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Journal articles on the topic 'Decision-making methods'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 May 2022

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1

Kostenko, Elena, Volodymyr Kuznichenko, and Volodymyr Lapshyn. "Comparison of Decision-Making Methods Comparison of Decision-Making Methods." Research in Applied Economics 6, no. 3 (August 26, 2014): 17. http://dx.doi.org/10.5296/rae.v6i3.5704.

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2

Schmitt, Richard. "Methods of Democratic Decision-Making." Radical Philosophy Review 21, no. 1 (2018): 129–51. http://dx.doi.org/10.5840/radphilrev20184385.

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The paper reflects on the methods democratic systems use for arriving at decisions. The most popular ones are elections where the majority rules and deliberative democracy. I argue that both of these do not measure up to the demands of democracy. Whether we use voting with majority rule or deliberative methods, only a portion of the citizenry is allowed to rule itself; minorities are always excluded. Instead of voting with majority ruler or deliberative methods, I suggest that we employ mediation (ADR) to reach agreement in democratic publics.

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3

Holmes-Rovner, Margaret. "Methods for Medical Decision Making." Medical Decision Making 12, no. 3 (August 1992): 159–62. http://dx.doi.org/10.1177/0272989x9201200301.

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4

Lahtinen, Tuomas J., Raimo P. Hämäläinen, and Juuso Liesiö. "Portfolio decision analysis methods in environmental decision making." Environmental Modelling & Software 94 (August 2017): 73–86. http://dx.doi.org/10.1016/j.envsoft.2017.04.001.

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5

N, Harikannan. "Decision Making Model for Supplier Evaluation and Selection Using MCDM Methods." Bonfring International Journal of Industrial Engineering and Management Science 4, no. 2 (May 9, 2014): 76–82. http://dx.doi.org/10.9756/bijiems.10303.

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6

Sokurenko, Ihor. "Classification of management decision making methods." Scientific Bulletin of the Odessa National Economic University 6, no. 269 (2019): 161–77. http://dx.doi.org/10.32680/2409-9260-2019-6-269-161-177.

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7

Carter, Kimbroe J., Nathan P. Ritchey, Frank Castro, Leonard P. Caccamo, Edward Kessler, and Barbara A. Erickson. "Analysis of Three Decision-making Methods." Medical Decision Making 19, no. 1 (January 1999): 49–57. http://dx.doi.org/10.1177/0272989x9901900107.

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8

Gvinepadze, Gela, and Tornike Shavishvili. "Methods for improving decision-making efficiency." Works of Georgian Technical University, no. 1(515) (March 26, 2020): 80–93. http://dx.doi.org/10.36073/1512-0996-2020-1-80-93.

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9

Renn, Ortwin, Birgit Blättel-Mink, and Hans Kastenholz. "Discursive methods in environmental decision making." Business Strategy and the Environment 6, no. 4 (September 1997): 218–31. http://dx.doi.org/10.1002/(sici)1099-0836(199709)6:4<218::aid-bse117>3.0.co;2-g.

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10

Zeng, Shouzhen. "Uncertain Intelligent Computational Decision-Making Methods." Recent Advances in Computer Science and Communications 14, no. 8 (February 19, 2021): 2465–66. http://dx.doi.org/10.2174/266625581408210219152347.

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11

Azadfallah, Mohammad. "Multi-Criteria Decision Making for Ranking Decision Making Units." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (January 2018): 17–36. http://dx.doi.org/10.4018/ijpmat.2018010102.

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There is no doubt the Data Envelopment Analysis (DEA) is a powerful method for the efficiency evaluation of Decision Making Units (DMUs) with multiple inputs and outputs. Despite its usefulness, DEA has some notable limitations. A significant drawback with this approach is that inability to fully rank the DMUs. In the extant literature, different methods for this purpose have been suggested. While, in the traditional method the first step for the DEA approach is used, and results of this step are input for the DEA ranking method in the second step. To reduce the computational complexity of the traditional method, a new Multiple Criteria Decision Making (MCDM) approach is proposed in this article. In the proposed approaches, one step can achieve full ranking for all DMUs. The results show that although out of 20 DMUs are first in the final ranking ordered by the DEA, the author proposed methods can consider full ranking. Agreement of the proposed methods with the existing approaches are measured by the Spearman's rank correlation coefficient technique. The findings of this study reveal that TOPSIS, Neo-TOPSIS, and AHP ranking results are consistent with the DEA ranking method. Therefore, these proposed methods appear as the possible alternatives to the DEA and DEA ranking models.

