Explaining monotonic ranking functions

2020 ◽  
Vol 14 (4) ◽  
pp. 640-652
Author(s):  
Abraham Gale ◽  
Amélie Marian
Keyword(s):  
Decision Making ◽  
Selection Process ◽  
A Priori ◽  
Data Distribution ◽  
Synthetic Data ◽  
Decision Processes ◽  
Decision Makers ◽  
Ranking Functions ◽  
High School Admissions ◽  
Parameter Values

Ranking functions are commonly used to assist in decision-making in a wide variety of applications. As the general public realizes the significant societal impacts of the widespread use of algorithms in decision-making, there has been a push towards explainability and transparency in decision processes and results, as well as demands to justify the fairness of the processes. In this paper, we focus on providing metrics towards explainability and transparency of ranking functions, with a focus towards making the ranking process understandable, a priori , so that decision-makers can make informed choices when designing their ranking selection process. We propose transparent participation metrics to clarify the ranking process, by assessing the contribution of each parameter used in the ranking function in the creation of the final ranked outcome, using information about the ranking functions themselves, as well as observations of the underlying distributions of the parameter values involved in the ranking. To evaluate the outcome of the ranking process, we propose diversity and disparity metrics to measure how similar the selected objects are to each other, and to the underlying data distribution. We evaluate the behavior of our metrics on synthetic data, as well as on data and ranking functions on two real-world scenarios: high school admissions and decathlon scoring.

ERP software selection using intuitionistic fuzzy and interval grey number-based MACBETH method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa Said Yurtyapan ◽  
Erdal Aydemir
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Selection Process ◽  
Intuitionistic Fuzzy Set ◽  
Decision Makers ◽  
Software Selection ◽  
Content Type ◽  
Intuitionistic Fuzzy ◽  
Expert Opinions ◽  
Erp Software

PurposeEnterprise Resource Planning (ERP) software which is a knowledge-based design on the interconnective communication of business units and information share, ensures that business processes such as finance, production, purchasing, sales, logistics and human resources, are integrated and gathered under one roof. This integrated system allows the company to make fast and accurate decisions and increases its competitiveness. Therefore, for an enterprise, choosing the suitable ERP software is extremely important. The aim of this study is to present new research on the ERP software selection process by clarifying the uncertainties and find suitable software in a computational way.Design/methodology/approachERP selection problem design includes uncertainties on the expert opinions and the criteria values using intuitionistic fuzzy set theory and interval grey-numbers to MACBETH multi criteria decision making method. In this paper, a new interval grey MACBETH method approach is proposed, and the degree of greyness approach is used for clarifying the uncertainties. Using this new approach in which grey numbers are used, it is aimed to observe the changes in the importance of the alternatives. Moreover, the intuitionistic fuzzy set method is applied by considering the importance of expert opinions separately.FindingsThe proposed method is based on quantitative decision making derived from qualitative judgments. The results given under uncertain conditions are compared with the results obtained under crisp conditions of the same methods. With the qualitative levels of experts reflected in the decision process, it is clearly seen that ERP software selection problem area has more effective alternative decision solutions to the uncertain environment, and decision makers should not undervalue the unsteadiness of criteria during ERP software selection process.Originality/valueThis study contributes to the relevant literature by (1) utilizing the MACBETH method in the selection of the ERP software by optimization, and (2) validating the importance of expert opinions with uncertainties on a proper ERP software selection procedure. So, the findings of this study can help the decision-makers to evaluate the ERP selection in uncertain conditions.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

An Application of the Integrated IBA-TOPSIS Model in Supplier Selection

2015 ◽  
Vol 7 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Ksenija Mandić ◽  
Boris Delibašić ◽  
Dragan Radojević
Keyword(s):  
Decision Making ◽  
Boolean Algebra ◽  
Supplier Selection ◽  
Selection Process ◽  
Real Life ◽  
Decision Makers ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Hidden Knowledge ◽  
Multi Attribute Decision Making

The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don't permit the identification of interdependencies among attributes. Therefore, the aim of this study is to propose a model for selecting suppliers of telecommunications equipment that includes the interaction between attributes. This interaction can model the hidden knowledge needed for efficient decision-making. To model interdependencies among attributes the authors use a recently proposed consistent fuzzy logic, i.e. interpolative Boolean algebra (IBA). For alternatives ranking they use the classical MADM method TOPSIS. The proposed model was evaluated on a real-life application. The conclusion is that decision makers were able to integrate their reasoning into the MADM model using interpolative Boolean algebra.

scholarly journals Application of Multi-Attribute Decision-Making Methods for the Selection of Conveyor

2021 ◽  
Author(s):  
Satyam Fulzele ◽  
Satywan Khatke ◽  
Shubham Kadam ◽  
Avinash Kamble
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Material Handling ◽  
Selection Process ◽  
Decision Makers ◽  
Variable Cost ◽  
Fixed Cost ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process

