A Decision Support Approach for R&D Project Selection

With the rapid development of science and technology, new technology is starting to be used in various fields including education. Education has a very important progress in a nation, because it can optimize individual potential. The educational process in higher education has a big influence on a student's future. However, there are many students who experience difficulties in choosing a college major after graduating from vocational high school (SMK) or senior high school (SMA), because of the complexity in identifying the suitability between interests and study programs. Decision making is a problem that everyone faces, especially in choosing an appropriate college major. There are many factors to consider, and with many options available, the decision-making process can be difficult. To overcome this problem, this research aims to create a decision support system (DSS) using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique For Order By Similarity To Ideal Solution) methods. The AHP method is used to solve complex problems by structuring a hierarchy of criteria and developing weights or priorities. However, when the AHP method is used with many criteria and alternatives, other methods are needed for more effective results. Therefore, a combined method of AHP and TOPSIS was chosen, where AHP focuses on pairwise comparison matrices and consistency analysis, while TOPSIS can measure relative performance and alternative decision making simply and efficiently. The results of research on decision support systems for selecting majors using the AHP and TOPSIS methods show that the application of the combined AHP-TOPSIS method can be used to determine the best alternative in selecting majors by comparing alternatives based on predetermined criteria. In addition, system testing results show that the system functions as expected and meets user needs. With a decision support system for selecting college majors implemented on the website, it can simplify the decision-making process for students and BK teachers in choosing college majors. The results of the calculation of the percentage of system feasibility in blackbox testing show a value of 95.71%, which indicates that this major selection decision support system website can be used.

Six-Sigma project selection using national quality award criteria and Delphi fuzzy multiple criteria decision-making method

A number of studies have been carried out on the factors determining port choice, derived from the perspectives of shippers, carriers or both. Recently, some studies using multi-criteria analysis, more specifically Saaty's analytical hierarchy process (AHP), have been undertaken to address port competitiveness and port selection by shipping lines. Based on a review of the literature on port selection, this article proposes a decision support system (DSS) for port selection using AHP methodology. The proposed DSS is web-based and thus it can be accessed by more decision makers and data collection can be carried out faster. Moreover, AHP addresses the issue of how to structure a complex decision problem, identify its criteria, measure the interaction among them and finally synthesise all the information to arrive at priorities, which depict preferences. AHP is able to assist port managers in obtaining a detailed understanding of the criteria and address the port selection problem utilising multi-criteria analysis. This article presents the architecture and the port selection procedure of the web-based DSS, and then illustrates three different cases. It shows how technology advancement can bring positive effects of strategic planning to shipping firms.

A simulation model that attempts to include simplified market and production characteristics of a hypothetical firm and a specific project selection decision mechanism is constructed. Three types of projects are assumed to exist—projects whose impact is to increase market share, decrease production cost and increase production capacity. An experiment aimed at two questions is conducted. The questions are (1) Do different market conditions affect project selection decisions and (2) over time, what patterns of project selection emerge. In the model and experiment, an attempt is made to capture the essence of Abernathy and Utterback's model of the innovation process so that it may be applied to more specific settings. Observed project selection patterns over time indicate an apparent relationship between market share increasing and production cost decreasing projects and Abernathy and Utterback's concept of product innovation, and similarly between capacity increasing projects and process innovation. The model can be viewed as an attempt at developing a linkage between the environment of a firm and an “iterative decision mechanism” as proposed by Baker and Sweeney.

