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Mental health care shortages in the United States are most pronounced in rural areas. This practice-change project aimed to increase access to quality mental health care in rural areas for the treatment of depression and anxiety via telemental health delivery of care. The project yielded improvements across project aims, including an increased percent of enrolled patients from Healthcare Provider Shortage Areas; a decrease in quality measures for depression, anxiety, and disability; and increased patient satisfaction with care. The project can serve as a template for other practices wishing to increase access to mental health care in rural areas.

Purpose Learning across teams and organisational levels enables organisations to deal with challenges that arise from changing contexts. Project-oriented organisations increasingly use programme management to cope with such challenges and improve performance. This paper aims to find out how different programme configurations affect learning across project teams and between project teams and their parent organisation in project-oriented organisations. Design/methodology/approach A case study of a project-oriented organisation involved in five infrastructure programmes was performed. Findings The studied programmes linked learning processes at group and organisational levels by creating relationships across project teams and their parent organisation and acting as a knowledge centre. Team learning benefits from the learning culture and stable environment that programmes create for project teams. This study indicates that a programme’s features and focus strongly determines whether a programme predominantly enhances learning across project teams or learning between project teams and their parent organisation. Originality/value Although programme management is increasingly used by project-oriented organisations, there are few studies relating to learning in programmes. This study provides new insights into learning across teams through programmes.

This paper presents the application of a meta-analysis approach to the evaluation of youth-learning data from the nationally distributed This is How We “Role” program. The application of meta-analysis for examining the impact of other multisite youth programs encountering similar data analysis challenges is discussed. At each This is How We “Role” program site, university partners collected data to examine youth-participant learning. Data analysis from these unique sites was challenging as the approach had to accommodate the innate heterogeneity across sites due to differences in implementation, sample size, and learning context. The meta-analysis method revealed details of the underlying variation between sites that could be masked by typical regression approaches, estimated overall program effects, examined subgroups and identified heterogeneity across project sites. The results showed the This is How We “Role” program generally increased learning at each site and as a whole, even though the program effects varied across sites. This example demonstrates the utility of using the meta-analysis approach to similar multi-site youth development programs.

The last decade has witnessed unprecedented changes in the technologies and processes involved in the construction industry. The philosophies associated with Industry 4.0 now reverberate in construction 4.0. Digitalization and interconnectivity in the cyber-physical systems of the sector are at the heart of such transformation. Construction 4.0 brings to the table a plethora of technologies and associated processes over the construction project lifecycle. The current study performs a state-of-art literature review to summarize the knowledge advancement in construction 4.0. A layered conceptualization spanning across project lifecycle utilizing the people-process-technology dimensions is presented to summarize the current understanding of Construction 4.0. The cyber-physical space is classified into the physical, digital tool, data, and core data security and interoperability layers. The inter-layer and intra-layer interactions and information flows are then conceptualized based on the extant literature, including the human interaction and interventions. The people-process-technology dimensions were discussed across the project lifecycle through interactions in these layers. It is observed that Construction 4.0 is set to be driven by data creation, data flow, data transformation, and data storage across the project lifecycle to ensure a collaborative environment across the stakeholders who interact and associate with different layers of Construction 4.0. The article finally presents challenges with the current formulations and explores ways to further our knowledge in the area.

PurposeThe purpose of this paper is to propose a data-driven scheme for identifying critical project complexity dimensions and establishing the trade-off across multiple project performance criteria.Design/methodology/approachThis paper adopts a hybrid approach using Bayesian Belief Networks (BBNs) and Artificial Neural Networks (ANNs). The output of the ANN model is used as input to the BBN model for prioritizing project complexity dimensions relative to multiple project performance criteria. The proposed process is demonstrated through a real application in the construction industry.FindingsWith a number of nonlinear interactions involved within and across project complexity and performance, it is not feasible to model and assess the strength of these interactions using conventional techniques. The proposed process helps in effectively mapping a “multidimensional complexity” space to a “multidimensional performance” space and makes use of data from past projects for operationalizing this mapping scheme by means of ANNs. This obviates the need for developing a parametric model that is both challenging and computationally cumbersome. The mapping function can be used for generating all possible scenarios required for the development of a data-driven BBN model.Originality/valueThis paper introduces a data-driven process for operationalizing the mapping of project complexity to project performance within a network setting of interacting complexity dimensions and performance criteria. The results of the application study manifest the importance of capturing the interdependency across project complexity and performance. Ignoring the underlying interdependencies and relying exclusively on conventional correlation-based techniques may lead to making suboptimal decisions.

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

PurposeIndustry uptake of digital modeling is improving. Recent evidence suggests building information modeling (BIM) is the commercial reality of today’s construction education, and the way of the future that has truly begun. Amongst the significance of this is BIM’s potential to revolutionize the industry. The purpose of this paper is to use the learning experiences of undergraduate students in two construction management subjects involving quantity measurement and cost estimation to explore students’ motivation toward BIM education. In particular, the study investigates decision factors underlying students’ selection of software for information management in a modeling environment.Design/methodology/approachA total of 674 undergraduate students from the same institution were surveyed, out of which 153 responses were retrieved. The data provide insights into decisions taken by students while metamorphosing traditional processes into BIM-driven outcomes, in the form of commercial estimates of a real life project reported through a bill of quantities. Some 29 decision factors were analyzed. These include prior training, flair for creativity, ease of use, economic reasons, learning outcomes, on-going technical support and support infrastructure. Reductionist methods involving factor analysis and Cronbach’sαreliability estimate procedures were used to investigate the most important decision factors from amongst the decision factors analyzed.FindingsResults show all the 29 decision factors are statistically significant. Access to on-going support, the mandatory requirement to use a particular tool to complete an assessment task and the requirement to use the tool for job duties are the most significant decision factors. Vendors’ persuasion and the capability of the tool to achieve better outcomes than others are least significant. Statistical correlations between the decision factors were obtained. They all suggest near-absolute correlations.Practical implicationsThe practical implications of these findings are vital. They help to unravel factors that promote students’ interest in BIM education, and contribute toward the development of software selection models that are relevant to professionals and incipient businesses.Originality/valueFuture studies on decision analysis can be built on the findings also. In particular, the decision factors help in developing creative cognitive solutions to BIM adoption issues. They also help on the challenge posed by the constraints of knowledge diffusion within and across project teams, and in designing tools that meet the requirements of non-design disciplines who also play vital roles in the BIM project environment.

