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The purpose of this study is to investigate the relationship between the absorptive capacity (AC) of a firm and project success (PS), with particular attention to the mediating role of customer knowledge management capability (CKMC) and the moderating role of environmental complexity (EC). By using data collected from Turkish SMEs across different sectors, the study seeks to understand how AC impacts project success, how CKMC mediates this relationship, and how EC moderates the link between AC and CKMC. The research contributes to both theory and practice by providing insights into these relationships and suggesting future research directions.

This study focuses on Small and Medium-sized Enterprises (SMEs) in Turkey, specifically within the cities of Istanbul, Ankara, Izmir, and Konya. To gather data, the researchers utilized a non-probabilistic convenience sampling method and distributed self-administered surveys to a selected pool of 918 respondents including shift supervisors, project managers, and team members within these SMEs. The surveys were translated to Turkish to avoid language issues. Out of the surveys distributed, 401 valid responses were collected, resulting in a response rate of 43.68%.

The main findings of the study indicate that a firm’s absorptive capacity (AC) positively impacts project success and customer knowledge management capability (CKMC). Furthermore, CKMC plays a mediating role, positively influencing project success. Additionally, the study reveals the moderating effect of environmental complexity (EC) on the relationship between AC and CKMC, suggesting that as EC becomes more complex, it strengthens the link between AC and CKMC. Moreover, CKMC was found to mediate the moderating effect of EC on the relationship between AC and project success, emphasizing the significance of environmental complexity in this interaction.

This study’s limitations stem from its cross-sectional approach, which limits the ability to establish causal relationships between the constructs of absorptive capacity (AC), customer knowledge management capability (CKMC), and project success. It does not examine other potential mediators, such as customer relationship capability and innovation capability. Furthermore, the existing literature on this topic is scarce, suggesting a need for further research, particularly on constructs like team skills for managing CKMC. There is also an unexplored area around the effects of different forms of complexity, such as resource and technical complexity. Finally, further research is needed to understand how SMEs, which often face resource constraints, leverage AC in different functional domains for successful new product development.

The study’s findings have significant practical implications for SMEs, highlighting the importance of absorptive capacity (AC) and customer knowledge management capability (CKMC) in promoting project success, particularly under conditions of environmental complexity. As businesses navigate uncertain environments, external knowledge acquisition becomes crucial for improvement and innovation. Efficient transformation of this knowledge can enhance project success rates. Thus, firms should cultivate a proactive, innovative, and risk-taking climate. Also, firms should regularly assess their AC and CKMC in the face of shifting stakeholder expectations and market competition. The ability to detect, integrate, and apply external knowledge in product and service development can significantly enhance project success rates.

This study’s originality lies in its exploration of the complex interplay between a firm’s absorptive capacity (AC), customer knowledge management capability (CKMC), environmental complexity (EC), and project success (PS). By examining Turkish SMEs across various sectors, the study uncovers the mediating role of CKMC and the moderating role of EC in the relationship between AC and PS. Furthermore, it reveals how the effect of AC on PS through CKMC strengthens with increasing environmental complexity. These findings offer fresh insights into the complexity theory and the factors influencing project success, providing a unique perspective for both academics and practitioners, with practical implications for managing SMEs in complex environments.

This study aims to obtain governance strategies for managing the complexity of megaprojects by analyzing the impact of individual factors and their configurations using the fuzzy-set qualitative comparative analysis (fsQCA) method and to provide references for project managers.

With the continuous development of the economy, society and construction industry, the number and scale of megaprojects are increasing, and the complexity is becoming serious. Based on the relevant literature, the factors affecting the complexity of megaprojects are determined through case analysis, and the paths of factors affecting the complexity are constructed for megaprojects. Then, the fsQCA method is used to analyze the factors affecting the complexity of megaprojects through 245 valid questionnaires from project engineers in this study.

The results support the correlation between the complexity factors of megaprojects, with six histological paths leading to high complexity and seven histological paths leading to low complexity.

It breaks the limitations of the traditional project complexity field through a “configuration perspective” and concludes that megaproject complexity is a synergistic effect of multiple factors. The study is important for enriching the theory of megaproject complexity and providing complexity governance strategies for managers in megaproject decision-making.

The purpose of this research is to develop a project complexity index (PCI) model using the best and worst method (BWM) to quantitatively analyze the impact of project complexities on the performance of metro rail projects.

This study employed a two-phase research methodology. The first phase identifies complexities through a literature review and expert discussions and categorizes different types of complexities in metro rail projects. In the second phase, BWM, a robust multi-criteria decision-making (MCDM) technique, was used to prioritize key complexities, and a PCI model was developed. Further, the developed PCI was validated through case studies, and sensitivity analysis was performed to check the accuracy and applicability of the developed PCI model.

