Safi Ullah
Xiaopeng Deng
Chiemela Victor Amaechi
Diana R. Anbar
Muhammad Waqas Ashraf- 1Southeast University, Nanjing, China
- 2Global Banking School, Manchester, United Kingdom
- 3Lancaster University, Lancaster, United Kingdom
Introduction: Due to the vastness of various construction practices globally, there is a need for knowledge mapping. Through the utilisation of research on Project Risk Management (PRM) for the Construction Industry, it is possible to carry out an investigation into the processes that pertain to knowledge management. To elaborate on the current research emphasis from three different points of view, namely the influence of political risk, risk assessment, and risk management strategies, the knowledge map analysis method has been elected as the appropriate approach. Knowledge mapping provides a systematic way to visualise research trends, identify gaps, and strengthen the understanding of PRM in international construction projects.
Methods: This scientific investigation, conducted in the field of risk management research, considers publications related to risk management. The study was conducted as a systematic literature review that adopted bibliometrics approach to explore the data from Dimensions database that have been reviewed using PRISMA 2020 statement. This study intends to present Knowledge Mapping for PRM in the Construction Industry, using data from 2000-2025. The analysis focused on three dominant research dimensions: political risk, risk assessment, and risk management strategies. It uses literature on studies that have been carried out on project risk and provides a comprehensive perspective on the topic.
Results: The knowledge maps revealed distinct clusters of research activity across the three focal areas. Political risk emerged as a consistent theme in studies addressing international and cross-border construction contexts. Research on risk assessment showed significant methodological diversity, while studies on risk management strategies tended to emphasise both technological tools and organisational processes. Overall, the mapping highlighted increasing scholarly attention to integrated and holistic approaches to PRM. Some under-researched areas, particularly knowledge-transfer processes and cross-national learning mechanisms, were also identified. The findings demonstrate that knowledge mapping is a valuable tool for understanding the evolution and priorities of PRM research in the construction industry.
Discussion: The study makes use of Knowledge Mapping to offer some suggestions for research areas concerning risk management in international construction projects. These knowledge maps are founded on the investigations that were conducted on project risk management. However, the development of Knowledge Maps offers good contribution to knowledge for best practices in the construction sector. By identifying patterns and gaps, the study provides guidance for future investigations and encourages the development of improved risk management practices in global construction projects. The resulting knowledge maps contribute meaningfully to the field by supporting better decision-making, improving risk-handling capabilities, and informing best practices for the construction sector.
1 Introduction
The management of risks associated with construction projects has been a focal point of research for several decades. As the construction industry evolves, the complexity and scope of project risks have expanded, necessitating innovative management strategies. Among these, the utilization of Knowledge Maps for identifying and managing risk sources has emerged as a promising approach, especially in the context of international construction projects. Knowledge Maps serve not only as tools for visualizing the stages and goals of a project but also as a means to foresee and navigate the intricacies of project lifecycle management, as evidenced by authors (Jiang et al., 2021; Renuka et al., 2014; Chen et al., 2025). However, some studies have applied knowledge management for ontology, taxonomy, and classification on aspects of the construction industry, such as organising documents pertaining to compliance on building permits (Beach et al., 2024; Fauth et al., 2024), Building Information Modelling (BIM) (Liu et al., 2016; Ding et al., 2016), engineering informatics (Hartmann and Trappey, 2020; Wei et al., 2021) as well as construction projects (Wang L. et al., 2024; Wang Y. et al., 2024).
Knowledge management uses various tools like VOS Viewer to conduct systematic reviews, as seen in the recent study by Idrees et al. (2023), which presented the publication trend on new product development projects and knowledge management, as well as the earlier study by Wei et al. (2021), which presented the publication trends on political risks impacting construction projects, and Obreja et al. (2024), looked at the publication trends on innovation in artificial intelligence. Given the inherent risks in construction projects, effective risk management is integral to project success. This involves a detailed process of identifying, assessing, and managing potential risks, a skill that requires both knowledge and expertise (Wideman, 2022; Willumsen et al., 2019). However, the field currently faces a challenge due to the lack of a comprehensive knowledge map that encapsulates the breadth of project risk management. Such a KM tool is essential for project managers to systematically approach risk identification, analysis, response planning, and ongoing monitoring (Amaechi et al., 2025a; Ullah et al., 2024; Afzal et al., 2021; Reich et al., 2008). While some knowledge mapping studies have looked at managing construction projects (Fang et al., 2020; Xu et al., 2022; Okudan et al., 2021), other knowledge mapping studies have looked at managing risks for different projects (Chen and Lou, 2019; Liu et al., 2024; Chen et al., 2025).
Recent literature has highlighted specific areas of concern in construction, including building construction, site selection, environmental valuation, and investment decisions, particularly in high-risk areas such as flood-prone locations (Ayoola et al., 2023; Oyetunji et al., 2023; Olukolajo et al., 2023; Wang et al., 2025). The effective management of knowledge in these areas is recognized as a crucial strategic asset, vital for long-term competitive advantage as emphasized by various authors (Wei et al., 2020; Liu et al., 2024). As businesses increasingly focus on knowledge management (KM) to improve access to and retrieval of information, the correlation between effective KM and enhanced enterprise performance is widely acknowledged (Marinho and Couto, 2022; Zhang et al., 2025). Yet, KM initiatives often suffer from ambiguity and varied interpretations.