Purpose To foster effective implementation of building information modelling (BIM), it is guided by standards and protocols that require files naming in a format, containing a string of letters and digits in a tightly defined manner, which is perceived to be time-consuming, error-prone and serves as a barrier to BIM adoption. This paper aims to present a BIM-based plug-in solution (Auto-BIMName) that facilitates automated naming in compliance with BIM standards. Design/methodology/approach The Auto-BIMName portal has an information management system (IMS) for generating a master information delivery plan (MIDP), which serves as pre-requisites to effective file naming. Once the naming schema is implemented through text input controls for a project name, volume, level and number, the Revit plugin communicates with its IMS to fetch the name string or concatenate the string in line with the ISO 19650 convention, where the IMS is unused. The system was validated through a simulated collaborative project. Findings System testing and evaluation confirmed that the Auto-BIMName will ease the process of file naming, thereby facilitating collaboration efficiency, naming consistency across project teams and lifecycle stages, ease of file naming, time-saving and inducement for BIM implementation, etc. By linking information from MIDP in the BIM execution plan, the platform enhanced information management processes and improved coordination across project teams and lifecycle stages. Originality/value Apart from demonstrating how the automated naming platform enhances project performance, information management and coordination, the paper provides a practical demonstration of how the construction industry will benefit from enhanced digitalisation and process automation.

To determinate the role of organizational learning across project-based organizations, this study applies a micro-level perspective of organizational learning theory to the social constructivist approach to address relational learning information collaboration that takes into account a strategic perspective involving the development of collective knowledge. The sample was distributed to 180 individuals from different targeted private universities from a total population of 1400 private universities that operate through collaborative ventures to test the research hypotheses. We were able to use 168 surveys in our statistical study after deleting 12 surveys with incorrect responses. Furthermore, value building continues to play a role in bridging the gap between corporate development and long-term strategic growth. Furthermore, exploratory purpose shows a major mediation function in inter-organizational learning, as well as the potential to sustain long-term partnerships with partners, as a beneficial result of partner diversity as a moderate factor. Information convergence was shown to be strongly linked for strategic achievement, as was corporate culture, competences and capabilities, and team cooperation

Due to the advancements in Information and Communication Technologies (ICT) in university education, e-learning has become an essential part of Architecture, Engineering, and Construction (AEC) education programs. Building Information Modeling (BIM) is an ICT that can be used as a powerful didactic method approach to improve e-learning outcomes. A collaborative BIM tool was implemented in a project design class in a civil engineering course. This study aims to analyze the way BIM technology supported resource sharing within and across project groups, reinforced the forms of group collaboration, and improved e-learning outcomes. This study was developed under the framework of the new educational model Tec 21 in the Tecnologico de Monterrey university system in Mexico. This study was evaluated using both qualitative (e.g., pyramid discussion) and quantitative methods (e.g., survey). The results showed that BIM helped to improve communication in the group, group sharing of resources, and supported different kinds of group collaboration. The collaborative BIM tool provided a location-independent central virtual workspace, whereas the BIM software provided enough individual capability and resources for accurate building modeling. The paper discusses the importance of embedding supportive ICTs, such as BIM, to improve e-learning in civil engineering courses, as well as the limitations and needs in this field.

Code comprehension, especially understanding relationships across project elements (code, documentation, etc.), is non-trivial when information is spread across different interfaces and tools. Bringing the right amount of information, to the place where it is relevant and when it is needed can help reduce the costs of seeking information and creating mental models of the code relationships. While non-traditional IDEs have tried to mitigate these costs by allowing users to spatially place relevant information together, thus far, no study has examined the effects of these non-traditional interactions on code comprehension. Here, we present an empirical study to investigate how the right information at the right time and right place allows users—especially newcomers—to reduce the costs of code comprehension. We use a non-traditional IDE, called Synectic, and implement link-able annotations which provide affordances for the accuracy, time, and space dimensions. We conducted a between-subjects user study of 22 newcomers performing code comprehension tasks using either Synectic or a traditional IDE, Eclipse. We found that having the right information at the right time and place leads to increased accuracy and reduced cognitive load during code comprehension tasks, without sacrificing the usability of developer tools.

Purpose: This article presents a recent research and development experiment on benefits analysis for adopting building information modeling/management (BIM) systems in megaproject delivery across work stages with regard to the needs of project stakeholders. It focuses on a new approach to benefits prioritization to support decision making against major challenges in megaproject delivery. Methodology: The study was underpinned by an extensive literature review on relevant research and practices across the world, and a questionnaire-based survey on the benefits from adopting BIM in megaproject delivery in Australia. In addition, this study yields new tools for value analysis with regard to the adoption of BIM systems in megaproject delivery, and this include a new calculation method for benefits prioritization, and a new value compass tool to support decisions making on BIM adoption. Findings: Through the extensive literature review that covers multidisciplinary areas relating to the use of BIM, a set of generic hypotheses was formulated on the comparative level of technical value that various stakeholder groups are expected to achieve from adopting BIM systems in megaproject delivery. These hypotheses were tested by using the questionnaire-based survey. A new benefits prioritization approach was developed to identify the key benefits of BIM systems in megaproject delivery. In addition, a compass tool was also developed to visualize the status of value achievement across project stakeholders in dealing with major challenges in megaproject delivery. Implications for Research and Practices: By using data collected from the Australian megaproject sector in addition to academic review in Australia, China, and United Kingdom, this experimental study revealed current professional perceptions on the benefits of adopting BIM systems in megaproject delivery in comparison with data and information reported by professionals concerning the adoption of BIM systems from both generic and specific point of view across multiple megaproject stakeholders. Value: This article provides useful information for both academic research and practical services in the context of quantitative Cost-Benefit Analysis (CBA) on the adoption of BIM systems in megaproject delivery when major challenges on professional competence, budget, schedule and sustainability need to be seriously dealt with. Findings from this experimental study can inform value engineering practice at both strategic and tactic level with regard to adopting BIM systems in megaproject delivery.