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12

Čabala, Ján, and Ján Jadlovský. "Solving Optimal Assembly Line Configuration Task by Multi-objective Decision Making Methods." Acta Electrotechnica et Informatica 17, no. 2 (June 1, 2017): 53–60. http://dx.doi.org/10.15546/aeei-2017-0017.

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13

Kashi, Kateřina, and Jiří Franek. "Applying Group Decision Making and Multiple Attribute Decision Making Methods in Business Processes." Applied Mechanics and Materials 693 (December 2014): 237–42. http://dx.doi.org/10.4028/www.scientific.net/amm.693.237.

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The aim of this applied research is to focus on real-life application of multiple attribute decision making (MADM) methods and their adaptation in a way which can be acceptable for business practice. The study will apply the group decision making methods on a Balanced Scorecard (BSC) as a type of performance measurement and strategic decision making. The study is mainly concerned with multiple criteria decomposition method of analytic network process (ANP) method, WINGS technique and entropy. This group of methods had been already applied in several business domains. However, majority of the implementation was only presented as an example how it could work in practice, but they were not investigated from the perspective of how much information they could provide to the management. In this paper, proposed methods will be used to determine which criteria are most important for the company within the Balanced Scorecard and results of all methods will be compared. The aim of this study is, by utilizing group MADM approach, to discover the areas of the BSC which must be improved so that a total performance increases.

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14

Jain, Satish Kumar. "A Decision Making in Selection of Bricks Using Multiple Attribute Decision Making Methods." European Journal of Engineering Research and Science 5, no. 12 (December 29, 2020): 121–25. http://dx.doi.org/10.24018/ejers.2020.5.12.2292.

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All building materials such as brick, cement, paint, lime, steel, glass, etc. of various brands with small variation in their specifications and cost are available in the markets of construction. It becomes very difficult for contractors, engineers, and owners to make right choice of materials logically to maintain good quality and minimum cost of the work. Improper choice may result in either bad quality or higher cost. Multiple Attribute Decision Making Methods are very helpful in selection of any material. These methods have been used largely in various fields of engineering for deciding best of available options. This paper presents an overview of Simple Additive Weighting Method (SAW), Weighted Product Method (WPM) and Analytical Hierarchy Process (AHP) methods which can be simply and successfully used for selection of bricks.

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15

Jain, Satish Kumar. "A Decision Making in Selection of Bricks Using Multiple Attribute Decision Making Methods." European Journal of Engineering and Technology Research 5, no. 12 (December 29, 2020): 121–25. http://dx.doi.org/10.24018/ejeng.2020.5.12.2292.

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All building materials such as brick, cement, paint, lime, steel, glass, etc. of various brands with small variation in their specifications and cost are available in the markets of construction. It becomes very difficult for contractors, engineers, and owners to make right choice of materials logically to maintain good quality and minimum cost of the work. Improper choice may result in either bad quality or higher cost. Multiple Attribute Decision Making Methods are very helpful in selection of any material. These methods have been used largely in various fields of engineering for deciding best of available options. This paper presents an overview of Simple Additive Weighting Method (SAW), Weighted Product Method (WPM) and Analytical Hierarchy Process (AHP) methods which can be simply and successfully used for selection of bricks.

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16

Agayev, F. B. "Analytical support of the procedural decision-making process." Mathematical machines and systems 4 (2020): 20–32. http://dx.doi.org/10.34121/1028-9763-2020-4-20-32.

