scholarly journals Embedding Crowd-Vote as Knowledge Source to Support Decision Making on University Program Selection

2021 ◽  
Vol 12 (3) ◽  
pp. 2120-2128
Author(s):  
Ismail, S Et.al
Keyword(s):  
Decision Making ◽  
Recommendation System ◽  
Influential Factors ◽  
Constructive Feedback ◽  
Expert Opinions ◽  
Freshmen Students ◽  
Program Selection ◽  
Thinking Process ◽  
First Time ◽  
Support Decision Making

Crowd-vote has implemented as a part of a university program recommendation system, complementing the aspect of knowledge management.  The recommendation system is developed to support freshmen students’ decision making during program selection and uses for first time of enrolment.  The challenges of decision-making among students is formed by many influential factors like family, agents, universities and others.  Popular decision making models include rational, intuitive, among others. Rational models have series of sequential steps that involve a thinking process, while intuitive models are more on people experiences and recognition of the pattern based on what people believe and think how it will work.  Other models attempt to combine both rational and intuitive aspects of decision. The challenge is foreseen in capturing experts’ opinion as part of students’ decision making, since experts are the good source of knowledge to strengthen the process.  A prototype is developed for this purpose and constructive feedback from experts and students were collected to examine the significant use of crowd-vote using questionnaire survey. The objectives of this paper are to investigate the use of crowd-vote in leveraging decision making, and to evaluate the implementation of crowd-vote in supporting decision making during program selection.  The results from expert opinions and students’ evaluation are discussed.

scholarly journals Thinking Fast and Slow: A CBR Perspective

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Srashti Kaurav ◽  
Devi Ganesan ◽  
Deepak P ◽  
Sutanu Chakraborti
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Human Cognition ◽  
Case Based Reasoning ◽  
Machine Learning Model ◽  
Intuitive Decision Making ◽  
Thinking Process ◽  
Real World Datasets ◽  
First Time ◽  
Fast Decision

In a path-breaking work, Kahneman characterized human cognition as a result of two modes of operation, Fast Thinking and Slow Thinking. Fast thinking involves quick, intuitive decision making and slow thinking is deliberative conscious reasoning. In this paper, for the first time, we draw parallels between this dichotomous model of human cognition and decision making in Case-based Reasoning (CBR). We observe that fast thinking can be operationalized computationally as the fast decision making by a trained machine learning model, or a parsimonious CBR system that uses few attributes. On the other hand, a full-fledged CBR system may be seen as similar to the slow thinking process. We operationalize such computational models of fast and slow thinking and switching strategies, as Models 1 and 2. Further, we explore the adaptation process in CBR as a slow thinking manifestation, leading to Model 3. Through an extensive set of experiments on real-world datasets, we show that such realizations of fast and slow thinking are useful in practice, leading to improved accuracies in decision-making tasks.

scholarly journals What drives inter-organisational knowledge management? The cause and effect analysis using a multi-layer multi-criteria decision-making framework

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hannan Amoozad Mahdiraji ◽  
Moein Beheshti ◽  
Vahid Jafari-Sadeghi ◽  
Alexeis Garcia-Perez
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Literature Review ◽  
Influential Factors ◽  
Extensive Literature ◽  
Sustainable Competitive Advantage ◽  
Effect Analysis ◽  
Content Type ◽  
Expert Opinions ◽  
Managerial Implications

Purpose Knowledge management seeks collaborative practices among organisations to generate technical, adapt and share knowledge to obtain a sustainable competitive advantage in cross-border business activities. This paper aims to disentangle the crucial determinants of knowledge management in inter-organisational arrangements settings. Design/methodology/approach In the first stage, after an in-depth literature review, the main knowledge management drivers are identified. In the second stage, based on the identified drivers, the importance and relationship between the drivers are evaluated by expert opinions from academic and executive activists. Eventually, in the last stage, a multi-layer decision-making approach has been proposed and used to determine the relationship and the importance of the drivers. Findings The findings of this paper assess the ranking of the different elements from experts’ opinions and discuss important theoretical and managerial implications. The influential factors were identified through an extensive literature review, which combined with the views of experts from academia and industry (international firms). Furthermore, the ranking of factors based on the experts’ overall opinion was used to discuss theoretical and managerial contributions. Originality/value This research provides a better understanding of the interrelationships between the key drivers of knowledge management, which helps management draw more effective strategies to address the cultural differences between firms. Moreover, understanding of the importance of the systems and structures that define the nature of the collaboration in inter-organisational settings, as well as the risks related to those are presented in this research.

scholarly journals An E-Commerce Recommendation System Based on Dynamic Analysis of Customer Behavior