Activity network analysis is a widely used tool for managing project risk. Traditionally, this type of analysis is used to evaluate task criticality by assuming linear cause‐and‐effect phenomena, where the size of a local failure (e.g., task delay) dictates its possible global impact (e.g., project delay). Motivated by the question of whether activity networks are subject to nonlinear cause‐and‐effect phenomena, a computational framework is developed and applied to real‐world project data to evaluate project systemic risk. Specifically, project systemic risk is viewed as the result of a cascading process which unravels across an activity network, where the failure of a single task can consequently affect its immediate, downstream task(s). As a result, we demonstrate that local failures are capable of triggering failure cascades of intermittent sizes. In turn, a modest local disruption can fuel exceedingly large, systemic failures. In addition, the probability for this to happen is much higher than anticipated. A systematic examination of why this is the case is subsequently performed, with results attributing the emergence of large‐scale failures to topological and temporal features of activity networks. Finally, local mitigation is assessed in terms of containing these failures cascades – results illustrate that this form of mitigation is both ineffective and insufficient. Given the ubiquity of our findings, our work has the potential of deepening our current theoretical understanding on the causal mechanisms responsible for large‐scale project failures.

The application of read-across and in silico tools for regulatory decision-making has been limited for pharmaceutical compounds to the assessment of genotoxic impurity. In contrast, the broad availability of toxicity data for industrial chemicals has triggered regulatory frameworks for read-across (e.g. ECHA Read-Across Assessment Framework), software tools and public databases for an automated process of gap filling in the context of safety assessment. This MiniReview provides an overview of the currently existing in silico and read-across approaches for chemicals together with recent developments for pharmaceutical compounds in these areas. It also highlights the differences and commonalities in the in silico safety assessment of industrial chemicals and drug candidates. Whereas toxicity data collection and sharing is now common practice for chemicals falling under the European REACH regulation (Registration, Evaluation, Authorisation and Restriction of Chemicals), the biggest hurdle for establishing preclinical safety databases for pharmaceutical compounds is the unwillingness to share proprietary data and lack of published data sets. In a recent consortium approach, thirteen pharmaceutical companies, eleven academic partners and six small to medium size enterprises (SMEs) of the bioinformatics sector joined forces over the last 7 years within the European Innovative Medicines Initiative project eTOX ('electronic toxicity') to design and implement a strategy for leveraging these preclinical data for small molecules and sharing them across project partners. The eTOX database has evolved as the largest preclinical toxicity database for drugs and drug candidates and currently contains more than 1900 different chemical structures and more than 8000 in vivo toxicity study data sets. It can be foreseen that the development and application of such databases for drugs or drug candidates will in the future also cross-fertilize the read-across and the in silico assessment of industrial or consumer chemicals particularly as soon as human safety data from clinical trials are integrated too.

Leadership is proven as a key factor impacting safety while researchers and practitioners are fostering proactive approaches to preventing workplace injuries. Practitioners' lack of leadership is one of the major causes for the continuous high-level accident frequency within the construction projects. An important yet still unsettled academic issue is how leadership impacts safety performance of construction projects, and how safety leadership can be improved. In order to probe into the mechanism by which leadership improves project safety, this study develops a safety leadership model for construction projects (SLMCP) in both theoretical and pragmatic perspectives. Theoretically, this model incorporates specific characteristics of construction projects and applies a multiple levels-of-management perspective to depict leadership's cascading influences across project stakeholders. Safety culture and safety management are the two major paths by which leadership impacts safety performance. Pragmatically, the action research (AR) method is used to validate the theoretical model empirically and develop feasible measures to implement safety leadership in practice. A five-round longitudinal evaluation confirmed in a case study the validity of SLMCP and the effectiveness of safety leadership improvement measures. This paper contributes to the body of knowledge by clearly depicting safety leadership's cascading top-down influencing mechanism in construction projects and providing concrete and validated measures for leadership improvement. The AR based intervention also establishes a general procedure for leadership promotion in practice. Conclusions of the paper serve as novel ideas and methods for workplace safety improvement in construction projects.

ContextAs developing high quality software becomes increasingly challenging because of the explosive growth of scale and complexity, bugs become inevitable in software systems. The knowledge of bugs will naturally guide software development and hence improve software quality. As changes in bug fixing code provide essential insights into the original bugs, analyzing change types is an intuitive and effective way to understand the characteristics of bugs. ObjectiveIn this work, we conduct a thorough empirical study to investigate the characteristics of change types in bug fixing code. MethodWe first propose a new change classification scheme with 5 change types and 9 change subtypes. We then develop an automatic classification tool CTforC to categorize changes. To gain deeper insights into change types, we perform our empirical study based on three questions from three perspectives, i.e. across project, across domain and across version. ResultsBased on 17 versions of 11 systems with thousands of faulty functions, we find that: (1) across project: the frequencies of change subtypes are significantly similar across most studied projects; interface related code changes are the most frequent bug-fixing changes (74.6% on average); most of faulty functions (65.2% on average) in studied projects are finally fixed by only one or two change subtypes; function call statements are likely to be changed together with assignment statements or branch statements; (2) across domain: the frequencies of change subtypes share similar trends across studied domains; changes on function call, assignment, and branch statements are often the three most frequent changes in studied domains; and (3) across version: change subtypes occur with similar frequencies across studied versions, and the most common subtype pairs tend to be same. ConclusionOur experimental results improve the understanding of changes in bug fixing code and hence the understanding of the characteristics of bugs.

The earliest human migration from Sunda (South-East Asian archipelago) to Sahul (Australia and New Guinea) is still heavily debated with proposed timings between c.65-45kaBP depending on the eviden...

This is a story of a design science research project that started in one domain, petrochemical refineries, before extending into another, technology consulting. Across the two domains, the problem was scoped, defined and refined as one of supporting knowledge-intensive work that takes place over time and across locations with teams of specialists. Significant empirical work and design efforts in fields like knowledge management, collaborative work, and business process design have yet to provide clear paths to successful intervention in this problem. We relied on design science research (DSR) and action design research (ADR) methods as we worked to develop two context-specific solutions. One solution, SPA, used semantic analysis of operator procedures for organizations in petrochemical refining to generate meaningful instruction sets in support of collaborative work on the refinery floor. The other solution, ReKon, decomposed consulting templates into meaningful sections for technology consulting so knowledge workers could access these templates across project phases in response to new consulting assignments. Together, the two artifacts exemplify a key design principle: anchoring knowledge units, not task sequences, in concrete artifacts may improve knowledge workers’ ability to respond to emergent complexities in knowledge-intensive work. The research project revealed three primary lessons. First, the time-consuming tasks of stakeholder interaction and development of seemingly simple artifacts allowed us to surface the complexities of organizational knowledge work in these domains. Second, ongoing and intense reflection away from the project activities was necessary to appreciate the theoretical depth. Third, the messy nature of design continued to grate against the systematic approach suggested by research methods.

PurposeThe purpose of this paper is to address the limitations of conventional risk matrix based tools such that both positive and negative connotation of uncertainty could be captured within a unified framework that is capable of modeling the direction and strength of causal relationships across uncertainties and prioritizing project uncertainties as both threats and opportunities.Design/methodology/approachTheoretically grounded in the frameworks of Bayesian belief networks (BBNs) and interpretive structural modeling (ISM), this paper develops a structured process for assessing uncertainties in projects. The proposed process is demonstrated by a real application in the construction industry.FindingsProject uncertainties must be prioritized on the basis of their network-wide propagation impact within a network setting of interacting threats and opportunities. Prioritization schemes neglecting interdependencies across project uncertainties might result in selecting sub-optimal strategies. Selection of strategies should focus on both identifying common cause uncertainty triggers and establishing the strength of interdependency between interconnected uncertainties.Originality/valueThis paper introduces a novel approach that integrates both facets of project uncertainties within a project uncertainty network so that decision makers can prioritize uncertainty factors considering the trade-off between threats and opportunities as well as their interactions. The ISM based development of the network structure helps in identifying common cause uncertainty triggers whereas the modeling of a BBN makes it possible to visualize the propagation impact of uncertainties within a network setting. Further, the proposed approach utilizes risk matrix data for project managers to be able to adopt this approach in practice. The proposed process can be used by practitioners while developing uncertainty management strategies, preparing risk management plans and formulating their contract strategy.

Background Characterizing the complexity of environmental exposures in relation to human health is critical to advancing our understanding of health and disease throughout the life span. Extant cohort studies open the door for such investigations more rapidly and inexpensively than launching new cohort studies and the Human Health Exposure Analysis Resource (HHEAR) provides a resource for implementing life-stage exposure studies within existing study populations. Primary challenges to incorporation of environmental exposure assessment in health studies include: (1) lack of widespread knowledge of biospecimen and environmental sampling and storage requirements for environmental exposure assessment among investigators; (2) lack of availability of and access to laboratories capable of analyzing multiple environmental exposures throughout the life-course; and (3) studies lacking sufficient power to assess associations across life-stages. HHEAR includes a consortium of researchers with expertise in laboratory analyses, statistics and logistics to overcome these limitations and enable inclusion of exposomics in human health studies. Objective This manuscript describes the structure and strengths of implementing the harmonized HHEAR resource model, and our approaches to addressing challenges. We describe how HHEAR incorporates analyses of biospecimens and environmental samples and human health studies across the life span - serving as a model for incorporating environmental exposures into national and international research. We also present program successes to date. Discussion HHEAR provides a full-service laboratory and data analysis exposure assessment resource, linking scientific, life span, and toxicological consultation with both laboratory and data analysis expertise. HHEAR services are provided without cost but require NIH, NCI, NHLBI, or ECHO funding of the original cohort; internal HHEAR scientific review and approval of a brief application; and adherence to data sharing and publication policies. We describe the benefits of HHEAR's structure, collaborative framework and coordination across project investigators, analytical laboratories, biostatisticians and bioinformatics specialists; quality assurance/quality control (QA/QC) including integrated sample management; and tools that have been developed to support the research (exposure information pages, ontology, new analytical methods, common QA/QC approach across laboratories, etc.). This foundation supports HHEAR's inclusion of new laboratory and statistical analysis methods and studies that are enhanced by including targeted analysis of specific exposures and untargeted analysis of chemicals associated with phenotypic endpoints in biological and environmental samples. Conclusion HHEAR is an interdisciplinary team of toxicologists, epidemiologists, laboratory scientists, and data scientists across multiple institutions to address broad and complex questions that benefit from integrated laboratory and data analyses. HHEAR's processes, features, and tools include all life stages and analysis of biospecimens and environmental samples. They are available to the wider scientific community to augment studies by adding state of the art environmental analyses to be linked to human health outcomes.

The fourth industrial revolution has affected most industries, including construction and those within the delivery chain of megaprojects. These major paradigm shifts, however, did not considerably improve the track record in predicting project outcomes and estimating required resources. One reason is the lack of unified data definitions and expandable knowledge representation across project lifecycle to represent megaprojects for analytics. This paper proposes and evaluates a unified ontology for project knowledge representation that facilitates data collection, processing, and utilization for industrial megaprojects through their lifecycle. The proposed Uniform Project Ontology, or UPonto, provides a data infrastructure for project analytics by enabling logical deductions and inferences, and flexible expansion and partitioning of the data utilizing linked data and the semantic web. The ontology facilitates cost normalization processes, temporal queries, and graph queries using SPARQL, while defining universal semantics for a wide range of project risk factors and characteristics based on comprehensive research of the empirical project risk and success literature augmented by practical considerations gained through expert consultations. UPonto forms the basis for a project knowledge graph to utilize unstructured data; it as well provides semantic definitions for smart IoT agents to consume project risk data and knowledge.

Managing business relationships successfully is critical for many professional service firms (PSFs) in order to be able to address complex client needs. Furthermore, the projectbased nature of PSFs’ work puts pressure on them to retain clients across project periods. Drawing on both net effect and configurational perspectives, this study provides a holistic understanding of the relative importance, and of the interplay of social and economic determinants of business relationship performance in the context of dynamic relationships between PSFs and their clients. Using data from 297 business clients, the results reveal that, overall, social determinants are more important than economic determinants as drivers of the client’s willingness to cooperate with a PSF in future. The importance of social determinants increases further in later relationship lifetime phases. The configurational analysis also reveals several equifinal constellations of social and economic determinants across the lifetime phases to drive a client’s willingness to cooperate in future. Therefore, no single determinant by itself is sufficient for ensuring relationship performance. We advance the literature by showing that distinct constellations of social and economic determinants are required to achieve the desired outcome, and that these constellations change across business relationship lifetime phases.

