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Cost contingency is widely employed to address project risks. This systematic literature review aims to develop a framework for understanding risks in project cost contingency estimation.

A systematic literature review of 859 abstracts and 67 full articles was conducted using a framework synthesis method.

The study establishes a six-element risk framework for project cost contingency estimation, encompassing event, consequence, uncertainty, probability, knowledge, and mitigation. Twelve risk dimensions in the project cost contingency estimation are further developed.

This study contributes to the project management literature by constructing a framework for understanding risks in project cost contingency estimation. This framework provides guidance for enhancing the accuracy of project cost contingency estimation.

Safety professionals' primary job is to execute safety control measures towards frontline personnel, and previous studies focus on the effectiveness of such controls. Rare research efforts, however, have been devoted to the effectiveness of management control measures towards safety professionals themselves. This study aimed to fill up this knowledge gap by examining whether safety professionals under differing management control configurations differ in their work attitudes, including affective commitment, job satisfaction, career commitment and intention to quit.

Drawing on a holistic view of control, five forms of management control, i.e. outcome control, process control, capability control, professional control and reinforcement, were investigated. A cross-sectional questionnaire survey targeting at construction safety professionals was conducted. The latent profile analysis approach was employed to identify how the five forms of management control are configured, i.e. identifying the distinctive patterns of control profiles. The Bolck–Croon–Hagenaars method was then used to examine whether safety professionals' work attitudes were different across the identified control profiles.

Seven distinct control profiles were extracted from the sample of 475 construction safety professionals. The overall test of outcome means showed that mean levels of affective commitment, job satisfaction and intentions to quit were significantly different across the seven profiles. The largest that was also the most desirable subgroup was the high control profile (n = 161, 33.9%). The least desirable subgroups included the low control profile (n = 75, 15.8%) and the low capability and professional control profile (n = 12, 2.5%). Pairwise comparison suggested that capability, professional and process controls were more effective than outcome control and reinforcement.

In theory, this study contributes to the burgeoning literature on how to improve the effectiveness of control measures targeted at safety professionals. The results suggested that effective management controls involve a fine combination of formal, informal, process and output controls. In practice, this study uncovers the ways in which managers leverage the efforts of safety professionals in achieving safety goals. Particularly, it informs managers that the control configurations, instead of isolated controls, should be executed to motivate safety professionals.

Sharing tacit knowledge across firm boundaries is challenging in architectural and engineering design projects as tacit knowledge is embedded in the designer’s mind. It thus requires autonomous motivation. This study aims to examine how clients integrate distributive justice (DJ), procedural justice (PJ) and interactional justice (IJ) to motivate tacit knowledge sharing in interorganizational architectural and engineering (A/E) design projects.

A theoretical model was built, describing how the combination of distributive, procedural and interactional justice influences tacit knowledge sharing. This model was then verified using latent profile analysis (LPA) of 360 A/E design projects.

A total offour subgroups with quantitatively different combinations of distributive, procedural and interactional justice were identified. Within each subgroup, the levels of the three forms of justice were quite aligned. The results indicate that clients often implement interorganizational justice in a collective manner. Among the four subgroups, projects with the highest level of justice combination have a significantly higher level of tacit knowledge sharing than the other three. This indicates that sharing of tacit knowledge is driven by the overall level of interorganizational justice.

The configurational approach complements previous research by presenting how combinations of interorganizational justice influence tacit knowledge sharing in A/E design projects.

Collaboration is essential to BIM-enabled construction projects (BECPs). To facilitate collaboration, various strategies have been proposed. Usually, project team adopts single collaboration strategy for convenience. However, BIM-based collaboration is rather dynamic and exposed to a lot of barriers and risks, which easily changes collaboration conditions among partners. Therefore, better understanding of collaboration conditions in BECPs is crucial to develop flexible and suitable strategies. To fill in the gap, this study intends to identify typical collaboration profiles in BECPs and develop a profile-oriented strategy selection framework.