Large infrastructure projects are high cost investments devoted to the construction and operation of long life, specific assets, characterized by demand uncertainty and irreversibility. Besides these technical characteristics, the usual institutional setting for the proposal, evaluation and selection of projects, is one of different agents in a context of asymmetric information, with their own, and sometimes conflicting, objective functions. The selection of large investment projects in a multi-government setting, as it is the case within the European Union, deserves some modelling of the decision taking process. Many infrastructure projects co-financed by the European Commission can be treated as investments proposed by a Member State, approved and partially financed by the Commission. Once it is assumed that the objective function of the European Commission and any Member State may differ it is worth examining the consequences in terms of the incentives in the actual system of selection and finance of large infrastructure projects. This paper addresses the adverse selection problem which may be favouring the construction of socially undesirable projects from a European perspective. One way out of this is a better design for project selection introducing alternative mechanism with new incentives aimed to the efficient allocation of public funds. Meanwhile, to gather new information can help in the screening of projects. This paper deals with the problem of increasing the information available through the use of known cost ranges and values determinant in the social profitability of high speed rail investment projects. The idea is to inverse the evaluation process, and to figure out the demand threshold required for a positive net social benefit, instead of estimating the net social benefit of the project given a demand forecast. This does not mean that the present incentives to inefficient investment will change, but relevant information on the starting demand volumes required for a project to be socially profitable will help in the discussion on the ranking of projects competing for public money.

The development of information and communication technology makes it easier for users in the industrial world to make decisions in choosing environmentally friendly suppliers more easily. This study aims to determine the selection of green suppliers of all the criteria that have been determined and make a decision support system for selecting green suppliers with the Fuzzy Inference System method. The method used in making identification of green supplier selection is to create criteria based on fuzzy rules and to make digital business modeling using business process modeling notation. Decision support there are 4 criteria used, namely price, reject quality, late delivery and environmental management. Based on the results of research conducted it is known that with the fuzzy inference system method that is assisted using matlab software, the optimization results on the fuzzy inference system show that prices are 20.5%, quality is 5.5%, environment is 5.5%, and material delays are 3%, then supplier performance in selecting green suppliers with a decision making system of 55% so that green supplier selection is obtained at abrasive companies.

A decision support system for fuzzy multi-objective multi-period sustainable project selection

As a relatively young software company, PT. Hexavara Tech needs to select incoming projects since the number of requests exceeds the amount that the company can manage. Currently, there are no guidelines for selecting projects, so the project selection process is less structured and subjective. In fact, project selection is faced with several qualitative and quantitative criteria that tend to be conflictual in achieving objectives. So in this study, the integration of Analytical Hierarchy Process (AHP) and Goal Programming (GP) methods is used to select software projects that consider limitations and multi-objectivity. Based on the calculation of the level of importance of the criteria using AHP, the sequence of project selection criteria is obtained, namely profit for the company (0.287), potential development of the project scope (0.155), initial development capital (0.1), the opportunity to get relations from clients (0.097), conformity to team capabilities (0.093), risks contained (0.078), increasing the value of the company's portfolio (0.073), the opportunity to create a template for the next project (0.07), and the opportunity to learn new technology (0.047). After the optimization process using GP, the best final results are obtained, namely the e-wallet development project of savings and loan cooperatives, development of an android-based online motorcycle taxi application, development of e-commerce design works, development of overseas money transfer applications, and development of a website framework for cross border e-commerce

Summary form only given. The management of the early phases of R&D is one of the most challenging tasks the management of a company encounters. R&D project selection is even more challenging, since it is made in a distributed environment, where the departments of a company have their own divergent objectives and strategies. The scattered expertise inside the company needs to be collected and combined to an effective R&D project selection solution. This paper describes the development of a groupware tool for R&D project selection. The tool was developed by combining AHP (analytic hierarchy process) with the groupware abilities of LotusNotes/Domino. A GDSS-laboratory (group decision support system) was utilized during the planning phase of the development to define the requirements for the tool. The tool covers the whole R&D project selection process from idea gathering to the final analysis phase. The tool supports the cooperation of experts from different departments to synthesize their knowledge and to define the best projects in a distributed, global company environment.

