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Carefully considering the Capability Maturity Model Integration (CMMI) Level 2 specific practice to “define project life cycle phases” (SP 1.3) is a key requirement, particularly when it comes to small and medium-sized software development organizations. This is a necessary step to help these organizations get nearer to achieving CMMI Level 2 certification. In this paper, we, therefore, report on our latest empirical study that recently explored both the perceptions and experiences of practitioners about SP 1.3 implementation. During our research, we visited three firms and carried out three in-depth interviews. We developed a SP 1.3 model using the different experiences and opinions of practitioners regarding SP 1.3 implementation. The four essential stages of this model are plan, design, review, and update/rework. Practitioners will receive advice in this model about implementing SP 1.3 effectively.

In many cases, some programs often have some milestone activities that decision makers need to pay attention to. In this case, managers must efficiently describe these different decision-making spaces and use this as a basis to optimize possible solutions. Choosing a suitable decision-making space has always been a major factor in decision-making management, and it is also one of the key factors that managers must determine when making plans. Multi-objective optimization is to optimize multiple objectives at the same time. Multi-objective optimization algorithms have been widely used in many technology industries. This article researched from two parts: model display and optimization algorithm. The first is to deepen the basic characteristics of project planning and decision-making when there are more decision-making spaces. Based on the existing decision-making network planning methods, combined with the situation analysis method, a decision-making network planning model that can show more decision-making space is established. Secondly, based on the actual improvement requirements, the multi-objective optimization method in the multi-decision network design model and the simulation model of activity exercise data are established. The purpose is to create a relatively complete project planning decision model and optimization algorithm that can select multiple decision spaces at the same time through the above experimental research.

There is growing interest in the ways that value is understood in the context of projects and within project-based settings. Recent studies emphasise the multiplicity of project value in various project settings as perceived by different project actors. Drawing on previous work on project value and project front-end, this study expands on the idea of multiplicity of project value in the early project definition phase. To this end, the study draws from empirical data on infrastructure projects provision, including semi-structured interviews with a set of highly experienced and senior level informants with extensive knowledge and familiarity of infrastructure project planning and front-end decision making. The study is bounded with a focus on London, UK as an example of a complex, highly established global city with a great reliance on its infrastructure and a well-established projects ecology. Through inductive qualitative data analysis the study explores the role of infrastructure projects as solutions to policy problems, the multiple and complex nature of value in project definition and identifies three value levels, which are instrumental for project definition: local value, sector value and user value. The multi-level value framework in the project front-end extends and complements early decision making in planning and setting up of infrastructure projects.

Time and cost estimations of project activities are challenging tasks for project managers and planners. As a result of the high level of risk and uncertainty present during the early stages of projects, the reliability of these estimations during project planning remains poor. This study argues that this reliability can be improved through using the ‘concept of stratification’. This concept considers a set of states and describes a system that receives inputs (associated with outputs), based on which the system transitions from one state to another. This provides a unique structure that is capable of considering uncertainty related to events that may occur during a project. This paper explains how the concept of stratification can be used to compute estimations of the time and cost of activities involved in a project. The method is illustrated with a construction project that has uncertain events. By determining specific activities’ estimated time and cost, the project's estimated time and cost can also be calculated. Thus, the proposed method increases the reliability of estimations of projects’ completion time and cost.

In project planning, traditionally, the project managers first schedule the project activities, and then plan for materials ordering and supplier selection. This disintegrated approach lacks in planning co-ordination and causes a loss in expected profit for the organization. In this study, a concurrent model is proposed for resource constraint project scheduling with materials ordering and suppliers selection problems. The proposed model aims to maximize overall net present value for the organization considering ordering cost, procurement cost, materials holding cost, and the project’s deadline penalty cost. The resource constraint project scheduling with materials ordering and suppliers selection is an NP-hard problem. Thus, a memetic algorithm hybridizing the genetic algorithm with a forward-backward improvement based local search is proposed to solve the proposed model. The proposed algorithm is tested on self-generated 120 instances varied from 30 to 60 activity projects with 4 to 8 suppliers. Experimental results show that the proposed genetic algorithm-based memetic algorithm approach generates better solutions than the standalone genetic algorithm. The concurrent project scheduling with materials ordering and supplier selection approach and solution methods have a significant implication for the managers to complete the project in an economic and timely manner.

In the research or project planning for the decommissioning of a nuclear power plant, one of several preparations will be the establishment of a list of potential radionuclides to be considered at the time of characterization or final status surveys. Reliable data for selection of potential radionuclides during the transition period to prepare for decommissioning will depend heavily on historical data at the site or, where possible, sampling analysis. However, during the transition period, direct sampling can be challenging, depending on the circumstances of the site or national regulation. A methodology of selecting potential radionuclides for nuclear facility sites which largely consists of three major processes: production of initial list of radionuclides, selection of the insignificant radionuclide that will be eliminated, and consideration of site characterization or sampling. For developing a preliminary list of potential radionuclides for Kori Unit 1 decommissioning, the list of initial radionuclides was made referring to the technical documents applied at decommissioned NPPs in the U.S and additional reference materials applied until the operation of NPPs in Korea. For the screening of insignificant radionuclides, we applied criterion of less than 0.1% of the amount of radioactivity inventory and confirmed the dose fraction using the RESRAD code. The final suit of radionuclides was established, which should be supplemented by reflecting site characterization and sampling process in the future. Thus, the methodology and results for the selection of potential radionuclides suggested in this paper can give an insight as a future reference to deriving DCGLs in relation to site remediation of decommissioning nuclear plants.

This paper develops and compares four multidimensional resource allocation models aimed to prioritize freight improvement projects for regional, state, and local transportation agencies such that return on investment is maximized. The proposed models are based on economic competitiveness with and without mutual exclusiveness in location, and equity in opportunity and outcome. Multiple dimensions of the models include the transportation mode, performance measures, improvement type, geographic regions, policy criteria, and time. Results from a case study in the State of Tennessee show that project selection based on equity in outcome provides the optimal balance between benefits and their distribution among counties, while project selection based on equity in opportunity results in the lowest total return on investment.

Activity-based teaching-learning describes the range of pedagogical approaches that involve learning by doing hands-on experiments or activities. It encourages students to actively participate in the teaching-learning process through problem-solving or hands-on activities, also the group based activity instructions help students to develop soft skills. The engineering exploration course is an innovative course offered to the first-year curriculum in order to transfer the student’s ideas into real-life products through a number of activities such as problem-solving, engineering design process, multi-disciplinary engineering skills, project planning, communication, teamwork, ethics, and sustainability. The course includes multidisciplinary modules that fulfill the requirement of the product development process and each module is designed to teach through activity-based instructions. The aim of the engineering exploration course implementation is to develop multi-disciplinary product development skills in engineering students in the first year. All the sessions of the course delivery were well planned by considering the need statements of each project group so that students can acquire the necessary skills during activity sessions and apply those during product development. The student groups are formed heterogeneously with a maximum of four students in each group. The activity kit was designed for each session by considering team size so that all team members take active participation during various activities and develop their technical as well as soft skills. The initial result of implementation shows that students have developed excellent multidisciplinary products in the group and acquired technical knowledge as well as soft skills. The responses of the students show that 68% of the students rated this activity 10 out of 10, and also gave some suggestions for improvement as it is implemented first time. The students were very positive about this initiative and involved in each activity during the product development process. From the attainment of the course outcomes, it is observed that all five outcomes were attained more than the targeted value of 75%.

This paper deals an uncertain environment with effective integration of various planning elements and optimization of project parameters. Time, cost and quality are the most important parameters that are optimized to fulfil the planned production and productivity. Moreover, in uncertain environments, there exist a lot of other conflicting objectives that may also need to be optimized. The proposed model aims to maximize total profit from selected products, while sequencing scheduling the products with various resource constraints with specified time intervals. Linear Programming, Variable and Separable Programming, Mathematical Model and Genetic Algorithm (GA), multiple criteria decision making technique, offers a good solution for this project planning problem. Planning and controlling several processes data simultaneously means more than simply dealing with multiple schedules with machining time. It involves the integration of resources, schedules, budgets and stakeholder needs. Productivity optimization has been studied by a number of researchers in recent years. The tools and techniques to schedule multiple processes of product with multi-resource constraints are limited and are successful in solving only small problems. Value Stream Mapping (VSM) is a lean/quality management tool which assists in establishing the current state of a process while aiding to uncover opportunities for improvement of the seven sources of waste. Productivity, customer and job satisfaction improves 5 M’s. Zero quality control and eliminating wastes.

This study aims to identify the associations among performance criteria in the delivery of Green Building (GB) projects and their underlying conditions. The performance criteria included are social sustainability, economic sustainability, environmental sustainability, quality, schedule, and cost. A mixed methods approach is used, combining both qualitative and quantitative analysis. The findings from an online questionnaire survey (n = 104) are quantitatively and qualitatively analysed. Delphi method is used while conducting the survey. Semi-structured interviews (n = 30) are conducted to support, complement and help triangulate questionnaire survey findings and are also subjected to qualitative analysis. For GB projects, cost and schedule performance have a positive association among each other while cost performance has a positive effect on economic sustainability. Social, economic, and environmental sustainability have a mutually positive effect on each other. Beside the mutually positive associations among most criteria, in some cases negative and even no associations are also identified. Different conditions that affect the associations among performance criteria are identified including project planning, quality of project development process, life-cycle perspective, project management, Project Delivery Method (PDM), client's vision and motivation, regional constraints, regional climate, compliance requirements, and innovation. These underlying conditions affect performance across multiple criteria. The existing literature is used to verify the significance of these conditions for successful GB project development. This study has both theoretical and practical implications. In practice, project teams and decision-makers will be able to understand which conditions might result in a good performance in some criteria but underperformance in some other criteria. By controlling these conditions, across the project life-cycle, the desired performance on different criteria may be achieved. In theoretical terms, the identified associations and underlying conditions can lead to more holistic decision-making and multi-objective optimization models specifically designed for GB projects. The study is unique in its aim as well as the methodology used and the depth and breadth of the collected data. The study limitations include potential cognitive bias from the survey participants as well as a sole qualitative discussion of the effects of the key identified conditions on performance criteria associations.

In the past decade, many efforts have been devoted to exploring the Critical Success Factors (CSFs) for Green Building (GB) projects. However, there is absence of a systematic review exploring these studies. Therefore, the paper presents a comprehensive review of publications from 2005 to 2018 on CSFs for GB projects. The results indicate there is a growing interest in the exploration of CSFs for GB projects since 2010. The main contributing contributors, institutions, countries and areas, as well as research methods in this area are summarized. The mostly identified CSFs for GB projects are “communication and cooperation between project participants”, “effective project planning and control”, “owner's involvement and commitment”, “clear goals and objectives” and “project manager's performance”. The contractors and owners were found more related to these identified CSFs. Finally, knowledge gaps are discussed and future research directions including: (1) more studies on relationships between the CSFs; (2) extending studies to cover all building types; (3) more investigation on CSFs for different project objectives; (4) more emphasis on how to implement CSFs for GB projects are proposed. The results could offer a favorable reference for researchers to obtain a thorough picture of the current research woks and facilitate further study in this area. The discussion of GB CSFs could also broaden the understanding of the best ways for implementing GB projects to practitioners thereby reducing the setbacks towards its implementation.

The success of a business project often relies on the accuracy of its schedule. Inaccurate and overoptimistic schedules can lead to significant project failures. In this paper, we explore whether the presence of anchors, such as relatively uninformed suggestions or expectations of the duration of project tasks, play a role in the project estimating and planning process. Our laboratory experiment contributes to the methodology of investigating the robustness and persistence of the anchoring effect in the following ways: (1) we investigate the anchoring effect by comparing the behavior in low and high anchor treatments with a control treatment where no anchor is present; (2) we provide a more accurate measurement by incentivizing participants to provide their best duration estimates; (3) we test the persistence of the anchoring effect over a longer horizon; (4) we evaluate the anchoring effect also on retrospective estimates. We find strong anchoring effects and systematic estimation biases that do not vanish even after the task is repeatedly estimated and executed. In addition, we find that such persisting biases can be caused not only by externally provided anchors, but also by the planner's own initial estimate.

© 2019 Elsevier Ltd In this paper we introduce a method for potential use in strategic environmental assessment (SEA) which integrates knowledge and tools of Collective Intelligence, Complexity Theory and Geoprospective, via the implementation of a technological Group-Spatial Decision Support System (GSDSS), usable for scenario building for infrastructure project planning. It operates on the basis of interdisciplinary consensus of a multidisciplinary group of experts, without strict dependency on a spatial analysis based on a single cognitive stance, using existing historical data. The method is used in a study case on planning of onshore wind energy in Mexico, which has been developed through a collaborative Geoweb application, and is functioning in a distributed and asynchronous real-time way, so-called Geospatial System of Collective Intelligence (SIGIC). The significance of this research lies in demonstrating the feasibility of a collective intelligence analysis aimed at proposing spatial locations in an energy transition context within an SEA framework.

