Search

The main purpose of the paper is to provide and apply the concept and techniques of multi-criteria decision-making under fuzzy environment in the prioritization and selection of projects in a portf...

Project selection for a portfolio is a pivotal decision in the pharmaceutical industry. In this paper, we study a portfolio optimization problem for pharmaceutical companies considering the uncertainty of the cost of each phase of drug development and the specific value of the annual budget. The presented optimization model is suitable to make investment decisions for multi-phase drug development projects and a stochastic approach is applied to handle the uncertainty in the model. Post-optimality analysis for annual budget is studied. An illustrative example is included to demonstrate the presented approach.

Manufacturing organizations are adopting Lean Six Sigma (LSS) and similar process improvement techniques in order to enhance their operational abilities. Irrespective of application of these process improvement programs, organizations are encountering major losses due to poor project selection. This study is carried out to determine the actual project selection process at industry level. Project selection is basically a “Multi-Criteria Decision Making (MCDM)” problem and it involves several factors. During the course of study different LSS project selection factors are identified and compared to select the most suitable project. In this study, leading nine project selection criteria have been shortlisted through literature review and expert opinion. “Best Worst Method (BWM)” is used for weight calculation of the selected criteria for project selection in one of the manufacturing organizations in India. BWM takes fewer steps for weight calculation as compared to various MCDM methodologies. Weight along with Pairwise comparison of projects was utilized to prioritize five different projects which are taken into consideration in this study.

The paper presents the current state of the art of the research in the term of Improvement Project Selection Methods (IPSMs). The study used a process framework approach and a systematic literature review to identify and classify various literature pertaining to IPSMs. In particular, the paper elaborates IPSMs summary taking into account different types of these projects and various types of decision-making method groups. The analysis is performed, including Scopus and Thompson/Reuters Web of Science databases, and determines possible gaps, issues and opportunities for further studies in the scope of the IPSM topic. The most important weaknesses of the analysed methods include: lack of approach that takes into account all IPs, lack of comprehensive criteria, lack of an appropriate method for calculating criteria weights, lack of group decision-making method, not considering limitations/constraints, failure to take into account the psychological conditions of decision-makers, failure to take into account the tendency to change assessments in the future.

One of the primary components of innovation management in research and development (R&D) organizations is project selection. In public sector R&D environments, it is essential that improvements are made to the selection processes. These improvements should address the unique challenges faced by these organizations in order to increase the quality of the decisions that are made. Modern decision support systems (DSS) have the potential to meet these needs. The implementation of effective DSS backed by solid data management practices and driven by artificial intelligence technologies has the potential to enhance the management of public sector R&D innovation.

Trade‐off analysis, one of the key tenets of multi‐objective optimization for the project selection problem in Transportation Asset Management (TAM), can help decision‐makers quantify and ...

In many applications, conservation organizations depend on one species to indicate the presence of another. While extensive research has gone into methods for selecting these indicator species, few studies have directly measured the performance of indicator species in guiding conservation actions. Here, we evaluated whether a small number of indicator species could be used to efficiently select barrier removal projects to restore breeding habitat access for many other Great Lakes migratory fishes in the highly fragmented tributaries of the North American Great Lakes. First, we used a dataset of the historical distributions of 35 species of native migratory fishes to identify four clusters of co-occurring species, and then selected an indicator species for each cluster based on within-group co-occurrence or range width. We evaluated the utility of these indicator species by using upstream habitat and removal costs for 103,894 dams and road culverts across 1800 tributaries of the Great Lakes. We compared the potential increase in accessible tributary habitat for each species when barrier removals were prioritized to maximize benefits for (1) each species itself, versus (2) possible indicator species. We found that for 80% of the species, habitat gains from indicator-based project selection were at least 75% of the maximum gains possible under species-specific planning. However, a small subset of species would receive few habitat gains under indicator-directed project selection. Overall, our findings suggest that a suite of indicator species could be an efficient basis for planning restoration efforts for a majority of native migratory fishes in the Great Lakes.