In a dynamic environment marked by competition, innovation, and constant change, knowledge and KM are crucial determinants of an organization’s trajectory towards success or failure (Kim et al., 2003). The challenge lies not only in making knowledge available but also in engaging individuals in the process of seeking, transferring, and utilizing this knowledge, as argued by Davenport and Prusak (1998). In a rapidly shifting economy, where unpredictability is the norm, the capacity to continuously create, share, and apply new knowledge is essential for organizational success, a concept underscored by Nonaka (2009). Nonaka’s categorization of knowledge into explicit and tacit forms, and his description of the ‘knowledge spiral’ as a method for generating and transforming knowledge, provide a foundational framework for understanding how knowledge is processed within organizations.
With the developments in technology, more recent works are presented on both innovation and sustainable approaches of KM called green knowledge management (Khan et al., 2024; Cabrilo et al., 2024; He et al., 2024). Some studies have applied sustainability to KM on construction projects, which has proven to be advantageous in the industry as green knowledge management (Wang L. et al., 2024; Wang Y. et al., 2024). However, traditional methods of KM involve explaining knowledge associations and using association rules, which have sometimes yielded unsatisfactory results due to their inability to adequately represent content associations (Watthananon and Mingkhwan, 2012; Yap and Skitmore, 2020). This study addresses this gap by presenting methods to enhance knowledge associations using a knowledge map, estimating an appropriate association value for each piece of information, and specifically focusing on its application in the technology-organisation-environment (TOE) context prevalent in construction projects.
The aim of this study is to develop a knowledge map of project risk management, grounded in a thorough review of relevant literature. This framework not only identifies the key components of project risk management but also elucidates the interdependencies and relationships between these components, thereby providing a more comprehensive understanding of the risk landscape in construction project management. The structure of the paper is thus: Section 1 introduces the work, while Section 2 gives some background on the literature. Section 3 gives the methodology while Section 4 gives the results of the work. Section 5 discusses the work while Section 6 concludes the work.
2 Literature review
2.1 Concept of Knowledge Map
The concept of knowledge maps has been explored extensively in various organizational contexts, serving as a tool to enhance competitive capabilities. This literature review examines key studies in the development and application of knowledge maps, particularly in the context of risk management in construction projects. Different studies present the knowledge mapping on the construction sector, ranging from project management and risk management (Wang L. et al., 2024; Wei et al., 2021; Doukari et al., 2024; Yang, and Liao, 2022), to construction technologies (Trask and Linderoth, 2023; Gade and Selman, 2023; Akinosho, et al., 2020; Abioye, et al., 2021).
Vega-Riveros et al. (1998), pioneered the use of concept maps in education, demonstrating their effectiveness in aiding undergraduate students in understanding biological maps. This application underscores the utility of knowledge maps in simplifying complex concepts, a feature relevant to project risk management. Similarly, Richardson (2001) applied a knowledge map, termed the ‘Skill Matrix’, to enhance staff competencies. This two-phase approach–assessing knowledge, abilities, and skills, followed by testing and evaluation–provides a framework that can be adapted for assessing risk management competencies in construction projects. Additionally, typical frameworks have been adapted for risk management by various studies (Deng and Low, 2014; Ullah et al., 2021; Ullah et al., 2024).
Eppler (2006), research proved instrumental in classifying knowledge maps into five categories, ranging from knowledge resource maps to knowledge development maps. This categorization is crucial in understanding the different dimensions of knowledge in organizations and their applicability in managing project risks. Lin and Hsueh (2003), further advanced this field by integrating data mining and retrieval techniques in the creation of knowledge maps. Their study, based on dissertations from the National Library of Taiwan, demonstrated improvements in knowledge and storage structures, highlighting the potential of knowledge maps for organizing and accessing complex information. Some standard keywords and themes in PRM are documented in the PMBOK (PMI, 2021). Hence, the conceptual framework developed for this study draws on approaches in knowledge management research regarding PRM. This systematic literature review, drawing from various sources including academic journals, industry reports, and case studies, is used for knowledge mapping (see Figure 1).
Figure 1. The study’s conceptual framework.
Kim (2014), offered a strategy for capturing and displaying organizational information through industrial knowledge maps, emphasizing their utility in presenting actionable solutions. Judith et al. (2004), employed network plans in their research to create graphical knowledge maps, effectively illustrating the relationships between different knowledge entities. This approach is particularly relevant for visualizing the interconnections among various risk factors in construction projects. Eppler (2006), further refined the concept of knowledge maps by categorizing them into classes and performing data cleaning to enhance understanding and memory. This refinement underscores the importance of clarity and precision in constructing knowledge maps for effective risk management. These studies have shown that systematic literature reviews are useful for identifying trends, patterns, and gaps in several fields of study. Comparative results of previously recognised risks that have been found in subsequent research to also affect project risks (Ullah et al., 2021; 2024; Amaechi et al., 2025a; WEF, 2025), served as another source of validation. As illustrated in Figure 2, the network of different risk areas was demonstrated to have an impact on projections of global development over the next 10 years, as given in the World Economic Forum’s (WEF) report (WEF, 2025).
Figure 2. The interconnection map on global risks with trends regarding their impact globally within the next decade. Permission was obtained to use the image from WEF. Copyright year: 2025. Publisher: WEF. Data: World Economic Forum Global Risks Perception Survey 2024–2025 (Source: WEF, 2025).