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In the process of legal research, private scientific methods are developed and used to study legal reality, such as the method of comparative jurisprudence, the method of interpretation (explanation) and the formal legal method. However, at the present stage of legal research, it is impossible to be limited only by these methods. Even legal scholars who consistently defend the status of dogmatic jurisprudence recognize that the application of these methods, with all their merits, sets a limiting framework in un-derstanding the practical action of positive law and the originality of its theoretical vision. Nevertheless, the application of these methods in the study of legal reality allows us to draw a conclusion about the general trends in the development of evaluative concepts that are fundamental in civil procedural law. It is offered an approach to the formation of a system of information support of procedural decision-making based on the application of fuzzy inference mechanism implemented in the logical basis of the feedforward multilayer neural network. Under this approach, a method to overcome the semantic uncer-tainty in the evaluation terms of procedural law is developed by using appropriate terms (fuzzy sets) of corresponding linguistic variables. As an example it is selected the Articles on “Violation of copyright or neighboring rights” of the Criminal Code of the Azerbaijan Republic based on which has been proposed formalism for the evaluation concept of “significant harm” in relation to the sanction applied. For mak-ing an adequate to evaluation concept notion it is proposed grading scale of possible sanctions, obtained on the basis of the description of the relevant legal norms in terms of fuzzy implicative rules.

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17

Rábová, I., V. Konečný, and A. Matiášová. "Decision making with support of artificial intelligence." Agricultural Economics (Zemědělská ekonomika) 51, No. 9 (February 20, 2012): 385–88. http://dx.doi.org/10.17221/5124-agricecon.

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  Development of software modules for decision support is currently a basic trend in the creation of enterprise Information Systems (IS). The IS is basically a support system of the enterprise Decision System, therefore we can regard it as a very important factor of the competition ability and enterprise prosperity. Conventional IS modules provide the enterprise managers a lot of useful information. Nevertheless, own decision process in view of difficulty, complexity or creation disability of decision process model is very often problematic. This contribution is oriented by its content to appropriate choice realization of modules for support decision processes by using of artificial intelligence methods.      

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18

Covello, Vincent T. "Decision Analysis and Risk Management Decision Making: Issues and Methods." Risk Analysis 7, no. 2 (June 1987): 131–39. http://dx.doi.org/10.1111/j.1539-6924.1987.tb00978.x.

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19

Wu, Wenshuai, Gang Kou, and Yi Peng. "Group decision-making using improved multi-criteria decision making methods for credit risk analysis." Filomat 30, no. 15 (2016): 4135–50. http://dx.doi.org/10.2298/fil1615135w.

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Credit risk analysis is a core research issue in the field of financial risk management. This paper first investigates the analytic hierarchy process (AHP) as a method of measuring index weights for group decision-making (GDM). AHP for group decision-making (AHP-GDM) is then researched and applied, taking into full account the cognitive levels of different experts. Second, the concept of grey relational degree is introduced into the ideal solution of the technique for order of preference by similarity to ideal solution (TOPSIS). This concept fully considers the relative closeness of grey relational degree between alternatives and the ?ideal? solution in order to strengthen their relationship. The AHP-GDM method overcomes the problem of subjectivity in measuring index weights, and the revised TOPSIS (R-TOPSIS) method heightens the effectiveness of assessment results. An illustrative case using data from Chinese listed commercial banks shows that the R-TOPSIS method is more effective than both TOPSIS and grey relational analysis (GRA) in credit risk evaluation. The two improved multi-criteria decision making (MCDM) methods are also applied to empirical research regarding the credit risk analysis of Chinese urban commercial banks. The results indicate the validity and effectiveness of both methods.

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20

Peniwati, Kirti. "Criteria for evaluating group decision-making methods." Mathematical and Computer Modelling 46, no. 7-8 (October 2007): 935–47. http://dx.doi.org/10.1016/j.mcm.2007.03.005.

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21

Vaddavalli, PravinK, Rashmi Deshmukh, JagadeshC Reddy, and ChristopherJ Rapuano. "Phototherapeutic keratectomy: Indications, methods and decision making." Indian Journal of Ophthalmology 68, no. 12 (2020): 2856. http://dx.doi.org/10.4103/ijo.ijo_1524_20.

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22

Baranov, V. V. "Structures and methods of dynamical decision-making." Nonlinear Analysis: Theory, Methods & Applications 30, no. 5 (December 1997): 2827–33. http://dx.doi.org/10.1016/s0362-546x(97)00131-4.

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23

Vergeer, Ineke, and John Lyle. "Mixing Methods in Assessing Coaches' Decision Making." Research Quarterly for Exercise and Sport 78, no. 3 (June 2007): 225–35. http://dx.doi.org/10.1080/02701367.2007.10599420.

