Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas

A Systems Engineering Methodology for Wide Area Network Selection using an Analytical Hierarchy Process

In this paper, we apply a systems engineering methodology to select the most appropriate wide area network (WAN) media suite, according to organizational technical requirements, using an Analytic Hierarchy Process (AHP). AHP is a mathematical decision modeling tool that utilizes decomposition, determination, and synthesis to solve complex engineering decision problems. AHP can deal with the universal modeling of process engineering decision-making, which is difficult to describe quantitatively, by integrating quantitative and qualitative analysis. We formulate and apply AHP to a hypothetical case study in order to examine its feasibility for the WAN media selection problem. The results indicate that our model can improve the decision-making process by evaluating and comparing all alternative WANs. This shows that AHP can support and assist an organization in choosing the most effective solution according to its demands. AHP is an effective resource-saver from many perspectives—it gives high performance, economic, and high quality solutions. Keywords: Analytical Hierarchy Process, Wide Area Network, AHP Consistency, WAN alternatives

Development of Hesitant Fuzzy-Based Project Selection Method with Consideration of Benefits, Opportunities, Costs and Risks

PT X, a power generation company, hasn’t been able to meet their target in the business development segment over the past few years. This is due to a problem detected in their Project Portfolio Management, in which PT X’s project selection method hasn’t considered the ambiguity nature of project’s information and risks. This study is going to develop a project selection method for PT X using MCDM (multi criteria decision making) with BOCR (benefit, opportunity, cost, risk) Concept to evaluate many criteria that need to be considered by the company, especially conflicting criteria such as benefit with cost and opportunity with risk. Not only that, hesitant fuzzy will be used because project itself has many uncertain or ambiguous information, so stakeholder will face difficulties in determining the value for the evaluation. From the integration of those things in this study, it is found that for PT X, Benefit has the biggest priority, followed by Opportunity, Risk, and Cost in Project Selection for PT X. It is also found that based on additive-BOCR, Project C gives the optimal value for PT X, followed by Project B, Project A, Project D, dan Project E.

Ranking and sensitivity analysis of key factors for successful project management performance: An application of AHP for Oil and Gas sector

The complexities faced by oil and gas projects due to uncertainties and risks, demand implementation of project management techniques for successful completion. Therefore this is made by using analytical hierarchy process, to identify and prioritize the key factors for successful project management performance of oil and gas projects. These factors are categorized into attributes of project staff, project planning process and assessment of project quality. Using Expert Choice, a hierarchy is developed followed by pairwise comparison based upon data collection from industrial experts of oil and gas sector. Results of analytical hierarchy process concluded that, project completion within estimated time and budget, clarity of objectives and involvement of top management are most crucial elements for improvement in project management performance of oil and gas projects. Whereas sensitivity analysis according to three different scenarios highlighted factors according to their relative importance

Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment

Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy ProcessFuzzy Inference System

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.11sciessciscopu

Supporting metropolitan Venice coastline climate adaptation. A multi-vulnerability and exposure assessment approach

Urban planning for adaptation to climate change privileges the construction of cognitive frameworks developed through the use of new spatial technologies and open-source databases. The significant and most highly innovative aspect concerns how resilience to CC under conditions of vulnerability and risk is defined, monitored and assessed. Based on these premises, this paper aims to explore a new methodology of climate vulnerability, exposure and risk analysis through multicriteria assessment techniques by activating a case study in the coastal municipality of Jesolo (Italy). Taking into consideration three main weather-climate impacts (Urban Flooding, Coastal Flooding and Urban Heat Island) the methodology searches for the best geo-referenced data that can best describe the recognizing impact of the cumulative impact condition through testing a GIS-based multi-attribute exploratory procedure. Intersectoral and multilevel vulnerability conditions at different spatial scales are configured. The analysis methodology continues using open source data (from Open Street Map) to construct local exposure information layers. Exposure combined with spatial vulnerability conditions allows the generation of multi-hazard mapping. Experimentation with multi-hazard climate-oriented spatial assessment can guide planning and public decision-making in new policy domains and target mitigation and adaptation actions in land planning, management and regulation practices. Finally, the proposed methodology can activate stakeholder engagement processes within municipalities to discuss the actual perceived risk and begin a collaborative journey with citizens to identify best practices and solutions to adopt in the areas indicated by the risk mapping