Thus, this justifies the systematic literature review (SLR) technique which was chosen because prior knowledge management and Project Risk Management research has successfully used it (Ullah et al., 2021; Amaechi et al., 2025a). Despite these advancements, the literature search reveals a gap in identifying the relations between different fields of knowledge and the in-depth connections of content within knowledge maps. Addressing this gap, our research aims to manage relevant knowledge contents and explain implicit relations using knowledge maps, thereby enhancing the efficiency and effectiveness of risk management in construction projects. Nakamori and Nakamori (2020), defines knowledge management (KM) as a dynamic process of identifying, optimizing, and managing knowledge to create value and sustain competitive advantages. In the realm of construction project risk management, knowledge maps play a pivotal role. Kara et al. (2020), emphasizes their use in visualizing current risk management processes and developing strategies to mitigate risks. This aligns with the findings of Lin and Hsueh (2003), which highlight the significance of knowledge maps in knowledge management. While a PMJ editorial by Klein and Müller (2021), gives the supporting need to have tools for the knowledge gathering process and relevant tools for project management, the textual background of Fensel et al. (2020), which gives an exposition on knowledge graphs as a basic tool in knowledge management, and methods of applying it.
Thus, some bibliometric data, spanning studies from Ling and Hoang (2010), to Hwang (2018), illustrates the diverse aspects of project risk and management addressed through knowledge maps. These variables range from the successful completion of the project, life cycle considerations, to the control of core technologies and local business partnerships. This broad spectrum of variables reflects the multifaceted nature of risk management in construction projects and underscores the potential of knowledge maps in providing a holistic understanding of these complexities. Another knowledge that stems from political risk mapping looks at the studies on countries’ influence in risk management for international construction (Charpin et al., 2021; Deng et al., 2014; Deng and Low, 2014; Aydogan and Koksal, 2013; 2014). However, there are unique issues identified in emerging economies based on international business contracts and international construction projects (Ramamurti and Singh, 2009; Deng et al., 2014; Mshelia and Anchor, 2019; Azad, 2016).
In summary, these works suggest that while these are key findings on the subject area, the use of innovative tools in project management is important. Thus, knowledge maps can be a versatile and powerful tool in knowledge management, particularly in the domain of construction project risk management (Wang et al., 2025; Amaechi et al., 2025a). This study builds upon this foundation, aiming to develop a comprehensive knowledge map that captures the intricacies of project risk and management, thereby contributing to the field’s evolving understanding of effective risk management strategies. The bibliometric data outlined in Table 1 present a comprehensive overview of the various knowledge map variables explored in the literature.
Table 1. The highlights of the bibliometric data used in the knowledge map research.
2.2 Agile and waterfall methodologies in knowledge mapping theory
The application of Agile and Waterfall methodologies to knowledge mapping offers a compelling lens for understanding and optimizing project risk management. The Waterfall model, with its linear, phase-based structure, aligns well with traditional knowledge-mapping approaches that emphasize static documentation, predefined workflows, and sequential risk analysis. This model supports the creation of structured knowledge maps that mirror the rigid progression of project phases such as risk identification, analysis, response planning, and monitoring, making it suitable for projects with clearly defined scopes and deliverables (Eppler, 2006).
In contrast, Agile methodologies introduce a dynamic, iterative approach to project management that complements more adaptive forms of knowledge mapping (Natarajan, and Pichai, 2024). Agile emphasizes continuous feedback, stakeholder collaboration, and incremental development, all of which facilitate the real-time updating and refinement of knowledge maps. These maps evolve alongside the project, capturing emergent risks and shifting priorities, thereby enhancing organizational agility and responsiveness (Kara et al., 2020). Agile’s flexibility allows for the integration of tacit knowledge from team members, which is often overlooked in rigid Waterfall structures (Natarajan, and Pichai, 2024).
The theoretical underpinning for this integration can be found in Nonaka’s knowledge spiral model (Nonaka, 1994), which describes the transformation of tacit knowledge into explicit knowledge through iterative cycles of socialization, externalization, combination, and internalization (Wang et al., 2025). This model resonates strongly with Agile environments, where knowledge is continuously generated, shared, and applied. In Waterfall contexts, Nonaka’s framework supports the formalization of knowledge at each project phase, ensuring that lessons learned and risk insights are systematically documented and reused.
Moreover, the Technology-Organization-Environment (TOE) framework, frequently referenced in construction project literature, provides a useful structure for evaluating how Agile and Waterfall methodologies influence knowledge mapping. Agile’s emphasis on technological adaptability and organizational learning fits well within the TOE model’s dynamic context, while Waterfall’s procedural clarity supports environmental compliance and regulatory alignment (Mokhtar, and Khayyat, 2022; Kaklauskas et al., 2010).
By synthesizing the structured clarity of Waterfall with the adaptive flexibility of Agile, knowledge maps can serve as hybrid tools that accommodate both stability and change (Myronenko, 2025). This duality is particularly valuable in the construction industry, where projects often span diverse regulatory environments, stakeholder expectations, and risk profiles. The integration of these methodologies into knowledge mapping not only enhances the visualization of risk interdependencies but also strengthens project teams’ strategic planning and execution capabilities (Secundo et al., 2022).
