scholarly journals Decision Making Using Multicriteria Analysis: A Case Study of Decision Modeling Career in Education

2017 ◽  
Vol 4 (2) ◽  
pp. 24 ◽  
Author(s):  
Ioannis Dimitrakopoulos ◽  
Kostas Karamanis
Keyword(s):  
Decision Making ◽  
Multicriteria Analysis ◽  
Multicriteria Decision Making ◽  
Evaluation Framework ◽  
Basic Principles ◽  
Multicriteria Method ◽  
The Right ◽  
The Cost ◽  
The University

The aim of this paper is to offer an applicable evaluation framework relating to the right choice of one’s profession via his/her studies. The first part of the paper consists of the basic principles of Multicriteria Decision Making. To begin with, the paper initially focuses on the Macbeth Method. This helps to provide a perspective for procedural types of decisions in which various qualitative and quantitative aspects are incorporated. In the second part of the paper, the above-mentioned multicriteria method is applied to a “real-world” case concerning a specific case of a student, Eva. For this specific study, it is concluded that the factors of greatest importance that lead to choosing the University Eva finally chose, were four: the cost of undergraduate studies, the reputation-status of the University, its logistics and infrastructure and its interconnections with other Universities and other Academic Institutions.

scholarly journals AHP Method to Support Decision Making for Sustainability

2020 ◽  
Vol 13 (4) ◽  
pp. 32
Author(s):  
Wail El hilali ◽  
Abdellah El manouar ◽  
Mohammed Abdou Janati Idrissi
Keyword(s):  
Decision Making ◽  
Business Models ◽  
Multicriteria Decision Making ◽  
Ahp Method ◽  
Telecom Operator ◽  
Fierce Competition ◽  
The Right ◽  
Scarcity Of Resources ◽  
New Framework

In these challenging times, finding a way to sustain the created value becomes a must. The fierce competition, the risk of disruption, the rise of customer awareness and the scarcity of resources, all these are few of many drivers that push companies to invest in sustainability. This paper is an attempt to enrich the literature about this subject. It mainly explores how to use the AHP method, a well-known multicriteria decision making technique, to decide about the right actions to implement, in order to reach sustainability. The paper is a continuity of a previous work that introduced a new framework that explained how companies could sustain their business models through information systems (IS). This approach was applied on a telecom operator, as a case study, to explain well how companies could choose the right actions to implement, in order to reach sustainability.

scholarly journals A Decision-Making Model Based on TOPSIS, WASPAS, and MULTIMOORA Methods for University Location Selection Problem

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110401
Author(s):  
Pınar Miç ◽  
Z. Figen Antmen
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Sensitivity Analyses ◽  
Population Increase ◽  
Location Selection ◽  
Order Preference ◽  
Criteria Weights ◽  
Product Assessment ◽  
The Right ◽  
The University

With the growing population increase and following young population’s desire to study at the university, political authorities are supporting university and higher education investments, especially in the last 10 years. This situation has increased the number of universities considerably. Because a university will provide socioeconomic dynamism to both the development of the country and the region, choosing the right university location has become a significant problem nowadays. In line with this, this study is focused on supporting the new university location decision in a wide region in Turkey where currently the number of universities in the region is relatively low despite the high population density in the area. Alternative cities to be utilized in the study are determined particularly taking the demographic structure into consideration and various multicriteria decision-making (MCDM) techniques are applied. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Weighted Aggregated Sum Product Assessment (WASPAS), and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) are applied to a real case study. Related criteria and alternative locations are specified by consulting seven experts. Within the study, both the results of these methods are presented, and also sensitivity analyses are conducted to observe how sensitive the results are to the changes in the criteria weights. The results obtained are purposed to aid decision makers in this field.

scholarly journals Aplikasi Penentuan Tunjangan Kinerja dan Rekomendasi Pegawai Universitas Singaperbangsa Karawang

2019 ◽  
Vol 3 (3) ◽  
pp. 191
Author(s):  
Aldi Jakaria ◽  
Ade Andri Hendriadi ◽  
Nina Sulistiyowati
Keyword(s):  
Decision Making ◽  
Employee Performance ◽  
Multiple Attribute Decision Making ◽  
Development Life Cycle ◽  
Multiple Attribute ◽  
Waterfall Model ◽  
Definition Of ◽  
The University

