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1 – 10 of 33Linlin Xie, Ziyuan Luo and Bo Xia
From a psychosocial perspective, this study aims to understand the impact of psychosocial safety climate (PSC) on the intent to stay of construction workers and provides practical…
Abstract
Purpose
From a psychosocial perspective, this study aims to understand the impact of psychosocial safety climate (PSC) on the intent to stay of construction workers and provides practical recommendations for construction enterprises to retain construction workers.
Design/methodology/approach
This study proposes the conceptual framework explained by the conservation of resources (COR) theory and develops a mediation model of “PSC – job satisfaction – intent to stay” within the framework supported by the stimulus–organism–response (SOR) model. Then, a questionnaire survey of 489 construction workers in Guangzhou was conducted and structural equation modeling (SEM) analysis was performed on the data collected.
Findings
Results show that PSC has a significant and positive effect on job satisfaction and intent to stay. In addition, job satisfaction partially mediates the effect of PSC on intent to stay. Hence, the theoretical model of “PSC – job satisfaction – intent to stay” has been empirically tested and supported.
Originality/value
This study is the first to investigate the effect of PSC on intent to stay and enriches the research on the retention of construction workers. The COR theory explains well the mechanism of PSC influence on intent to stay, thus expanding its application to the construction field. Moreover, this study provides practical recommendations for construction enterprises to retain workers so as to build a stable and productive workforce.
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Nayana Dissanayake, Bo Xia, Martin Skitmore, Bambang Trigunarsyah and Vanessa Menadue
The purpose of this study was to prioritize the appropriate generic contractor selection criteria for Engineering–Procurement–Construction (EPC) projects in the construction…
Abstract
Purpose
The purpose of this study was to prioritize the appropriate generic contractor selection criteria for Engineering–Procurement–Construction (EPC) projects in the construction industry.
Design/methodology/approach
Proceeding from a review of previous studies and validation by a small group of experts, a preliminary set of 16 criteria was first identified. This was followed by three rounds of Delphi surveys: firstly, with 64 experienced participants confirming the relevance of the 16 criteria; secondly, with a reduced subgroup of 47 more experienced participants scoring the importance of each; and finally, providing the opportunity for these 47 to revise their scores in the light of knowing the aggregated results of the previous round.
Findings
The results show the consensus view, of which the most important criteria are ranked as past performance, project understanding, technical attributes, key personnel, health and safety, past experience, time, management, financial, contractual and legal, quality, cost, relationships, environmental and sustainability, organizational and industrial relations, and geographic location.
Originality/value
The findings are useful for both practitioners and academics in making a significant contribution to the body of knowledge of the EPC process. This will assist in providing a better understanding of criteria importance and pave the way to developing an EPC contractor selection model involving the criteria most needed to objectively identify potential contractors and evaluate tenders.
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Xiaoyan Jiang, Sai Wang, Yong Liu, Bo Xia, Martin Skitmore, Madhav Nepal and Amir Naser Ghanbaripour
With the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a…
Abstract
Purpose
With the increasing complexity of public–private partnership (PPP) projects, the amount of data generated during the construction process is massive. This paper aims to develop a new information management method to cope with the risk problems involved in dealing with such data, based on domain ontologies of the construction industry, to help manage PPP risks, share and reuse risk knowledge.
Design/methodology/approach
Risk knowledge concepts are acquired and summarized through PPP failure cases and an extensive literature review to establish a domain framework for risk knowledge using ontology technology to help manage PPP risks.
Findings
The results indicate that the risk ontology is capable of capturing key concepts and relationships involved in managing PPP risks and can be used to facilitate knowledge reuse and storage beneficial to risk management.
Research limitations/implications
The classes in the risk knowledge ontology model constructed in this research do not yet cover all the information in PPP project risks and need to be further extended. Moreover, only the framework and basic methods needed are developed, while the construction of a working ontology model and the relationship between implicit and explicit knowledge is a complicated process that requires repeated modifications and evaluations before it can be implemented.
Practical implications
The ontology provides a basis for turning PPP risk information into risk knowledge to allow the effective sharing and communication of project risks between different project stakeholders. It can also have the potential to help reduce the dependence on subjectivity by mining, using and storing tacit knowledge in the risk management process.
Originality/value
The apparent suitability of the nine classes of PPP risk knowledge (project model, risk type, risk occurrence stage, risk source, risk consequence, risk likelihood, risk carrier, risk management measures and risk case) is identified, and the proposed construction method and steps for a complete domain ontology for PPP risk management are unique. A combination of criteria- and task-based evaluations is also developed for assessing the PPP risk ontology for the first time.
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Mohamed Saad Bajjou and Anas Chafi
Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do…
Abstract
Purpose
Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.
Design/methodology/approach
This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.
Findings
This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.
Originality/value
To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.
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Yuan Jiang, Emma García-Meca and Jennifer Martinez-Ferrero
Sustainability development goals (SDGs) cannot be achieved without a concerted effort from businesses and other organisations, being the corporate level is one of the keys to the…
Abstract
Purpose
Sustainability development goals (SDGs) cannot be achieved without a concerted effort from businesses and other organisations, being the corporate level is one of the keys to the achievement of SDGs. This study aims to explore the relationship between firms' adoption of SDG reporting in China and two main corporate-level factors, namely, board characteristics and ownership factors. Also, this study aims to determine which set of drivers – those related to board or ownership factors – exerts a greater influence on this reporting.