The integration of Agile and Waterfall methodologies into project risk management is grounded in distinct theoretical frameworks (Shrivastava, and Rathod, 2017). The Waterfall model is supported by Systems Theory, which treats projects as structured systems with interdependent components. This theory reinforces Waterfall’s linear progression and detailed planning, enabling systematic knowledge capture and transfer (Luca, 2022). In contrast, Agile methodology draws from Complexity Theory, which embraces the dynamic and unpredictable nature of projects. Agile fosters adaptive learning and decentralized decision-making, allowing knowledge maps to evolve in real time. Both models are further enriched by Knowledge Management Theory, which emphasizes transforming tacit knowledge into explicit forms to enhance organizational performance, an essential process in construction projects (Adesina, and Ocholla, 2024).
In practice, the Waterfall model supports structured documentation and static knowledge maps developed during the planning phase (Saravanos, 2025a; 2025b; Saravanos and Curinga, 2023). While this ensures clarity, it may limit responsiveness to emerging risks. Agile, however, promotes dynamic and iterative knowledge sharing, with continuously updated maps informed by sprint reviews and stakeholder input. This responsiveness enhances the relevance and utility of knowledge, making Agile particularly effective for proactive risk management in complex environments. (See Table 2).
Table 2. Comparative overview of agile and waterfall models in relation to knowledge effectiveness and theoretical foundations.
Integrating Agile and Waterfall methodologies into knowledge mapping practices enhances the overall effectiveness of risk management in construction projects. While Waterfall provides a solid foundation for structured knowledge, Agile introduces flexibility and responsiveness, making knowledge maps more actionable and relevant throughout the project lifecycle.
3 Methodology
3.1 Research method
The methodology for this investigation synergizes the analysis of recent studies on project risk management, drawing on both academic and industry insights. This approach is pivotal in developing a comprehensive understanding of knowledge maps and work patterns in the field, which is essential for in-depth exploration. This review builds a substantial foundation for the development of the knowledge map using various sources (Shokouhyar et al., 2019; Ruangpan et al., 2020; Amaechi et al., 2025a; Amaechi et al., 2025b; Chen et al., 2025). The research commences with a systematic literature review, meticulously examining publication data on the subject to unearth prevailing trends and gaps in the current body of knowledge. Systematic literature review has been conducted in earlier studies ranging from risk management (Amaechi et al., 2025a), to political risk (Wei et al., 2021), down to composite structures (Amaechi et al., 2025b). The guideline adopted is the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guideline (Vu-Ngoc et al., 2018; Page et al., 2021; Haddaway et al., 2022). For this systematic literature review, the PRISMA statement 2020 was adopted and the PRISMA flow diagram was developed. The search query utilised in this systematic literature review is “knowledge mapping” for “project risk management” in “construction”, from 2000 to 2025. The search was conducted by extracting data from the Dimensions database. However, the screening involved the use of six (6) academic databases- EBSCO, Science Direct, Taylor and Francis, MDPI, Springer and Dimensions. In that vein, the results obtained from the literature search were correlated with publication data in the discussions. In this paper, some of the discussions include knowledge management paradigms as they relate to construction projects. In a nutshell, the methodology of this study presents a holistic approach to developing a knowledge map for project risk management (see Figure 3). It seamlessly blends a thorough literature review with practical applications, supported by a multidimensional analysis that captures the essence of contemporary project management challenges and opportunities.
Figure 3. The methodology used in the knowledge map research.
3.2 PICO table
The PICO table specifically designed for the search regarding “Knowledge Mapping on Project Risk Management in the Construction Industry”. PICO (Population, Intervention, Comparison, Outcome) provides a structured way to frame the research question and define review parameters, especially useful in a systematic literature review or evidence synthesis (See Table 3).
Table 3. PICO framework regarding knowledge mapping for project risk management in construction.
3.3 Research question (derived via PICO)
How can knowledge mapping, developed through a systematic literature review, enhance the understanding and management of project risks in the construction industry compared to traditional risk management methods?
3.4 Framework for risk management knowledge map
The framework developed in this study comprises the following key components:
1. Risk Identification: Identifying potential risks that could impact project success.
2. Risk Analysis: Assessing the likelihood and impact of identified risks.
3. Risk Response Planning: Developing strategies to mitigate or manage identified risks.
4. Risk Monitoring and Control: Monitoring risks and implementing appropriate responses.
This framework emphasizes the interdependencies between these components, illustrating how each phase informs the next, thereby providing a holistic view of the risk management process (Jiang et al., 2021; Winge et al., 2019; Martins et al., 2019). Figure 4 represents the framework of risk management knowledge map.
Figure 4. The framework of risk management knowledge map.
3.5 Knowledge mapping process
The recent study by Rane et al. (2021) acknowledges the limitations of traditional task-based project management methodologies and explores the application of knowledge maps to capture the dynamic nature of projects. This approach moves beyond conventional task completion to understand and manage the know-how within project organizations. It also recognizes the vital role of the human element in knowledge mapping, where individual experiences, behavioural tendencies, and knowledge shape the knowledge map, emphasizing the importance of selecting project managers with the right skills and expertise (Bell DeTienne and Jackson, 2001).
Furthermore, an earlier study by Kaklauskas, et al. (2010) presented construction project management aspects considered to develop knowledge map. Also, the study incorporates an integrated assessment of project management, considering a broad spectrum of factors including organizational, managerial, technical, economic, social, cultural, ethical, psychological, and educational aspects. This comprehensive approach is vital for understanding the multifaceted nature of project management and for developing a knowledge map that reflects these diverse dimensions (Ogunlana et al., 2002; Kaklauskas et al., 2010). An earlier study by Kaklauskas et al. (2010) provided typical aspects of construction project management used in developing its framework, while a recent study by Rane et al. (2021) presented some processes for knowledge mapping.
