Project Management Research Articles

State Tolerance of Ambiguity Drives Performance and Well-Being Outcomes Within Project Managers: Evidence from a Five-Wave Longitudinal Study

This study investigates Tolerance of Ambiguity in project managers, focusing on how their ability to navigate ambiguous situations varies over time and influences their performance. In a four-week study of 275 project managers, we tracked changes in Tolerance of Ambiguity in project managers and found that these temporary fluctuations were significantly associated with positive mood, adaptive performance, and project progress. Factors such as self-control, coping skills, creativity, and supportive leadership emerged as key drivers of these changes. This study highlights Tolerance of Ambiguity as a dynamic, context-dependent competency in project managers, offering novel insights for enhancing project managers’ ability to navigate ambiguous situations.

Assessing the impact of artificial intelligence on project efficiency enhancement

The study explores the impact of artificial intelligence (AI) technologies on project management (PM) across different industries. It aims to assess how AI adoption in PM affects project efficiency. The study surveyed 159 project supervisors and specific project managers implementing projects from 7 industries in the Republic of Kazakhstan: software, green energy, engineering, construction, science, transport, and tourism. The research used variance and linear regression analyses to evaluate the relationship between AI adoption and project efficiency level measured by the Likert scale from 1 to 5 and test the associated hypotheses. The results show that AI adoption varies among industries, with software, construction, and scientific projects being the most active users. The study also found that the use of AI differed across eight project performance domains, with the stakeholder domain using voice technologies and process automation and the uncertainty domain using fewer tools. Projects with higher AI adoption rates showed higher efficiency scores (for example, in Software projects, the AI adoption rate is 3.2; the efficiency rate is 3.3), while those with lower efficiency levels (for example, in the Tourism industry, the AI adoption rate is 1.9; the efficiency rate is 2.2) showed the worst results. Decision-making systems, process automation, and voice technologies are the three most critical AI technologies PM professionals use to improve project efficiency. Acknowledgments This research has been funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19680313).

What impacts the productivity performance of government construction projects?

PurposePrevious research has advanced in two-stage construction project productivity (CPP) evaluation by integrating site efficiency (SE) in the delivery and utilisation effectiveness (UE) in the post-delivery stages. The literature has separately addressed the factors affecting these three constructs. However, the interrelationships among them are rarely discussed together. This study aims to systematically identify the influencing factors of CPP, SE and UE and disentangle interrelationships among the three constructs.Design/methodology/approachThe paper first reviews the literature about the two-stage project productivity evaluation framework for government construction projects. Then this paper proposes hypotheses regarding the relationships between the three constructs and identifies influencing factors associated with the constructs. Based on questionnaire survey from over 200 government construction project professionals in China, the structural equation modelling is adopted to validate the hypotheses.FindingsThe paper provides empirical insights that CPP can be directly influenced by UE to a large extent but indirectly impacted by SE through its effects on UE. The findings indicate that CPP is not a simple sum of SE and UE, and consequently reveals the complex, non-linear and indirect relationships between SE and CPP.Research limitations/implicationsFuture research should further extend the timeframe boundary to merge the pre-delivery stage (e.g. design and planning), findings of which may propose a more generalised understanding and reduce the bias resulting from pre-delivery activities.Originality/valueThis paper contributes to construction facility management literature by explaining the mediating role of UE on the relationship between SE and CPP. Therefore, this paper offers practitioners an integrated management logic in strategically combining project and facility management into government project management.

Identifying and assessing the impact of 4M1E factors on construction project delays in Afghanistan using structural equation modeling

AbstractConstruction projects in Afghanistan are often challenged by significant delays, posing severe challenges to their successful completion. This study aims to comprehensively assess the impact of various delay factors using the 4M1E framework Man, Machine, Material, Method, and Environment within the Afghan construction sector. By employing a validated Structural Equation Modeling (SEM) approach, the research investigates both direct and indirect effects of these factors on project delays. The analysis reveals that environmental and material factors are particularly influential, with environmental changes often exacerbating delays across other dimensions. The findings underscore the complex interdependencies among the 4M1E factors, highlighting the need for targeted strategies to manage the delay effectively. Practical recommendations are provided to enhance project management practices, with implications that extend beyond Afghanistan to other developing countries facing similar challenges. This study contributes to the academic discourse on construction delays, offering actionable insights for practitioners, policymakers, and stakeholders in the construction industry.

Культурная политика России: проектный вектор креативного сектора

The dissemination of project management principles and the development of the creative sector in the context of cultural and civilizational changes are closely linked to the renewal of methodological approaches to the study of cultural policy in Russia. Humanistic ideas regarding quality of life, the reproduction of cultural identity, and the strengthening of human capital are oriented towards preserving value bases and creating opportunities for the development of a creative economy. The achievement of the outlined goals is facilitated by the innovation and thoughtfulness of the project management mechanism, based on humanitarian values and ideals. In accordance with these principles, three approaches to the strategy of modern cultural policy in Russia have been identified, generalized in conceptual value-semantic discourses. The system of targets that make up the essence of the state cultural policy includes the idea of value justifications for economic growth during the introduction of qualitatively new technologies and approaches into the system of innovative public administration.

Training and Support Practices and Insights in the Sustainability of mHealth Implementations in Sub-Saharan Africa

We conducted an interview-based study to understand the training and support practices and insights that influence sustainable implementations of mHealth projects of varying mHealth technologies. The qualitative assessment was inspired by the Consolidated Framework for Implementation Research adapted with the recommended questions for guiding the implementation of training programs. Participants in the study (N=16) were both international and in-country researchers managing projects in Sub-Saharan Africa. We chose to focus on training and support as it is often the interface between international and in-country components of these projects. Participants agreed on the central role of training in the implementation of mHealth projects and are following best practices. There was often a division in the responsibility of training between international and in-country researchers reflecting the distinction between project management and local implementation adaptions. One of the main findings is the importance of individualized continuous retraining to make deployments robust with respect to changing conditions with technology and personnel, an aspect that has been managed a bit differently with varying mHealth technologies as we present.

A Tentative Analysis of the Interactions Between the Building Sector and SDGs

Objective: This study aims to examine the relationship between the construction industry and the United Nations, focussing on the interactive effects and the degree of connection between the building sector and sustainable development goals (SDGs). Theoretical Framework: This topic delineates the fundamental concepts and theories that support the research. Examining all 17 SDGs and the construction industry's participation is prominent, establishing a robust foundation for comprehending the investigation's background. Method: The research process thoroughly examines credible academic sources and subsequent analysis. Data was gathered via an extensive literature examination of scholarly publications and official sources. Results and Discussion: The findings demonstrated the connections between the building sector and the SDGs. Some objectives, particularly objectives 3, 6, 7, 9, 11, 12, 13, and 15, are recognised as closely related to the construction sector. Additional studies must expand the sample size by gathering more primary data to corroborate the existing findings. Research Implications: The practical and theoretical consequences of this research are examined, offering insights into the application and influence of the results on practices within the construction and built environment sector. These consequences may pertain to the construction industry and associated project management fields. Originality/Value: This study enhances the literature by thoroughly examining the relationships between the building industry and all 17 SDGs by reviewing credible academic publications. This research is significant and valuable as it advances the sustainable transformation of the construction industry to enable the effective realisation of SDGs.

Investigating Facilities and Supporting Tools for Blended Learning in Project Management Training: A Case Study in Bahrain

This study explores and offers practical, actionable recommendations for Blended Learning (BL) facilities and supporting tools for project management training programs in Bahrain. The proposed strategy is categorized into two main areas: technology and environment. Technological tools include Learning Management Systems (LMS), such as the OPEN (Online Project EducatioN) Platform, Knowledge Management Systems (KMS), AI-driven tools, laptops, smartphones, and reliable internet connectivity. In addition, they are complemented by the second part of a healthy and conducive classroom environment. The study also emphasizes the critical role of the Bahrain Quality Authority (BQA) Framework in maintaining and improving the quality and effectiveness of BL initiatives. By drawing on prior research published by the author, this paper outlines the final strategies to enhance BL training outcomes, and hence providing a valuable model for Bahrain training organizations.