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24

Randolph, John, and Michael Bauer. "IMPROVING ENVIRONMENTAL DECISION-MAKING THROUGH COLLABORATIVE METHODS." Review of Policy Research 16, no. 3-4 (June 24, 2005): 168–91. http://dx.doi.org/10.1111/j.1541-1338.1999.tb00882.x.

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25

San Cristóbal, José Ramón. "Contractor Selection Using Multicriteria Decision-Making Methods." Journal of Construction Engineering and Management 138, no. 6 (June 2012): 751–58. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000488.

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26

Molnár, Sándor. "New Methods of Decision Making Under Uncertainty." International Journal of Economic Behavior and Organization 3, no. 2 (2015): 5. http://dx.doi.org/10.11648/j.ijebo.s.2015030201.12.

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27

Kadane, Joseph B. "Bayesian methods for health-related decision making." Statistics in Medicine 24, no. 4 (2005): 563–67. http://dx.doi.org/10.1002/sim.2036.

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28

Lansdowne, Zachary F. "Ordinal ranking methods for multicriterion decision making." Naval Research Logistics 43, no. 5 (August 1996): 613–27. http://dx.doi.org/10.1002/(sici)1520-6750(199608)43:5<613::aid-nav2>3.0.co;2-8.

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29

Solomon, David H. "Geriatric Assessment: Methods for Clinical Decision Making." JAMA: The Journal of the American Medical Association 259, no. 16 (April 22, 1988): 2450. http://dx.doi.org/10.1001/jama.1988.03720160070033.

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30

Solomon, D. H. "Geriatric assessment: methods for clinical decision making." JAMA: The Journal of the American Medical Association 259, no. 16 (April 22, 1988): 2450–52. http://dx.doi.org/10.1001/jama.259.16.2450.

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31

Lapiga, A. G., and V. V. Polyakov. "On statistical methods in fuzzy decision-making." Fuzzy Sets and Systems 47, no. 3 (May 1992): 303–11. http://dx.doi.org/10.1016/0165-0114(92)90295-f.

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32

Charles, Joni S., and Cecilia Temponi. "Enhancing analytical methods of collective decision making." Atlantic Economic Journal 25, no. 4 (December 1997): 428. http://dx.doi.org/10.1007/bf02298353.

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33

Zakay, Dan. "Decision making in action: Models and methods." Acta Psychologica 85, no. 3 (May 1994): 263–64. http://dx.doi.org/10.1016/0001-6918(94)90039-6.

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34

Gombitová, Dagmar, and Dušana Dokupilová. "Innovative Expert Methods in Strategic Decision Making." Quality Innovation Prosperity 26, no. 1 (March 31, 2022): 90–109. http://dx.doi.org/10.12776/qip.v26i1.1643.

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Purpose: This study introduces managerial techniques applied for the first time in the high-level strategic public policy decision-making process in Slovakia with an aim to assess the strategic decision-making of groups of experts in a methodologically supported environment. It compares groups of internal analysts and external specialists and should demonstrate the extent to which these two groups are able to process problems analytically and suppress intuition. Methodology/Approach: Multi-criteria decision methods are used when deciding on complex problems. One of the most popular and most frequently used is the Analytic Hierarchy Process. Application of this method enables measurement of preference consistency, and its relationship with cognitive reflection. Findings: Consistency of judgement was very similar in both groups. The prioritisation of measures resulted in a similar set of priorities determined by both groups. The assumed relationship of consistency and cognitive reflection score and/or overconfidence was not detected, and decision makers proved to be well calibrated. Research Limitation/Implication: The main limitation of our research was the small sample size of decision makers, which complied with the requirements of the decision method, but was not sufficient to confirm the statistical validity. Originality/Value of paper: The introduction of the multi-criteria decision method into decision-making for public policy strategies combines practical policy exercises with scientific research on high-stakes decisions and enables to carry out participatory decision-making process with relevant stakeholders.

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35

Kochin, Dmitry, and Leonas Ustinovičius. "VERBAL DECISION MAKING ANALYSIS." Technological and Economic Development of Economy 10, no. 1 (March 31, 2004): 32–39. http://dx.doi.org/10.3846/13928619.2004.9637650.