Engineering and construction (E&C) infrastructure projects are unique, complex and have historical trends of cost–time overruns and lapses in coping with the increasing challenges and opportunities. E&C projects neither have one single right way to organise nor resolve the challenges. Technology, though not always matured, is now more easily available. This chapter focuses on people issues and contributes a strategic project management leadership (SPML) framework with learning/experiencing facilities for leadership capacity development and integration across project management (PM) levels for transformational change. With organisational support, over time, the SPML is expected to advance innovative leadership capacities of the individuals, infrastructure PM, and the organisation to reduce cost–time overruns and to cope with the challenges and opportunities for sustainability.

This paper outlines a logical prototype for a websocket-dependent, collaborative, online coding platform. It aims to improve seamless code updation, sharing, and collaborating for small to medium development projects—the lack of which leads to massive coding redundancy due to multiple members working on the same project. The paper lists out the foundational features, along with the technologies that can be utilized to realize the objective of creating a platform that allows easier team-based coding. The final proposed platform will allow developers to create and share compiled code across project members without the need of an execution environment, URL sharing or version control, and will implement code-focused ideas like real-time collaboration, multiple code support, online compilation, and administrator room system. It proposes the use of newer, emerging technologies, and stacks like websockets and real-time databases, while also explaining the reason behind the use of these technologies.

Greater emphasis is now being placed on User Involvement as a factor imperative to Success in Project Scope Management. Although Project Scope Management Processes have a tendency to centre on various factors pertaining to the collecting criteria, defining scope and verifying scope, controlling scope is viewed as being fundamental to the management process as a whole. Furthermore, Success in Project Scope Management in the modern-day competitive business setting is recognised as resting on efficient and effective processes applied across Project Scope Management. One essential factor in achieving success in this arena is that of User Involvement. In this regard, the point is presented that Project Scope Management and User Involvement may be implemented in such a way so as to enhance Successful Project Scope Management. A questionnaire-centred survey approach utilizing Project Scope Management Processes and User Involvement to Successful Project Scope Management, encompassing management- and strategy-level employees, totalling 295, was applied in order to establish the link, both indirect and direct, between particular elements influencing four different IT departments at the governmental level. The data gathered underwent analysis through the use of SPLS (Smart Partial Least Square). This work provides a valuable contribution for professionals in the field, both in terms of researchers and practitioners, and further highlights the different ways in which project managers can arrange and modify Project Scope Management Processes in pursuit of their efforts to enhance the mediation of Successful Project Scope Management through User Involvement.

Building Tnformation Modeling (BTM) is known as a tool for collaboration among construction organisations in generating and managing data across the construction lifecycle. Despite from the advantages of engaged from BTM (i.e; reduce the number of clashes within the construction process, improve the building visualization, and shorten the planning period), most of the contractor’s organisations are still hesitant to deploy the technology. The aim of this paper is to comprehend the challenges in adopting BTM across project phases. A semi-structured interview was conducted through eight respondents from contractor’s organisations which adopt BTM. The interview data were recorded and analysed using ATLAS.ti software. As a result, the finding demonstrated eight (8) substantial challenges in adopting BTM including staff resistance, selection of software and hardware, lack of knowledge an information of BTM, lack of data of return on investment of BTM, implementation cost and benefits, lack of demands from the clients, lack of supply chain buy-in, and lack of standards-policy makers. Meanwhile, another ten (10) challenges for instance training and education, culture change, ownership and intellectual property, contractual agreement, authenticity, product liabilities risks, legal uncertainties and affection to the business environment are remarked as least challenges revealed by the participants. Tn spite, two (2) additional challenges which are not mentioned by the previous researchers were disclosed by the participants which are trustworthiness and organisation’s politic. On this balance, all the challenges grouped into six major elements; people, software and hardware, cost, product, standard, and others. Thus, it is expected that the finding shall bring significant and knowledge for the construction practices to understand the challenges in adopting BTM across construction projects.

One of the reasons for using personas is to align user understandings across project teams and sites. As part of a larger persona study, at Al Jazeera English (AJE), we conducted 16 qualitative interviews with media producers, the end users of persona descriptions. We asked the participants about their understanding of a typical AJE media consumer, and the variety of answers shows that the understandings are not aligned and are built on a mix of own experiences, own self, assumptions, and data given by the company. The answers are sometimes aligned with the data-driven personas and sometimes not. The end users are divided in two groups: news producers who have little interest in having data-based insights of news consumers and producers for social media platforms who have more interest in this information. One of the reasons for using personas is to align user understandings across project teams and sites. As part of a larger persona study, at Al Jazeera English (AJE), we conducted 16 qualitative interviews with media producers, the end users of persona descriptions. We asked the participants about their understanding of a typical AJE media consumer, and the variety of answers shows that the understandings are not aligned and are built on a mix of own experiences, own self, assumptions, and data given by the company. The answers are sometimes aligned with the data-driven personas and sometimes not. The end users are divided in two groups: news producers who have little interest in having data-based insights of news consumers and producers for social media platforms who have more interest in this information.

In recent years the expected standard for facial animation and character performance in AAA video games has dramatically increased. The use of photogrammetric capture techniques for actor-likeness acquisition, coupled with video-based facial capture and solving methods, has improved quality across the industry. However, due to variability across project pipelines, increased per-project scope for performance capture, and a reliance on external vendors, it is often challenging to maintain visual consistency from project to project, and even from character to character within a single project. Given these factors, we identified the need for a unified, robust, and scalable pipeline for actor likeness acquisition, character art, performance capture, and character animation.

This report discusses regression models to analyse planned and actual expenditure data from projects in an Australian Defence capital investment program. Variations in expenditure from that planned have the potential to create cash flow problems in Defence. Therefore, an understanding of the relationship between planned and actual expenditure will improve project planning and portfolio financial management. It is also useful to understand if families of projects behave differently to each other because differences may indicate varying management practices across project domains or differences in the nature of project families. The regression model accommodates project time and military domain effects, heteroscedasticity, repeated measures and nonlinear relations between planned and actual annual project expenditure. The nonlinear model is linearized into an additive lognormal model and fitted via a linear mixed models methodology that facilitates modelling the within project covariance structure. Generally, projects underspend against the plan early in their life and overspend in later years. For each year, there are significant differences in expenditure rates between domains, but the expenditure rate does not depend on planned expenditure. The model may be used by project and portfolio planners to test likely spending variations from plan and to then adjust expenditure plans accordingly; it, therefore, provides a tool to measure project and financial risk.