The process of knowledge mapping follows these steps, according to recent study (Rane, et al., 2021):
1. Objective Setting: Understanding project objectives and creating data points representing relevant information.
2. Connection Drawing: Establishing connections between key elements or topics to form a map that demonstrates how information is interrelated.
3. Visualization: Using tools like color-coding and graphical representations to indicate severity levels and relationships between issues.
4 Results
4.1 Bibliometrics output using knowledge maps
In this section, the bibliometrics output was conducted using knowledge maps. The publication trend analysis conducted on the research area from 2000 to 2025, shows that there is a rising trend in research interest in this area. However, the knowledge graph in Figure 5 shows that some of the publications in each year are increasing and sometimes drop by different rates, which might be attributed to different reasons, such as research funding or construction needs. Hence, further research is required on the needs analysis of knowledge management in construction projects.
Figure 5. The knowledge map on publication trend analysis for the research area.
For the citation analysis, the data obtained from the network visualization is presented in Figure 6. It was obtained using VOS viewer and the Dimensions database for the top 500 researchers. Some filtering was conducted using just the highest set of connected items, as well as ignoring publication outputs that had over 25 authors in it. As seen in Figure 6, the citations for this research area are covered from a range of sources, and the researchers who cite these works are also researching on works that are related to this knowledge area.
Figure 6. The knowledge map on citation analysis for the research area.
For the co-authorship analysis, the data obtained from the network visualization is presented in Figure 7. It was obtained using VOS viewer and Dimensions database, for the top 500 researchers. Some filtering was conducted using just the highest set of connected items, as well as ignoring publication outputs that had over 25 authors in it. As seen in Figure 7, the co-authorships for this research area are covered from a range of sources, and the researchers who collaborate on these related knowledge management works are also researching on works that are related to this knowledge area.
Figure 7. The knowledge map on co-authorship analysis for the research area.
The research conducted using the criteria of research category is represented in Figure 8. It shows the knowledge graph on research category for the research area, classifying by the Fields of Research using ANZSRC (2020). From the knowledge graph, it is evident that there were 10 research categories, as the highest field of research is Information and Computing Sciences with 48 publications. It was followed by Commerce, Management, Tourism and Services with 47 publications, followed by Built Environment and Design with 37 publications, followed by Engineering with 35 publications. Next was Human Society with 6 publications, followed by Economics with 4 publications, then Psychology with 2 publications. The least field of research had 1 publication, and it was a position shared by three fields of research, namely, Earth Sciences, Health Sciences as well as Philosophy and Religious Studies.
Figure 8. The knowledge graph on research category for the research area, classifying by the Fields of Research using ANZSRC (2020).
The research conducted using the criteria of research category is represented in Figure 9. It shows the knowledge graph on research category for the research area, classifying by Sustainable Development Goals (SDG). From the knowledge graph, it is evident that there were 10 research categories, as the highest field of research is Sustainable Cities and Communities with 10 publications. It was followed by Industry, Innovation and Infrastructure with 9 publications, then Quality Education with 4 publications, then followed by Responsible Consumption with 3 publications. It was followed by three SDGs that have produced 2 publications, namely, Good Health and Wellbeing, Climate Action as well as Peace, Justice and Strong Institutions. It was followed by three SDGs that have produced 1 publication, namely, Affordable and Clean Energy, Life on Land as well as Partnerships for the Goals.
Figure 9. The knowledge graph on research category for the research area, classifying by Sustainable Development Goals (SDG).
The other aspect considered involves the analysis of source titles in the research area, covering journal articles in Table 4 and book series in Table 5. From Table 4, Buildings has the highest publications in the research area with 91 citations and citations mean of 30.33. It was followed by Journal of knowledge economy with 3 publications, 69 citations and citations mean of 23.00. It was followed by Journal of Asian Architecture and Building Engineering, with 3 publications, 10 citations and citations mean of 3.33. Next is the Communications in Computer and Information Science, with 3 publications, 15 citations and citations mean of 5.00. It was followed by International Journal of Information Management, with 2 publications, 253 citations, and citations mean of 126.50, followed by Automation in Construction, with 2 publications, 58 citations, and citations mean of 29.00, then followed by Sustainability, with 2 publications, 24 citations, and citations mean of 12.00, and then International Journal of Project Management, with 2 publications, 132 citations, and citations mean of 66.00. Others found in Table 4 had 1 publication in the research area. Also, from Table 5, the highest book series is IFIP Advances in Information and Communication Technology, with 7 publications, 101 citations, and citations mean of 14.43. It was followed by Lecture Notes on Data Engineering and Communications Technologies, with 5 publications, 10 citations and citations mean of 2.00, followed by Lecture Notes in Computer Science, with 4 publications, 24 citations, and citations mean of 6.00, then Communications in Computer and Information Science, with 3 publications, 15 citations and citations mean of 5.00. This shows that while some of the works in this research area were published in related journals. There are some works that were published as book chapters and contributions made to conference book series.
Table 4. The source titles in this research area for journal articles.
Table 5. The source titles in this research area for book series.