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The paper presents the ideology of a qualitative approach to decision making ‐ verbal decision analysis. The authors have analyzed existing quantitative approaches and pointed out their main disadvantages. They formulated the requirements for decision‐making methods taking into account these disadvantages: psychological correctness of a dialog with decision maker (DM), strict mathematical proof of the methods and checking of DM information for consistency. The authors present the results of research on psychological correctness of operations of preference elicitation from DM. Several existing verbal decision analysis methods are briefly mentioned.

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36

YU, Xiaohan, Zeshui XU, and Shousheng LIU. "SYSTEMATIC DECISION MAKING: A EXTENDED MULTI-CRITERIA DECISION MAKING MODEL." Technological and Economic Development of Economy 23, no. 1 (January 22, 2017): 157–77. http://dx.doi.org/10.3846/20294913.2016.1212121.

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Considering some complex multi-criteria decision making (MCDM) problems, in which decision environment is dynamic, there are various interdependences among criteria, and plans (systematized alternatives) consisting of multiple time sequential interdependent actions, cannot be well handled by means of the existing MCDM methods, therefore, we develop a systematic decision making (SDM) as an improvement and supplement of the classic MCDM in this paper. The SDM is for prescribing methods of evaluating and selecting the most favourite plan (a system) from a group of feasible ones concerning influences of time-varying criteria system under dynamic external environment. Through detailed analysis, we separate a SDM problem into multi-period MCDM subproblems, and then a plan can be a combination of time sequential strategies in which each strategy (a subset of actions) is a feasible decision choice of corresponding MCDM sub-problem. After clarifying variety of interdependences, interactions and interrelationships in the SDM problems, such as criteria-interdependences, action-interdependences, interactions between criteria and criteria system, interactions between actions and strategies, interactions between strategies and plans, interactions between internal environment (criteria system) and external environment, feedbacks from external environment to the corresponding MCDM sub-problems, and interrelationships among MCDM sub-problems and so on, we transform the SDM into multi-period interrelated MCDM model which can be dealt with more easily by using multiple optimization models. At the end of the paper, three typical properties of the SDM are proposed and most of the existing MCDM models are pointed out as special cases of the SDM.

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37

Saaty, Thomas L., and Daji Ergu. "When is a Decision-Making Method Trustworthy? Criteria for Evaluating Multi-Criteria Decision-Making Methods." International Journal of Information Technology & Decision Making 14, no. 06 (November 2015): 1171–87. http://dx.doi.org/10.1142/s021962201550025x.

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Decision makers often face complicated decision problems with intangible and conflicting criteria. Numerous multi-criteria decision-making (MCDM) methods have been proposed to handle the measurement of the priorities of conflicting tangible/intangible criteria and in turn use them to choose the best alternative for a decision. However, the presence of many MCDM methods bewilders users. The existence of these methods becomes a decision problem in itself, and decision makers may be uncertain about which one to use. Thus the comparative analysis and evaluation of various MCDM methods has come under scrutiny by both researchers and practitioners in order to discover if there are logical, mathematical, social or practical reasons why one method is better than another. Criteria for their evaluation are the first important issue that needs to be resolved. In this paper, 16 criteria are introduced that may be used to judge and evaluate various MCDM methods. The criteria proposed and some guidelines for their evaluation are given to help readers evaluate these MCDM methods.

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38

Triantaphyllou, Evangelos, and Stuart H. Mann. "An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox." Decision Support Systems 5, no. 3 (September 1989): 303–12. http://dx.doi.org/10.1016/0167-9236(89)90037-7.

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39

McCreery, Ann M., and Edmond Truelove. "Decision making in dentistry. Part II: Clinical applications of decision methods." Journal of Prosthetic Dentistry 65, no. 4 (April 1991): 575–85. http://dx.doi.org/10.1016/0022-3913(91)90302-d.

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40

Mashego, Maite Sara. "Lone ranger decision making versus consensus decision making: Descriptive analysis." Journal of Governance and Regulation 4, no. 4 (2015): 548–52. http://dx.doi.org/10.22495/jgr_v4_i4_c4_p12.

