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The activities using drum resources restrict the operation of multi-project systems. However, existing monitoring methods are not suitable for the characteristics of drum activities in the multi-project system. The authors therefore propose an adaptive capacity constraint buffer monitoring model based on the attributes of drum activities, aiming to build a high-efficiency progress control framework for multiple projects.

Considering the attributes and the interrelationship of drum activities, the monitoring reference points are determined on the basis of decentralized buffers. The authors next set action thresholds according to the relationship between the drum activities' interval margin and buffer consumption, and then the corresponding monitoring measures are taken.

The empirical results show that, compared to the classic methods, the proposed approach can effectively monitor the progress of the drum plan and realize the dual optimization of multi-project duration and cost.

The buffer consumption at the follow-up monitoring time point is neglected when determining the action thresholds. Prediction methods can be introduced to present more all-sided monitoring.

This paper fulfils the dual optimization of multi-project duration and cost. It provides a reference guide for project managers.

A capacity constraint buffer monitoring method suitable for a multi-project environment is produced.

The purpose of this paper is to quantify the evolutionary mechanism of coronavirus disease 2019 (COVID-19) impact on international construction multi-projects.

From three concepts of complexity, stressor and detractor risks, a multi-project simulation model under COVID-19 outbreak is proposed to study the characteristics of contingency with three peaks of ordered and disordered states. Specially, COVID-19 brings forth mitigation fee, epidemic prevention fee, holdup fee and schedule delay fee of multi-projects. By integrating parametric model, Monte Carlo and chaos theory, a comparative analysis of its contingency with or without COVID-19 is conducted. Summarizing the simulated results, their total contingencies at certain risk tolerance are obtained at two status of static at one-time point and dynamic over time. Meanwhile, some major risks including detractors, complexities and stressors are screened out for mitigation, especially for epidemic prevention and control. Eventually, the real case is illustrated to demonstrate its validity.

It provides a quantitative analysis framework for the impact of epidemic, a once-in-a-century black swan event with a long tail, on construction multi-projects.

It conduct an effective model to quantify impacts of COVID-19 on international construction multi-projects for implementing effective counter-measures, which lay foundation for claims among different stakeholders.

The term of detractor risk is applied to describe COVID-19 and quantify its impact upon international construction multi-projects. Further, a hybrid model by integrating parametric model and Monte Carlo in type I/II model is proposed to simulate their contingencies at disordered states. Finally, the simulated outcomes of these models are used to guide effective risk control to meet the requirements by the client.

This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.

This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.

The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.

A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.

Despite the knowledge transfer between projects has received increasing attention from scholars, few scholars still conduct comprehensive research on inter-project knowledge transfer from both horizontal and vertical perspectives. Besides, knowledge transfer is affected by multiple antecedent conditions, and these factors should be combined for analysis. Therefore, this paper aims to explore the key factors influencing knowledge transfer between projects using the fuzzy-set qualitative comparative analysis (fsQCA) method from both horizontal and vertical perspectives and how these factors combine to improve the effectiveness of knowledge transfer (EKT) between projects.

First, nine factors affecting knowledge transfer between projects were identified, which were from the four dimensions of subject, relationship, channel, and context, namely temporary nature (TN), time urgency (TU), transmit willingness (TW), receive willingness (RW), trust (TR), project-project transfer channels (PPC), project-enterprise transfer channels (PEC), organizational atmosphere (OA), and motivation system (MS). Then, the source of the samples was determined and the data from the respondents was collected for analysis. Following the operation steps of the fsQCA method, variable calibration, single condition necessity analysis, and configuration analysis were carried out. After that, the configurations of influencing factors were obtained and the robustness test was conducted.

The results of the fsQCA method show that there are five configurations that can obtain better EKT between projects. Configuration 3 (∼TN * ∼TU * TW * RW * TR * ∼PPC * PEC * MS) has the highest consistency, indicating that it has the highest degree of the explanatory variable subset. Configuration 1 (∼TN * ∼TU * TW * RW * PEC * OA * MS) has the highest coverage, meaning that this configuration can explain most cases. Also, the five configurations were divided into three types: vertical transfer, horizontal-vertical transfer, and channel-free transfer category.

Firstly, this study explores the key factors influencing knowledge transfer between projects from four dimensions, which presents the logical chain of influencing factors more clearly. Then, this study divided the five configurations obtained into three categories according to the transfer direction: vertical, horizontal-vertical, and channel-free transfer, which gives implications to focus on both horizontal knowledge transfer (HKT) and (VKT) when studying knowledge transfer between projects. Lastly, this study helps to realize the exploration of combined improvement strategies for EKT, thereby providing meaningful recommendations for enterprises and project teams to facilitate knowledge transfer between projects.

Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.

In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.

Due to the frenetic and dynamic working conditions ascribed to architecture, engineering and construction (AEC) project organizations, enormous research has addressed the poor mental health propensity of project management practitioners (PMPs). However, research has not considered the distant factors related to organizational design causing poor mental health. Therefore, this study addresses the problem by integrating institutional theory, agency theory and resource-based theory (RBT) to explore the relationship between organizational design elements: project governance, knowledge management, integrated project delivery, project management skills and mental health management indicators. Examples of mental health management indicators include social relationships, work-life balance and project leadership.