4.2 Benefits of the knowledge maps
This study underscores the importance of effective data gathering in developing knowledge maps, particularly in the construction industry. The use of knowledge mapping for project risk management has shown encouraging results in improving project outcomes. This strategy has been effective in identifying potential risk areas and creating efficient mitigation plans by systematically cataloguing and visualizing knowledge resources. Knowledge mapping has emerged as an essential method for capturing and utilizing both tacit and explicit information in the construction sector, where projects are often complex and prone to a wide range of unforeseen risks. One of the findings of the knowledge map is the impact that risks like political risks have on the construction industry (Sun et al., 2021). Knowledge maps are also utilized to identify risks and prepare for them through proper planning. In other words, knowledge maps help us control risk by identifying potential risks and crafting appropriate responses. This may involve strategies to mitigate risks or the development of action plans if a risk materializes, as discussed by Winge et al. (2019) and Ullah et al. (2024). Techniques in employing knowledge maps for project risk and risk management may include analyzing past projects for risk identification, creating “what-if” scenarios to evaluate potential risks, and developing methods to quantify the impact of risks, as noted by Kucuk Yilmaz (2019). The utilization of different academic sources to study typical risks, such as political risks, is illustrated in Figure 10, showcasing the diverse applications of knowledge maps in risk management.
Figure 10. Knowledge map on journals with related papers on political risks as typical risks from WoS database (Source: Wei et al., 2021; Permission was obtained from authors).
4.3 Political risk management using knowledge maps
The use of knowledge maps in project risk management, especially regarding political risks, has demonstrated considerable effectiveness. Several studies, including those by Martins et al. (2019) and Renuka et al. (2014), illustrate the application of knowledge maps in this field. These studies employ various visualization tools, such as mind maps and diagrams, alongside the creation of risk registers and risk management plans. The impact of utilizing knowledge maps is evident in the enhanced visibility of risk, increased efficiency in risk management processes, improved decision-making, and strengthened risk control capabilities, as highlighted by de Araújo Lima et al. (2020). Additionally, key aspects of using knowledge maps in project risk management, like risk identification, evaluation, and the development of countermeasures, are crucial for effective risk handling (Shokouhyar et al., 2019).
Organizations are increasingly relying on knowledge maps to identify potential risks, assess their impacts, and formulate appropriate countermeasures. This proactive approach is essential for staying ahead of potential issues, thereby increasing the chances of project success, as suggested by Rane, et al. (2021). Given the significant impact of political risks on international construction contracts, such risks have been specifically addressed in knowledge mapping initiatives. Political risk refers to the likelihood of political unrest, government interference, or changes in laws and regulations negatively impacting the business environment. Effective risk management involves the process of detecting, evaluating, and mitigating these risks to minimize their adverse effects on organizations, a concept elaborated by Kucuk Yilmaz (2019).
To manage political risks, organizations can employ knowledge maps that detail various political risks, such as expropriation risk, political violence risk, and regulatory risk. These maps can also outline strategies to mitigate such risks, including adopting political risk insurance, forming joint ventures, and pursuing diversification. This comprehensive approach to organizing and visualizing political risk and risk management knowledge can be seen in Figure 11, which presents a detailed knowledge map of risk management, demonstrating how various risks and mitigation strategies are interconnected (Kucuk Yilmaz, 2019).
Figure 11. Knowledge map of risk management.
4.4 Functions of the knowledge maps in the construction sector
In the construction industry, knowledge maps have proven to be indispensable tools for identifying, assessing, and mitigating various risks. Almeida and Soares (2014), notes that knowledge maps serve as an effective means to organize and display information within a specific domain, graphically illustrating the relationships and interconnections between different concepts. This graphical representation facilitates a deeper understanding of the knowledge domain, aiding in the decision-making process.
Project managers leverage knowledge maps to pinpoint potential risks and evaluate their possible impact on projects. Once risks are identified, strategies are formulated to mitigate these risks effectively, including developing contingency plans, establishing monitoring systems to track environmental changes, and creating proactive strategies to address potential problems. This comprehensive approach ensures that projects are completed within their timelines and budgets, effectively mitigating risks along the way (Rane et al., 2021).
Various methodologies have been proposed for project risk management (PRM), including the “framework” approach, which emphasizes identifying project threats and opportunities. In recent years, there has been a significant increase in the use of software tools for PRM tasks, such as project risk analysis (PRA), which offer predictive analytics capabilities to assess the potential impact of risks on project performance (Tamminen and Poucher, 2020).
Despite recognizing the benefits of knowledge management (KM) initiatives, construction companies often face challenges in implementing and sustaining these initiatives (Wang et al., 2025). Cultural issues, particularly in project-oriented construction firms, play a crucial role in effective knowledge management. Egbu et al. (2001) emphasize that task-focused, short-term labor can hinder continuous learning and knowledge sharing within organizations.
These insights form the basis for the authors’ development of a generic and adaptable Integrated Knowledge Management model. Recent studies have presented various areas of knowledge management systems, offering a visual representation of how knowledge is organized and managed in the construction sector (Almeida and Soares, 2014).
Moreover, the proactive use of knowledge maps in risk management empowers project managers to anticipate risks and plan, accordingly, ensuring the successful completion of projects and minimizing the impact of unforeseen issues (Durst and Zieba, 2019; Jiang et al., 2021). The need for a comprehensive understanding of both potential risks and mitigation strategies is evident, as is the use of software tools to support risk analysis and management tasks (Martins et al., 2019; Khan et al., 2021).
As the volume of knowledge grows, it becomes challenging for users to navigate and understand the relationships and connections within stored knowledge. Knowledge maps, as a method of knowledge management, address this challenge by creating associations between related materials, thereby simplifying access to information (Watthananon and Mingkhwan, 2012; Renuka et al., 2014). Figure 12 presents the knowledge map for the areas of knowledge management systems, demonstrating how knowledge maps can be utilized to manage and navigate the complexities of information for general purposes.