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Consensus decision making, concerns group members make decisions together with the requirement of reaching a consensus that is all members abiding by the decision outcome. Lone ranging worked for sometime in a autocratic environment. Researchers are now pointing to consensus decision-making in organizations bringing dividend to many organizations. This article used a descriptive analysis to compare the goodness of consensus decision making and making lone ranging decision management. This article explored the models, roles, tools and methods of consensus decision making. The results were that consensus decision making brings people together and cements the relationship among employees. The lone ranger’s decision is only consented to by staff but inwardly disagreeable resulting in short term benefits but long term collapse of organizations.

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41

Wei, Guiwu, and Xiaofei Zhao. "METHODS FOR PROBABILISTIC DECISION MAKING WITH LINGUISTIC INFORMATION." Technological and Economic Development of Economy 20, no. 2 (June 28, 2014): 193–209. http://dx.doi.org/10.3846/20294913.2014.869515.

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With respect to decision making problems by using probabilities, immediate probabilities and information that can be represented with linguistic labels, some new decision analysis are proposed. Firstly, we shall develop three new aggregation operators: generalized probabilistic 2-tuple weighted average (GP-2TWA) operator, generalized probabilistic 2-tuple ordered weighted average (GP-2TOWA) operator and generalized immediate probabilistic 2-tuple ordered weighted average (GIP-2TOWA) operator. These operators use the weighted average (WA) operator, the ordered weighted average (OWA) operator, linguistic information, probabilistic information and immediate probabilistic information. They are quite useful because they can assess the uncertain information within the problem by using both linguistic labels and the probabilistic information that considers the attitudinal character of the decision maker. In these approaches, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, we give an illustrative example about selection of strategies to verify the developed approach and to demonstrate its feasibility and practicality.

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42

Bahashova, Natalia, Hanna Matukova, and Lllia Kulchikovskyi. "EFFICIENCY OF DECISION-MAKING METHODS IN PROJECT MANAGEMENT." Scientific Journal of Polonia University 32, no. 1 (April 3, 2019): 47–52. http://dx.doi.org/10.23856/3205.

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The research contains analysis and characteristics of existing decision-making methods applicable to project management theory. It is aimed at determining appropriate decision-making methods for various objects of a project manager.

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43

Pearman, Alan, Gerard Colson, and Christian de Bruyn. "Models and Methods in Multiple Criteria Decision Making." Journal of the Operational Research Society 42, no. 3 (March 1991): 262. http://dx.doi.org/10.2307/2583325.

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44

Walters, Tyler. "Contemporary Archival Appraisal Methods and Preservation Decision-Making." American Archivist 59, no. 3 (July 1996): 322–38. http://dx.doi.org/10.17723/aarc.59.3.w4th5pp861802870.

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45

Pearman, Alan. "Models and Methods in Multiple Criteria Decision Making." Journal of the Operational Research Society 42, no. 3 (March 1991): 262. http://dx.doi.org/10.1057/jors.1991.58.

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46

Böckenholt, Ulf, and Elke U. Weber. "Use of formal Methods in Medical Decision Making." Medical Decision Making 12, no. 4 (December 1992): 298–306. http://dx.doi.org/10.1177/0272989x9201200409.

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47

Antucheviciene, Jurgita, Zdeněk Kala, Mohamed Marzouk, and Egidijus Rytas Vaidogas. "Decision Making Methods and Applications in Civil Engineering." Mathematical Problems in Engineering 2015 (2015): 1–3. http://dx.doi.org/10.1155/2015/160569.

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48

Odu, G. O. "Weighting methods for multi-criteria decision making technique." Journal of Applied Sciences and Environmental Management 23, no. 8 (September 11, 2019): 1449. http://dx.doi.org/10.4314/jasem.v23i8.7.

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49

Akram, Muhammad, Ghous Ali, Neha Waseem, and Bijan Davvaz. "Decision-making methods based on hybrid mF models." Journal of Intelligent & Fuzzy Systems 35, no. 3 (October 1, 2018): 3387–403. http://dx.doi.org/10.3233/jifs-172282.

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50

LeBoeuf, Robyn A., and Eldar Shafir. "Problems and methods in naturalistic decision-making research." Journal of Behavioral Decision Making 14, no. 5 (2001): 373–75. http://dx.doi.org/10.1002/bdm.392.

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