Researchers have suggested that residents’ acceptance of wind turbines follow a U-shaped curve over time, starting with generally positive attitudes about wind energy, dipping once a project is proposed, and then rebounding after construction. This research considers how residents’ perceptions of the benefits and negative impacts of wind turbines shift post-construction by surveying the same individuals (n = 520) at two time periods after a nearby wind project became operational. We find that residents’ perceptions follow two separate trajectories based on their perception of the fairness of the wind siting planning process and—to a lesser extent—whether they have a direct financial stake in the wind project. Residents who perceived a fair planning process tended to perceive greater benefits of wind turbines, job creation, and revenues for landowners specifically, while residents who perceived an unfair process perceived significantly greater negative impacts, including visual and noise problems, reduction of nearby property values, and human health problems. These results suggest that while energy business models that extent direct financial compensation to more landowners impact the attitudes of residents in the short-term, resident attitudes about procedural justice may have implications that extend well beyond the project planning stage, impacting long-term support for adding new and repowering old turbines.

The inclusion of sustainability factors in projects is considered a challenge for technicians, managers and decision makers. Sustainability projects deal with a large number of criteria from different areas, making the decision-making process more complex and uncertain. Multicriteria methods can guide project choices to reach their objectives; however, they are not able to manage the overlap and conflicting aspects of these objectives, called trade-offs. Trade-offs are considered to be an integral part of any sustainability project, since they address conflicting objectives, taking into account environmental, social and economic aspects. In some studies, trade-offs have been approached from the view of their formation process, or from how they can be identified in projects. However, there is a gap in the literature related to structured procedures to support decision-makers after the identification of trade-offs. Therefore, this paper proposes a tool to support trade-off management in the decision-making process in complex sustainability-focused projects. The Trade-Off Decision-Making tool assists the project planning stage, unfolding into two sequential phases: guidelines to be considered for the management of trade-offs; and trade-offs management operationalization. The guidelines were developed based on literature best practices, while the trade-offs management originated from the operationalization of five comparative analyses carried out between conflicting objectives, using a structured worksheet. The proposed tool contributes to the proper handling of conflicting objectives in sustainability projects not only in managerial but also operational areas. Our guidance structure for handling trade-offs provides greater robustness, objectivity and traceability to the choices made during the planning of sustainability projects.

CO2 Storage Readiness Levels are presented to communicate those storage site technical appraisal, Carbon Capture and Storage (CCS) project planning and permitting activities that have been completed, and what remains to be achieved for a CO2 storage site to become operational. The framework is based on the experience of site planning in the UK, The Netherlands and site operation in Norway and is applied to more than 700 sites. It extends and complements the industry commercial project development classification to encompass sites at lower levels of understanding, data availability and interpretation. Flexibility within the framework allows communication of the level of understanding of all prospective sites and enables comparison of sites in different permitting jurisdictions. Application of standardised levels informs the duration of permitting and resources invested to achieve contingent storage resource.

Carbon capture and storage (CCS) is a critical technology for ensuring a range of clean energy options are available to meet future energy demands. Offshore storage can be linked to large point-sources of carbon dioxide (CO2) while avoiding many of the logistical difficulties and potential risks encountered when siting onshore projects, especially in densely populated areas of the East Coast of the United States. Offshore storage along mid-Atlantic region was studied under the U.S. Department of Energy (DOE) funded Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project (MAOCSRAP) and as a subtask under the Midwest Regional Carbon Sequestration Partnership (MRCSP). The assessment was conducted as a technical collaboration between Battelle, Rutgers University, Lamont-Doherty Earth Observatory at Columbia University, state geological surveys of Delaware, Maryland and Pennsylvania, United States Geological Survey-Woods Hole Coastal and Marine Science Center, and Harvard University. Major objectives were to complete a systematic carbon storage resource assessment of the of the mid-Atlantic offshore coastal region from the Georges Bank Basin (GBB) through the Long Island Platform (LIP) to the southern Baltimore Canyon Trough (BCT), examine offshore storage risk factors, and engage industry and regulatory stakeholders through development of a Road Map to assist future project planning and implementation. Various publicly available data sets, such as seismic data, well-logs, and core data, were integrated to define geologic characteristics of candidate storage sites and calculate prospective CO2 storage resources for Cretaceous- and Jurassic-age sandstone sequences of the mid-Atlantic offshore sub-regions. The combined dataset helped to identify and map potential storage zones within sequences of the Logan Canyon, Missisauga, and Mohawk formations, as well as the regionally extensive caprock comprised of the Dawson Canyon shale. Prospective storage resource estimates and formation-specific storage efficiency values were calculated with static volumetric and dynamic methods. Regional-scale estimates range from 150 to 1136 gigatonnes (Gt) for the combined storage zones, with high estimated storage resource (≥ 2.4 megatonnes [Mt] CO2/km2) occurring in the northern BCT near the Great Stone Dome (GSD) structure. Results of local scale simplified dynamic reservoir simulation in the GSD indicate that injection rates of 1 Mt CO2/year may be sustained within the time and pressure constraints assumed for a commercial storage project. An initial, qualitative assessment of technical risk factors present in mid-Atlantic offshore areas was conducted. Overall, the mid-Atlantic offshore area benefits from the large spatial extent, thick sequences of sands, lack of previous oil and gas wellbores, and distance from populated development. Geomechanical stability, reservoir variability, and soft sediment deformation were identified as moderate risk factors in some areas. No highly critical risk factors were identified that would impede CO2 storage along the study areas. Input and participation from government, industry, and environmental groups helped to address next steps needed for future CCS project planning and implementation in the study region. Recommended near-term actions are to develop site screening through advanced geologic modeling, implement stakeholder outreach and risk mitigation strategies, identify industry and research goals, and develop regulatory pathways. Recommended mid-term actions are to validate subsurface properties with new data, conduct a cost-benefit analysis, and develop a monitoring, verification, and accounting (MVA) plan. Long term-recommended actions are to implement a plan for large-scale CCS operations using the previous findings, conduct site design, permitting, and construction, and upscale infrastructure. This project represents an important first step by completing a high-level CO2 storage resource assessment and building the knowledge infrastructure necessary to support the development of full-scale offshore carbon storage.

The paper focused on evaluation of stakeholder capacity to implement the millennium village primary school meal project in Kenya. The study which was anchored on the stakeholder theory as well as the Context Input Process Product (CIPP) model of evaluation used mixed methods research design with ex-post facto and case study as its two research elements. The mixed methods was adopted because when both qualitative and quantitative approaches are used in a single study, the strengths of both produce a research synergy in which the collective benefits are greater than what is obtained from either approach when used alone. A sample size of 186 participants was selected from seven (7) primary schools using stratified random sampling. The participants selected purposively included pupils, teachers, head teachers, parents, Area Education Officer (AEO) and project staff. Data was collected using questionnaires, face to face interview guide, Focus Group Discussion (FGD) and document analysis guide. The study findings indicated that the project was implemented with great success as indicated by stakeholders' capacity to understand project objectives, their involvement in project planning and implementation and their positive attitude towards the project. This has contribute to poverty reduction in the community through the project and sustainable approaches for project implementation.

