The construction process is inherently prone to risks. Risk management is an essential and integral part of project management on all construction projects. Risk analysis is one of the core components of risk management that enables professionals to quantify and analyze risks that may pose potential threats to project performance in terms of various parameters. This research was conducted to identify and analyze risks associated with residential construction in Bangalore. In this study, risk and its impact on time and cost was identified and analyzed. Schedule impacts of project risks were supplemented by conducting quantitative risk analysis such as Monte Carlo simulation and sensitivity analysis using the Primavera risk analysis software. In case of cost, the cost variance was found out and mitigation measures were given. Thus, by effectively managing the risks, organization has more timely, comprehensive and deeper understanding of risks which in turn facilitates better decision making and confidence to take on new ventures or even to accept higher level of risk.

Outbreak response can be viewed as a project for which the window of opportunity for planning is often quite limited. Therefore, regular evaluation for sharing the lessons learned is crucial, especially in the cases of national and global crises. As one of the major global concerns, the novel coronavirus, also known as COVID-19, has infected and killed many people in several countries worldwide. Hence, it is worth analyzing the performance of different countries in this regard. In this paper, the confirmed Case Fatality Rate (cCFR), and the confirmed Case Recovery Rate (cCRR) are considered as the main performance criteria, and the data are analyzed utilizing statistical confidence intervals (CIs) implemented in Python. The results identify the regions with high cCFR and low cCRR, as well as the regions with low cCFR and high cCRR. Finally, it is suggested to systematically transfer the knowledge and lessons learned from the high performing countries to where such information and knowledge is needed.

Nowadays, with the increasing number of projects in organizations, managers are enthusiastic about managing and controlling projects, and as projects become more complex and cause unforeseen risks, project management becomes even more critical. Using the earned value management method to control the current status of projects, and predicting the future status of projects has had many advantages. Representing the status of the project, and predicting the project performance by various indicators are some features of this method. As these indicators are deterministic, the risk of the prediction increases when the number of risks goes up in a project. Therefore, statistical methods can be employed to estimate the statistical distribution of risks and notably boost predicting accuracy. The purpose of this paper is to present a method for predicting project duration and cost of the project and selecting the best action plan. Control charts are used along with the earned value management method to increase accuracy. This model also provides the possibility of selecting the best action plan to improve project performance. Moreover, this method can be applied in each project phase separately. Finally, a case study is used to investigate the validity of the proposed method.

Distinguishing and diminishing risks in today’s projects are crucial for project success. Almost every project is facing several risks throughout the project timeline. Construction projects in Finland are also facing project risks due to the complexity of the project. To minimize the impact of risks, an effective risk management approach must be incorporated into every project which also includes the effectiveness and measurement of its performance. Managing the risks is an important job but measuring the RM performance is crucial. Thus, the objective of this study is to analyze the risk management (RM) and risk management performance measurement (RMPM) through an indepth empirical analysis of two complex construction projects of Finland. To achieve the objective, a qualitative case study is followed by the authors of this article to identify the RM processes, major and minor risks of the projects, RM strategies to mitigate them and RM performance measurement strategies. Overall, this article provides a comparative analysis of RM and RMPM for construction projects and it can be used as a basis for further research into RM perspective in complex construction projects.

The objective of this study is to identify factors affecting the performance of the construction investment project management in Vietnam. The author conducted a survey at 458 small and medium sized enterprises in Hanoi, Da Nang and Ho Chi Minh City. The author used SPSS 20.0 software for analysis, some analytical methods were used such as: descriptive statistical methods; Evaluate the reliability of Cronbach's Alpha reliability coefficient and Exploratory Factor Analysis (EFA) method. We calculated the average value of the scale to assess the influence of independent factors on the dependent variable. Multivariate regression analysis method was also used to test the suitability of the research model. The research results indicate that the effectiveness of construction investment project management in Vietnamese enterprises was affected by factors including (1) Consultants; (2) Investor; (3) Contractors; (4) Capital sources; (5) External factors and (6) Advantages in the implementation process of construction investment projects. Moreover, two factors, the advantages in the project implementation process and the external factors, had the most effects on the effectiveness of construction investment project management of small and medium enterprises in Vietnam.