Over the last decade, a globalization of the software industry took place, which facilitated the sharing and reuse of code across existing project boundaries. At the same time, such global reuse also introduces new challenges to the software engineering community, with not only components but also their problems and vulnerabilities being now shared. For example, vulnerabilities found in APIs no longer affect only individual projects but instead might spread across projects and even global software ecosystem borders. Tracing these vulnerabilities at a global scale becomes an inherently difficult task since many of the existing resources required for such analysis still rely on proprietary knowledge representation. In this research, we introduce an ontology-based knowledge modeling approach that can eliminate such information silos. More specifically, we focus on linking security knowledge with other software knowledge to improve traceability and trust in software products (APIs). Our approach takes advantage of the Semantic Web and its reasoning services, to trace and assess the impact of security vulnerabilities across project boundaries. We present a case study, to illustrate the applicability and flexibility of our ontological modeling approach by tracing vulnerabilities across project and resource boundaries.

Implementation of knowledge sharing frameworks within project-based organisations often fails due to numerous challenges and obstacles. This study focuses on identifying the challenges and solutions of knowledge sharing within project life cycle. Particularly, this research investigates the challenges and solutions of knowledge sharing via a single case study conducted in an Iranian consulting engineers firm. By doing so, we designed a questionnaire in developing the concept of knowledge sharing and moving toward a more comprehensive knowledge sharing framework based on systemic literature review. The analysis of the case study assisted us to develop a conceptual framework to overcome the identified obstacles and challenges of knowledge sharing. This study also aims to provide a practical framework to assist knowledge management professionals in successful implementation of knowledge sharing initiatives within project-based organisations.

The European ARTEMIS ACROSS project aims to overcome the limitations of existing Multi-Processor Systems-on-a-Chip (MPSoC) architectures with respect to safety-critical applications. MPSoCs have a tremendous potential in the domain of embedded systems considering their enormous computational capacity and energy efficiency. However, the currently existing MPSoC architectures have significant limitations with respect to safety-critical applications. These limitations include difficulties in the certification process due to the high complexity of MPSoCs, the lacking temporal determinism and problems related to error propagation between subsystems. These limitations become even more severe, when subsystems of different criticality levels have to be integrated on the same computational platform. Examples of such mixed-criticality integration are found in the avionics and automotive industry with their desire to integrate safety-critical, mission critical and non-critical subsystems on the same platform in order to minimize size, weight, power and cost. The main objective of ACROSS is to develop a new generation of multi-core processors designed specially for safety-critical embedded systems; the ACROSS MPSoC. In this paper we will show how the ACROSS MPSoC overcomes the limitations of existing MPSoC architectures in order to make the multi-core technology available to the safety-critical domain. The proposed approach enables efficient certification, complexity management, mixed-criticality integration and the development of temporally deterministic hard real-time systems. The major technological innovations of ACROSS are an increased level of design abstraction, message-based interfaces for core-to-core communication and reliable fault and error containment established by a novel time-triggered network-on-chip. The achieved results comprise, a novel architecture for MPSoCs, a prototype implemenation on FPGA technology as a proof-of-concept, a comprehensive set of middle-ware services and multiple demonstrators that show the benefits of the ACROSS Architecture in real world industrial applications.

Adaptation projects may be difficult to prioritize and finance, as the results of projects are difficult to quantifiably measure and compare across project types, and no singular “unit” for adaptation outcomes exists. The Higher Ground Foundation is developing the Vulnerability Reduction Credit (VRC™), which incorporates cost/benefit analysis and per capita vulnerability equalization tools to measure the outputs of climate adaptation projects. The VRC quantifies in a singular unit measures to reduce vulnerability to climate change. This chapter summarizes the structure and utility of VRCs and shows through a case study from Talle, Niger, how VRCs are created and integrated into Sahelian community adaptations to heterogeneous climate risks such as flooding and droughts. VRC analysis and crediting may serve as a monitoring and evaluation tool and as an instrument to help secure project finance while supporting sustained adaptation. The chapter further considers the potential benefits to governments, donors and economies. VRC financing has advantages over standard development assistance models, particularly for project risk management, project preparation, enhanced transparency of adaptation spend, and scaling of successful pilot projects throughout an economy.

Integration aims to bridge disciplines and bring together knowledge that is fragmented across these disciplines. However, practical integration in Natural Resource Management (NRM) remains out-paced by the increasing pressures on natural resources. Research must become more effective at producing tools appropriate for NRM praxis (IAASTD 2009).Quantitative integrated modelling (IM) offers NRM the precision of mathematical formalism for rigorously evaluating hypotheses, testing concepts and comparing management options. To support IM, software tools have made great leaps in recent years. On the other hand, the knowledge of how to apply this "cyber infrastructure" remains mostly tacit and no adequate guidelines are available to support project managers in choosing cyber infrastructure that is appropriate for a specific project.The objective of this paper is to define a framework and a benchmark against which the efficiency of integrated modelling for natural resource management (IM-NRM) processes can be evaluated. First, the IM challenge is characterized by defining complexity, knowledge requirements and, using concepts from organizational theory, three strategies of knowledge acquisition. These include individual learning, collaboration within staff and cooperation with third parties. Next, the three strategies are used to categorize the organizational challenge of IM-NRM with five metaphors. Cyber infrastructure plays a pivotal and distinct role in each metaphor by sharing knowledge across project members. One of these metaphors, the "Modelling Playground," is defined as an optimal combination of the three strategies.Finally, this perspective is used to describe two NRM projects, one from academia and one from a governmental program. Both case studies have undergone significant changes in organizational structure and in knowledge acquisition strategies. The initial choice of cyber infrastructure proved insufficient for these changes and resulted in significant adjustment costs.In conclusion, it is suggested that guidelines for cyber infrastructure used in NRM, which take into consideration the aspired goals, the constraining organizational context and incentive structures, are crucial to improve the effectiveness of NRM. It is also suggested that lesson learning be based on the framework of organizational theory, as well as an action-based approach, to create a test Modelling Playground as a learning hub.

