Search results

1

Analysis of complex decision problems based on cumulative prospect theory

100%

DUDZIŃSKA-BARYŁA R.

Operations Research and Decisions

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2018

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vol. 28

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issue 3

5-16

EN

Complex risky decision problems involve sequences of decisions and random events. The choice at a given stage depends on the decisions taken in the previous stages, as well as on the realizations of the random events that occurred earlier. In the analysis of such situations, decision trees are used, and the criterion for choosing the optimal decision is to maximize the expected monetary value. Unfortunately, this approach often does not reflect the actual choices of individual decision makers. In descriptive decision theory, the criterion of maximizing the expected monetary value is replaced by a subjective valuation that takes into account the relative outcomes and their probabilities. This paper presents a proposal to use the principles of cumulative prospect theory to analyse complex decision problems. The concept of a certainty equivalent is used to make it possible to compare risky and non-risky alternatives.

2

Energy prosumers: profiling the energy microgeneration market in Lower Silesia, Poland

88%

ROPUSZYŃSKA-SURMA E., WĘGLARZ M., SZWABIŃSKI J.

Operations Research and Decisions

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2018

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vol. 28

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issue 1

75-94

EN

Microgeneration of energy has the potential to become an important component of the energy policy of many governments, because it may substantially lower carbon emissions and reduce the need for new infrastructure. Nevertheless, from recent studies it follows that, even in the developed countries, microgeneration technology is far from being widely adopted. In this study, we use data collected in a survey conducted in Lower Silesia, a south-western region of Poland, to build behavioural profiles of energy consumers, in order to get some insights into barriers to microgeneration becoming extensively adopted. In particular, we exploit the decision tree method to determine typical attributes of potential prosumers, to find the relative importance of these attributes and, finally, to make some predictions based on data that were not used in constructing the model. From our findings, it follows that economical criteria are the most important triggers for considering the installation of microgeneration technologies. Thus any governmental initiative promoting pro-ecological behaviours, including the use of renewable energy sources, should be based primarily on financial incentives to succeed.

3

On the right approach to selecting a quality improvement project in manufacturing industries

88%

TEWARI P. C., MITTAL K., KHANDUJA D.

Operations Research and Decisions

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2017

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vol. 27

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issue 1

105-124

EN

Continuous improvement is the core of any successful firm. Talking about manufacturing industries, there is huge potential for continuous improvement to be made in various work areas. Such improvement can be made in any section of industry in any form such as quality improvement, waste minimization, system improvement, layout improvement, ergonomics, cost savings, etc. This case study considers an example of a manufacturing firm which wanted to start a quality improvement project (QIP) on its premises. