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Article
Publication date: 21 December 2023

Libiao Bai, Xuyang Zhao, ShuYun Kang, Yiming Ma and BingBing Zhang

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions…

Abstract

Purpose

Research and development (R&D) projects are often pursued through a project portfolio (PP). R&D PPs involve many stakeholders, and without proactive management, their interactions may lead to conflict risks. These conflict risks change dynamically with different stages of the PP life cycle, increasing the challenge of PP risk management. Existing conflict risk research mainly focuses on source identification but lacks risk assessment work. To better manage the stakeholder conflict risks (SCRs) of R&D PPs, this study employs the dynamic Bayesian network (DBN) to construct its dynamic assessment model.

Design/methodology/approach

This study constructs a DBN model to assess the SCRs in R&D PP. First, an indicator system of SCRs is constructed from the life cycle perspective. Then, the risk relationships within each R&D PPs life cycle stage are identified via interpretative structural modeling (ISM). The prior and conditional probabilities of risks are obtained by expert judgment and Monte Carlo simulation (MCS). Finally, crucial SCRs at each stage are identified utilizing propagation analysis, and the corresponding risk responses are proposed.

Findings

The results of the study identify the crucial risks at each stage. Also, for the crucial risks, this study suggests appropriate risk response strategies to help managers better perform risk response activities.

Originality/value

This study dynamically assesses the stakeholder conflict risks in R&D PPs from a life-cycle perspective, extending the stakeholder risk management research. Meanwhile, the crucial risks are identified at each stage accordingly, providing managerial insights for R&D PPs.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 27 October 2023

Muhammad Saiful Islam, Madhav Nepal and Martin Skitmore

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural…

Abstract

Purpose

Power plant projects are very complex and encounter serious cost overruns worldwide. Their cost overrun risks are not independent but interrelated in many cases, having structural relationships among each other. The purpose of this study is, therefore, to establish the complex structural relationships of risks involved.

Design/methodology/approach

In total, 76 published articles from the previous literature are reviewed using the content analysis method. Three risk networks in different phases of power plant projects are depicted based on literature review and case studies. The possible methods of solving these risk networks are also discussed.

Findings

The study finds critical cost overrun risks and develops risk networks for the procurement, civil and mechanical works of power plant projects. It identifies potential models to assess cost overrun risks based on the developed risk networks. The literature review also revealed some research gaps in the cost overrun risk management of power plants and similar infrastructure projects.

Practical implications

This study will assist project risk managers to understand the potential risks and their relationships to prevent and mitigate cost overruns for future power plant projects. It will also facilitate decision-makers developing a risk management framework and controlling projects’ cost overruns.

Originality/value

The study presents conceptual risk networks in different phases of power plant projects for comprehending the root causes of cost overruns. A comparative discussion of the relevant models available in the literature is presented, where their potential applications, limitations and further improvement areas are discussed to solve the developed risk networks for modeling cost overrun risks.

Details

Construction Innovation , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 11 December 2023

Mohammad Hosein Madihi, Ali Akbar Shirzadi Javid and Farnad Nasirzadeh

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 19 October 2023

Niv Yonat, Shabtai Isaac and Igal M. Shohet

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

Abstract

Purpose

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

Design/methodology/approach

In this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.

Findings

The theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.

Research limitations/implications

Sociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.

Practical implications

The theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.

Social implications

ToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.

Originality/value

The contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 4 April 2023

Giustina Secundo, Gioconda Mele, Giuseppina Passiante and Angela Ligorio

In the current economic scenario characterized by turbulence, innovation is a requisite for company's growth. The innovation activities are implemented through the realization of…

Abstract

Purpose

In the current economic scenario characterized by turbulence, innovation is a requisite for company's growth. The innovation activities are implemented through the realization of innovative project. This paper aims to prospect the promising opportunities coming from the application of Machine Learning (ML) algorithms to project risk management for organizational innovation, where a large amount of data supports the decision-making process within the companies and the organizations.

Design/methodology/approach

Moving from a structured literature review (SLR), a final sample of 42 papers has been analyzed through a descriptive, content and bibliographic analysis. Moreover, metrics for measuring the impact of the citation index approach and the CPY (Citations per year) have been defined. The descriptive and cluster analysis has been realized with VOSviewer, a tool for constructing and visualizing bibliometric networks and clusters.

Findings

Prospective future developments and forthcoming challenges of ML applications for managing risks in projects have been identified in the following research context: software development projects; construction industry projects; climate and environmental issues and Health and Safety projects. Insights about the impact of ML for improving organizational innovation through the project risks management are defined.

Research limitations/implications

The study have some limitations regarding the choice of keywords and as well the database chosen for selecting the final sample. Another limitation regards the number of the analyzed papers.