2021 ◽  
Vol 13 (19) ◽  
pp. 10786
Author(s):  
Farah Tawfiq Abdul Hussien ◽  
Abdul Monem S. Rahma ◽  
Hala B. Abdulwahab
Keyword(s):  
Decision Making ◽  
Recommendation System ◽  
Technological Development ◽  
Absolute Error ◽  
Customer Behavior ◽  
Experimental Results ◽  
User Interest ◽  
The Right ◽  
Realistic Prediction ◽  
Support Decision Making

The technological development in the devices and services provided via the Internet and the availability of modern devices and their advanced applications, for most people, have led to an increase in the expansion and a trend towards electronic commerce. The large number and variety of goods offered on e-commerce websites sometimes make the customers feel overwhelmed and sometimes make it difficult to find the right product. These factors increase the amount of competition between global commercial sites, which increases the need to work efficiently to increase financial profits. The recommendation systems aim to improve the e-commerce systems performance by facilitating the customers to find the appropriate products according to their preferences. There are lots of recommendation system algorithms that are implemented for this purpose. However, most of these algorithms suffer from several problems, including: cold start, sparsity of user-item matrix, scalability, and changes in user interest. This paper aims to develop a recommendation system to solve the problems mentioned before and to achieve high realistic prediction results this is done by building the system based on the customers’ behavior and cooperating with the statistical analysis to support decision making, to be employed on an e-commerce site and increasing its performance. The project contribution can be shown by the experimental results using precision, recall, F-function, mean absolute error (MAE), and root mean square error (RMSE) metrics, which are used to evaluate system performance. The experimental results showed that using statistical methods improves the decision-making that is employed to increase the accuracy of recommendation lists suggested to the customers.

scholarly journals Penerapan Fuzzy SAW untuk Rekomendasi Penentuan Penerima Bantuan Pembangunan Rumah Tidak Layak Huni

2020 ◽  
Vol 2 (1) ◽  
pp. 36-42
Author(s):  
Rony Arzian ◽  
Zaenal Abidin ◽  
Pahrul Irfan ◽  
Muhammad Yunus
Keyword(s):  
Decision Making ◽  
Recommendation System ◽  
Black Box ◽  
Fuzzy Variables ◽  
The Poor ◽  
The Social ◽  
Weight Value ◽  
Manual Testing ◽  
Support Decision Making

Construction of Non-Habitable Homes (RTLH) is a government program managed by thesupervision of the Social Service (Dinas Sosial) in the form of housing construction assistancefunds for the poor. In its realization, assistance is still often found to be lacking on target. It isbecause the determination of beneficiaries is not correctly selected, and there are no standardmethods based on existing criteria. These problems require a system that can providerecommendations that conform to clear standards and use techniques that accounted. FuzzySimple Additive Weighting (SAW) method is one method used in decision making. This methodcalculates criteria to get ranking weights to support decision making. The process of selectingcriteria and determining fuzzy variables carried out as a primary process in this method. Afterthe fuzzification weight value obtained, ranking done to use as a reference in the decision makingof recipients. Based on the results of manual testing, the system made is under the effects ofmanual calculations with a level of accuracy reaching 100%, so that implemented as a basis formaking decisions. While testing, the black box system found that all the requirements tested canrun following the overall system functionality. With this recommendation system, it can help thedecision to find the recipients of the Fund for Non-Occupable Homes Construction Assistanceso that it is more targeted.

IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Rahma Hayati ◽  
Mesran Mesran ◽  
Taronisokhi Zebua ◽  
Heri Nurdiyanto ◽  
Khasanah Khasanah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Knowledge Based ◽  
Computer Based ◽  
Support Decision Making ◽  
Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

Doping in sports – conscious lack of interest or ethical Everest?

2017 ◽  
Vol 65 (4) ◽  
Keyword(s):  
Decision Making ◽  
General Population ◽  
Medical Setting ◽  
Doping In Sports ◽  
Physician Relationship ◽  
Pharmaceutical Agents ◽  
Similar Development ◽  
Level Performance ◽  
Elite Sports ◽  
Support Decision Making

Within a clinical sports medical setting the discussion about doping is insufficient. In elite-sports use of pharmaceutical agents is daily business in order to maintain the expected top-level performance. Unfortunately, a similar development could be observed in the general population of leisure athletes where medical supervision is absent. As a sports physician you are facing imminent ethical questions when standing in between. Therefore, we propose the application of a standardised risk score as a tool to promote doping-prevention and launch the debate within athlete-physician-relationship. In the longterm such kind of risk stratification systems may support decision-making with regard to «protective» exclusion of sporting competition.

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