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Inter-organisational collaboration is becoming increasingly important in complex projects; some project customers even formally require evidence of collaborative competence from potential providers. The purpose of this paper is to explore the governance of collaboration and the ways in which it is enacted in practice for complex projects.

The study is based on a qualitative analysis of 29 semi-structured interviews, primary data from meetings and events supported by secondary data, including standards and industry-specific contract templates.

The paper identifies how collaboration can be effectively governed in complex projects through the emerging role of the collaboration standard and its impact on contractual and relational governance mechanisms. The standard sets higher-level institutional guidelines that affect the way in which collaboration is governed in complex projects. It helps formalise informal relational practices whilst also providing guidelines for building flexibility in contracts by including coordination- and adaptation-oriented provisions conducive to collaboration.

The paper demonstrates the emerging role of the collaboration standard and its influence on contractual and relational mechanisms deployed in complex projects. It shows how the standard can formalise and codify informal collaborative practices and help transfer related learning across projects, thereby contributing towards the dual requirement for standardisation and flexibility in project settings.

This paper explores how public buyers' capabilities promote collaboration with private suppliers to obtain enhanced performance in complex projects.

The authors conducted two case studies on the procurement of complex military projects by the Brazilian armed forces involving public buyers and private suppliers. The authors followed the Gioia methodology to inductively analyze data from interviews, official documents, media articles and project meeting notes.

The authors identified public procurement capabilities that are antecedents of collaborative trust-based relationships with suppliers in complex public-private projects. The authors unpack these capabilities in three subsets: abilities to manage the bidding and contracting process, to handle relationships with prominent stakeholders, such as audit control bodies and to manage knowledge acquired within and across current and past projects. By developing these capabilities, public buyers can build collaborative trust-based relationships with suppliers, which enable the conciliation of operational performance (i.e. on-time delivery, budget and scope compliance) and policy goals (i.e. inclusion of local suppliers in supply chains).

The authors extend the literature on the enablers of trust and collaboration in buyer-supplier relationships by providing a detailed account of which capabilities are necessary on the buyer side in complex projects, especially when accountability standards create barriers for collaborative practices. The authors also reinforce the importance of the operations and supply chain management scholarship in policy debates by showing how buyer-supplier interactions can create value in complex projects with public and private sectors.

This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions.

The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations.

A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works.

The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity.

The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.

Abnormal behaviors such as rework, backlog, changes and claims generated by project organizations are unavoidable in complex projects. When abnormal behaviors emerge, the previously normal state of interactions between organizations will be altered to some extent. However, previous studies have ignored the associations and interactions between organizations in the context of abnormal organizational behaviors (AOBs), making this challenging to cope with AOBs. As a result, the objective of this paper is to explore how to reduce AOBs in complex projects at the organizational level from a network perspective.

To overcome the inherent limitations of a single case study, this research integrated two data collection methods: questionnaire survey and expert scoring method. The questionnaire survey captured the universal data on the influence possibility of AOBs between complex project organizations and the expert scoring method got the influence probability scores of AOBs between organizations in the case. Using these data, four organizational influence network models of AOBs based on a case were developed to demonstrate how to destroy AOBs networks in complex projects using network attack theory (NAT).

First, the findings show that controlling AOBs generated by key organizations preferentially and improving the ability of key organizations can weaken AOBs network, enabling more effective coping strategies. Second, the owners, government, material suppliers and designers are identified as key organizations across all four influence networks of AOBs. Third, change and claim behaviors are more manageable from the organizational level.

Project managers can target specific organizations for intervention, weaken the AOBs network by applying NAT and achieve better project outcomes through coping strategies. Additionally, by taking a network perspective, this research provides a novel approach to comprehending the associations and interactions between organizations in the context of complex projects.

This paper proposes a new approach to investigating AOBs in complex projects by simultaneously examining rework, backlog, change and claim. Leveraging NAT as a novel tool for managing the harmful effects of influence networks, this study extends the knowledge body in the field of organizational behavior (OB) management and complex project management.

The purpose of this paper is to extend the learning boundaries of traditional project capability, which follows the linear planning paradigm, in order to include non-linear complex projects that cannot be completely specified and planned in advance, and so require continuous learning over their life cycles.

Based on an earlier empirical investigation, where complex-project capability (CPC) is developed through dynamic organizational learning based on non-linear problem solving, the paper examines some of the conceptual and practical implications of this process insight. The focus here is on incomplete pre-given knowledge and emergent knowledge creation during CPC development.

Using the three interrelated dimensions of project type, knowledge creation method, and organizational learning approach, the paper reinterprets Karl Popper’s linear problem solving model for learning in traditional projects by introducing the concept of knowledge entropy (disorder) for learning in non-linear complex projects. The latter follows a path from “order to disorder to order” rather than from “order to order” under traditional assumptions.

By identifying a common learning process at individual, group, and organizational levels, developing CPC can be viewed as a “learning organization”. This multi-level approach facilitates research into distributed organizing for emergent knowledge creation during CPC development.

In contrast to traditional planned projects with up-front prior knowledge, complex projects are characterized by incomplete knowledge. The challenge of dealing with knowledge uncertainty in complex projects through continuous learning has practical implications for project learning, planning, knowledge management, and leadership.

The concept of knowledge entropy (disorder) extends the learning boundaries of traditional projects, where little learning is anticipated, by including complex projects with knowledge uncertainty requiring continuous learning.