Universitas Singaperbangsa Karawang does not yet have a system and criteria for assessing the performance of non-P3K employees. Currently the staffing office at the University of Singaperbangsa Karawang does not yet have a way to determine how an employee is entitled to a Performance Allowance. Based on these facts, a website-based employee performance allowance information system will be created with a case study of the staff of the singaperbangsa karawang university. The system to be built includes the definition of criteria, data processing to become the best employee recommendation / promotion and determination of Employee Performance Allowances. The methodology used is software engineering and uses the Software Development Life Cycle (SDLC) method with the waterfall model because it is in accordance with the research that will be carried out with a relatively short stage of system usage. The calculation process is done by using the method of fuzzy multiple attribute decision making with weighted product because this method determines the weight value for each attribute, then proceed with a ranking process that will select the best alternative from a number of alternatives. The system created can provide information about the amount of employee performance benefits and recommendations for promotion for employees. After evaluating the user, this system gets a response that is easy to understand and easy to understand on each menu on the system. Looking at the benefits of this system is useful when it will provide performance allowances to employees and at the time will determine the employees who are reconditioned for promotions. The design of employee recommendation decision support systems using fuzzy multiple attribute decision making is done by completing the weighted product to produce alternatives after verification with the existing data getting 60% accuracy.

The Single Most Consequential Thing We Do in Universities

2013 ◽  
pp. 304-329
Author(s):  
Grant Campbell
Keyword(s):  
Decision Making ◽  
Learning Outcomes ◽  
Academic Careers ◽  
Important Thing ◽  
Constructive Alignment ◽  
The University ◽  
University Of Manchester ◽  
Giving Feedback

Assessing students (including giving feedback and making decisions based on assessments) is arguably the single most important thing done in universities in terms of tangible impacts on people’s lives, but assessment is hard to do. Academics are seldom trained in assessment, and for many it is the most worrying aspect of the job. The University of Manchester operates a New Academics Programme for its probationary lecturers, running over three years and encompassing research, teaching, and administrative aspects of academic careers, culminating in a reflective portfolio. This case study describes the introduction of an assessment component into this programme, including its motivation, content, implementation, and evolution, and its reception by the new academics. The assessment component of the New Academics Programme is now delivered in two sessions at different times of the year. The first covers the importance of assessment and gives guidance for designing good assessments and giving feedback. The second session goes more deeply into constructive alignment and learning outcomes, leading on to decision making in exam boards, and ending with a focus on cultivating academic judgement.

Suggested Model for Business Intelligence in Higher Education

Data Mining ◽  
2013 ◽  
pp. 550-566 ◽  
Author(s):  
Zaidoun Alzoabi ◽  
Faek Diko ◽  
Saiid Hanna
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Business Intelligence ◽  
University Management ◽  
Suggested Model ◽  
Business Decision ◽  
Data Mining Approach ◽  
Input Processing ◽  
The University

BI is playing a major role in achieving competitive advantage in almost every sector of the market, and the higher education sector is no exception. Universities, in general, maintain huge databases comprising data of students, human resources, researches, facilities, and others. Data in these databases may contain decisive information for decision making. In this chapter we will describe a data mining approach as one of the business intelligence methodologies for possible use in higher education. The importance of the model arises from the reality that it starts from a system approach to university management, looking at the university as input, processing, output, and feedback, and then applies different business intelligence tools and methods to every part of the system in order to enhance the business decision making process. The chapter also shows an application of the suggested model on a real case study at the Arab International University.

