Knowledge-Oriented Leadership, Team Cohesion, and Project Success: A Conditional Mechanism

We examined the impact of knowledge-oriented leadership on project success via team cohesion and the moderating role of valuing people and project complexity on this relationship. We collected data from 121 project employees in Pakistan in a two-wave field survey at an interval of 15 days. The results showed a positive association between knowledge-oriented leadership and project success, and team cohesion partially mediated this relationship. Valuing people positively moderated the relationship between knowledge-oriented leadership and team cohesion. Project complexity had a negative but insignificant moderating effect on project success. The theoretical and practical implications of these findings are discussed.

Assessment of Construction Project Complexity

Objective: Project complexity is a crucial factor in project management that presents auxiliary obstacles to reaching project objectives (cost, time, safety, and quality). This study aims at understanding project complexity and factors affecting project complexity. The overall objective of the study is to determine the nature of complexity and characteristics, identify the important complex factors that influence the complexity of the project, factor weight of the complex factors, and develop a proposed construction complexity index (CCI). Methods: According to the literature review, the Analytic Hierarchy Process (AHP) method is used to measure the affecting factors of project complexity. Results: This paper developed an index to measure complexity based on factor weights called construction complexity index (CCI). The validity of this index was verified by studying 3 cases. The construction complexity index (CCI) proposed here allows measuring the complexity of the projects in Egypt. The results of this paper provide guidelines on how to successfully manage the complexity of the project. Conclusion: Project complexity management relates to the challenge of dealing with technical competence, professional diversity, uncertainties, and unforeseen events in project implementation. Project managers, who are critical to effectiveness or failure, need skills such as adaptation, creativity, and flexibility to meet this challenge. Therefore, this study provides guidelines to help practitioners to develop their capabilities in managing complex projects. Moreover, this paper enables participants to identify factors affecting the complexity of projects and how to calculate this complexity through the complex index. The outcomes of this study can be used by practitioners to develop a complexity assessment and management tool, which would enable industry practitioners to allocate resources effectively on complex construction projects. This research aimed to develop a measure by which the complexity of construction projects in Egypt can be evaluated and establish guidelines on avoiding complexity in projects.

BIM Performance, Project Complexity, and User Satisfaction: A QCA Study of 39 Cases

Although the realization of building information modeling (BIM) performance is the basis for the generation of user’s satisfaction, few studies have explored the influence path between BIM performance and BIM user’s satisfaction in recent years. Therefore, to enrich the research results of BIM user’s satisfaction and provide reference schemes for engineering practice, this study adopts the fsQCA (fuzzy-set qualitative comparative analysis) method, taking 39 project cases using BIM technology as the base sample to analyze the influence path between BIM performance and user’s satisfaction. Moreover, this study is based on the configuration theory, examining four elements of BIM performance: BIM accuracy, information integration, functional advantages and manager support, and the complexity of the project. Finally, this study identifies three types of configuration results: performance type, support type, and comprehensive type. The performance type can achieve high user satisfaction in relatively complex projects; the support type requires executive support to improve user satisfaction in less complex projects, and the comprehensive type improves satisfaction through multiple BIM performances without considering project complexity.

A System Dynamics Analysis of Value Creation in Project Context

The focus of this paper is on analyzing the value creation dynamics in the project implementation phase. By value creation, we mean the activities, processes, and strategies that the project team uses to increase benefits and/or reduce costs in the project. By synthesizing the literature on project management and system dynamics, we developed a simulation model with various structures underlying project dynamics. We considered four structures that influence project realized value: project team features, project characteristics, project controls and value creation processes, and project remedial actions due to ripple effects. The resulting model can systematically examine the interplay of value creation processes: work progression, rework, redesign and innovation, and rescheduling. We used the model to explain how the project team’s capability, motivation, and speed of making the best-for-project decisions ensure that the value creation goals are met. We simulate various scenarios that show the significance of the processes and their influencing structures on the realized value. The results present how endogenous and exogenous drivers of system behavior unfold over time and provide a richer understanding of the effect of various model structures such as project complexity and uncertainty on value creation.

