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.

Project stakeholder management deals with managing and fulfilling stakeholder expec-tations and has tended to focus on the stakeholders of the organization or the project viewpoint. The thematic, spatial and temporal objects of the research were to analyze the stakeholders and projects portfolio determination based on key stakeholders of a public university in Iran in 2019. In first step, stakeholders are identified. There are 12 stakeholder groups involved the university under study. In the second step using the power/interest matrix, stakeholder categorization and positioning was performed. In the following, a mathematical model for optimizing the portfolio of projects was presented and solved. This model was developed to maximize college profit while simultaneously considering the expectations and the requirements of four key stakeholders - the board of trustees, faculty members, researchers and the Ministry of Science. These findings may mainly reflect the strategic decisions at the university.

Over the past four decades, portfolio selection has been one of the most important con-cerns of researchers, project managers, project-oriented companies, and public agencies around the world. Although numerous studies have been done in this field, still there is a room for more improvement in both theory and practice. One of the yet unspoiled topics in this field is improving and balancing the efficiency of sub-portfolios while paying attention to portfolio optimization. This study employs data-mining tools to categorize projects into sub-portfolios and rank them. Multiple Criteria Decision Making (MCDM) methods are also used to weigh the criteria on which the ranking process is based. Finally, a novel multi-objective model is designed to optimize the efficiency of sub-portfolios and the gain of the main portfolio. The model is solved by NSGA II algorithm. This study introduces a hybrid framework by which project portfolio selection process can be carried out regarding strategic alignment, cost, and risk.

The volume of rural road construction projects has increased over the last decade in Bangladesh though these projects are experiencing failure in terms of time for completion. Therefore, this study focuses on nine risk factors specifically in case of Bangladesh. The objectives are to examine and quantify the contribution of supply chain risk factors on completion time of rural road projects and to assess the prioritization of iden-tified risks. An insignificant number of researches have been performed on the effect of supply chain risks on completion time of rural roads in Bangladesh. To the best of authors’ knowledge, the three factors such as, upper contract price, prolong rainy season and time of monitoring have not yet been used as independent variables in any re-search. A linear model has been drawn and the proposed model shows that upper contract price, delay of the site handover, delay of site materials mobilization, change of scope and prolong rainy season cause time overrun, whereas, time of monitoring, delay in payment and delay in submission of contract schedule did not have significant effect on time. These findings will help the government of Bangladesh take the necessary actions to complete the projects on time.

The Health Care system is changing from the hospitalization to the home care, and the World Health Organization has announced that the rate of care-dependent elderly people in Europe will considerably increase within the next decades. Thus, scientific planning for this area is an essential factor to improve the community health. This paper aims to develop a mathematical modeling for Home Health Care Routing and Scheduling Problem and to solve it by means of Simulated Annealing (SA) algorithm considering real condition (staff vehicle traveling, conditions of patients and so forth). We permit interdependent services for patients in which they can order as many services as they want with any relation between them (Multiple Services) and supposed time window for each service. The mathematical formulation of the problem is coded in GMAS software, which is a well-known commercial software for solving optimization problems. In addition, for large-scale problems where GAMS is unable to solve, SA algorithm is applied to tackle the problems. Finally, sensitivity analysis on the most important parameters (number of services and number of patients with interdependent Multiple services) are conducted. The results reveal that when each patient can order infinite services with any relation between them, complexity of the problem increases, but SA algorithm can solve large instances with reasonable solution in the less computational time. Thus, SA algorithm shows a rational performance for large instances. Moreover, the most important factors that affect the objective value and the run time of the problems are number of patients, and number of patients with interdependent multiple services.