ReS-Algorithm for Converting Normalized Values of Cost Criteria Into Benefit Criteria in MCDM Tasks

2020 ◽  
Vol 19 (05) ◽  
pp. 1389-1423
Author(s):  
Irik Z. Mukhametzyanov
Keyword(s):  
Performance Indicator ◽  
Multicriteria Decision Making ◽  
Measurement Scale ◽  
Multidimensional Data ◽  
Sorting Algorithm ◽  
Data Normalization ◽  
Basic Principles ◽  
Normalization Methods ◽  
The Cost ◽  
Invariant Properties

A review of modern methods of data normalization in the tasks of multicriteria decision-making and multidimensional classification is presented. The invariant properties of linear normalization methods are determined. Two basic principles of normalization of multidimensional data are defined: preservation of dispositions of natural and normalized values on the measurement scale and the absence of a displacement in the areas of normalized values of various criteria relative to each other. A method is proposed for converting normalized values of cost criteria to profit criteria based on the reverse sorting algorithm (ReS-algorithm). The ReS-algorithm preserves the dispositions of the natural and normalized values of the attributes of the alternatives and eliminates the displacement the areas of normalized values of the cost criteria relative to the profit criteria, which ensures the equality of the contributions of various criteria to the performance indicator of the alternatives.

An integrated machine learning: Utility theory framework for real-time predictive maintenance in pumping systems

2020 ◽  
pp. 095440542097051
Author(s):  
Raghad M Khorsheed ◽  
Omer Faruk Beyca
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Utility Theory ◽  
Predictive Maintenance ◽  
Manufacturing Operations ◽  
Pumping Stations ◽  
Bearing Failures ◽  
Temperature Levels ◽  
The Right

Bearings are the most widely used mechanical parts in rotating machinery under high load and high rotational speeds. Operating continuously under such harsh conditions, wear and failure are imminent. Developing defects give rise to even-higher vibration and temperature levels. In general, mechanical defects in a machine cause high vibration levels. Therefore, bearing fault identification and early detection enables the maintenance team to repair the problem before it triggers catastrophic failure in the bearing. Machine downtime is thus avoided or minimized. This paper explores the use of Machine Learning (ML) integrated with decision-making techniques to predict possible bearing failures and improve the overall manufacturing operations by applying the correct maintenance actions at the right time. The accuracy of the Predictive Maintenance (PdM) module has been tested on real industrial production datasets. The paper proposes an effective PdM methodology using different ML algorithms to detect failures before they happen and reduce pump downtime. The performance of the tested ML algorithms is based on five performance indicators: accuracy, precision, F-score, recall, and an area under curve (AUC). Experimental results revealed that all tested ML algorithms are successful and effective. Furthermore, decision making with utility theory has been employed to exploit the probability of failures and thus help to perform the appropriate maintenance interventions. This provides a logical framework for decision-makers to identify the optimum action with the maximum expected benefit. As a case study, the model is applied on forwarding pumping stations belonging to the Sewerage Treatment Company (STC), one of the largest sewage stations in Qatar.

scholarly journals Outsourcing energy retrofitting of hotel buildings: the decision-making process

2019 ◽  
Vol 266 ◽  
pp. 01016 ◽  
Author(s):  
M.F.F. Fasna ◽  
Sachie Gunatilake
Keyword(s):  
Decision Making ◽  
Energy Performance ◽  
Decision Making Process ◽  
Existing Buildings ◽  
Energy Retrofit ◽  
Energy Efficiency Improvement ◽  
Adoption And Implementation ◽  
Energy Service ◽  
The Right

Poor energy performance of existing buildings worldwide has led to a crucial need to retrofit existing buildings to minimise energy consumption. Among the existing buildings, hotels use as much as 50% of their total expenses on energy and offer significant opportunities for energy efficiency improvement. Yet, comparatively the level of implementation of energy retrofits found to be low, which has attributed to, inter alia, the absence of a clearly defined process for ensuring the delivery of energy retrofit projects and lack of proactive guidance for project teams to ensure that they make the right decisions at the right time to achieve the desired outcomes. Since many energy retrofit projects in existing hotels are carried out with the involvement of an external contractor, or an Energy Service Company (ESCO), this study focuses on investigating the decision-making process in implementing energy retrofits when the project is outsourced to an external party. An in-depth case study is used to obtain insights into the critical decisions to be taken and key activities to be performed throughout the decision-making process. The findings are used to propose a step-by-step decision-making process comprising of three key phases: i.e., pre-retrofit, retrofit implementation and post-retrofit. It is hoped that the decision-making process developed in this study will serve as a roadmap for the effective adoption and implementation of energy retrofits in existing hotel buildings when an external contractor is involved.

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