may come from different layers and there is interest game among decision experts. Therefore, it is an extremely important topic to aggregate the information of decision experts who are involved in hierarchical relations and gaming relations so as to effectively address game conflicts and reach game cooperation.

First, a programming model is established to minimize the difference of expert opinions in hierarchical decision-making, and the method to solve the optimal solution is given. Second, the cooperative game model and its properties are discussed by using cooperative game and Shapley value, and the method to determine the weight vector between layers is also proposed.

This model can quickly aggregate information and achieve game equilibrium among decision-makers with hierarchical relationships. It can be widely used in decision evaluation with hierarchy structure and has certain practical value.

In order to solve the problem that experts at different levels may have conflicts of interest in multilayer grey situation group decision-making process, cooperative game and Shapley value theory are introduced into the study, and a multilayer grey situation group decision-making model based on cooperative game is constructed. The validity and practicability of the model are illustrated by an example.

The development of complex products and systems is a continuously iterative process from customer requirements to a mature design. Design changes derived from multisources occur frequently during the design process. Furthermore, change propagation will impose impacts on design costs and lead times. In view of this, how to predict and control the propagation of multisource design change to reduce the changes impact is an urgent issue in the development of complex product.

In this paper, a new four-phase routing approach based on weighted and directed complex networks is proposed for multisource design change propagation. Phase I: as the foundation of this research, a product network model is established to quantify describe the complex product. Phase II: the hub nodes are identified based on the LeaderRank algorithm, which can be regarded as multisource nodes of design changes. Phase III: a calculation method for change propagation intensity is proposed, which improves the systematicness and accuracy of the evaluation results. In this paper, change propagation intensity is defined by four assessment factors: importance degree of parts, execution time of design tasks, coupling strength between parts and propagation likelihood. Phase IV: a routing method of multisource design change propagation and ant colony optimization algorithm are proposed in this paper, which can solve the coupling conflicts among change propagation paths and improve the search efficiency by using the parallel search strategy.

The proposed method and another method are used to search the optimal propagation path of multisource design change of a motorcycle engine; the results indicate that this method designed in this study has a positive effect on reducing the change impact, market response time and product design costs when design change occurs in the products design process.

The authors find a new method (a network-based four-phase routing approach) to search the optimal propagation path of multisource design change in complex products design.