Project risk management in Iranian small construction firms

The objective of this study is to evaluate RM in small projects in Iran using identification of status, barriers, and the impact of RM on project performance. In this study, theoretical foundations and research literature were first developed through library, and then a questionnaire about these variables was designed and distributed among a number of experts in the active construction companies. Data were collected from 40 projects submitted by 25 experts from 5 executive companies. According to the studies, 10 barriers are identified as major obstacles to RM implementation in such projects, prioritized as follows: (1) lack of potential benefits, (2) not economical, (3) lack of time, (4) lack of budget, (5) lack of knowledge, (6) lack of government legislation, (7) lack of manpower, (8) low profit margin, (9) complexity of analytical tools, and (10) competition among SMCs. The findings of this research can provide an in-depth understanding of RM in small projects in Iran and make benefits of RM convincing to the participants of small projects.

МОДЕЛЬНИЙ ПІДХІД У МЕТОДОЛОГІЇ УПРАВЛІННЯ ПРОЕКТАМИ

Вступ. У деяких математичних моделях управління проектами виникає потреба встановлення максимального радіусу гіперсфери, зануреної в поліедральну галузь. Сучасний математичний апарат теорії оптимізації сумісно із застосуванням комп’ютерних технологій дає змогу розв’язувати нелінійні задачі оптимізації, але завжди існує доцільність лінеаризації складних нелінійних задач. Таке спрощення дає змогу використовувати точні класичні методи оптимізаційного розв’язку, на відміну від наближених, для нелінійної оптимізації. Поставимо завдання строгого математичного зведення (лінеаризації) багатовимірної нелінійної задачі оптимізації про занурення гіперсфери максимального радіусу в опуклу ділянку типу поліедру. Нехай маємо замкнений поліедр, поданий системою лінійних алгебраїчних нерівностей. У ділянці замкненого поліедру необхідно розмістити гіперсферу максимального радіусу. Мета. У статті проаналізовано модель установлення максимального радіусу гіперсфери, розміщеної (зануреної) у поліедральну ділянку (опуклу множину, обмежену прямими лініями), яка забезпечує врахування великої множини факторів, серед яких – управління інтеграцією (Project Integration Management); предметна ділянка проекту (Project Scope Management); управління якістю (Project Quality Management); управління часом (Project Time Management); управління вартістю (Project Cost Management); управління комунікаціями (Project Communication Management); управління контрактами (Project Procurement Management); управління ризиками (Project Risk Management). Результати. У моделі запропоновано строге математичне зведення (лінеаризація) нелінійної оптимізаційної задачі про розміщення гіперсфери максимального радіусу в опуклу ділянку типу поліедру до задачі лінійної оптимізації. Таким чином, задача про розміщення гіперсфери найбільшого радіусу в поліедрі формулюється як задача лінійної оптимізації. Висновки. Строго доведено можливість лінеаризації задачі про занурення гіперсфери максимального радіусу у поліедр. Задачу зведено до класичної задачі лінійної оптимізації, яка може бути розв’язана відомими методами. Запропонований підхід узагальнюється на задачі довільної скінченої вимірності.

The utilization of project risk monitoring and control practices and their relationship with project success in construction projects

Risk monitoring and control is often poorly implemented in construction projects because of a failure to monitor and manage identified risks. Construction companies experience significant losses due to project managers' lack of project risk monitoring and control in construction projects. Most studies have concentrated on risk identification, risk assessment, and risk analysis processes while neglecting crucial risk management processes of risk control, risk monitoring, and risk response. The lack of research on these three crucial processes highlights a gap in the literature concerning how these processes can increase the delivery of successful projects. The purpose of this study was to examine whether the utilization of project risk monitoring and control practices was related to project success in construction projects in the United States. An electronic survey instrument was used to collect data from a sample of 50 construction project managers in the Dallas-Fort Worth area in the state of Texas, in the United States. Spearman rho correlation analysis was used to examine the relationship between project risk monitoring and control practices and project success. The results of this study indicated that all project risk monitoring and control practices, including risk reassessment, risk audits, contingency reserves analysis, and risk status meetings, were significantly and positively related to project success in construction projects. One of the recommendations presented in this study was that future research should conduct the same study in developing countries to see if the study’s findings remain the same and generalizable. The study concluded that construction organizations should regularly consider the importance and usage of project risk monitoring and control practices and apply them to improve the success rate of a project.

Risk Management Metrics

This chapter describes how risk management deals with the detection, the evaluation and the precedence of the risks in the process of project management. There is always an uncertainty factor related to the decisions of an investment while managing a project. Risk management is a proactive approach to deal with such future events that can lead to slow performance of the software project management. For successful risk management; there are different metrics that have been used in the past and are being getting used in the present for inspecting the progress of a project at specific points in a timeline that help in reducing the amount of risk. For the adoption of effective metrics for risk management, data is required. All of the metrics can be applied to the different domains of project, process and product. The chapter also covers strategies to advance, distinguish, estimate, and forecast the risk management process. A review of the key point indicators (KPIs) are also integrated along with the project metrics to signify the future and the present renderings.

Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

Risk management in the project management system

The article reveals the impact of risks on the implementation of projects of various directions. The mechanism of identifying and managing risks in the project management system is considered in order to make effective management decisions and bring the actual indicators of time, resources and quality to the planned values. The paper uses the SWOT analysis method, which allows strategic planning based on the study of external and internal environment conditions, followed by the formation of four groups: strengths and weaknesses, opportunities and threats. As a result, of the conducted research, a project risk register was formed.

Identification of Factors Affecting Risk Appetite of Organizations in Selection of Mega Construction Projects

Risk appetite is a crucial component that plays a key role in the decision-making process of project risk management. Despite rising scholarly interest in project risk management, risk appetite has received little attention thus far. A well-defined risk appetite ensures that all decisions taken throughout the course of a project are consistent with an organization’s ultimate strategic aim. This research aims to identify the factors affecting the risk appetite of megaproject selection in the construction sector. The study adds to the knowledge of risk appetite in mega construction project selection and qualitatively examines the factors affecting risk appetite. Exploratory research design is used to identify these factors. The factors are identified using semi-structured interviews of 30 practitioners from the top and middle management working on mega construction projects. Thematic analysis was performed using NVIVO academic software. The most highlighted factors are financial attributes, board of directors’ agility, political factors, project location and demographics. The proposed conceptual framework identifies the factors affecting the risk appetite of mega construction project selection. These factors may be utilized as a starting point by construction project organizations to evaluate the risk appetite of a mega construction project. Risk appetite-based project selection will decrease chances of failures, delays, and cost overruns in mega-projects. These factors can be used by researchers as a rationale for developing predictive or descriptive models of project selection based on risk appetite.

A Logic-Based Risk Engineering Approach to Support the Decision-Making Process of Upstream Projects

The exploration and production of hydrocarbons is undeniably a high-risk venture. Uncertainties are in every activity, from the exploration phase up to facilities construction and plants operation. To allow decision makers understanding the uncertainty associated with the decisions they were asked to face, in the 70ies of the past century, when the oil shockwaves upset the entire business world (Bood & Postma, 1997), it was introduced the use of scenario analysis. Since then, stochastic analyses, such as Monte Carlo simulations, started permeating the oil & gas world. Yet, as Lewis et al. (2004) highlighted, despite the benefit greatly outweighs the effort generally required to perform these analyses, managers not seldom refrained themselves from using these tools to support their decision-making processes. And this, as highlighted by Judah (2016), despite risk mitigation is the very core of the oil & gas business as risks at stake are many, namely: drilling risk, subsurface risk, cost & schedule risk, procurement risk, performance risk, health, safety, and environment (HSE) risk, geopolitical risk, and price risk. Today, the energy transition is imposing new challenges to the oil & gas sector. Even amongst those companies that have embraced (quantitative) structured approaches to support their investment decisions, there is another challenge to face: the integration of all risks in one approach capable of capturing the overall complexity of oil & gas projects and highlighting the effects of variations of both endogenous and exogenous risks on the overall profitability of the opportunity at stake (or the portfolio of opportunities). Risks are typically assessed separately by each function with different quantitative approaches that leave grey zones of interpretation where inter-functional risks can grow and create decisional inefficiencies. Aware of this, Eni integrated risk management, started last year a project aimed at enhancing the project risk management process. The innovative approach followed leverages on artificial logic and allows to consider the full life cycle of an investment proposal. In line with the evolution of company's mission and vision, the aim was to assess the project risk in a more comprehensive way by considering endogenous risks (such as permits, drilling, engineering, procurement, construction) jointly with exogenous ones (such as climate change, cyber security, credit, and country). The manuscript explains the methodology used, the results achieved, and the expected benefit for the company in adopting the innovative approach to risk engineering in supporting investments decisions.

Measuring the impact of risk on LCOE (levelized cost of energy) in geothermal technology

Geothermal technology has a high level of uncertainty and, thus, requires thorough risk analysis for economic decisions. The levelized cost of energy (LCOE) is a basic economic analysis widely used in determining an investment or energy mix. Many reputable institutions and government agencies provide LCOE, to which they apply different levels of discount rates to reflect project risk. To this end, the weighted average cost of capital (WACC) is frequently used as a proxy for project risk-adjusted discount rate. However, whether using a higher discount rate for a riskier project is appropriate in calculating LCOE has not been scrutinized. The purpose of this paper is to propose a certainty equivalent method of LCOE as an alternative way for considering risk. We present a theoretical background and formula based on the utility theory, improving the probabilistic LCOE estimation methodology of previous studies. We also perform scenario analysis to show how the certainty equivalent model changes LCOE reflecting different level of risk of the individual variables, which traditional LCOE does not. Additionally, we suggest that the traditional LCOE should be used prudently, recognizing it can distort the result when an individual project has a different level of risk from the industry average.