In the traditional project planning approach, the manager first schedules the project activities and then plans the material ordering timetable accordingly. But in this approach, the tradeoff and association between the project implementation costs and ordering expenses are disregarded. This approach is also ill-suited for modern organizations that are under growing public pressure to support inter and intra generational justice and introduce environmental and social objectives to their competitive strategy and business mission. This paper provides an integrated framework for the Project Scheduling and Material Ordering (PSMO) problem with sustainability considerations. The proposed framework consists of two phases: (a) quantifying the environmental and social merits of the potential suppliers of the project resources, and (b) constructing and solving a mathematical model based on the acquired data. The model is able to determine the activities schedule, material ordering time and quantity, and the supplier selection that maximize the project NPV and the environmental and social benefits of its suppliers. The presented model falls within the class of NP-Hard problems, so two multi-objective metaheuristic algorithms, namely NSGA-II and MOPSO were modified to serve as solution methods for this model. For small problems, the performance of these methods was compared with that of second version of the augmented e-constraint (AUGMECON2) method, but for larger problems, where the exact method was unable to produce a solution within a reasonable time, these two algorithms were compared with each other. The results showed that regardless of problem size, NSGA-II outperforms MOPSO in the majority of evaluation metrics. The paper also includes a case study conducted on the trackbed construction project in Section 5 of Mianeh-Bostanabad-Tabriz railway in Iran, which demonstrates the applicability of the proposed model and provide an illustrative example of its implementation.

The growing trend to use agile methodologies in project management significantly affects the importance of the selection process of an appropriate management methodology for the project’s size and type. For many projects, hybrid methodologies that are a compromise between soft and hard approaches apply to project management. It is a pragmatic approach used by medium and large organizations, combining predictability and manageability of the traditional process, with high efficiency and flexibility of agile methodologies. To support the research and development process of these methodologies, the authors proposed the use of agent paradigm and the use of multi-agent systems. Its use is a consequence of adaptability of agents to simulate the work of project teams. To test its usefulness, a multi-agent AGOMO (AGent-Object Model) was built and used in the work of the team producing an IT system based on the interaction of agent behaviours and components of the agent system environment. Using this model, research experiments were carried out by evaluating the SCRUM and RUP software production process and the appropriate methods and tools for project planning.

The model of PGE – Product Generation Engineering describes the development of new technical products as follows: subsystems from one or more existing technical systems are the basis and starting point for every development. This is referred to as the “reference system”. It determines the structure and subsystems of a new product or serves as a basis for new development activities, respectively. Considering the role of the reference system, a new technical product is a new product generation. The development of each of its subsystems is one of three types of variation: carry over variation, embodiment variation and principle variation. The latter two are the share of new development. The iPeM – integrated Product engineering Model describes the development as a combination of activities, e.g. “detect ideas”, “verify and validate” or “built up prototype”. This contribution investigates the relation between the three types of variation and the activities of product engineering, by answering the following research questions: •Which activities of product engineering are necessary to implement the different variations in PGE? •Which factors influence this relationship between activities of product engineering and variations in PGE? Answers to these questions build up on interviews with eleven experts from development practice and two cases by authors of this contribution. The results show that the implementation of each variation in PGE includes several different activities of product engineering. Furthermore, this set of activities depends on the type of variation. Taking into account additional observations the idea of variations as company specific activity patterns is developed: each type of variation in PGE is related to a set of activities of product engineering where the characteristics of these relations depend on company-specific factors but can be similar across several development projects of this company. Hence, using those activity patterns process planning, including innovative potential, cost and risk estimation, is possible.

This research presents a novel computer-based system for the selection of mobile cranes in building construction. The proposed system integrates four main modules: an algorithm known as the analytical hierarchy process (AHP), the simple multi-attribute ranking technique (SMART), an experience-based algorithm, and a system database. The AHP module assesses the importance of the selection criteria, while SMART applies multi-attribute utility theory. The experience-based algorithm completes the calculations necessary for selecting the best and most technically appropriate crane alternative, and the database module hosts information about 37 different mobile cranes. The methodology followed to achieve the research objective consisted of three main phases. The first involved conducting a comprehensive literature review to identify selection criteria for mobile cranes, as well as a number of face-to-face interviews with experts to finalize the list of selection criteria considered. Face-to-face interviews were also conducted with local experts to obtain a framework for the current practice of crane selection and identify areas in need of improvement. Phase two involved using AHP for data collection in order to assess the importance of the identified criteria. The final phase included an analysis of the collected information and development of a computer application. The system was tested on a hypothetical project and validated using a real-world endeavor to demonstrate its effectiveness for a number of construction management functions, including project planning, scheduling, cost estimation, and the efficient use of available resources. This study determined the most significant selection criteria to be rental cost, crane availability, and safety considerations. The results show the capabilities of the proposed system, as well as its flexibility when working with a wide range of inputs.

In the process industry, plant production is completely halted every so many years for large-scale maintenance comprising inspection, repair and overhaul. It is paramount that this shutdown maintenance is completed according to the planning, which requires timely availability of replacement parts. In this setting, we present a spare parts optimization model and algorithm that includes the cost-time trade-off and precedence constraints between maintenance activities. The objective is to balance between spare parts ordering cost and the expected project delay cost due to waiting for spare parts. Using two-stage stochastic programming, spare parts ordering policies are determined in the first stage and a detailed project schedule is developed in the second stage. We propose a sample average approximation with importance sampling and pruning of dominated activities to solve the problem, and demonstrate that this method solves large instances quickly. We also consider heuristics, e.g. the standard project management approach based on the widely used critical path method and two heuristics that draw from spare part inventory control literature. These heuristics give poor solutions.

One of the key challenges in project organizations is the alignment of portfolio management with major corporate strategies. Usually, project-based organizations use shared resources to control and plan the project portfolio. Therefore, the exploitation of shared resources and project planning decisions made in this regard can change the progress of projects and affect the success rate of the projects. In this article, the integration of system dynamics with multi-objective decision making is applied to address project portfolio selection. The project portfolio has been modeled using four basic dimensions including technology, complexity, innovation and time sensitivity. The aim is to plan and control the progress of project portfolio while maximizing the strategic adaptation subject to the changes of the human resources. For this purpose, a two-stage MO-PSO with TOPSIS is proposed for portfolio selection problem that can solve real-world instances of the problem in a reasonable time. The result of the sensitivity analysis indicated that the proposed decision support system (DSS) provides insights into the impact of strategic alignment on project portfolio selection. According to the simulation results, the integrated methodology of this research can assist in choosing the suitable projects to achieve a project's strategic goals following the organization strategy.