Originality/value

The analysis demonstrated how much the use of ML techniques for project risk management is still new and has many unexplored areas, given the increasing trend in annual scientific publications. This evidence represents an opportunities for supporting the organizational innovation in companies engaged into complex projects whose risk management become strategic.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

Keywords

Article
Publication date: 27 July 2023

Binchao Deng, Xindong Lv, Yaling Du, Xiaoyu Li and Yilin Yin

Inefficiency dilemmas in project governance are caused by various risks arising from the characteristic of construction supply chain projects, such as poor project performance…

Abstract

Purpose

Inefficiency dilemmas in project governance are caused by various risks arising from the characteristic of construction supply chain projects, such as poor project performance, conflicts between stakeholders and cost overrun. This research aims to establish a fuzzy synthetic evaluation (FSE) model to analyze construction supply chain risk factors. Corresponding risk mitigation strategies are provided to facilitate the improvement performance of ongoing construction supply chain projects.

Design/methodology/approach

A literature review is utilized to reveal the deficiencies of construction supply chain risk management. Thus, a total of five hundred (500) questionnaires are distributed to construction professionals, and four hundred and thirty-five (435) questionnaires are recovered to obtain the evaluation data of construction professionals on critical risk factors. Additionally, the FSE is used to analyze and rank the significance of critical risk factors. Finally, this research discusses nine critical risk factors with high weight in the model, and explains the reason for the significance of critical risk factors in the construction supply chain.

Findings

The questionnaire results show that the thirty-one (31) identified critical risk factors are verified by related practitioners (government departments, universities and research institutions, owners, construction units, financial institutions, design units, consulting firms). Thirty-one (31) identified critical risk factors are divided into common risks, risks from contractors and risks from owners. The most significant factors in the three categories, respectively, are “political risks,” “owner's unprofessional” approach and “cash flow.” Managing these risks can facilitate the development of the construction supply chain.

Originality/value

This paper expands the research perspective of construction supply chain risk management and complements the risks in the construction supply chain. For practitioners, the research result provides some corresponding measures to deal with these risks. For researchers, the research result provides the direction of construction supply chain risk treatment.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 18 March 2024

Lucas Melchiori Pereira and Sheila Walbe Ornstein

Properly allocating an organization's activities within a building is vital to reducing the relational complexity arising from process–environment interactions. Multiple…

Abstract

Purpose

Properly allocating an organization's activities within a building is vital to reducing the relational complexity arising from process–environment interactions. Multiple relationships are mapped, and certain interferences are only identified after these have been processed. The method/software employed for this task is Mapping Activity Environment Allocation (MAEA). However, data input and interpretation of results depend on the usability conditions of the organization's agents. This paper presents MAEA's usability test results.

Design/methodology/approach

Test sessions and interviews were carried out with seven agents registered at a University Hospital. Participants were instructed to think aloud during its use, and immediately afterward, responded to semi-structured interviews. Test sessions were audio recorded and screen captured.

Findings

Participants found the software easy to use and pointed out valuable implications for professional and academic use. In addition to relationship, priority and parallelism data, customized visualizations were created, including organizational charts, flowcharts and activity flow routes on the floor plan.

Practical implications

MAEA's simplicity allows non-designers to conduct evidence-based assessments and decisions. It allows designers to test their proposals during the programming and outline proposal stages.

Social implications

A more detailed definition of design requirements from the beginning increases the conditions to successfully achieve project goals.

Originality/value

The ability to map the allocation of activity-spaces in the pre-design phase of building architecture allows for early identification of interactions, aiding in the development of more robust project requirements during programming.

Details

Archnet-IJAR: International Journal of Architectural Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2631-6862

Keywords

Article
Publication date: 14 July 2023

Marya Tabassum, Muhammad Mustafa Raziq, John Lewis Rice, Felipe Mendes Borini and Anees Wajid

Taking a co-creation perspective and integrating knowledge-based and resource-based perspectives, the authors examine the role of customer participation in organizational…

Abstract

Purpose

Taking a co-creation perspective and integrating knowledge-based and resource-based perspectives, the authors examine the role of customer participation in organizational performance and project success. The authors also investigate the mediating role of knowledge integration and the moderating role of requirement risk for these relationships in uncertain contexts.

Design/methodology/approach

The authors undertook two studies. The first study was carried out in 2018 in which the authors drew on survey data from 150 information technology (IT) sector employees and examined the mediating role of knowledge integration in the relationship of customer participation with organizational performance and project success. In the second study undertaken in 2020, the authors drew on data from 92 IT and telecom sector employees and examined the moderating role of requirement risk in the relationship between customer participation and knowledge integration. Study 2 was conducted during the COVID-19 pandemic when employees were largely working from home and were more sensitive to risks and uncertainty about the scope and system requirements. Both studies were survey-based, and analysis was carried out using structural equation modeling.

Findings

The authors’ two-study examination indicated that knowledge integration positively mediates the relationship of customer participation with organizational performance and project success during the co-creation process. Furthermore, the authors demonstrate that when requirement risks are high, customer participation relationship with knowledge integration is weaker.

Originality/value

The authors show that integrating customer knowledge is critical to project success and organizational performance. By identifying risk uncertainties and environmental contingencies, the authors highlight the constraints of customer participation for knowledge integration, organizational performance and project success. The authors provide some key study findings based on survey data obtained from project teams during two periods (normal and pandemic).

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 7 July 2023

Wensheng Lin, Guangbin Wang, Yan Ning, Qiuwen Ma and Shuyuan Dai

Megaproject performance measurement (MPM) has received great attention in the project management community, but it primarily focused on the design of performance measures or…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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