Project management value has moved from ideas of 'value management' to ideas of 'understanding how stakeholders value different things'. In line with this new paradigm, value in megaprojects is influenced by the complex morass of stakeholders involved. This paper explores how stakeholders engage with the megaproject delivery process and value creation. From extant literature, the author reviews the definition of megaprojects and discusses their characteristics. Value and stakeholder value was also discussed. It was proposed that internal stakeholders are concerned with the value from 'project management deployment' while external stakeholders are primarily concerned with the 'value from project outcome'. Using a framework, the relationship between external stakeholders and value from project outcome was argued for. Internal stakeholders and the relationship with value from project management deployment were also argued for. Hence, a Value framework that can be used to determine what value needs to be generated for internal and external stakeholders is proposed. Future research is discussed including the need to further develop this value framework to identify different internal and external stakeholder value across project life cycle and product life cycle. DOI 10.5592/otmcj.2012.3.5 Research Paper

Application of indicator-based management tools to evaluate performance and taking measures to mitigate the negative effects on project performance contributes to improvement. This research paper presents the findings of the analysis of performance of public funded smallholder irrigation projects in Tanzania with the aim to inform improvement actions. Through opinion survey of a sample of policy or decision makers and implementers of projects, and a case study of 16 smallholder irrigation projects, conceptual and physical data were collected and analyzed. The findings show that performance assessment in irrigation sub-sector in Tanzania is ad hoc, fragmented and done mainly during the construction phase, in donor funded projects. Seventy percent of 20 highly ranking performance indicators considered suitable in Tanzania also have high potential to improve project performance in the Tanzanian irrigation industry. These indicators constitute the key performance determinants. Forty percent of performance indicators currently used in Tanzania, which include the traditional time and cost indicators, are considered not significant in improving performance. Time and cost overrun of 16 investigated projects was in the tune of 50% and 8% respectively. The factors affecting project performance are diverse but interrelated, with possible common root causes, and effects cutting across various project processes. The mitigation measures are also interrelated and cut across project processes, and therefore, require integrative approaches.

In 2007, the low level of young adults with developmental disabilities who were employed in the 3 months postgraduation from high school led the Washington State legislature to authorize and fund the Jobs by 21 Partnership Project. The intent of the project was to identify and demonstrate best practices in sustainable partnerships among Washington State's school and adult service systems. Results indicated that participants in the project were more likely to be employed following school exit and had stronger employment outcomes than students who did not participate. Further, data suggest that improved employment outcomes were supported by the leveraging and maximization of financial and in-kind resources and the strengthening of collaborative relationships across project stakeholders.

A team at the University of Minnesota conducted the Collaboratives for Excellence in Teacher Preparation (CETP) core evaluation between 1999 and 2004. The purpose of the CETP core evaluation was to achieve consensus among CETP project leaders and project evaluators on evaluation questions; to develop, pilot, and field test evaluation instruments tied to the questions; and to collect data to document the accomplishments of the CETP projects. This chapter examines the relationship between project-level involvement in the CETP core evaluation and the use of the evaluation by project principal investigators (PIs) and evaluators. The chapter examines the tensions and trade-offs that arose from attempting to balance voluntary involvement by project PIs and evaluators in the planning and development of the evaluation with the need to collect complete and comparable data across project sites. © Wiley Periodicals Inc., and the American Evaluation Association.

Knowledge sharing is indispensable for business organisations. The construction industry is one of the sectors in which intensive knowledge is spread across project-based teams. This study sheds light on which method is better for knowledge sharing within construction organisations: technology-based or face-to-face meetings. This research aims to understand organisational knowledge sharing by identifying and exploring the motivations and consequences of using face-to-face interaction vs. technology-based communication in project-based teams. This was undertaken through a qualitative case study with 15 employees of a large construction organisation. A qualitative analysis revealed four main factors related to worth adding a technology-based to face-to-face communication: the use of multiple communication strategies for knowledge sharing, whether sharing of all information via technology is allowed, legal restrictions, and limits on face-to-face communication due to work pressures. These findings contribute to the existing literature by identifying barriers and preferences regarding tools for sharing knowledge in a construction firm.

Understanding links from new highway construction or capacity expansion to regional growth patterns is crucial for transportation planners and policy makers. In this paper, we incorporate a lagged adjustment regional growth model into a quasi-experimental research design to examine the association between new highway investments and land use change in three California counties. Our study areas provide a mix of urban, small town, and exurban highway projects in order to explore the different effects across project types and geographic contexts. The central finding of this research is that while improvements in surface transportation infrastructure can have large impacts on growth patterns, the nature of the effect depends on the context of the highway investment.

This paper examines the impact of internal competition that occurs when new technology challenges the technology in a firm's existing products. New-technology development projects are traditionally judged by market success—and most fail. If we examine their impact on existing-technology product development, a different interpretation arises. Drawing on the literature on the influence of social factors on interfirm search and adoption of new technologies, this study argues that similar processes occur intrafirm. Evidence from a field study on new-technology product development in high-technology firms shows that internal competition influences existing-technology product development groups to integrate the new technology into the next generation of their own products. The reason is twofold. First, these groups shift their search toward the new technology and allocate resources to gain a deeper understanding of it. Second, access to internal information and the mobility of workers across project boundaries benefit the existing-technology groups. The findings provide a model of innovation that illustrates an endogenous process of internal competition. This often political and contentious process can have a strong influence on technology adoption and integration.

The clean development mechanism (CDM) contributes to technology transfer by financing emission reduction projects using technologies not available in the host countries. This paper provides the most comprehensive analysis of technology transfer in the CDM to-date, covering 3296 registered and proposed projects. Roughly 36% of the projects accounting for 59% of the annual emission reductions claim to involve technology transfer. Technology transfer is more common for larger projects and projects with foreign participants. Technology transfer is very heterogeneous across project types and usually involves both knowledge and equipment. As the number of projects increases, technology transfer occurs beyond the individual projects. This is observed for several of the most common project types in China and Brazil with the result that the rate of technology transfer for new projects in those countries has fallen significantly.

Researchers have examined building information modeling (BIM), or parametric three-dimensional computer-aided design, from a myriad of technological perspectives. Many of these studies focus on examining or enhancing the interoperability of building information modeling technologies across project networks. The interoperability of business practices that must complement technological interoperability has been largely ignored. In this paper we examine building information modeling practice paradigms in project networks. We combine qualitative and quantitative data and analytical approaches to investigate 26 specific cases of firms using BIM tools. We identify four distinct practice paradigms and then induce an evolutionary model for building information modeling practice paradigm trajectories in project networks. The findings highlight the importance of understanding and developing interorganizational work practices to reap the benefits of building information modeling.