This study establishes a six-dimensional collaborative behavior matric based on a comprehensive literature review to profile collaboration. Then a questionnaire survey is conducted to collect the collaboration data from 162 BECPs in China. Finally, latent profile analysis (LPA) is utilized to identify the typical collaboration profiles in BECPs.

Through LPA, four profiles are identified, including restricted collaboration profile, smarmy collaboration profile, intuitive collaboration profile, and modest collaboration profile. A profile-oriented strategy selection framework is also established to match strategies with collaboration profiles. Two major categories of strategies are proposed to promote these collaboration profiles including trust building and elevating strategies and collaborative behaviors facilitating strategies.

These identified profiles can provide an insightful understanding on the diversified collaboration conditions in BECPs.

The profile-oriented strategy selection framework will help managers develop strategies flexibly to promote collaboration in BECPs.

This study validates four typical collaboration profiles in BECPs. Moreover, a profile-oriented strategy selection framework is also established for collaboration facilitation in BECPs.

Project managers rely on control strategies to deliver excellent outputs. However, little is known about how clients' project managers select control strategies in projects which are knowledge-intensive and have intangible outputs. This study aims to examine how clients' project managers select project control strategies in professional service projects.

A questionnaire survey of 360 architectural and engineering (A/E) design projects was adopted. Data were analyzed through the hierarchical regression.

Both clients' knowledge of measuring outcomes and process uncertainty give rise to their project managers setting up behavior and social controls. Level of process uncertainty positively moderates the impact of client's knowledge of measuring outcomes on outcome control.

This study mainly examined the client's knowledge of measuring outcomes and process uncertainties. Future studies could be conducted to expand the scope by including other contextual factors, for instance market and regulatory factors.

From the client side, if they want to simultaneously adopt outcome, behavior and social controls, they would need to increase their knowledge of measuring outcomes by adopting established assessment tools or appointing a third party to assist in design outcome evaluation.

This study contributes to the body of knowledge by showing that the level of intangibility of project outputs influences the types of control system which project managers adopt.

Drawing upon the ambivalence literature, the purpose of this paper is to explore clients’ ambivalence caused by the co-existence of trust and distrust and to investigate how clients respond to the ambivalence.

Qualitative research strategies using multiple data sources were adopted. Face-to-face interviews were the major method for gathering data. Additional data sources included archival cases, official reports, regulations and rules and survey reports.

The results identified that clients’ ambivalence occurs in the face of the co-existence of trust and distrust. Clients might trust contractors on certain aspects and distrust of others or when they realize that trust and/or distrust have mixed merits and demerits. As a response strategy to the ambivalence, clients may choose to oscillate between trust and distrust in accordance with contractors’ quality and cost performance.

One limitation is that dwelling fit-out projects are generally small in size. Parties in small size projects might have different mindsets than large projects. Thus, it is worthwhile to extend the framework to the context of large projects.

Managers or clients should be aware of the double-edged sword nature of trust and distrust. To deal with the ambivalence resulting from co-existence of trust and distrust, a proper balance of trust and distrust might be effective.

This study contributes an ambivalence approach to the trust research in project management.

One of the solutions to manage large public projects that are complex and difficult to manage is through relationship management. Although formal and relational approaches have been adopted in managing relationships, it is widely recognized that participants from developed and developing economies have different mindsets toward these two approaches. The purpose of this paper is hence to elucidate the more effective practices for managers to manage relationships in large public projects that are in countries of different sizes and stages of development.

A structured questionnaire survey was conducted. Multiple stakeholders involved in public construction projects in Singapore and China that include public sector clients and consultants, private sector contractors and conszultants, were approached for data collection to provide information on one of their completed large public project.

Both Singapore and China primarily adopt contractual governance by making rational decisions, pursuing profit and using the contract to guard against trouble. Participants in Singapore are more deeply committed and work more collaboratively than their counterparts in China. Project partners in China build stronger relationships, which may be due to the importance of “guanxi” to conduct business activities there.