The problem of electric network expansion has different implications concerning the definition of criteria for the comparison of different candidate projects. Transmission expansion planning usually involves a set of economic and technical influences on market framework and on network operation over defined scenario evolutions, or even combining generation and transmission planning, although the application to real-sized networks usually implies cost-benefit analysis. In this paper, a methodology for performance analysis of a set of network development projects is proposed, including zonal market framework and load flow analysis, in order to individuate possible candidate projects and their influence on active power losses, admissible load increase and admissible renewable generation increase. Those merit indicators are compared among candidate projects by means of Analytic Hierarchy Process (AHP) method, aiming at determining the most promising solution under different weights of criteria. Moreover, the influence of network development investment cost on project selection is assessed by means of an extension of AHP. The procedure is applied to yearly operation of NREL-118 test system.

This study aims to provide recommendations for gaming laptops using the AHP method with criteria for Hardware used, Graphics Card, Design, Cooling System, Reliability, Connectivity, Price, so that it becomes a solution for gamers in choosing the right laptop for gaming. The decision support system for gaming laptop selection recommendations developed is implemented using the Analytical Hierarchy Process (AHP) method. Where the AHP method can describe complex multi-factor or multi-criteria problems into a hierarchy, then the importance of each variable is given a subjective numerical value to be compared with other variables through a paired comparison matrix. Based on the assessment results using the AHP method, a recommendation for choosing the first gaming laptop by Dell Gaming G15 with a value of 0.806, the second model recommendation was obtained by Acer Nitro with a value of 0.5745, the third model recommendation was obtained by MSI Bravo 15 B5DD with a value of 0.524.

The Analytic Hierarchy Process (AHP) is a powerful decision-making tool for handling complex, multi-criteria situations. Developed by Thomas L. Saaty in the 1970s, AHP structures problems into a hierarchical format, enabling the systematic evaluation of alternatives based on multiple criteria through pairwise comparisons and numerical scales. Consequently, this chapter explores AHP’s methodology, practical applications, and implementation strategies. It provides a detailed guide on the AHP process, from problem definition and hierarchy structuring to conducting pairwise comparisons, calculating priorities, and synthesizing results. The chapter includes diverse case studies illustrating AHP’s utility in domains such as VMCPU frequency selection for task scheduling, project selection, supply chain management, strategic planning, environmental sustainability, and healthcare. Practical implementation advice covers structuring decision hierarchies, ensuring consistency in pairwise comparisons, performing sensitivity analyses, and addressing challenges such as subjective judgments and data quality issues. The chapter concludes with recommendations for effectively applying AHP, highlighting the importance of stakeholder involvement, transparency, and integrating AHP with other decision-making tools. Emphasizing the flexibility and broad applicability of AHP, the chapter underscores its value in facilitating informed and transparent decision-making in various contexts.

Within a dynamic setting, optimal corporate strategy management for a multi-division corporation involves restructuring a portfolio of Strategic Business Units (SBUs) periodically so as to maximize the firm's market value. Real option theory has been applied to model and explain managerial flexibility for both project selection and operational decisions. In general, optimal corporate strategy has focused on strategic environments and characteristics of business units rather than on managerial flexibility. In this article, we develop a feasible discrete-time model for optimal corporate strategy that incorporates both endogenous and exogenous factors and is consistent with the value-based criterion for maximizing shareholders’ wealth.

Having made a globalisation decision, a contracting firm subsequently needs to make market selection decisions that are influenced by the level of uncertainty or the risks involved, the probability of winning the bid and the expected profitability, or based on generally expected utility. This paper aims to develop a globalisation entry decision-supporting tool integrating resource-based view (RBV), dynamic capabilities and Porter’s generic value chain for international project selection. Through the combination of a questionnaire survey and an interview survey analysed by partial least squares structural equation modelling, a globalisation entry decision-supporting tool for facilitating project selection decision for contractors venturing internationally was developed. This study attempts the usage of an anomaly-seeking method in combining theories from three streams of strategic management concepts – namely, RBV, dynamic capabilities and Porter’s generic value chain theories – into an integrated decision-supporting tool for risk forecasting and project selection in the international construction market. This study contributes to the knowledge of risk assessment by enhancing the current international entry decision tools with a firm’s capability component. The model developed enables a firm to be informed of the combination of the firm’s capabilities needed to lower the exposure to certain risks.

The ambiguous proposal evaluation problem