Figure 12. Areas of knowledge management systems.
5 Discussion
5.1 Risk management requirements from knowledge maps
The findings of this study underscore the pivotal role of risk management in the construction industry, particularly in the context of emerging markets. Risk management is essential for maintaining the impact of risks and vulnerabilities within acceptable limits while considering cost-effectiveness. This process involves the implementation of various countermeasures, which are vital in reducing threats or vulnerabilities. Importantly, risk management is not a one-time process but rather a continuous cycle that needs to be repeated with changes in the environment or periodically.
In this study, the creation of a comprehensive knowledge map incorporating several risk management components signifies a substantial advancement in project management. The knowledge map serves as a crucial tool, providing project managers with an in-depth understanding of project hazards and effective management strategies. This tool is instrumental in improving project success rates by offering an organized method for recognizing, evaluating, and controlling risks. The knowledge map essentially acts as a roadmap, navigating the intricacies of risk, which in turn facilitates better decision-making throughout the project lifecycle. Figure 13 presents knowledge maps for the management of construction, demonstrating how knowledge maps can be utilized to manage and navigate the complexities of information in the construction industry.
Figure 13. Knowledge map for management of construction.
The integration of knowledge maps into risk management processes in the construction industry presents a promising avenue for enhancing project success. This approach not only aids in the systematic identification and mitigation of risks but also encourages proactive decision-making and strategic planning. The need for continuous improvement in project execution and the development of innovative management tools like knowledge maps are vital for advancing the field of project risk management. There is the real-life application of various tools, like risk registers, to ensure safety through effective risk management (Okudan et al., 2021; Ullah et al., 2024; Renuka et al., 2014; Tah and Carr, 2001). In addition, there are various routes that can be considered in risk management, which can be based on the sources. Figure 14 presents a typical knowledge map that represents risk sources affecting project success, while Figure 15 provides a typical knowledge map using the risk breakdown structure to visually represent how different project risks interact and impact project outcomes.
Figure 14. Typical flowchart on types of risks affecting project successful completion (created with Canva).
Figure 15. A typical risk breakdown structure highlighting Project risks (reproduced from Tah and Carr, 2001, Copyright © 2001 Civil-Comp Ltd and Elsevier Science Ltd, with permission from Elsevier.).
5.2 The necessity for knowledge management in the construction industry
In today’s globalized world, characterized by rapid information exchange, the construction industry faces the challenge of adapting to knowledge-based economies. The ability to effectively manage human capital is crucial, as knowledge has become a key competitive advantage in business. Organizations are increasingly evaluated based on the quality and application of their knowledge stock, impacting economic indicators like GDP growth rate. The construction industry, a major pillar of many economies, is no exception. Knowledge Management (KM) has become essential for enhancing business performance within this sector. The recognition of KM’s importance is growing, as evidenced by a body of research emphasizing the need for strategic management of organizational knowledge (Kim, 2014; McRea and Langdon, 2003; Senaratne and Sexton, 2009). Among the conceptual mind maps found on project management are some designed by Srinivasan (2013). However, the implementation of KM in construction is often fragmented and lacks a cohesive framework. The sector’s project-based nature, involving ad hoc teams and diverse projects, presents unique challenges to effective KM, particularly in knowledge sharing and transfer (Yu and Yang, 2018; Marinho and Couto, 2022). Despite these challenges, leveraging knowledge effectively is crucial for managing the increasing complexity and demands of contemporary construction projects (Okudan et al., 2021; Eken et al., 2020).
Organizations are turning to information and communication technologies to develop KM systems that support knowledge creation, storage, retrieval, transfer, and application. However, the unique nature of KM systems, lacking specific input, process, and output specifications, makes their implementation more challenging compared to traditional business information systems (Anwar et al., 2019) or project risk management (Ullah et al., 2024; Wang and Cheng, 2022; Wang et al., 2004). Understanding the benefits and constraints affecting KM implementation is vital for the construction sector to harness its full potential (Marinho, and Couto, 2022; Lin and Hsueh, 2003; Taghavi et al., 2021). Thus, the variables considered for the knowledge map research is tabulated in Table 6, thus requiring the needs analysis conducted.
Table 6. The Needs analysis for the knowledge map research using the variables.
5.3 Lessons learnt and recommendations
From this study, several key lessons and actionable recommendations have emerged:
• Encourage open communication and knowledge sharing: Fostering an environment that promotes open communication and knowledge sharing is fundamental. Incorporating regular meetings, workshops, and integrating knowledge-sharing practices into organizational policies can facilitate this culture.
• Employ advanced technologies: Utilizing advanced technologies like artificial intelligence and machine learning can streamline the knowledge mapping process, enabling efficient data analysis and trend identification. Recent studies by Dike et al. (2023) and Dike et al. (2024), have shown that knowledge maps are used to assess environmental conditions in regions like the Niger Delta area of Nigeria, where it was used for ranking risk levels, as in Figure 16.
• Customize knowledge maps for specific projects: Tailoring knowledge maps to individual construction projects ensures that identified risks and knowledge areas are relevant and actionable. The framework on project risk management in construction is depicted with the knowledge map in Figure 17.
• Continuous learning and adaptation: Establishing ongoing processes for updating knowledge maps and integrating lessons learned from past projects is crucial for continuous improvement.