Abstract In the present time of innovation, conveyor assume an exceptionally indispensable part and have huge significance for material handling in different enterprises. A conveyor is essentially utilized for moving any sort of material from one area to other. It is made with nearer precisions, hence the expense related with manufacturing is additionally high. In this manner, it should work with better productivity. The choice of the best conveyor is a crucial activity for designers. Designers need to recognize different variables that will influence the functionalities of the conveyor system to limit bottlenecks in the system. An efficient methodology should be accomplished for the conveyor selection. Subsequently, the current work aims to the selection process of the best option for conveyor by using four decision making methods such as analytical hierarchy process, technique of order preference by similarity to ideal solution, compromise ranking method and Deng’s similarity based method. The selection is done among four alternatives based on six attributes viz: fixed cost each hour, variable cost each hour, conveyor speed, product width, product weight and flexibility. The analytical hierarchy process is used to determine weights of the attributes based on relative importance of each attribute. It is also observed that A3 conveyor is best suitable conveyor. Hence the above proposed strategies help decision-makers to examine and choose the best conveyor by considering the rank obtained of the alternatives.

ALGORITHM FOR SELECTION OF LAUNCH ELEMENTS IN THE PRESENCE OF A PRIORI INFORMATION ABOUT ITS COMPOSITION AND STRUCTURE

2018 ◽  
pp. 114-119
Author(s):  
O. I. Nemykin
Keyword(s):  
Decision Making ◽  
Loss Function ◽  
Selection Process ◽  
A Priori ◽  
Measurement Information ◽  
A Priori Information ◽  
Space Objects ◽  
Alternative Hypotheses ◽  
Priori Information ◽  
Selection Of

Traditional methods of the theory of statistical solutions are developed for cases of making single-valued two-alternative or multialternative solutions about the class of an object. Assuming the possibility of ambiguous multi-alternative (in the case of solving the problem of selection of space objects of three-alternative) decisions on the classification of of space objects at the stages of the selection process, a modification of the traditional statistical decision making algorithm is required. Such a modification of the algorithm can be carried out by appropriate selection of the loss function. In the framework of the Bayes approach, an additive loss function is proposed, the structure of which takes into account a priori information on the structure and composition of launch elements in relation to the classes «Launch vehicle» and «spacecraft». The algorithm of decision making is synthesized under the conditions of a priori certainty regarding the probabilistic description of the analyzed situation. It is shown that the problem of verifying three-alternative hypotheses can be reduced to an independent verification of three two-alternative hypotheses, which makes it possible to take particular solutions in the solution process and use a different set of the signs of selection for the formation of solutions for individual classes of space objects. The peculiarities of the implementation of the selection algorithm are discussed in the presence of a priori information and measurement information on starts of a limited volume. The synthesized Bayesian decision making algorithm has the properties necessary to solve the problem of selection of space objects at launch in real conditions in the presence of measuring information specified in the form of a training sample. Its architecture allows to form unambiguous and ambiguous decisions about each space object in the launch.

Using Network Analysis to Improve Decision Making for Partner Selection in Inter-Organizational Networks

2013 ◽  
Vol 4 (3) ◽  
pp. 26-39
Author(s):  
Laura Ponisio ◽  
Pascal van Eck ◽  
Lourens Riemens
Keyword(s):  
Decision Making ◽  
Network Analysis ◽  
Best Practices ◽  
Ad Hoc ◽  
Decision Processes ◽  
Decision Makers ◽  
Development Projects ◽  
It Professionals ◽  
Analysis Techniques ◽  
Development Levels

Professionals in decision making roles are often faced with the problem of choosing partners for closer cooperation, for instance, to start new joint IT development projects or for harvesting best practices. The large amounts of information involved in these decision processes obscure possibilities, and therefore choices are made ad hoc. In this article, the authors present an approach that uses concrete data and network analysis to support decision makers in processing and understanding this information. Central in the authors’ approach are questionnaires capturing aspired and current development levels of the processes of the cooperating organizations and graphs generated using network analysis techniques. The advantage of the authors’ approach, which they validated via expert interviews, is that results are semi-automatically translated to visualizations; which in turn offer an overall view of the current and aspired situation in the network without losing the ability to pinpoint particular, individual processes of interest. This, in turn, enables IT professionals to make better decisions.