The project selection problem has attracted significant attention among construction project participants. Typically, a contractor can execute one or more projects from available projects. This study introduces a new strategy to help contractors in evaluating and selecting suitable construction projects. The new strategy is based on identifying multiple criteria that affect construction projects as well as developing and using a model that supports decision based on the analytic hierarchy process. Furthermore, a fuzzy risk analysis model is proposed to analyze and quantify some of the identified criteria to help contractors select minimally risky projects. Market conditions, financial resources, project conditions, time delays, and cost overruns are five identified criteria that control the selection. Through identifying 70 subsidiary factors, the effects and importance of the first three criteria were determined through a field survey, while time delay and cost overrun criteria were analyzed and quantified through the risk analysis model. The new strategy was applied on a real case study comprising two HVAC system projects in the construction industry (project 1 in Egypt and project 2 in Saudi Arabia). Criteria and causes that yield different effects on the new strategy to support contractor decision and selection control are discussed in detail. Risk factors were ranked according to their importance, and their effects on both time and cost were clarified. The results obtained from the investigated case study showed 55.5% support for project 2, and only 44.5% support for project 1. This strategy is applicable to other case studies in different countries with different projects, criteria, and execution activities.

Limited external financing creates a hedging motive that distorts resource allocation for investment projects. I study these distortions through a dynamic model with endogenous collateral constraints. The hedging motive can be broken into three components: expected future productivity, leverage capacity, and current net worth. Although constrained firms behave as if averse to transitory fluctuations in net worth, they can endogenously pursue increased exposure to both persistent factors that predict future productivity and fluctuations in credit tightness. The most constrained firms abstain from financial hedging, while still distorting capital-allocation decisions, thereby influencing firm-level volatility. These distortions contribute to a potential explanation for the negative cross-sectional relationship between volatility and net worth. This paper was accepted by Gustavo Manso, Finance.

Innovation agencies, that is organizations with the primary focus of funding applied research and technological development, evaluate project proposals to select the most promising proposals for funding. At the moment, there is only little verified knowledge available on project evaluation and selection processes of innovation agencies. We want to show how projects are evaluated and selected in these organizations. We want to also make a contribution for better understanding the variety of the utilized processes by pointing out the reasoning behind some of the most important practices. This article therefore focuses on the following questions: How are projects selected in innovation agencies? What are the employed procedures and practices? Are there differences in procedures and practices and what would be the reason for these differences? The basis for answering these questions is a study produced for the European Association of National Innovation Agencies, Taftie. There we have analysed the project selection procedures of 18 programmes run by 12 European innovation agencies. To do so, we have produced an overview of existing selection procedures of the innovation agencies, analysed, and compared the procedures along the stages of a typical selection process. The key points of interest were role of evaluators, selection criteria, ranking procedures, and general process issues.

The integration of two of the biggest giants in the computing world has resulted in the development and advancement of new methodologies in data processing. Cognitive computing and big data analytics are integrated to give rise to advanced technologically sound algorithms like MOIWO and NSGA. There is an important role played by the E-projects portfolio selection (EPPS) issue in the web development environment that is handled with the help of a decision making algorithm based on big data. The EPPS problem tackles choosing the right projects for investment on the social media in order to achieve maximum return at minimal risk conditions. In order to address this issue and further optimize EPPS probe on social media, the proposed work focuses on building a hybrid algorithm known as NSGA-II-MOIWO. This algorithms makes use of the positive aspects of MOIWO algorithm and NSGA-II algorithm in order to develop an efficient one. The experimental results are recorded and analyzed in order to determine the most optimal algorithm based on the return and risk of investment. Based on the results, it is found that NSGA-II-MOIWO outperforms both MOIWO and NSGA, proving to be a better hybrid alternative.

In the second half of the 1950s, when all resources of the Soviet Union were directed at making as fast as possible a nuclear bomb as a weapon of deterrence, scientists did not leave any stone unturned in their efforts to convince the managers of the Soviet nuclear project of the need to begin work on the peaceful use of atomic energy. The story of how a decision was made to create the world’s first NPP and how the reactor design was selected is told on the basis of archival documents, and the role of nuclear industry scientists and managers who influenced the decision is reflected.

The article describes the model of a complex organizational management system where the several approaches are simultaneously implementing: functional, process and design. The relevance of applying integrated assessment mechanisms to management tasks in organizational systems, in particular, to solving the problems of coordinated decision-making, is substantiated. The reasons for the inconsistency of interests in the decision-making process are described. Examples of management tasks in organizational systems are given. The example of solving the problem of selecting projects into a portfolio using the integrated assessment mechanism is considered in detail. A set of evaluation criteria is given and convolution matrices are described. The development plan for the project assessment mechanism including risk assessment, taking into account the rank of expert is proposed.