Precedence relationships used in project planning mean for most professionals the traditional Start-to-Start-z (SSz), Finish-to-Start-z (FSz), Finish-to-Finish-z (FFz) and Start-to-Finish-z (SFz) relationships where z stands for the minimal necessary duration between the defined endpoints (Start or Finish) of the activities. These relationships have been serving professionals for more than 50 years, and there is not much visible effort for further developing them, despite some well-established critiques on the modeling capability of the Precedence Diagramming Method (PDM). The purpose of this research is: a) gathering those well-known and lesser-known developments of logical relationships that can be used for modeling some, so far, un-modelable problems b) classifying them by using a classification scheme that has been developed for this purpose and c) developing algorithms for time analysis when missing. The following earlier developments are discussed: maximal precedence relationships, point-to-point precedence relationships, continuous precedence relationships, relationships with AND/OR logical switches and bidirectional precedence relations. The classification shows that 24 types of logical relationships exist, but that algorithms exist only in four types, and are missing in twenty cases. The missing algorithms are provided here. The main contributions to the Body of Knowledge are: a) providing a classification scheme for precedence relationships b) definition of 24 precedence relationships based on the classification categories c) developing the missing time analysis algorithms for twenty cases d) presenting a single unified algorithm that handles all the 24 types of precedence relationships.

Conforming to the development of the carbon capture, utilization and storage (CCUS) in China, it has the necessity and possibility of launching several large-scale CCUS demonstration projects. The Ordos Basin is one of the greatest opportunity target areas for CCUS demonstration opportunities in China. As facing severe water shortage, carbon dioxide (CO2) enhanced oil recovery (CO2-EOR) is a helpless option in the coming large-scale development process of Yanchang Oilfield, the Ordos Basin, China. As a shining model of the CCUS, the CO2-EOR is attracting much more attention in China than before. However, the leakage risk of sequestered CO2 drives the necessity in monitoring of the CCUS process in practice. The aim of our research is to develop an integrated monitoring scheme and to identify related key monitoring indicators for CO2-EOR Demonstration Project at Yanchang Oilfield. In this paper, the detailed monitoring plan was tailored for the Jingbian CO2-EOR Block at the Yanchang Oilfield according to the existing situation of monitoring technologies and project planning in China. The principles and suggestion was finally proposed for the selection of key monitoring indicators for a long-term CO2-EOR activity in the Ordos Basin.

Educational mobility is familiar to diploma and associate degree faculty and is emphasized in the Institute of Medicine Report, The Future of Nursing. Utilizing this premise, a team of nurse educators and administrators implemented the principles of organizational redesign, change process, and project planning to facilitate a transformation from a hospital-based diploma program to a university bachelor of science in nursing program. The process described truly exemplifies the fact that “it does take a village” to create success.

Global ecosystems are increasingly threatened and altered by anthropogenic pressures and multiscale environmental disturbances. These disturbed ecosystems need to be restored to maintain vital ecosystem services. Strategies which do not consider integrated approach of restoration interventions may shift the ecosystems to more degraded states. In this study, we reviewed previously published primary articles to determine and describe the importance of ecosystem restoration governance components, viz. legal, financial, social and technological, and proposed an integrated framework of ecological restoration. We determined that without tracking restoration practices into restoration governance framework, the short-term restoration efforts are less likely to drive the ecosystem towards desired reference site conditions. Success of restoration can typically be observed only after years or decades (depending on the scale of the project and environment), so there should be an accountable institution overseeing the project for this period of time. We recommend integrating governance components from project planning to monitoring and evaluation phase. Further, we propose implementing restoration activities through a stable institutional entity that can foster collaboration and coordination with partners and stakeholders. Integrating components of restoration governance increase the likelihood of the restoration programs to be successful and sustainable, and provides opportunities to learn from the experiences.

This paper presents geographic maps of the profitability of PV and CPV solar projects over 1,960,000 km2. Such maps supplement the irradiance maps used in solar project planning and are relevant to government policy makers to assess the impact of incentives on profitability. Also, they are useful to solar project developers to identify geographical areas in which a required rate of financial return can be expected. Eight such maps of central Canada are presented in this paper and show the impact on profitability of different levels of government incentives, the difference in profitability between PV and CPV and the impact on profitability of delaying a project start date from 2016 to 2020. Government incentives of 10%–30% of the capital cost improve the internal rate of return (IRR) by between 0.7 and 4.67. For PV, the orientation of the modules is optimized to achieve maximum IRR resulting in an IRR increase of between 1.3% and 8.2%. Since CPV is a more recent technology than PV, its capital costs are projected to decline faster and we quantify the impact on IRR by showing that CPV has a higher IRR than PV of between 0.55 in 2016 and 3.6 in 2020.

Selection of suitable urban stormwater harvesting sites and associated project planning are often complex due to spatial, temporal, economic, environmental and social factors, and related various other variables. This paper is aimed at developing a comprehensive methodology framework for evaluating of stormwater harvesting sites in urban areas using Multi Criteria Decision Analysis (MCDA). At the first phase, framework selects potential stormwater harvesting (SWH) sites using spatial characteristics in a GIS environment. In second phase, MCDA methodology is used for evaluating and ranking of SWH sites in multi-objective and multi-stakeholder environment. The paper briefly describes first phase of framework and focuses chiefly on the second phase of framework. The application of the methodology is also demonstrated over a case study comprising of the local government area, City of Melbourne (CoM), Australia for the benefit of wider water professionals engaged in this area. Nine performance measures (PMs) were identified to characterise the objectives and system performance related to the eight alternative SWH sites for the demonstration of the application of developed methodology. To reflect the stakeholder interests in the current study, four stakeholder participant groups were identified, namely, water authorities (WA), academics (AC), consultants (CS), and councils (CL). The decision analysis methodology broadly consisted of deriving PROMETHEE II rankings of eight alternative SWH sites in the CoM case study, under two distinct group decision making scenarios. The major innovation of this work is the development and application of comprehensive methodology framework that assists in the selection of potential sites for SWH, and facilitates the ranking in multi-objective and multi-stakeholder environment. It is expected that the proposed methodology will assist the water professionals and managers with better knowledge that will reduce the subjectivity in the selection and evaluation of SWH sites.