Application of servant leadership in the delivery of strategic government projects in Gauteng Province Case

This qualitative research investigates the influence of servant leadership on the execution of strategic government initiatives, with a particular emphasis on the Reconstruction and Development Programme (RDP) in Kwa-Thema. The project outcomes were investigated by collecting data from 10 participants using convenience sampling to investigate the impact of servant leadership traits, including empathy, commitment, empowerment, humility, ethical stewardship, long-term vision, and resilience. Thematic analysis was implemented to pinpoint critical themes and insights that were pertinent to the success and obstacles of the project. The research tackles a critical issue: project failures frequently result from inadequate leadership, which impedes team cohesion, collaboration, and overall performance (Swart et al., 2022). Additionally, the results suggest that servant leadership significantly improves project delivery by ensuring transparency, promoting collaboration, and aligning projects with community requirements. The impact of leadership on project achievement was discovered to be mediated by employee motivation and engagement. The study's limitations include its emphasis on a particular region and project type, which implies the necessity of conducting more extensive research. There are two recommendations: the integration of servant leadership principles into project management practices and the provision of targeted training for leaders to improve team dynamics and project outcomes.

Unveiling the mechanisms between project manager leadership competencies and team performance: an empirical study

Purpose This study aims to explore the influence of construction project manager competencies on team performance, using structural equation modeling (SEM) within the framework of social information processing theory. It investigates the multidimensional nature of project manager competencies and their impact on team processes and outcomes. Additionally, the study examines the mediating role of team processes in the relationship between competencies and team performance. Design/methodology/approach Drawing on data collected from 483 construction professionals in China, this study uses SEM to analyze the relationships among project manager competencies, team processes and team performance. Findings The results demonstrate a significant and positive effect of competencies on team performance. Specifically, task-related competencies directly contribute to performance, while people-related competencies enhance leader-member relations, and self-related competencies exert a gradual, cumulative influence. Moreover, the research confirms a three-factor competency structure and elucidates the nuanced mediating roles of team learning, monitoring and climate in the competency-performance relationship, shedding light on how specific competencies affect different stages of team development. Originality/value This study contributes to project management literature by applying social information processing theory to elucidate how project managers influence team cognition through competencies. From a practical standpoint, it advocates for a competency-based approach to project manager selection and training, aiming to enhance team performance. Overall, this research advances the understanding of the intricate interplay between project manager competencies and team performance, using SEM and a theoretical perspective rooted in social information processing theory.

Application and prospect of machine learning techniques in cost estimation of building projects

PurposeMachine learning (ML) technologies are increasingly being applied in building cost estimation as an advanced method to overcome the challenge of insufficient data and subjective effects of experts. To address the gap of lacking a review of ML applications in building cost estimation, this research aimed to conduct a systematic literature review to provide a robust reference and suggest development pathways for creating novel ML-based building cost prediction models, ultimately enhancing construction project management capabilities.Design/methodology/approachA systematic literature review according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) was adopted using quantitative bibliographic analysis and qualitative narrative synthesis based on the 70 screened publications from Web of Science (WOS) and Scopus databases. The VOSviewer software was used to prepare the thematic focus from the bibliographic data garnered.FindingsBased on the results of a bibliographic analysis, current research hotspots and future trends in the application of ML to building cost estimation have been identified. Additionally, the mechanisms behind existing ML models and other key points were analyzed using narrative synthesis. Importantly, the weaknesses of current applications were highlighted and recommendations for future development were made. These recommendations included defining the availability of building attributes, increasing the application of emerging ML algorithms and models to various aspects of building cost estimation and addressing the lack of public databases.Research limitations/implicationsThe findings are instrumental in aiding project management professionals in grasping current trends in ML for cost estimation and in promoting its adoption in real-world industries. The insights and recommendations can be utilized by researchers to refine ML-based cost estimation models, thereby enhancing construction project management. Additionally, policymakers can leverage the findings to advocate for industry standards, which will elevate technical proficiency and ensure consistency.Originality/valueCompared to previous research, the findings revealed research hotspots and future trends in the application of ML cost estimation models in only building projects. Additionally, the analysis of the establishment mechanisms of existing ML models and other key points, along with the developed recommendations, were more beneficial for developing improved ML-based cost estimation models, thereby enhancing project management capabilities.