• Invest in education and training: Providing training programs to educate staff about knowledge mapping is essential for effective implementation and maintenance.
• Inclusive participation in knowledge mapping: Engaging all relevant stakeholders in the knowledge mapping process is important to ensure comprehensive risk identification and management. Such as using ASTA Powerproject software to design a project for constructing a commercial building (see Figure 18).
Figure 16. The mapping for the risk level of the Niger Delta coastline (Permission was obtained from authors, Copyright 2024 The Authors, licesend under CC-BY 4.0; Source: Dike et al., 2024).
Figure 17. The knowledge map on the framework for knowledge management in construction.
Figure 18. Knowledge management using ASTA Powerproject software to design a project for constructing a commercial building.
Implementing these recommendations can significantly enhance project risk management in the construction sector, leading to more successful and sustainable project outcomes. The study highlights the need for a strategic and holistic approach to KM in construction, recognizing its potential to drive innovation and efficiency in the industry. The rapid evolution in the built environment necessitates an unwavering commitment to site safety and the successful completion of projects in the construction industry. Thus, these lessons are used to develop the framework in Table 7.
Table 7. Framework from lessons drawn on knowledge mapping in construction.
6 Conclusion
This study has highlighted the crucial role of Knowledge Mapping in Project Risk Management within this sector. Through a comprehensive review of literature and an analysis of past studies on project risk management, the research provides a detailed perspective on the application of Knowledge Mapping in addressing risk management challenges in multinational construction projects. The study specifically delves into the influence of political risk, risk assessment, and risk management strategies, employing Knowledge Mapping as a key analytical tool. This approach has allowed for a nuanced exploration of current research themes in the field of risk management.
The findings underscore the importance of Knowledge Mapping as an invaluable tool for improving project risk management in construction. By employing this method, professionals can systematically identify, analyze, and manage potential risks, fostering a more effective response to the unique challenges encountered in construction projects. Knowledge Mapping enables the consolidation of collective expertise and experiences within the industry, empowering construction professionals to make more informed and proactive decisions in risk mitigation.
Furthermore, Knowledge Mapping facilitates the creation of an accessible and dynamic knowledge base. This approach ensures that critical insights and lessons are not only recorded but also shared across projects, contributing to the ongoing enhancement of risk management practices in the construction sector. In future works, digital ontology tools like Protégé can be used to conduct the knowledge map in this area. As the industry continues to grow and face new challenges, the application of Knowledge Mapping in project risk management will be pivotal for achieving success, sustainability, and fostering innovation. The adoption of this approach promises to bring about transformative improvements in project outcomes, both in the present and in the future of the construction industry.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
SU: Data curation, Conceptualization, Validation, Methodology, Visualization, Investigation, Resources, Writing – review and editing, Software, Formal Analysis, Writing – original draft. XD: Project administration, Visualization, Funding acquisition, Data curation, Resources, Formal Analysis, Validation, Conceptualization, Methodology, Writing – review and editing, Supervision, Writing – original draft, Investigation, Software. CA: Visualization, Conceptualization, Methodology, Data curation, Investigation, Validation, Resources, Writing – review and editing, Writing – original draft, Supervision, Project administration, Formal Analysis. DA: Investigation, Resources, Validation, Conceptualization, Writing – review and editing. MA: Resources, Data curation, Conceptualization, Writing – review and editing, Project administration, Methodology.
Funding
The authors declare that financial support was received for the research and/or publication of this article. The authors acknowledge that this research study is funded by the National Natural Science Foundation of China (NNSFC-71771052 and NNSFC-72171048). The financial support received for the doctoral research is greatly appreciated. The funding support from the School of Engineering, Lancaster University, UK, for the Engineering Department Studentship, as well as from the Engineering and Physical Sciences Research Council (EPSRC)'s Doctoral Training Centre (DTC), UK, is greatly appreciated. In addition, the funding of Foreign Postgraduate Scholarship by Niger Delta Development Commission (NDDC), Port Harcourt, Nigeria, is appreciated. This research also acknowledges the BOLD25 Initiative of Universiti Tenaga Nasional, Malaysia.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Generative AI was used in the creation of this manuscript.
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Abbreviations
CEM, Construction Engineering Management; KM, Knowledge Management; PERT, Project Evaluation and review technique; PRM, Political Risk Management; RBS, Risk Breakdown Structure; RM, Risk Management; RMP, Risk Management Process; SIA, System of Integrated Assessment; TOE, technology-organisation-environment; WoS, Web of Science.
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Keywords: knowledge map, knowledge management, project risk, risk management, construction project, construction industry, bibliometrics, content analysis
Citation: Ullah S, Deng X, Amaechi CV, Anbar DR and Ashraf MW (2026) A systematic literature review on knowledge mapping for project risk management in the construction industry. Front. Built Environ. 11:1677904. doi: 10.3389/fbuil.2025.1677904
Received: 01 August 2025; Accepted: 05 November 2025;
Published: 27 January 2026.
Edited by:
Piero Bevilacqua, University of Calabria, ItalyReviewed by:
Jorge Pedro Lopes, Instituto Politécnico de Bragança, PortugalSandeep Poddar, Lincoln University College, Malaysia
Copyright © 2026 Ullah, Deng, Amaechi, Anbar and Ashraf. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Safi Ullah, ZW5nbnJzYWZpMUBnbWFpbC5jb20=; Chiemela Victor Amaechi, Y2hpZW1lbGF2aWNAZ21haWwuY29t