The comparative study provides managers with different sets of governance practices to adopt to improve the relationships with public clients in large public projects under different environments. In large public projects in developed countries, participants should rely more on relational practices that show commitment and teamwork, while those in developing countries participate in activities that build up their social networks.

Megaproject performance measurement (MPM) has received great attention in the project management community, but it primarily focused on the design of performance measures or frameworks. Yet, whether MPM utilization can improve megaproject performance and how project actors use MPM to improve megaproject performance is less well understood. This study aims to investigate whether and how the use of MPM can contribute to better megaproject performance.

Through the lens of the lever of control, this study conceptualizes MPM utilization as diagnostic use and interactive use. A holistic research model and related hypotheses integrating MPM use, project complexity and megaproject performance were established. The model was validated using a partial square-structural equation modeling method.

Based on 214-megaproject data collected through a questionnaire survey in China, the results show positive effects of diagnostic use and interactive use on megaproject performance. Both, however, have substitutional interaction effects. The moderating results suggest that the higher project complexity weakens the positive effects of MPM utilization on megaproject performance.

This study advances megaprojects performance measurement and management literature by validating the value of MPM utilization on performance. It also presents practical implications for project managers to improve performance by appropriate MPM utilization.

More attention should be paid to project managers’ (PMs) job satisfaction as they play an important role in ensuring projects are completed successfully. The purpose of this paper is to identify human resource management (HRM) policies and practices that lead to higher PMs’ job satisfaction.

A questionnaire survey was conducted on PMs who are working in construction firms and project management consultancy firms. Data were collected via random, convenience and snowball sampling. The data collected were analysed using partial least square-structural equation modelling, independent samples t-test and Pearson’s correlation.

The findings show that PMs who are satisfied with their firms’ HRM practices and job rewards also have higher job satisfaction. Several HRM strategies that give rise to higher job satisfaction are identified, e.g. a system to recognise and develop talent, and taking active steps to identify and develop backups in case of emergency. Unfortunately, some practices are not implemented to a significant extent, and these include: systematically recruiting and retaining talented PMs, encouraging PMs to plan for their careers, offering performance and development coaching, and appraising employees.

The limitations include the low response rate and the relatively small sample size of 81. The profile of respondents is largely from construction companies with more than 150 staff, and, therefore, the findings are more applicable to medium- to large-sized construction firms.

The study identified many HRM practices and policies that are significantly associated with PMs’ job satisfaction, yet many of these are not implemented to a significant extent by the employers. The practical implication is that employers of PMs should systematically implement these in order that their PMs have higher job satisfaction which is important for a project’s success.

The originality of this research is that the HRM practices and policies that are associated with job satisfaction of PMs are uncovered. Its value is in showing that PMs derive greater job satisfaction when HRM policies encompass talent development, career coaching and a personalised management style. Among these important practices, those that have been neglected were also identified. The study offers recommendations on the HRM practices that firms should be put in place for their PMs to experience higher job satisfaction.

The purpose of this paper is to make a correlation analysis between students’ online learning behavior features and course grade, and to attempt to build some effective prediction model based on limited data.

The prediction label in this paper is the course grade of students, and the eigenvalues available are student age, student gender, connection time, hits count and days of access. The machine learning model used in this paper is the classical three-layer feedforward neural networks, and the scaled conjugate gradient algorithm is adopted. Pearson correlation analysis method is used to find the relationships between course grade and the student eigenvalues.

Days of access has the highest correlation with course grade, followed by hits count, and connection time is less relevant to students’ course grade. Student age and gender have the lowest correlation with course grade. Binary classification models have much higher prediction accuracy than multi-class classification models. Data normalization and data discretization can effectively improve the prediction accuracy of machine learning models, such as ANN model in this paper.

This paper may help teachers to find some clue to identify students with learning difficulties in advance and give timely help through the online learning behavior data. It shows that acceptable prediction models based on machine learning can be built using a small and limited data set. However, introducing external data into machine learning models to improve its prediction accuracy is still a valuable and hard issue.