Uncertain Project Environments Research Articles

Mapping the knowledge domain of stakeholder perspective studies in construction projects: A bibliometric approach

Construction projects require the effective collaboration among the various types of stakeholders involved to succeed, thus leading to stakeholder perspective studies in construction projects. The study proposes an integrated bibliometric approach to detect the knowledge evolution, domain and frontier with a broader searching scope compared with manual review. A total of 752 peer-reviewed academic papers published until the end of 2017 are used. The knowledge evolution indicates seven milestones in history, namely, stakeholder concept, method, identification, assessment, management, influence and complexity. The identified knowledge domain consists of four major research areas which are society, sustainability, analytical tool and project management. The knowledge frontier is also revealed, including a dearth of detailed discussions on stakeholder engagement in sustainable urban projects, lack of generalisation of stakeholder studies in complex construction projects, limited application of dynamic and simulation stakeholder analysis in uncertain project environment and few instant and accurate approaches to integrate stakeholder information. The study provides a holistic knowledge map for the past, current and future of stakeholder perspective studies in construction projects.

A knowledge-based expert system to assess power plant project cost overrun risks

Preventing cost overruns of such infrastructure projects as power plants is a global project management problem. The existing risk assessment methods/models have limitations to address the complicated nature of these projects, incorporate the probabilistic causal relationships of the risks and probabilistic data for risk assessment, by taking into account the domain experts’ judgments, subjectivity, and uncertainty involved in their judgments in the decision making process. A knowledge-based expert system is presented to address this issue, using a fuzzy canonical model (FCM) that integrates the fuzzy group decision-making approach (FGDMA) and the Canonical model (i.e. a modified Bayesian belief network model). The FCM overcomes: (a) the subjectivity and uncertainty involved in domain experts’ judgment, (b) significantly reduces the time and effort needed for the domain experts in eliciting conditional probabilities of the risks involved in complex risk networks, and (c) reduces the model development tasks, which also reduces the computational load on the model. This approach advances the applications of fuzzy-Bayesian models for cost overrun risks assessment in a complex and uncertain project environment by addressing the major constraints associated with such models. A case study demonstrates and tests the application of the model for cost overrun risk assessment in the construction and commissioning phase of a power plant project, confirming its ability to pinpoint the most critical risks involved ̶ in this case, the complexity of the lifting and rigging heavy equipment, inadequate work inspection and testing plan, inadequate site/soil investigation, unavailability of the resources in the local market, and the contractor's poor planning and scheduling.

Selecting project-critical path by a new interval type-2 fuzzy decision methodology based on MULTIMOORA, MOOSRA and TPOP methods

Abstract In this paper, a novel decision methodology of critical path determination is introduced that not only considers project time but also considers project cost, risk, quality and safety. To address uncertain project environment, interval type-2 fuzzy sets (IT2FSs) are presented in the proposed decision methodology. The ratings of each activity and the weight of each criterion are described by IT2F-numbers. To address this multi-criteria decision problem, a new version of MULTIMOORA and MOOSRA methods are extended to IT2F-uncertainty and are used to determine project’s critical paths. In addition to addressing IT2FSs, the method is enhanced by replacing the commonly applied dominance theory by a new version of multi-approaches multi-criteria decision-making technique, namely technique of precise order preference (TPOP). Finally, in order to display the applicability of the presented methodology, an existing case study from the literature to aircraft prototype batch is adopted and solved. Furthermore, a case study of construction project is solved by proposed methodology. Also, sensitivity analysis and comparative analysis are carried out, and the results are discussed. The validity of the proposed methodology is confirmed by solving two decision methods of the recent literature. Furthermore, the sensitivity analysis illustrates that the critical path of the project is approximately insensitive to weights of new MULTIMOORA method's main parts.

Study on Dynamic Situation Management of Uncertain Project and Program Environment

Study on Dynamic Situation Management of Uncertain Project and Program Environment

Applying utility theory in uncertain project environments with multiple goals

In project environments, normally, multiple conflicting goals are being incorporated for decision making which associated with uncertain and incomplete information. The main purpose of the project management process is to minimise total project cost and completion time simultaneously; however these affecting factors in project management are conflicting objectives and those have to be efficiently compromised. Going through literature indicated utility theory has not been previously applied in project management environment while deeply incorporated through economics sciences. This study applies the utility theory through solving cost and time trade-off problems in uncertain environments. Here, considering decision maker's (DM) preferences, cost and time utility functions are then determined. Further, the overall utility function has to be optimised. Since the proposed function appropriately assessed, the best decision is being made and maximum satisfaction for DM is reached.

Applying Utility Theory in uncertain project environments with multiple goals

Applying Utility Theory in uncertain project environments with multiple goals

A review of analytical models, approaches and decision support tools in project monitoring and control

This paper reviews the problems, approaches and analytical models on project control systems and discusses the possible research extensions. We focused on literature in Earned Value Analysis (EVA), optimization tools, and the design of decision support systems (DSS) that will contribute to helping project managers in planning and controlling under uncertain project environments. The review reveals that further research is essential to develop analytical models using EVA metrics to forecast project performance. It also suggests that DSS should be model driven, function as early warning systems and should be integrated to commercial project management software.