The insurance sector provides insurance protection for complex project deals in Ghana. The study assesses the service quality of insurance of complex project deals in the construction industry of developing countries, specifically Ghana. The objectives are to identify the insurance typologies in complex project deals in the construction industry, to assess the level of construction insurance quality, and to assess the challenges faced in complex project insurance.

A comprehensive literature review was conducted to analyze the previously related works on insurance in the construction industry. The study then adopted quantitative research strategy where a structured questionnaire survey was used to collect information from construction industry professionals. The data analysis was organized in accordance with the specific objectives of the study with the aid of mean score analysis and independent sample t-test. The study again measured the reliability of the adopted scale using Cronbach's alpha, which indicated that all the items reliably measured what they were intended to measure, and thereby, statistical tools can be applied to give in-depth meanings.

The insurance typologies for complex projects were discovered by the study, as well as the available service qualities of insurance. The study again made it clear that the major challenges capable of affecting complex construction project are low quality of insurance companies' services and the gap in statutory and legal systems.

The major constraint in this study was the issue of taking only Ghana as a developing country to generalize the result. This is then to provide lessons for other developing countries.

The findings from this study will be useful to construction firms, insurance firms, and regulatory bodies by identifying the effectiveness of insurance as a risk mitigation measure in construction. The study will help the insurance firms to better position themselves to meet the demands of the construction industry. As the findings of this study are Ghana-specific, it is also to provide lessons for other developing countries.

This study delves deep into the complex construction project insurance service quality in developing countries, specifically Ghana.

The purpose of this paper is to facilitate further understanding of project complexity by highlighting the factors contributing to project complexity as reported by the practitioners facing the “actuality” of projects.

A qualitative research approach was undertaken by conducting semi‐structured interviews with the primary focus on the aerospace industry. Participants are involved in a variety of project settings, exhibiting different types and levels of complexity.

Analysis of responses highlights “people” issues as the main factor contributing to project complexity and the importance of soft skills in managing complex projects.

The research is based on a limited number of respondents from the aerospace sector. This will be further refined and improved upon by compiling views of additional practitioners involved in multiple aerospace projects.

The main research conclusions are that “hard” project management skills help to organise, plan and manage, and track changes during the course of the project. However, understanding of project complexity and its contributing factors helps practitioners to understand the dynamic, social and complex contexts of projects, thus highlighting the importance of “soft” skills.

This paper proposes the “project complexity triangle – people, product and process”, highlighting their importance as the three major areas contributing to project complexity.

Relationship management evolves with dynamic and complex environments of megaprojects. However, studies on the longitudinal measurement of relationship management performance for each stakeholder in dynamic and complex project environments are lacking. The purpose of this research is to propose an NK-network evolution model to evaluate stakeholder performance on relationship management in the development of megaprojects.

The model input includes the stakeholder-associated issues and stakeholders' relational strategies, the co-effects of which determine the internal effects of relationship management in megaprojects. The model processing simulates the stakeholder performance of relationship management under the dynamic and complex nature of megaprojects. The NK model shows the dynamic stakeholder interactions on relationship management, whereas the network model presents the complex stakeholder structures of the relationships between stakeholders and relevant issues. The model output is the evolution graph to reveal the weak stakeholder performance on relationship management in the timeline of the project duration.

The research finding reveals that all stakeholders experience the plunge of stakeholder performance of relationship management at the decision-making moment of the planning stage. Construction, environmental and pressure groups may experience the hardship of relationship management at the start of the construction stage. The government is likely to suffer difficulties in relationship management in the late construction stage. Local industry groups would face challenges in relationship management in the middle of the construction stage and handover stage.

The research provides a useful approach to measuring weak moments of relationship management for each stakeholder in various project phases, considering the dynamic and complex environments of megaprojects. The proposed model extends the current knowledge body on how to make project stakeholder analysis by modelling dynamic and complex environments of megaprojects, with bridging the knowledge domains of evolution modeling techniques and network methods.

Project-based industries face major challenges in controlling project cost and completing within the budget. This is a critical issue as it often connects to the main objectives of any project. However, accurate estimation at the beginning of the project is difficult. Scholars argue that project complexity is a major contributor to cost estimation inaccuracies. Therefore, recognising the priorities of acknowledging complexity dimensions in cost estimation across similar industries is beneficial in identifying effective practices to reduce cost implications. Hence, the purpose of this paper is to identify the level of importance given to different complexity dimensions in cost estimation and to recognise best practices to improve cost estimation accuracy.

An online questionnaire survey was conducted among professionals including estimators, project managers, and quantity surveyors to rank the identified complexity dimensions based on their impacts in cost estimation accuracy. Besides, in-depth interviews were conducted among experts and practitioners from different industries, in order to extract effective practices to improve the cost estimation process of complex projects.

Study results show that risk, project and product size, and time frame are the high-impact complexity dimensions on cost estimation, which need more attention in reducing unforeseen cost implications. Moreover, study suggests that implementing a knowledge sharing system will be beneficial to acquire reliable and adequate information for cost estimation. Further, appropriate staffing, network enhancement, risk management, and circumspect estimation are some of the suggestions to improve cost estimation of complex projects.

The study finally provides suggestions to improve cost estimation in complex projects. Further, the results are expected to be beneficial to learn lessons from different industries and to exchange best practices.

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.