The Effect of Dynamic and Static Choice Sets on Political Decision Making: An Analysis Using the Decision Board Platform

1997 ◽  
Vol 91 (3) ◽  
pp. 553-566 ◽  
Author(s):  
Alex Mintz ◽  
Nehemia Geva ◽  
Steven B. Redd ◽  
Amy Carnes
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
A Priori ◽  
Decision Makers ◽  
Strategy Selection ◽  
Political Decision ◽  
Choice Sets ◽  
Static Versus Dynamic ◽  
Political Decision Making ◽  
Choice Set

Previous studies of political decision making have used only “static” choice sets, where alternatives are “fixed” and are a priori known to the decision maker. We assess the effect of a dynamic choice set (new alternatives appear during the decision process) on strategy selection and choice in international politics. We suggest that decision makers use a mixture of decision strategies when making decisions in a two-stage process consisting of an initial screening of available alternatives, and a selection of the best one from the subset of remaining alternatives. To test the effects of dynamic and static choice sets on the decision process we introduce a computer-based “process tracer” in a study of top-ranking officers in the U.S. Air Force. The results show that (1) national security decision makers use a mixture of strategies in arriving at a decision, and (2) strategy selection and choice are significantly influenced by the structure of the choice set (static versus dynamic).

scholarly journals Zeno's paradox in decision-making

2016 ◽  
Vol 283 (1828) ◽  
pp. 20160291 ◽  
Author(s):  
James M. Yearsley ◽  
Emmanuel M. Pothos
Keyword(s):  
Decision Making ◽  
Unique Feature ◽  
A Priori ◽  
Decision Processes ◽  
Decision Models ◽  
Quantum Zeno Effect ◽  
Classical Probability ◽  
Opinion Change ◽  
Zeno Effect ◽  
Zeno's Paradox

Classical probability theory has been influential in modelling decision processes, despite empirical findings that have been persistently paradoxical from classical perspectives. For such findings, some researchers have been successfully pursuing decision models based on quantum theory (QT). One unique feature of QT is the collapse postulate, which entails that measurements (or in decision-making, judgements) reset the state to be consistent with the measured outcome. If there is quantum structure in cognition, then there has to be evidence for the collapse postulate. A striking, a priori prediction, is that opinion change will be slowed down (under idealized conditions frozen) by continuous judgements. In physics, this is the quantum Zeno effect. We demonstrate a quantum Zeno effect in decision-making in humans and so provide evidence that advocates the use of quantum principles in decision theory, at least in some cases.

scholarly journals Multicriteria Decision Making Based on Archimedean Bonferroni Mean Operators of Hesitant Fermatean 2-Tuple Linguistic Terms

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-19 ◽  
Author(s):  
Huijuan Wang ◽  
Xin Wang ◽  
Lidong Wang
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Linguistic Terms ◽  
Fundamental Properties ◽  
Bonferroni Mean ◽  
Special Cases ◽  
Geometric Bonferroni Mean ◽  
Parameter Values ◽  
Uncertainty Information

The study is concerned with the representation and aggregation of complex uncertainty information. First, the concept of hesitant Fermatean 2-tuple linguistic sets (HF2TLSs) is introduced for characterizing an individual’s imprecision preferences and assessing information by combining 2-tuple linguistic terms and Fermatean fuzzy sets. The advantage of hesitant Fermatean 2-tuple linguistic information is that it can handle higher levels of uncertainty and express the decision-makers’ hesitancy. Second, we extend Bonferroni mean (BM) operators under the background of HF2TLSs for the sake of their application in information fusion and decision making. The Archimedean t-norm and s-norm- (ATS-) based hesitant Fermatean 2-tuple linguistic weighted Bonferroni mean (A-HF2TLWBM) operator and the ATS-based hesitant Fermatean 2-tuple linguistic weighted geometric Bonferroni mean (A-HF2TLWGBM) operator are developed by considering the interrelationship between any two variables. The main benefit of the proposed operators is that these operators deliver more complete and flexible results compared to existing methods. Moreover, some fundamental properties and special cases are examined by adjusting parameter values. Finally, an approach is designed as a support for handling decision making problems, and an example regarding investment selection is provided to demonstrate the practicality of the designed method with a detailed discussion of parameter influence and comparisons with the existing methods.

Deciding for Responsibility and Legitimation: Alternative Interpretations of Organizational Decision‐Making

2017 ◽  
Author(s):  
Nils Brunsson
Keyword(s):  
Decision Making ◽  
Local Governments ◽  
Empirical Studies ◽  
Decision Processes ◽  
Decision Makers ◽  
Organizational Decision Making ◽  
Empirical Validity ◽  
Organizational Action ◽  
National Governments

Recent studies have questioned the empirical validity of the equating of decision and choice and pointed at another role that organizational decisions sometimes play — the role of mobilizing organizational action, a role that requires less rationality than choice. But choice and mobilization are not the only roles of decision-making and decisions in organizations. This chapter argues that two additional roles exist — decisions may allocate responsibility and legitimacy to decision-makers and organizations. The chapter also considers how the different roles can explain the design of decision processes, the use of information and the number of decisions in organizations. The discussion is based on empirical studies of decision processes in such organizations: in local governments, national governments, and company boards. The eight decision processes studied concern city budgets, investments and disinvestments, and governmental programmes.

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