During their lifecycles, buildings are changed and adapted to the requirements of generations of users, residents and proprietaries over several decades. At the end of their life time, buildings undergo either retrofit or deconstruction (and replacement) processes. And, modifications and deviations of the original building structure, equipment and fittings as well as the deterioration and contamination of buildings are often not well documented or only available in an outdated and unstructured way. Thus, in many existing buildings, incomplete, obsolete or fragmented building information is predominating and hampering retrofit and deconstruction project planning. To plan change or deconstruction measures in existing buildings, buildings are audited manually or with stationary laser scans which requires great effort of skilled staff and expensive equipment. Furthermore, current building information models or deconstruction planning systems are often not able to deal with incomplete building information as it occurs in existing buildings. We develop a combined system named ResourceApp of a hardware sensor with software modules for building information acquisition, 3D reconstruction, object detection, building inventory generation and optimized project planning. The mobile and wearable system enables planner, experts or decision makers to inspect a building and at the same time record, analyze, reconstruct and store the building digitally. For this purpose, a Kinect sensor acquires point clouds and developed algorithms analyze them in real-time to detect construction elements. From this information, a 3D building model and building inventory is automatically derived. Then, the generated building reconstruction information is used for optimized project planning with a solution algorithm of the multi-mode resource-constrained project scheduling problem (MRCPSP) at hand. In contrast to existing approaches, the system allows mobile building recording during building walkthrough, real-time reconstruction and object detection. And, based on the automatically captured and processed building conditions by sensor data, the system performs an integrated project planning of the building deconstruction with available resources and the required decontamination and deconstruction activities. Furthermore, it optimizes time and cost considering secondary raw material recovery, usage of renewable resources, staff qualification, onsite logistics, material storage and recycling options. Results from field tests on acquisition, reconstruction and deconstruction planning are presented and discussed in an extensive non-residential case study. The case study shows that the building inventory masses are quite well approximated and project planning works well based on the chosen methods. Nevertheless, future testing and parameter adjustment for the automated data processing is needed and will further improve the systems' quality, effectiveness and accuracy. Future research and application areas are seen in the quantification and analysis of the effects of missing data, the integration of material classification and sampling sensors into the system, the system connection to Building Information Modelling (BIM) software via a respective interface and the transfer and extension to retrofit project planning.

The concept of marginal land is often used to justify land availability and inform land allocation for biofuel projects. However, marginal lands can provide other valuable ecosystem services. Using interviews with multiple stakeholders and fieldwork in three collapsed biofuel projects in Ghana, this paper shares perspectives on how the ecosystem service approach (ESA) can offer a better basis for selecting land for biofuel projects. Expert interviews with key stakeholders (e.g. Lands Commission) in biofuel value chains in Ghana highlight the lack of consensus of what constitutes marginal land, with two dominant interpretations coming up; (i) land unsuitable for food production and (ii) land unsuitable for cost-effective agricultural production. Both interpretations however do not reflect the ecosystem services lands provide, as well as the significant cultural values attached to them. Our empirical work shows that many ecosystem services are obtained from the supposedly marginal lands that are neglected from both interpretations, as well as the standard project planning and Environmental Impact Assessment (EIA) processes. We make the case that when compared to the current marginal land narrative, the ESA offers a better lens for understanding local land uses, in managing emerging tradeoffs and providing information for locating biofuel projects. Our findings suggest that expanding the scope of EIAs by integrating elements of the ESA can go a long way towards informing site selection for biofuel investments.

A major source of uncertainty in civil engineering projects arises from the geological and geotechnical variability at the project site. This paper presents an approach to quantify such uncertainty, and to rationally incorporate them into estimates of cost contingency. Contrary to the conventional approaches that rely on individual expert's opinion or data from past projects, the proposed approach allows site-specific assessments of the intrinsic geotechnical variability through geostatistical techniques. Such uncertainty can be reduced through geotechnical investigation, and spatial tessellation techniques are proposed to facilitate determination of the optimal locations of new boreholes. Cost-effectiveness of the boreholes can be evaluated based on the corresponding reductions in geotechnical uncertainty and their influence on the budget. The approach is illustrated using a hypothetical excavation scenario, where the project costs are affected by uncertainty in the subsurface strata, particularly the rockhead level across the site. Under the specific site conditions, a Pareto frontier is developed to reveal the relationship between the number of boreholes to be drilled and potential savings in contingency budget. Through this approach, the study promotes better utilization of geotechnical information and rational assessments of project risks associated with their variability, which may lead to improved project planning and resource allocation.

Building Information Modeling (BIM), as a rising technology in the Architecture, Engineering and Construction (AEC) industry, has been applied to various research topics from project planning, structural design, facility management, among others. Furthermore, with the increasing demand for energy efficiency, the AEC industry requires an expeditious energy retrofit of the existing building stock to successfully achieve the 2020 Energy Strategy targets. As such, this article seeks to survey the recent developments in the energy efficiency of buildings, combining energy retrofitting and the technological capabilities of BIM, providing a critical exposition in both engineering and energy domains. The result is a thorough review of the work done by other authors in relevant fields, comprising the entire spectrum from on-site data acquisition, through the generation of Building Energy Models (BEM), data transfer to energy analysis software and, finally, the identification of major issues throughout this process. Additionally, a BIM-based methodology centered on the acquired knowledge is presented. Solutions for as-built data acquisition such as laser scanning and infrared thermography, and on-site energy tests that benefit the acquisition of energy-related data are explored. The most predominant BIM software regarding not only energy analysis but also model development is examined. In addition, interoperability restrictions between BIM and energy analysis software are addressed using the Industry Foundation Classes (IFC) and Green Building Extensible Markup Language (gbXML) schemes. Lastly, the article argues the future innovations in this subject, predicting future trends and challenges for the industry.

Prefabricated prefinished volumetric construction (PPVC) is an innovative and cleaner approach that has restructured the production of the construction industry. It can improve the workflow continuity, increase the efficiencies in the use of resources, minimize construction wastes, and reduce the number of on-site contractors as well as construction durations. While the benefits of PPVC have been widely recognized over past two decades, the constraints on using PPVC remains unexplored. As a result, the aims of this study are to investigate the significant constraints demotivating the adoption of PPVC and to propose a group of feasible mitigation strategies to tackle these constraints. To achieve these goals, a comprehensive literature review was conducted first, followed by a structured questionnaire survey administered to 41 Singapore-based construction organizations. Lastly, an in-depth case study was conducted to verify the empirical findings. The analysis results showed that the top five significant constraints were “extensive coordination required prior to and during construction”, “need for additional project planning and design efforts”, “increased transportation and logistics considerations”, “requirement for early commitment”, and “higher initial cost than conventional construction method.” It also revealed the top three most effective mitigation strategies: “encouraging close collaborations between project stakeholders during the early phase of the project”, “use of BIM to improve coordination and facilitate communication among project stakeholders”, and “offering training courses for project team and workers to enhance their knowledge and skills”. This study contributes to the body of knowledge by examining the constraints and mitigation strategies for the adoption of PPVC. Also, the findings from this study are informative to the industry practitioners to have a better understanding and implementation of PPVC.