Effects of M & E Planning Process on Performance of County Government Funded Water Projects in Kisii County, Kenya

Purpose: Project Monitoring and Evaluation (M&E) is a critical component of the project management phase, which if not properly handled, may lead to project failure. Currently, Kenya faces transitional challenges from a centralized state to devolved governance system. This has prefigured both challenges and opportunities. The decentralized form of governance has exerted pressure on especially the performance of government water departments in funded water projects in counties. Despite this need most county governments initiate water projects without putting into consideration the importance of having effective M&E frameworks. One aspect that has not been given much consideration is effective implementation of M&E systems as advised by M & E experts. The aim of the study was to analyze the effect of M & E Planning process on performance of county government funded water projects in Kisii County Methodology: The study will adopt a descriptive survey design. The study target population includes 201 county water staff managing 90 water projects across the county. The census method was used to research the 201 staff involved in water projects. The primary data was collected by use of questionnaires and Key Informant interviews. Quantitative data was analyzed by employing descriptive statistics and inferential analysis, and the results were presented by tables and figures. Whereas, qualitative data was done through narrative analysis and presented in form of verbatim and narrations. Findings: M&E planning enables the construction of a logical framework that acts as a roadmap guiding the project's progress and allowing the stakeholders to understand the relationships between different project elements. The positive effect of M&E planning on project implementation affirms the pivotal role of this planning process in guiding and optimizing the execution of water-funded projects in Kisii County. Unique Contribution to Theory, Practice and Policy: This study was anchored in the program theory. Project managers and policymakers should emphasize the importance of these planning components, recognizing them as integral drivers of project success. Furthermore, capacity-building initiatives focusing on these planning aspects can further enhance the efficiency and effectiveness of M&E planning practices.

Perancangan Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Terbaik pada PT XYZ menggunakan Metode TOPSIS

PT XYZ is a company in the field of construction, development, and management of construction projects. They are responsible for planning, managing, and implementing construction projects, both for infrastructure and commercial buildings. The previous assessment did not have a weighting of the criteria assessment and took time to process the value of each employee because the assessment still used a manual method (assisted by calculator calculations) so that the employee calculation process was processed one by one. This is not in accordance with the director's expectations and has an impact on the assessment being inaccurate and detrimental to the company in terms of time. Therefore, to evaluate the performance of top employees at PT XYZ, this decision support system application was created, with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method which can produce a simple Decision Support System with an easy-to-understand and logical concept in the PT XYZ Employee Performance Assessment.

Quantitative risk assessment: methodology and application in an automaker body-in-white production line project

Purpose: this research aims to introduce a novel methodology, termed Quantitative Risk Assessment for body-in-white projects, to forecast the expected project completion time and total project cost. This methodology is demonstrated through application to a real project within an automotive manufacturer in Brazil. Theoretical framework: the study employs established risk analysis methods (e.g., program evaluation and review technique, preliminary hazard analysis, Gaussian curve, Monte Carlo simulation) alongside project management tools for problem characterization (e.g., project requirements, assumptions, work breakdown structure). Methodology/Approach: the methodology presented in this paper follows a sequence of methods that: (i) identify the hazards; (ii) evaluate the probability of risks associated with each project task; (iii) assess their consequences and impact on project costs; and, finally, (iv) quantify the risks to predict a probability spectrum for the project’s total cost. This allows estimating an emergency reserve and categorizing the risk level to inform stakeholders. Findings: The paper reveals that, among the 66 identified hazards, there is a 37% probability of the project duration exceeding 200 days, and the project has been categorized as high risk (i.e., more than a 20% probability that additional costs will exceed 20% of the estimated project budget). Research, practical & social implications: this study enables organizations to forecast the potential impacts of risks on project schedules and costs through comprehensive risk assessments, providing valuable input for project risk management. Originality/ Value: the study’s value lies in the originality of its risk assessment methodology applied to automakers’ body-in-white projects. Keywords: Automaker. Body-in-White. Monte Carlo Simulation. Probabilistic modeling. Quantitative risk assessment.