Probabilistic multiobjective optimization of sustainable engineering design

As the global population reaches 7 billion and standards of living are increasing, engineers are being pressured to use limited natural resources to satisfy ever-increasing demand. Project engineers are currently charged with achieving a balance between cost and duration, and must consider environmental factors to reach sustainable development. This work proposes a novel probabilistic multi-objective optimization algorithm to attain sustainable construction cost, project duration, and CO2 emissions simultaneously in an uncertain project environment. The novel algorithm, which is based on Particle Swarm Optimization integrated with Monte Carlo simulation, is applied to generate a low-carbon economy and cleaner production. A typical construction project is selected to demonstrate the application of proposed algorithm for making sustainable decisions under multi-objectives. The proposed method demonstrated its risk analysis capacity by obtaining non-dominant optimized solutions for cleaner construction. This paper contributes to facilitating project managers in achieving a design that satisfies technical and quality requirements with lowest cost, shortest duration, and minimal adverse impacts on the environment.

Introducing AgiLean to construction project management

The complexity of construction projects is the main reason, why the construction industry is searching better ways of managing construction projects. Recently, the industry tries to get benefit from the adoption of two management methodologies. On the one hand there is Lean construction, which works well for stable and predictable project environments. On the other hand, there is Agile project management [PM], which works well for dynamic and uncertain project environments. Construction projects, however, are exposed to predictable and paradoxically uncertain environments at the same time. Hence there is a need for a methodology which merges Lean and Agile to a holistic unit. The objective of this contribution is to introduce such a methodology. Such a methodology does not exist so far and is different from the “Leagile” approach, which uses Lean and Agile methods in the execution phase sequentially. Through undertaking a comprehensive literature review and through conducting 22 interviews with practitioners in the field of construction PM, Lean, Agile a new methodology is introduced, which is conceptualised as “AgiLean PM”.

An integrated scheduling and control model for multi-mode projects

In today’s highly competitive uncertain project environments, it is of crucial importance to develop analytical models and algorithms to schedule and control project activities so that the deviations from the project objectives are minimized. This paper addresses the integrated scheduling and control in multi-mode project environments. We propose an optimization model that models the dynamic behavior of projects and integrates optimal control into a practically relevant project scheduling problem. From the scheduling perspective, we address the discrete time/cost trade-off problem, whereas an optimal control formulation is used to capture the effect of project control. Moreover, we develop a solution algorithm for two particular instances of the optimal project control. This algorithm combines a tabu search strategy and nonlinear programming. It is applied to a large scale test bed and its efficiency is tested by means of computational experiments. To the best of our knowledge, this research is the first application of optimal control theory to multi-mode project networks. The models and algorithms developed in this research are targeted as a support tool for project managers in both scheduling and deciding on the timing and quantity of control activities.

Effects of the information presentation format on project control

In this paper, we investigate the relationship between the information presentation format and project control. Furthermore, the effects of some system conditions, namely the number of projects to be controlled and the level of time pressure, on the quality of the project control decisions are analyzed. Information provided by Earned Value Analysis is used to monitor and control projects, and simulation is applied to replicate and model the uncertain project environments. Software is developed to generate random cost figures, to present the data in different visual forms and to collect users’ responses. Having performed the experiments, the statistical significance of the results is tested.

Robust optimization models for the discrete time/cost trade-off problem

Developing models and algorithms to generate robust project schedules that are less sensitive to disturbances are essential in today's highly competitive uncertain project environments. This paper addresses robust scheduling in project environments; specifically, we address the discrete time/cost trade-off problem (DTCTP). We formulate the robust DTCTP with three alternative optimization models in which interval uncertainty is assumed for the unknown cost parameters. We develop exact and heuristic algorithms to solve these robust optimization models. Furthermore, we compare the schedules that have been generated with these models on the basis of schedule robustness.

Robust Project Network Design

Traditional project planning tools and methodologies fail to address the dynamic uncertainties that can arise during project execution. In this article, we develop an approach to enable project managers to design project networks capable of performing predictably under uncertainty. We integrate a validated project organization design simulation tool (Virtual Design Team) with a robust design experimental method to enable robust project network design. We test the framework on a 13-month, U.S. $11.5M public renovation project. We find that: (1) it is possible to integrate the project organization design tool with the robust design experimental method for the test case project; (2) the integrated approach enables project managers to identify and simulate the combination of interventions that will lead to the most robust project performance; and (3) the integrated approach can extend the capabilities of project managers to design project networks in dynamically uncertain project environments. The findings highlight the need to explore new ways to achieve predictable project performance in dynamically uncertain project execution environments.

The role of project target clarity in an uncertain project environment

Product development is recognized as cross‐functional teamwork that has become important in the fast‐paced, globally competitive environment. Despite an extant body of knowledge on the importance of fuzzy front‐end planning and functions of goals in the management literature, the impact of uncertain project environment and goal setting mechanisms in front‐end planning is not fully understood. Product development literature presents numerous case studies or conceptual papers that emphasize the importance of upfront planning and a need for team building; however, large‐scale empirical studies are rare. This paper presents a model linking uncertain project environment, project target clarity, teamwork and its outcome measures (i.e. a product's value to customer and time to market). The data were analyzed from 205 product development projects of firms from the USA and Canada. Valid and reliable instruments were developed to assess the nature and impact of inter‐relationships of these variables. Results from structural model tests indicate that uncertain project environment influences the nature of project targets which in turn affects the level of teamwork. Teamwork is an important process outcome for enhancing value to customer and time to market. Management implications are discussed as well.