Purposive sampling method was adopted to collect survey data from 90 PMPs in 60 AEC firms in Australia. Structural equation modelling (SEM) was utilized to test the relationship between the variables.

The research found that project governance, knowledge management and integrated project delivery are positively correlated to mental health management indicators. However, the research finding suggests that project management skills have a negative impact on mental health management indicators.

The findings offer guidelines to AEC firms on achieving positive mental health management outcomes through concentration on project governance, knowledge management and integrated project delivery. It further calls for a reconsideration of existing project management skills causing poor mental health management outcomes.

An optimal control model is built considering the private sector's opportunistic effort diversion and reciprocal effort improvement, while a numerical study is conducted to draw some managerial implications.

In infrastructure PPP projects, private sectors may opportunistically divert part of their effort from the current projects to other projects to allocate their limited human resources. Nevertheless, this effort diversion can be inhibited by dynamic incentives since the private sectors reciprocally exert greater effort into the current projects when receiving the dynamic incentives. This article investigates how the government specifies the output standard that the private sector should meet and offers dynamic incentives to mitigate the private sector's opportunistic effort diversion.

The output standard for the private sector to acquire the dynamic incentives should be specified as the output level corresponding to the private sector's optimal long-run stationary equilibrium (OLSE) effort level, which decreases with its reciprocal preference level but increases with its effort-diverting level. The optimal dynamic incentives comprise an initial incentive and a periodic OLSE incentive, which declines with the reciprocal preference level but improves with the effort-diverting level. Besides, the numerical study reveals that the government should distinguish whether the bidders have high effort-diverting levels and, if so, should focus on their reciprocal preference levels and decline the bidders with low reciprocal preference to avoid utility loss.

This article provides a theoretical model combining opportunistic behavior with reciprocal preference through an optimal control lens, thus embedding the problem of incentive design into a broader socioeconomic framework.

The purpose of this study is to ascertain and list the most effective management strategies in efficiently handling the project complexities to enhance the performance of the project.

To fulfill the aim of this study, a comprehensive literature review was conducted, and the qualitative Delphi technique in two rounds was applied. Participants of the Delphi technique consisted of 12 subject matter experts (SMEs) with cumulative experience of 250 years in working in construction projects. In the first round of the Delphi technique, SMEs were asked to provide complexity management strategies to address the complexities due to 37 complexity indicators (CIs) under 11 complexity categories. In the second round of the Delphi technique, SMEs identified the top three management strategies for each of the 37 CIs.

This study collected the outcome of the two-round Delphi technique and based on the output developed the list of strategies to manage complexities related to each indicator. For example, establishing a well-informed governance team, assigning a Project Manager (PM) when the number of projects is more than one in an organization, and assigning a PM efficient enough to communicate with higher authority effectively will help in managing complexity that arises due to faulty assessment of the influence of a project on the organization’s overall success.

This study will help practitioners in effectively managing the project complexities, and thus will reduce the monetary loss associated with project complexities.

Documentation plays a key role in navigating the costs of construction projects. Traditional document management systems (TDMS) used in developing countries, however, hinder the achievement of expected cost targets. Although the electronic document management system (EDMS) has been implemented to improve documentation, the Sri Lankan construction industry has failed to effectively adapt to it. Hence, this study aims to provide strategies for the effective application of EDMS to the cost management of Sri Lankan mega construction projects.

This study uses a qualitative approach followed by 12 semi-structured expert interviews. Quantity surveying experts were selected through judgemental sampling. Manual content analysis was used to analyse the data.

The EDMS is more suitable for megaprojects than traditional methods of documentation in terms of functionality, neutrality, interoperability, space, reversibility and delivery speed. However, there are contradictory views about cost and security. Furthermore, five transitional challenges of EDMS have been identified under the three key themes of cost, stakeholder perception and technical difficulties. Four reasons were also identified as causing these five challenges. Seven suggestions were made to deal with these transitional challenges and three key feasible solutions for the Sri Lankan construction industry regarding the EDMS were identified. Development of Sri Lankan software with low initial cost was highlighted as the most feasible solution.

This is a novel study to investigate the applicability of EDMS to cost management mechanisms of megaprojects in Sri Lanka. The findings reveal transitional challenges and appropriate feasible solutions for EDMS adaptation. This can be applied to the cost management of megaprojects in other developing countries as well.

Architectural, engineering and construction (AEC) project organizations are under constant pressure to improve the mental health of project management practitioners (PMPs) due to complexity and dynamism involved in project management practices. Drawing on institutional theory, this research explores how external environmental factors, political factors, economic factors, social factors, technological factors, environmental factors and legal factors (PESTEL), influence mental health management indicators that contribute to positive mental health.

Purposive sampling method was used to collect survey data from 82 PMPs in 60 AEC firms in Australia. Structural equation modelling was used to test the hypotheses based on 82 items of data collected from PMPs.

Overall, this study revealed interesting findings on the impact of external environmental factors on mental health. The hypothesized positive association between political factors and mental health management indicators was rejected. The data supported the proposed hypothetical correlation between economic factors and mental health management indicators and the influence of social factors on mental health management indicators. Moreover, a hypothetical relationship between technological factors and mental health management indicators was supported. The significant positive impact of environmental factors on mental health management indicators proposed was supported, and legal factors’ positive correlation on mental health management indicators was also supported.

Despite the limitations, the present findings suggest that all the external environment factors except political factors shape mental health management outcomes.