Search results

This study aims to clarify the psychological mechanism of international contractors' fraud by linking performance pressure to fraudulent intention through the displacement of responsibility and addressing the moderating role of moral intensity.

Based on moral disengagement theory, performance pressure was hypothesized to be positively associated with fraudulent intention by mediating the displacement of responsibility. Drawing on the issue-contingent theory, moral intensity was hypothesized to inhibit the relationship between performance pressure and displacement of responsibility in three aspects: magnitude of consequences (MC), probability of effect (PE) and social consensus (SC). The scenario-based questionnaire was conducted to collect information from contractors spread across 50 countries. The partial least squares structural equation modeling was employed to assess the proposed model.

The results demonstrated that performance pressure was positively associated with the fraudulent intention, and displacement of responsibility exerted a positive partial mediating impact between performance pressure and fraudulent intention. Regarding moral intensity in the moderating analysis, the negative moderating role of MC and PE was significant, while that of SC was insignificant.

This study provides international construction practitioners with a deep understanding of the formation mechanism of fraud at the psychological level.

It clarifies the psychological mechanism from performance pressure to fraudulent intention by integrating a mediation impact from the displacement of responsibility and a moderation effect from MC and PE. It contributes to the sparse research on how situational factors shape individuals' fraudulent intentions in the international context. It provides a fresh perspective on fraud by constructing a formation model from moral psychological theories.

Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective; therefore, internal corporate drivers and external pressures play a crucial role in encouraging them to engage in sustainable CSR practices. This study systematically examines the dynamic impact of internal and external stakeholders on the CSR practices of CICs.

This study adopted a structural equation model (SEM) to identify and validate a correlation between stakeholders and CSR practices. Standardized causal coefficients estimated in SEM were used to construct a fuzzy cognitive map (FCM) model to illustrate the effect of stakeholders on CSR practices with linkage direction and weights. Predictive, diagnostic, and hybrid analyses were performed to dynamically model the variation in stakeholders on the evolution of CSR practices.

The empirical results demonstrate that (1) employee participation in CSR has the greatest impact on CSR practices, followed by CSR strategies, partner and customer expectations, and finally government regulations. (2) In the early stage of CSR fulfillment, CSR strategies have the greatest influence on CSR practices; in the later stage of CSR fulfillment, employee participation in CSR has the greatest influence on CSR practices. (3) In the long run, the most effective and economical integrated interventions are those that address employee participation in CSR, partner expectations and customer expectations, and intervention in CSR strategies is needed if the level of CSR practice needs to be improved in the short term.

This study contributes to the research on the influence mechanisms of CSR practices of CICs and systematically analyzes their dynamic influence on CSR practices of CICs from the perspective of stakeholders.

This study aimed to identify a specific taxonomy of entry modes for international construction contractors and to develop a decision-making mechanism based on case-based reasoning (CBR) to facilitate the selection of the most suitable entry modes.

According to the experience orientation of the construction industry, a CBR entry mode decision model was established, and based on successful historical cases, a two-step refinement process was carried out to identify similar situations. Then the validity of the model is proved by case analysis.

This study identified an entry mode taxonomy for international construction contractors (ICCs) and explored their decision-making mechanisms. First, a two-dimension model of entry mode for ICCs was constructed from ownership and value chain dimensions; seven common ICC entry modes were identified and ranked according to market commitment. Secondly, this study reveals the impact mechanism of the ICC entry mode from two aspects: the external environment and enterprise characteristics. Accordingly, an entry mode decision model is established.

Firstly, sorting out the categories of entry mode in the construction field, which provide an entry mode list for ICCs to select. Secondly, revealing the impact mechanism of ICC entry mode, which proposes a systematic decision-making system for the selection of ICC entry mode. Thirdly, constructing a CBR entry mode decision-making model from an empirical perspective, which offers tool support and reduces transaction costs in the decision-making process.

The study on entry modes for ICCs is still in the preliminary exploratory stage. The authors investigate the entry mode categories and decision-making mechanisms for ICCs based on Uppsala internationalization process theory. It widens the applied scope of Uppsala and promotes cross-disciplinary integration. In addition, the authors creatively propose a two-stage retrieval mechanism in the CBR model, which considers the order of decision variables. It refines the influence path of the decision variables on ICCs' entry mode.

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.

This study is devoted to examining the peer effects of engineering enterprises’ internationalization from the viewpoint of industry subdivision and how information and competition alter peer effects. Furthermore, the heterogeneity of peer effects is analyzed based on manager characteristics.

In this study, multiple regression analysis was conducted on a sample of 38 Chinese engineering enterprises listed in the Engineering News-Record’s top 250 international contractors over the period of 2013–2021. This study collected the paired data from the enterprise annual reports and the China Stock Market & Accounting Research database.

The results reveal that (1) there exist peer effects within the subdivided industry of the engineering field; the quality of information disclosure of peer enterprises and degree of market competition moderate the peer effects; (2) the peer effects of internationalization are more pronounced in engineering enterprises with managers who have lower ability, hold greater power or are older.