A hybrid approach based on critical chain for project buffer consumption prediction and monitoring

PurposeThe critical chain project buffer monitor process addresses uncertainty and variability in project duration. However, classical buffer monitor methods only consider buffer consumption, while the dynamic allocation of buffer zones and the buffer consumption trend of activities are ignored. This paper presents the innovative framework for dynamic monitoring of project buffer which covers the dynamic buffer allocation, predictive analytics of buffer utilization and a new monitoring technique based on control chart graph.Design/methodology/approachFirst, a dynamically buffer allocation model is framed, and buffer zones are given to the activities considering risks. Then, a predictive model amalgamating Bayesian Optimization, Convolutional Neural Networks, and Long Short-Term Memory networks (BO-CNN-LSTM) is framed. Finally, a new buffer monitor framework is constructed that takes into account historical information about buffer usage and utilizes two thresholds derived from control chart theory.FindingsThis approach is empirically tested on a representative agricultural website project in China. The results show that, first, the dynamic buffer allocation makes better use of the project buffer, reduces buffer waste and increases the possibility of timely completion of the project. Second, the BO-CNN-LSTM model predicts better than Long Short-Term Memory (LSTM) and Grey Neural Network Model (GNNM), providing project managers with new management insights and perspectives. Third, the novel monitoring procedure makes the leveraging of historical data possible in the control of the schedule deviations, allowing for more timely interventions in the course of the implementation of the project.Originality/valueA new project buffer monitoring method suitable for uncertain project environments is proposed.

Bridging the gap: a framework for monetizing BIM by integrating industry insights for informed decision-making

PurposeThis study addresses the critical imperative of quantifying building information modeling (bimalliance) benefits by augmenting existing methodologies, with a focus on monetization. Engaging industry practitioners, the research develops a comprehensive framework through an exhaustive literature review and a survey in the Swedish construction industry, incorporating insights from 128 respondents.Design/methodology/approachThe framework, validated by industry experts, systematically assesses tangible BIM benefits against associated costs. It introduces a novel method in construction, addressing the lack of a unified approach. The resulting framework facilitates nuanced feasibility determinations by systematically evaluating BIM benefits against costs.FindingsDespite its acknowledged limitations, the framework effectively captures a comprehensive range of costs and benefits, providing a more accurate and detailed estimation of BIM’s impact on project outcomes.Practical implicationsWith practical implications, the framework enhances BIM understanding and application, contributing to effective project management throughout the construction supply chain lifecycle. Moreover, it aims to improve efficacy within the architecture, engineering, construction and operations industry.Originality/valueThe study empowers organizations and decision-makers with a bespoke tool for evaluating BIM feasibility, contributing to decision-making through a clarified numerical representation.

The story of the green PM

The book review introduces the concept of the Green PMO (Project Management Office), an initiative led by Eman Deabil to integrate sustainability into project management practices. It explores how the Green PMO was conceived, driven by global challenges like climate change and social inequalities, and developed into a collaborative book involving professionals from over 20 countries. The Green PMO provides practical frameworks, strategies, and case studies to help PMOs embed sustainability in their operations. By uniting project managers globally, it aims to drive meaningful, lasting change while fostering thought leadership and networking opportunities in sustainable project management.