The analysis revealed that location complexity exerted the most substantial influence on project performance, followed by environmental, organizational, technological and contractual complexities. Sensitivity analysis revealed the varying impacts of complexity indices on the overall project complexity.

The study's findings offer a novel approach for measuring project complexity's impact on metro rail projects. This allows stakeholders to make informed decisions, allocate resources efficiently and plan strategically.

The existing studies on project complexity identification and quantification were limited to megaprojects other than metro rail projects. Efforts to quantitatively study and analyze the impact of project complexity on metro rail projects are left unattended. The developed PCI model and its validation contribute to the field by providing a definite method to measure and manage complexity in metro rail projects.

Project complexity (PC) governs project success, but the project management literature primarily focuses on performance measures and rarely examines the complexity factors, especially for megaprojects. This paper aims to determine the most significant complexity factors for the railway megaprojects in India.

A mixed approach using the Delphi and best–worst method (BWM) helped to identify, validate and determine the most critical factors that require intervention to diminish variance from project performance.

The BWM resulted in stakeholder management, followed by organizational and technological complexity as significant complexity factors, and the varied interests of the stakeholder as the most important among the 40 subfactors.

The finding indicates the necessity for strategic, tactical and operational-level interventions to effectively manage the complexity affecting project efficiency because of the varied stakeholders. This paper will guide the project and general managers to prioritize their resources to handle complexity for effective project performance measured in terms of time, cost and quality and help them make strategic decisions. The research findings of this study are expected to help researchers and practitioners in better planning and smoother execution of projects. In addition, this study would help the researchers formulate policies and strategies for better handling of the projects.

This study adds significant value to the body of knowledge related to PC in megaprojects in developing countries. The result of the investigation underlined that nine complexity factors and seven unique subfactors, namely, the sustainable environment, timely availability of information, communication in both directions, interdepartmental dependency and coordination, design, statutory norms, site challenges, socioeconomic conditions, the tendency of staff to accept new technology and the frequent changes in the requirements of stakeholders are significant in railway megaprojects. The BWM is applied to rank the complexity factors and subfactors in the case area.

Megaproject's construction is essential for the development and economic growth of any country, especially in the developing world. In Kuwait, megaprojects are facing many restrictions that discourage their execution causing a significant delay in bidding, design, construction and operation phases with the execution quality being affected. The objective of this study is to develop a complexity measurement model using analytic hierarchy process (AHP) for megaprojects in Kuwait, with a focus on the New Kuwait University multi-billion campus Shadadiyah (College of Social Science, Sharia and Law (CSSL)) as a case study.

The study applies a hybrid fuzzy analytic hierarchy process (FAHP) method to compare the results with those obtained using the conventional AHP method. This can facilitate the project management activities during the different stages of construction. Data were collected based on the results of a two-round Delphi questionnaire completed by seniors and experts of the selected project.

It was found that project modeling methodology was responsible for complexity. It was grouped under several categories that include technological, goal, organizational, environmental and cultural complexities. The study compares complexity degrees assessed by AHP and FAHP methods. “Technological Complexity” scores highest in both methods, with FAHP reaching 7.46. “Goal Complexity” follows closely behind, with FAHP. “Cultural Complexity” ranks third, differing between methods, while “Organizational” and “Environmental Complexity” consistently score lower, with FAHP values slightly higher. These results show varying complexity levels across dimensions. Assessing and understanding such complexities were essential toward the completion of such megaprojects.

The contribution of this study is on providing the empirical evidential knowledge for the priority over construction complexities in a developing country (Kuwait) in the Middle East.

Inter-organizational collaboration is the organizational guarantee and key link to achieve the goals of megaproject management. Project governance has always played an important role in the construction of megaprojects, but the relationship between project governance and organizational collaboration is unclear. The purpose of this study is to explore the role paths of different project governance mechanisms in influencing the collaborative behaviors of stakeholders and collaborative performance and to elucidate the mechanism of project governance on inter-organizational collaboration.

A conceptual framework was developed based on a comprehensive literature review, termed the structural equation model (SEM). The hypotheses of the model were tested based on data obtained from a questionnaire survey of 235 experts with experience in megaprojects within the construction industry in China.

The results show that project governance positively contributes to the collaborative behavior of megaproject stakeholders and the collaborative performance of the project team. Collaborative behavior acts as a partial mediator between project governance and the collaborative performance of the megaproject inter-organization alliance. The complexity of the project modulates the relationship between the governance mechanism of the project and the collaborative behavior of the stakeholders, which affects the collaborative performance of the megaproject inter-organization alliance.

The findings provide theoretical and practical implications for promoting positive collaborative behavior among stakeholders in megaproject selection and improving the collaborative performance of megaproject inter-organization alliances.