This paper aims to shed light on whether the Merger & Acquisition (M&A) among several cases create values for Vietnam small and medium enterprises (SMEs). Using 48 months of actual data to compare the pre- and post- merger performance, the study evaluates the impacts of the M&A on business performance collected from HOSE stock exchange website. The result shows that out of 11 chosen key performance indicators (KPIs) and those selected firms only we have 2 KPIs with better results while 6 KPIs do not change and 3 KPIs are even worse after the M&A. In addition, the finding indicated that very few actions were implemented and hence unsurprisingly, the M&A outcomes did not really match with firms’ original expectations. From the theory and the actual results of the analysis, the study provides a number of practical areas that companies should focus on to increase the chance of success for their M&A.

Project scheduling models with resource constraints and multi-mode activities aims to create a schedule for carrying out activities considering precedence constraints and available resources in order to minimize the project duration. In the real world, we face uncertainty related to projects, where there are no historical data, hence, we should rely on the experts' judgements to estimate activity durations. For this purpose, in this paper, the 99-simulation method is used to deal with uncertainty. The exact mathematical programming model is presented in this paper and the hybrid algorithm based on Genetic Algorithm is used to solve this type of project scheduling problem which finds the near-optimal solution in a short computational time. Finally, the effectiveness of the proposed model is examined with a numerical example.

Every nation in the globe endeavours to achieve sustainable growth in its various industries. The construction industry has an enormous contribution to the economy primarily for the developed nations experiencing urgent demands to develop and expand their infrastructure. While this expansion is taking place through projects, it is essential to find the factors affecting completion of project premium. This paper investigates the main time delay and cost overrun causes in construction projects within Oman related to clients, contractors, and consultants. Through a comprehensive literature review, reasons for delays and cost overrun are determined and a survey targeting 100 project managers was conducted to indicate top causes among them. The findings may help the government develop better policy and construction firms to modify criteria procedures to avoid such drawbacks.

The main issue for portfolio managers is to find a feasible schedule that guarantees the availability of the resources required by the activities at the dates they are scheduled, which is the classical objective of the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP). This paper goes one step further and presents an algorithm that solves the RCMPSP where each project has a different priority for the organization. With this information, the algorithm uses a market-based mechanism to determine what activities should receive preferential treatment during the scheduling process. Therefore, among the multiple possible schedules that comply with the resource constraints (i.e. the solution provided by classical approaches to RCMPSP), our approach allows obtaining a schedule for the portfolio in which, beyond minimizing the duration of the portfolio, the activities are scheduled considering the portfolio manager’s priorities.

Resource-Constrained Project and Multi-Project Scheduling Problems (RCPSPs and RCMPSPs) have been essential topics of study over the last three decades. Both prob-lems consist of activities that must be scheduled subject to precedence and resource constraints. This paper surveys studies of RCPSPs and RCMPSPs under consideration of four categories of project activities, simply recorded as categories A, B, C, and D. Category A refers to activities can be performed using fixed resources along The Y-axis over fixed durations along The X-axis, and cannot be interrupted. Category B applies to activities that can be performed using the same type of resource in category A but can be interrupted. Category C refers to activities that can be performed using flexible resources over flexible durations and cannot be interrupted. Category D refers to activities can be performed using flexible resources over flexible durations and can be interrupted. Many algorithms have been developed to solve the RCPSPs and RCMPSPs when activities are classified individually under category A, B, or C. However, in practice, welding, cutting or assembly activities in a manufacturing projects for an oil cargo can be under a new category so-called D. The project manager can speed up or slow down these activities by allocating or removing more resources, and these activities can be interrupted or can be resumed at any time. From the perspective of activity categories, we intend to review the literature on RCPSPs and RCMPSPs and to obtain the new research directions for solving the problems.