Sustainability, circular economy, and projects: research opportunities

This editorial explores the intersection of sustainability, circular economy, and project management, highlighting its growing relevance in the contemporary context. Sustainability is deeply integrated into management modern practices, incorporating economic, social, and environmental dimensions. The circular economy, as an alternative to the traditional linear economic model, aims to reintegrate products and materials into the production live cycle, minimizing waste and maximizing resource use. Digital technologies such as IoT, AI, and blockchain provide new opportunities for implementing sustainable practices in real time, especially within the context of Industry 4.0. In project management, the incorporation of sustainability principles is crucial for ensuring long-term success. Frameworks such as the P5 Standard and PRiSM offer practical tools for integrating these concepts of sustainability into the daily routines of project professionals, promoting resource efficiency and social responsibility. The active engagement of stakeholders and the development of specific frameworks are essential for advancing project management that generates positive environmental and societal impacts. The editorial also highlights various research opportunities related to the integration of sustainability and the circular economy in project management. Research opportunities include understanding the impact of circular economy principles on project efficiency, stakeholder engagement in sustainable projects, and the development of frameworks aligned with the Sustainable Development Goals (SDGs). By addressing these topics, researchers and organizations not only address environmental challenges but also gain a competitive advantage.

Adoption challenges of sensing technologies in construction project management in sub-Saharan African countries

PurposeThe use of technology has increased in the industrial sector over the years. This has propelled the construction industry to follow suit by enhancing construction technology to experience the associated benefits. However, technology adoption in the construction environment has not been smoothly implemented. This article aimed to determine the obstacles to adopting sensing technology in managing construction projects in three major sub-Saharan African nations.Design/methodology/approachThe study adopted a quantitative approach using structured questionnaires. The questionnaire link was sent to construction professionals in Nigeria, Ghana and South Africa, of which 120 were responded. Data received were analysed using the Statistical Package for Special Science (SPSS) to generate mean scores and the Kruskal–Wallis test and component analysis.FindingsThe results show that construction professionals face herculean tasks when adopting sensing technology in construction project management. Some prominent challenges are initial cost, lack of proper information technology (IT) infrastructure, power supply, lack of well-trained staff, maintenance cost, operating cost, cost of training, technology immaturity and resistance to change. The results also revealed that adoption challenges differ in these three countries, which may be attributable to the economic development level.Practical implicationsDespite the importance of sensing devices in construction industries, the study has revealed that Sub-Saharan African countries face enormous challenges in adopting them in project management and execution. This situation may hinder the industry’s ability to benefit from this technology in terms of efficiency, effectiveness and safety management, which may ultimately affect their cash flows.Originality/valueThe study provides a valuable understanding of the challenges encountered in implementing sensing technology in the construction sector in major countries within sub-Saharan Africa. These findings will enable the countries examined and other African countries to become cognizant of the challenges and implement strategies to overcome them, thereby enhancing performance in the construction industry.

Research on Deflection Risk Assessment for Steel Box Girder Bridges Based on GA-BP Neural Network

Steel box girder bridges constitute a pivotal structural component in modern bridge engineering, confronting intricate mechanical environments and dynamic conditions during construction, with a particularly notable risk of deflection. Risk assessments predominantly rely on traditional mechanical analyses and empirical judgments, which need help to fully capture the dynamic construction changes and latent risks. This study introduces an innovative risk assessment methodology grounded in finite element analysis (FEA) and optimized by a genetic algorithm-enhanced back propagation neural network (GA-BP) to address these limitations. This approach entails constructing an FEA model to precisely simulate and predict the mechanical behavior during the construction phase, with field data validation ensuring the model’s accuracy. The GA-BP assessment model is established by further incorporating the genetic algorithm to optimize the BP neural network, enabling comprehensive, systematic, and efficient risk assessment. Through practical application case studies, this methodology demonstrates the ability to accurately identify the critical risk factors influencing deflection during the construction phase of steel box girder bridges, providing a scientific basis for construction control. This research holds significant theoretical value and practical significance, and it offers a scientific foundation for risk management, construction optimization, and safety assurance in future bridge engineering projects, thereby enhancing the overall quality and safety of bridges.