Design/methodology/approach
This research examines the impact of ownership and board-level factors on the SDG reporting of Chinese firms in the period 2016–2018, with a final sample of 455 firm-year observations operating in 11 activity sectors.
Findings
The results support the following: firstly, that board independence and size and the existence of a corporate social responsibility (CSR) committee favours firms addressing SDGs in their sustainability reporting while greater levels of foreign or institutional ownership are negatively related to a company's adoption of SDG reporting; secondly, two-stage logit regression results revealed that board-level factors exert greater explanatory power in the prediction of this reporting and have bigger weights in affecting the SDGs reporting.
Practical implications
This study focuses on assessing the drivers of SDGs; namely, what internal factors will facilitate companies' better implementation of SDG reporting to bridge the gap in this field, not only extending the investigation of corporate governance factors affecting SDGs but also examining the impact of corporate ownership on SDG reporting.
Originality/value
This study enriches and provides support for previous studies examining the drivers of SDGs in the private sector. In academia, addressing SDGs in business is still an emerging research stream that is still in an embryonic state; the reporting of SDGs in business is quite under-investigated in the sustainability literature. Moreover, literature on the drivers that promote better implementation of SDGs in business is even more scarce and incomplete. Some previous studies have ignored the impact of board size and the CSR committee. At the same time, there is no research to date on the impact of ownership on companies' SDGs reporting, which has been proved to play a large role in firms sustainability reporting.
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Chao Xia, Bo Zeng and Yingjie Yang
Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between…
Abstract
Purpose
Traditional multivariable grey prediction models define the background-value coefficients of the dependent and independent variables uniformly, ignoring the differences between their physical properties, which in turn affects the stability and reliability of the model performance.
Design/methodology/approach
A novel multivariable grey prediction model is constructed with different background-value coefficients of the dependent and independent variables, and a one-to-one correspondence between the variables and the background-value coefficients to improve the smoothing effect of the background-value coefficients on the sequences. Furthermore, the fractional order accumulating operator is introduced to the new model weaken the randomness of the raw sequence. The particle swarm optimization (PSO) algorithm is used to optimize the background-value coefficients and the order of the model to improve model performance.
Findings
The new model structure has good variability and compatibility, which can achieve compatibility with current mainstream grey prediction models. The performance of the new model is compared and analyzed with three typical cases, and the results show that the new model outperforms the other two similar grey prediction models.
Originality/value
This study has positive implications for enriching the method system of multivariable grey prediction model.
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Yi Li, Xinyu Zhou, Xia Jiang, Fan Fan and Bo Song
This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines…
Abstract
Purpose
This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.
Design/methodology/approach
The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).
Findings
Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.
Practical implications
The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.
Originality/value
The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.
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Dongdong Song, Wenxiang Qin, Qian Zhou, Dong Xu and Bo Zhang
The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose…
Abstract
Purpose
The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose of this study is to find the correlation between the initial aging of epoxy coatings and the typical marine atmospheric environmental factors.
Design/methodology/approach
The epoxy coatings were subjected to a one-year exposure in three typical marine atmospheres. Meanwhile, principal component analysis, linear regression and Spearman and gray correlation analysis were applied to quantify the environmental characteristics and establish correlations with the coating aging.
Findings
The results indicate that the coating will undergo macroscopic fading and chalking upon exposure to the marine atmosphere, while microscopic examination reveals holes, cracks and partial peeling. The adhesion performance and electrochemical properties of the coating deteriorated with prolonged exposure, coating aging mainly occurs with the generation of O-H bonds and the breakage of molecular chains such as C-N and C-O-C. The coating was most deeply aged after exposure to the Xisha, followed by Zhoushan and finally Qingdao. Environmental factors affect the photooxidative aging and hydrolytic degradation processes of coatings and thus coating aging. To further demonstrate the correlation between environmental factors and coating aging, principal component analysis was used. The correlation model between environmental factors and coating aging was subsequently obtained. The correlation model between the rate of coating adhesion loss (E) and the comprehensive evaluation parameter of environmental factors (Z) is expressed as E = 0.142 + 0.028Z. Meanwhile, the Spearman correlation analysis and gray correlation method were used to investigate the impact of each environmental factor on coating aging. Solar irradiation, relative humidity and wetting time have the highest correlation with coating aging, which are all above 0.8 and have the greatest influence on coating aging; wind speed and temperature have the smallest correlation with coating aging, which are about 0.6 and have the least influence on coating aging.
Originality/value
This paper establishes a correlation between typical marine environmental factors and coating aging performance, which is crucial for predicting the service life of other coatings in diverse environments.
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Quntao Wu, Qiushi Bo, Lan Luo, Chenxi Yang and Jianwang Wang
This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the…
Abstract
Purpose
This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.
Design/methodology/approach
With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.
Findings
The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.
Originality/value
It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.
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