Investigating the Causal Relationships between Project Complexities and Project Cost: An Empirical Study from New Zealand

Project complexity is usually considered as one of the main causes of cost overruns, resulting in poor performance and thus project failure. However, empirical studies focused on evaluating its effects on project cost remain lacking. Given this circumstance, this study attempts to develop the relationship between project cost and the multidimensional project complexity elements. The study assumes complexity as a multidimensional factor including the task, organization, market, legal, and environment complexities. And it adopts an empirical evidence-based structural model to account for the relationships between project cost and project complexity. By doing so, a quantitative assessment of multidimensional project complexity has been developed. The findings suggest that task and organization complexities have direct effects on project cost, while market, legal, and external environment complexities have indirect effects on project cost. The practical contribution is that the findings can improve the understanding of which dimension of complexity significantly influences project cost and the need to focus efforts on strategically addressing those complexities.

A theoretical framework for classifying project complexity at the preconstruction stage using cluster analysis techniques

PurposeThe accuracy and reliability of subjectively assessing a construction project's complexity at the pre-construction stage is questionable and relies upon the project manager's tacit experiences, knowledge and background. The purpose of this paper is to develop a scientifically robust analytical approach by presenting a novel classification mechanism for defining the level of project complexity in terms of work contents (WCs), scope, building structures (BSs) and site conditions.Design/methodology/approachEmpiricism is adopted to deductively analyze variables obtained from secondary data within extant literature and primary project data to develop project type classifications. Specifically, and from an operational perspective, a two-stage “waterfall process” was adopted. In stage one, the research identified 56 variables affecting project complexity from literature and utilized a structured questionnaire survey of 100 project managers to measure the relevance of these. A total of 27 variables were revealed to be significant and exploratory factor analysis (EFA) is adopted to cluster these variables into six-factor thematic groups. In stage two, data from 62 real-life projects (including the layout and structural plans) were utilized for computing the factor score using the six-factor groups. Finally, hierarchical cluster analysis (HCA) is adopted to classify the projects into collected distinctive groups and each of a similar nature and characteristics.FindingsThe developed theoretical framework (that includes a novel complex index) provides a robust “blueprint platform” for main contractors to compile their project complexity database. The research outputs enable project managers to generate a more accurate picture of complexity at the pre-construction stage.Originality/valueWhile numerous research articles have provided a comprehensive framework to define project complexity, scant empirical works have assessed it at the pre-construction stage or utilized real-life project samples to classify it. This research addresses this knowledge gap within the prevailing body of knowledge.

An early-stage project complexity assessment tool for the AEC industry

Purpose Complex projects require careful management. They may expose stakeholders to greater risks and place additional demands upon resources. In the initial stages of project development, however, little may be known about the nature and magnitude of such complexity. This paper aims to ensure that this gap is at least subjectively assessed and addressed. Design/methodology/approach Research, using focus group workshops with a convenience sample of construction professionals, was carried out to test the validity of a Project Early Stage Complexity Assessment Tool (PESCAT). The PESCAT concept brings together selected complexity theories and uses subjectively based measures for assessment. Findings The findings confirm that an early-stage project complexity assessment tool is practicable and can contribute to project management practice in the construction industry. It should be applied by individual project stakeholders using small teams of experienced staff. PESCAT explores project complexity through “filter” sets of perspective factors which should be customised to reflect the stakeholder’s role and processes in a project. Originality/value In the initial complexity assessment model, resolution space and uncertainty were tested as project complexity parameters. However, in subsequent versions of the tool, four measures (differentiation and differentiation uncertainty; interdependency and interdependency uncertainty) are used in an innovative way that focuses users’ attention more clearly and points to a more targeted approach for addressing project complexity. The value of our model lies in its practical application and the project management benefits it can deliver.