Project success is a complex and often illusory construct. Nonetheless, it is crucially contingent towards enabling appropriate and effective allocation of resources in project management practice. Mass house building projects (MHBPs) represent one of the largest and most established project-based sectors of the construction industry in most developing economies. Above all, the management skills required on these projects differ significantly from the one-off projects often encountered in the construction industry. While some success criteria may be common across project types, there is no denying the fact that some determinants of success are likely to be unique to projects of specific characteristics. This research sets out to address what constitutes the determinants of success in MHBPs. A questionnaire survey is used to establish property developers’ perception of critical success criteria in MHBPs in Ghana. Data analysis (involving one-sample t-test) reveals some interesting findings in regard to how property developers perceive the importance of the project success criteria. Factors analysis reveals four underlying clusters named in order of their significance as environmental-impact, customer satisfaction, quality and cost and time. This systematic approach towards understanding the taxonomy of the success dimension in MHBPs is important for re-enforcing effective project management practices in this significant sector of the construction industry.

The outsourcing of complex activities has become a common organizational practice. Yet very little research has focused on the implications of how these activities are divided up among outsourcing partners. Drawing on structural contingency theory, we argue that: (1) because activities within stages of complex projects are highly interdependent, outsourcing structures where owner firms do not maintain high levels of dominance over the activities that are performed will pose control and coordination challenges, leading to poor project performance; (2) the adverse effects of poorly structured outsourcing arrangements will spill over to subsequent project stages when activities are interdependent across project stages; and (3) dividing activities among large numbers of contractors or distributing work evenly among contractors exacerbates coordination and control problems further contributing to poor project performance. Our empirical analysis of 323 capital facility construction projects supports our predictions. Overall, these results provide strong evidence that some outsourcing structures are more costly than others and that because of the nature of complex projects the detrimental effects of poorly structured outsourcing are often not completely observable at the time activities are completed. We discuss the implications of our findings for capital construction and for outsourcing more generally.

Modularization involves breaking up a system into discrete chunks, which communicate with each other through standardized interfaces, rules, and specifications. It is a broad concept with various interpretations and meanings across research disciplines. The complexity and scope of a module is not captured sufficiently and clearly in the construction management and engineering literature, and the impact of modularization across project phases has not been fully explored and articulated. Therefore, the main question addressed in this paper relates to the inherent meaning of what is a module in the context of different phases of a building project. In addressing this question, this paper empirically investigates the use of modularity in 15 construction projects situated in Italy, Germany, Brazil, and the United Kingdom. The findings of this research suggest that a design-based and an operations-based perspective of modularity coexist, and that there is the need for an integrated view of modularity ac...

I examine cost forecasts for 49 fiber-optic and wireless networks funded by the Recovery Act. I find that grantees did not systematically underbid for projects. They did, however, underestimate and overestimate costs with nearly equal frequency, and escalate costs on average by 202 percent in cost per institution and 37 percent in cost per fiber mile. For four outputs, I ask whether cost forecasts predicted actual construction. I find that grantees overestimated fiber miles and indirectly connected institutions, while meeting targets for directly connected institutions and points of interconnection. I do not find budget, technology, or institution effects to explain the quality of cost forecasts in these outputs. My findings suggest that low-price bids can be cost-effective across project types. With data from the applicant pool, I compare offers from 116 projects with 657 rejected proposals.

This paper contributes to boundaryless career research by focusing on how past diversity in the career patterns acquired across prior project-based industries and within the same project-based industry may influence current project performance. This study examines the “knowing how” elements accumulated in the past by team members across and within project-based industries as career-related measures of diversity. To address this issue, this paper analyzes the creative context of Italian TV drama series production teams by investigating the career patterns of 1736 actors who worked in this industry from 1996 to 2010. To quantify the differences between career patterns, optimal matching analysis is used. This study finds an inverted U-shaped relationship between past career diversity accumulated across project-based industries and current project-performance; the study finds further that past career diversity achieved within the same project-based industry negatively moderates the inverted U-shaped relationship between past career diversity accumulated across project-based industries and current project-performance. These findings are consistent with the idea that the two patterns of career achievement – across project-based industries and within the same project-based industry – are not complementary but rather serve as imperfect substitutes.

PurposeThe goal of this paper is to discuss critical success factors (CSF) for implementing enterprise portals by comparing them with CSF for ERP implementations.Design/methodology/approachIn order to identify and rank CSF for portal implementations, the paper followed a multi‐method design, following a two‐stage approach with the first stage analyzing the state‐of‐the‐art of portal implementation by interviewing portal integrators in Germany and a follow‐up stage with a focus on CSF, thereby identifying and analyzing the CSF for portal (implementation) projects in general and across project stages. Then the findings are compared with the results of a similar study on CSF in ERP (implementation) projects.FindingsWhen comparing CSF for portal projects with CSF of ERP projects, some similarities were found but also some differences with respect to top management support, project management, communication, selection of the software package and business process re‐engineering.Research limitations/implicationsThere are limitations with regard to the comparability of both studies as both studies used different samples.Practical implicationsBased on these findings, measures to improve the engineering and management of portals can be proposed and developed.Originality/valueUp to now, there are neither detailed studies focusing on the identification and evaluation of CSF for portal projects nor studies that try to compare portal and ERP projects. The paper tries to fill this gap.

Building Information Modeling (BIM) is a systematic process used to model information involving the use of computer-generated (n-dimensional) software to simulate the planning, design, construction, and operation of a building. Currently, BIM technology is an important approach used by most project clients (public and private) to boost project effectiveness in terms of time, cost and quality of construction projects to meet client demand. However, previous studies showed that BIM-based project implementation in Malaysia faces greater challenges due to project attributes that causes low demand of project clients to adopt BIM. Hence, the purpose of the paper is to investigate the impact of project attributes towards client demand by adopting BIM across project life cycle. A crosssectional survey was conducted in Malaysia among the three project stakeholders: the public sector, private sector, and contractors using BIM for their projects. Seven (7) significant project attributes (i.e., feasibility, definition, duration, project location, objectives, size and type) and three (3) triangle of client demand (i.e., time; cost; quality) were subjected to Parametric Pearson Correlation. The results showed that there exist a significant relationship between the project attributes and client demand. The results suggest that project clients (public and private) should take a consideration of project attributes in fulfilling the client demand at the early stage of project commencement to maximize the BIM benefits to other stages of construction.