This study delves into the dynamics between Agile Response to Change (AR), Adaptive Scoping (AS), Stakeholder Engagement (SE) and Project Performance (PP), with a special focus on the moderating influence of Project Complexity (PC). The research, grounded in a thorough literature review, identifies critical gaps in these areas and examines the extent to which PC moderates the effects of AR, AS and SE on PP, offering new perspectives for managing complex projects.

The research develops a conceptual model based on a critical analysis of existing literature. A comprehensive questionnaire was designed, incorporating 28 items to measure AR, AS, SE, PP and PC. Data was collected from 136 project managers across various industries, and the responses were analysed using structural equation modelling (SEM) to explore the complex interplay between these variables.

The analysis revealed that internal AR (ARint) significantly enhances both quantitative (PPqt) and qualitative aspects of PP (PPql). AS and SE were found to positively influence PPql, but their impact on PPqt was not significant. Interestingly, PC was observed to negatively moderate the relationship between ARint and PPql, while its moderating effect on the relationship between ARint and PPql was not significant. The study also notes that PC does not significantly alter the positive correlations between AS, SE and PPql.

This research contributes to the existing body of knowledge by elucidating the relationships between ARint, AS, SE and different dimensions of PP. It uniquely explores the role of PC as a moderating variable in these relationships, offering valuable insights for practitioners and researchers in the field of complex project management.

This study aimed to address a gap in subcontractor management by focusing on previously unexplored complexities surrounding subcontractor management in developing countries. While past studies concentrated on selection and relationships, this study delved into how effective subcontractor management impacts project success.

This study used the Bayesian Network analysis approach, through a meticulously developed questionnaire survey refined through a piloting stage involving experienced industry professionals. The survey was ultimately distributed among participants based in Accra, Ghana, resulting in a response rate of approximately 63%.

The research identified diverse components contributing to subcontractor disruptions, highlighted the necessity of a clear regulatory framework, emphasized the impact of financial and leadership assessments on performance, and underscored the crucial role of main contractors in Integrated Project and Labour Cost Management with Subcontractor Oversight and Coordination.

Previous studies have not considered the challenges subcontractors face in projects. This investigation bridges this gap from multiple perspectives, using Bayesian network analysis to enhance subcontractor management, thereby contributing to the successful completion of construction projects.

Official development assistance (ODA) education projects have played a crucial role in improving education and training fields in developing countries, but are often facing several considerable challenges (e.g. long implementation time). Thus, this study aims to identify critical success factors (CSFs) in ODA education projects and investigate the influences of CSFs on ODA project performance measured by 11 nonprofit outcomes (NPOs).

A comprehensive literature review and expert interviews were conducted to compile a list of 35 potential success factors for ODA education projects. Using a survey questionnaire, 143 valid responses were collected from practitioners joining ODA projects in Vietnam. Various statistical methods (e.g. mean score method, Spearman rank correlation test, analysis of variance test, factor analysis and regression analysis) were used to analyze the collected data.

This research identified seven CSFs for ODA education projects in Vietnam: comprehensive project management competency (C1), clarity and compliance in project execution (C2), transparency and committed funding (C3), external context conditions (C4), well-controlled design and project management procedures (C5), preparations in equipment and complexity insight (C6) and punctual site delivery (C7). Furthermore, the results of regression analysis indicated that comprehensive project management competency (C1) and transparency and committed funding (C3) could significantly affect various NPOs.

This study offers significant insights for practitioners (e.g. project managers) to improve ODA projects’ performance and effectiveness in the education and training sector of a developing country context (like Vietnam).

Insufficient time allocation for the bidding period occurs, causing drawbacks to both parties, the client and the bidder. Hence, this study aims to evaluate the time allocated for preparing a bid proposal as per the National Competitive Bidding (NCB) in the Sri Lankan context.

The study has adopted a mixed method approach and expert interviews and document review to detect, analyse and validate the issues, and solutions based on NCB along with the adequacy of the allocated bidding period used as main data collection tools. Both qualitative and quantitative data were analysed through manual content analysis and inferential analysis respectively.

Overall, 24 local issues with the existing competitive bidding process and solutions for each were identified. Among the 24 local issues, it was unanimously agreed by all interviewees that three specific issues require attention and improvement. These issues are related to the standard and incompleteness of bidding documents, inaccurate BOQ quantities measured by the consultant or the main contractor, and the excessive number of bidding document amendments by the consultant. It was revealed that a maximum of 42 calendar days (6 weeks) is sufficient for the bidding process while a minimum of 21 calendar days (3 weeks) is insufficient.

The findings of this study would be recommended that Information and Communication Technology Agency (ICTA) understand the necessity of revising the NCB reference to the time allocated for the preparation of bids. By recognising the importance of sufficient time allocation for bid preparation, this research serves as a practical guide for authorities involved in policy formulation, aiding them in implementing revisions that align with the dynamic requirements of bidding procedures.