The findings of this study contribute to understanding the peer effect in the process of internationalization of engineering enterprises, and help enterprises to effectively supervise the irrational behavior of top managers, so as to develop better internationalization strategies.

The results extend peer effects to the subdivision industry of the engineering field. Furthermore, this study also enriches the relevant research on peer effects among enterprises by empirically supporting the moderating role of information and competition as well as analyzing the heterogeneity of the peer effects from the perspective of manager characteristics.

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

Given the increasing importance of engineering insurance, it is still unclear which specific factors can enhance the role of engineering insurance as a risk transfer tool. This study aims to propose a hybrid approach to identify and analyze the key determinants influencing the consumption of engineering insurance in mainland China.

The empirical analysis utilizes provincial data from mainland China from 2008 to 2019. The research framework is a novel amalgamation of the generalized method of moments (GMM) model, the quantile regression (QR) technique and the random forest (RF) algorithm. This innovative hybrid approach provides a comprehensive exploration of the driving factors while also allowing for an examination across different quantiles of insurance consumption.

The study identifies several driving factors that significantly impact engineering insurance consumption. Income, financial development, inflation, price, risk aversion, market structure and the social security system have a positive and significant influence on engineering insurance consumption. However, urbanization exhibits a negative and significant effect on the consumption of engineering insurance. QR techniques reveal variations in the effects of these driving factors across different levels of engineering insurance consumption.

This study extends the research on insurance consumption to the domain of the engineering business, making theoretical and practical contributions. The findings enrich the knowledge of insurance consumption by identifying the driving factors specific to engineering insurance for the first time. The research framework provides a novel and useful tool for examining the determinants of insurance consumption. Furthermore, the study offers insights into the engineering insurance market and its implications for policymakers and market participants.

This study aims to investigate the factors influencing the social responsibility performance of Belt and Road Initiative (BRI) megaprojects. Specifically, it examines the role of isomorphic pressures and the joint influence of perceived benefits and top management support on megaproject social responsibility performance (MSRP).

Drawing from institutional theory, social exchange theory, and top management literature, this study established a conceptual model featuring eleven hypotheses. Subsequently, a questionnaire survey was administered to collect data from 238 actively engaged participants in BRI megaprojects. Structural Equation Modelling was utilised to analyse the data.

The empirical findings indicate that mimetic and coercive pressures positively influence MSRP. Perceived benefits and top management support significantly enhance MSRP. Moreover, perceived benefits and top management support partially mediate the effects of coercive and mimetic pressures. However, when it comes to normative pressures, their impact on MSRP is solely channelled through the support of top management.

This study is one of the early endeavours to explore the factors influencing the social responsibility performance of BRI megaprojects. It sheds light on the interplay between external pressures and internal factors in shaping social responsibility efforts in these projects. These findings are of particular significance for BRI actors and stakeholders, offering guidance for enhancing social responsibility strategies within the context of BRI megaprojects.

In traditional Bayesian belief networks (BBNs), a large amount of data are required to complete network parameters, which makes it impractical. In addition, no systematic method has been used to create the structure of the BBN. The aims of this study are to: (1) decrease the number of questions and time and effort required for completing the parameters of the BBN and (2) present a simple and apprehensible method for creating the BBN structure based on the expert knowledge.

In this study, by combining the decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modeling (ISM) and BBN, a model is introduced that can form the project risk network and analyze the impact of risk factors on project cost quantitatively based on the expert knowledge. The ranked node method (RNM) is then used to complete the parametric part of the BBN using the same data obtained from the experts to analyze DEMATEL.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively.

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively. The obtained results are based on a single case study project and may not be readily generalizable.

The presented framework makes the BBN more practical for quantitatively assessing the impact of risk on project costs. This helps to manage financial issues, which is one of the main reasons for project bankruptcy.

This paper aims to identify the unidimensionality and reliability of 84 factors that influence the performance of construction projects and develop a confirmatory factor analysis (CFA) model.

The study adopted a deductive research approach and started by identifying the positive factors that influence construction project performance. This was followed by the modification of the identified factors. After that, a questionnaire was developed out of the factors for data collection. Exploratory factor analysis was used to establish the factor structure of the positive factors, and this was verified using CFA afterwards. A model fit analysis was performed to determine the goodness of fit of the hypothesised model, followed by the development of the confirmatory model.

The study demonstrated substantial correlation in the data, sufficient unidimensionality and internal reliability. In addition, the estimated fit indices suggested that the postulated model adequately described the sample data.

The paper revealed that performance can be enhanced if stakeholders identify and leverage the positive factors influencing performance. The paper suggests that project stakeholders, particularly government, project owners, consultants and construction firms, can improve project performance by critically examining economic and financial systems (EFS), regulation and policy-making systems (RPS), effective management practices (EMP) and project implementation strategies (PIS).

The contribution of this paper to the present literature is identifying the positive factors and developing the confirmatory factor model. The model comprised 42 positive variables under four indicators: EMP, RPS, PIS and EFS.