This study looks into one of the most promising low carbon city planning initiatives in China, namely Shenzhen's International Low Carbon City (ILCC). First as a collaborative project between the Dutch and Chinese partners, the ILCC's international partners have expanded to include other countries, such as Germany, Italy, France, Australia and the US. This paper investigates the influence of these international actors in the development process of the ILCC and their benefits in the long run, through knowledge transfer and accumulation of resource. The paper first highlights a broad understanding of ‘low carbon city’ followed by detailed discussions on discourses of ‘low carbon city’, ‘eco-city’, and ‘low carbon eco-city’ in China. Then it provides insights on knowledge transfer in low carbon city development, and particularly the Sino-Foreign cases of China. The authors then introduce the case of study (ILCC) and highlight its visions, project planning, and partnerships. Using primary and secondary data, it then maps the ILCC's international actors and their roles, and then analyses their behaviours and impacts in the project's planning and development process. Next, the paper summarises the research findings with further updates on the case of ILCC. The authors conclude that the engagement between Chinese and international partners differ in three forms and they are (1) the type of involvement; (2) the level and timeframe of involvement; (3) the level of Influence in the project's multiple stages. The paper concludes that the role played by an international partner evolves as the project proceeds.

There is no consensus on how to judge the quality of Research Through Design (RTD) projects, which makes them difficult to plan and evaluate. In response, this study provides a framework for discussing and positioning RTD projects in terms of quality. It draws on theory on research quality and an original analysis of 25 RTD papers to identify how known quality indicators are applied. Our findings show that most papers align with these indicators, especially those associated with pragmatist research. Nonetheless, there are opportunities to enrich discussions on quality in RTD and we propose recommendations to this end. These recommendations can support more mindful and transparent project planning and reporting, and better assessment of and discussions on quality.

Upstream natural gas projects are extremely complex and encounter a range of non-technical risks (NTRs) and technical risks (TRs) that frequently get in the way of timely project delivery. Despite their economic and social importance and the massive investments underpinning them, these projects are frequently plagued by significant schedule overruns. Risks are considered during project planning, but the interactions between NTRs and TRs on project performance remain largely anecdotal and theoretically underdeveloped. In this paper, we apply structural equation modelling to data collected from natural gas projects in Australia to empirically investigate the relationships between NTRs, TRs, and project schedule delay. The results indicate that NTRs are much more significant than TRs in influencing delays, and have a stronger influence on TRs, thereby exacerbating delays. The moderation effect of project complexity related to project size is also found to have a significant effect on the relationship between risks and delays. These findings provide insight on the direct, indirect, and mediating effects of risks that decision-makers should take into consideration when assessing project risks. By shedding a useful amount of new light on these interactions and complexities, this contribution will deepen the theoretical understanding of these phenomena and help practitioners to improve project schedule performance within the extractive industries.

The substandard condition of wastewater systems in the US, accompanied by the lack of financial resources for renewal are hindering adequate operation and maintenance of deficient sewer systems. Information about current and future pipe condition, as well as information about the impact of possible pipe failures are an integral part of an efficient asset management program and can help stakeholders make the best decisions to prioritize rehabilitation and/or replacement projects. Typically, pipes in the worst structural conditions are prioritized and budgeted within the capital improvement project planning. To be able to predict future pipe conditions, many methods have been developed and successfully implemented that incorporate pipe inspection data to predict the future state of these assets. Additionally, methodologies exist for determining the consequences of pipe failures economically, socially, and environmentally. These methods have been incorporated into decision support systems (DSS) that help utility managers determine when to rehabilitate or replace their assets. DSS for trenchless pipe renewal allow utility managers to determine the most suitable method to renew their assets, given known defects in the pipe. The aim of this paper is to provide a review of risk management methods that allow pipeline managers to estimate likelihood of failure and quantify consequence of failure of sewer pipes. Additionally, an updated review of existing DSS for trenchless pipe rehabilitation is presented and analyzed. Finally, recommendations are made to improve existing methods to make the risk management process for trenchless rehabilitation decision making more efficient and practical.

ContextSoftware project plan is the basis of the project execution, and its quality depends on completeness of software scope definition. A method is required that should gauge the completeness of different aspects of scope definition, thus, providing guidance to practitioners to reconsider areas that have not been defined well. ObjectiveThis paper aims to evaluate completeness of software project scope definition. It identifies a detailed list of different aspects of software project scope definition, and builds a method where numerical score can be assigned to a scope definition. MethodA detailed list of different elements of software project scope definition is identified through literature. These elements are then empirically evaluated through an electronic survey, conducted with the industrial experts. Once finalized, these elements are ranked and assigned weights to systematically build a scorecard that is used to calculate scope definition score. Evaluation of the proposed method is done through a series of formal experiments. ResultsEvaluation results suggest that the proposed method is useful not only in calculating completeness of software projects scope definition, but it also serves as a guide for practitioners to determine specific aspects that require further consideration.

The University of British Columbia has an interest in incorporating life cycle environmental impacts and financial information into project planning, as well as research and teaching. As part of a tall wood building research program with the UBC Sustainability Initiative and Dept. of Civil Engineering, a comprehensive life cycle assessment (LCA) and life cycle costing (LCC) study was done of two student high-rise residential buildings, based on the result of whole building LCA done by Athena Sustainable Materials Institute and whole building LCC done by Sensible Building Science. These buildings are of similar design but Brock Commons Tallwood House has a hybrid mass-timber structure and Ponderosa Commons Cedar House has a more traditional concrete structure. This paper will include a brief overview of the research process, data collection, analysis, and key results. The paper will then focus on the main opportunities, challenges, and lessons learned from both the results of the LCA/LCC projects and the process of conducting the study.

The proposed study examines the notion that software project managers do not necessarily choose the optimal Gantt chart while planning a software project. This suboptimal choice is biased by psychological perceptions of complexity, as well as by perceptions of risk level (anxiety). We claim that since the optimal plan is naturally more complex, the perceived complexity of Gantt charts influences project managers’ decisions and, when possible, causes them to avoid it. We assume that a “complexity adjustment” algorithm that would enable project managers to adjust the complexity of the Gantt chart to the required level of complexity will allow the manager to choose from among all relevant possible plans the one that meets project’s constraints, while the structural relationships between plan’ work units are at the level of complexity preferred by the manager (e.g., preference for serial activities over parallel ones). Such “feature” will enable managers to adjust the required level of complexity according to work-related anxiety levels. To assist in defining the research question and the relevant manipulations, a pre-test examined the perceived complexity of different basic relationships between work units (serial vs. parallel) and the perceived level of work-related anxiety.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. This paper proposes a novel approach for identifying the best implementation situation for each activity in a project by optimizing and balancing time, cost, quality, and risk criteria under uncertain circumstances. A hesitant fuzzy linguistic term set (HFLTS) approach is proposed to determine the status of project activities in the presence of quality and risk criteria alongside time and cost. Afterwards, a multi-objective linear programming (MOLP) model is formulated for time, cost, quality, and risk trade-off (TCQRT). To validate the model, a research and development project in the food industry is investigated. The results indicate that the project's time compared to the deterministic approach was reduced by 20%. Completing the R&D project earlier than other competitors brings a higher profit for the company than trade-off expenses, even without considering the quality and risk trade-off benefits of the proposed approach. Considering uncertainty in the risk and quality of activities in a project via HFLTSs and optimizing all four elements of time, cost, quality, and risk simultaneously are the main values of this research. The proposed approach can be employed by managers to adopt and optimize project planning and scheduling while optimizing the trade-offs among TCQR factors in uncertain circumstances.

In this study, based on the whole stages of planning, construction and operation of the projects of various sectors in a low-carbon industrial park, a method of accounting GHG emissions is established to analyze comprehensively different GHG sources through a multi-angle approach. A low-carbon industrial park in Chongqing, China, was chosen for a case study. The results show that from 2006 to 2011, total GHG emissions of this industrial park increased by 69.1% from 1.23Mt CO2e to 2.08Mt CO2e, and will reach 4.34Mt CO2e in 2015 according to the planning of new projects. GHG emissions of operational projects are much bigger than projects under construction. Overall, the industry sector is the biggest source of GHG emissions in the park, accounting for about 92.4% of the total volume in 2006 and 85.9% in 2011, and the share will be 83.5% according to the 2015 project planning. Regarding the future low carbon development of the studied industrial park, this paper suggests that it should focus on the industry sector, extend the aluminum processing industrial chain, and actively introduce high value-added and energy-efficiency projects.

Successful development of Information Systems (IS) Projects has been a source of competitive advantage for many organizations. This paper proposes the Cost and Time Project Management Success – CTPMS, an essential measure in this context because projects must dynamically address cost and time success under an agreed scope. The goal of the paper is to identify the project management practices through which an organization can optimize the CTPMS of IS development projects. Because multiple factors can influence project management success, we analyze a real-world sample of 899 IS projects of a leading bank, using hierarchical models to account for the effects of predictors at four levels of analysis: portfolio network, project, project manager, and team. In addition to proposing and discussing a new measure of project management success for information systems development projects, we identified that project size, duration, postponement, and project manager formal power showed positive effects, whereas team size and team allocation dispersion presented negative effects. The results suggest guidance for factors such as team member allocation and prioritization, among others.

There is growing pressure on project managers to demonstrate the value of their projects to the funding organization. However, most projects lack a robust process for realizing such strategic value. While the literature recognizes the importance of project governance for enabling benefits realization, this research area lacks empirical evidence. Accordingly, this paper analyzes the relationships between effective project governance, benefit management, and project success. A scale for evaluating effective project governance was developed and validated based on feedback from 21 project governance experts. Subsequently, an international survey of 333 projects was used to test proposed relationships. The results indicate effective project governance improves project success both directly and through an enhanced benefit management process. Additionally, the most effective project governance and benefit management practices for improving project success are identified, such as the development and monitoring of a high quality project business case. The resulting model sets the foundations for a theory that explains how effective project governance enhances project success and enables the realization of strategic objectives through projects.

This paper reports two empirical studies on how the use of different contract types affects, directly and indirectly, the outcomes of software projects. The first study evaluates the effect of contract type on project failure using information from a large international dataset of small-scale, outsourced software projects and tasks. The second study proposes and tests how the use of contracts is connected with project outcome using information about Norwegian software projects with a public client. Both studies find that the use of fixed price contracts is connected with a higher risk of project failure compared to time and materials types of contracts. The results from the second study suggest that different project outcomes with different contract types is explained by differences in how the provider is selected, how the client is involved in the project, the use of agile practices and the use of benefit management during project execution.

Construction project performance relies on different dimensions of project management. Among those, integration management is of paramount importance since effective project management starts with the integration of processes and people within a construction project. This study investigates the influence of various components of integration management on construction project management performance and quantifies the relationship between those components and integration management. The proposed components of integration management are the development of a project charter, knowledge integration, process integration, staff integration, supply chain integration, and integration of changes; whereas the dimensions of project management performance are time, cost, quality, safety, and client satisfaction. A questionnaire was designed and administered to construction professionals and data from 121 projects was analyzed using structural equation modeling. The data was analyzed by using software, called SPSS AMOS. The findings of the research indicate that integration management has a strong impact on project management performance. The study contributes to the project management body of knowledge in that it develops a conceptual framework consisting of specific components for integration management, reveals the impact of integration management on performance, and proposes several tools and strategies for enabling effective integration along the project life cycle. Industry practitioners may benefit from the framework developed by considering the components proposed and following strategies recommended for construction phases.

Despite considerable investment in river restoration projects, there is still limited information on the efficacy and success of river restoration activities. One of the main reasons is poor or improper project design, resulting in common problems such as: not addressing the root cause of habitat degradation; not establishing reference conditions, benchmarks and not defining endpoints against which to measure success; inappropriate uses of common restoration techniques because of lack of pre-planning; and inadequate monitoring or appraisal of restoration projects. In this paper peer-reviewed and grey literature and a large database of existing case studies were reviewed to identify the prevailing challenges river managers face when planning and developing river restoration projects. To overcome these current challenges an integrated project planning framework has been developed that incorporates adaptive management and project management techniques. It encapsulates key concepts and decision support tools to advance the existing sequence of project identification, project formulation, project implementation and post-project monitoring to incorporate multidisciplinary decision making to meet specific environmental and socio-economic objectives. The proposed river restoration project planning framework is adaptable and can therefore be applied to any project development scenario locally, regionally or internationally.

This paper empirically studies the importance of managing design changes in dealing with time delay and cost overruns in construction projects. The main objective of this paper is to identify the causes of design changes and the implications on the Malaysian construction projects measured in terms of cost and time. It also aims to determine how rework induced from the design changes is detrimental to project performance and to suggest recommendations on how to overcome the related problem with project learning and effective communication in building construction. To investigate the factors giving rise to design changes, a total of 43 causes were first identified through a comprehensive literature review. The factors are categorised into client, consultant, contractor, site and external-related themes. This is followed by a qualitative research study involving semi-structured interviews with 12 experienced industry practitioners comprising of clients, consultants, and contractors. Critical incident technique employing content analysis is used to analyse the interviews transcripts in detail to provide a rich picture of the causes of design changes, the implications for project delivery performance, enablers of effective communication, enablers of project learning and types of reusable project knowledge. The research findings were further integrated to develop a collaborative model to manage design changes using effective communication and project learning approach. This model highlights the importance of effective communication and project learning towards improving the level of competency and cohesiveness of project team in managing future projects. Capturing and sharing of reusable project experiences is essential towards maximising the benefits of past experiences (lessons learned), shortening the learning curve and adding value to future projects in design change management.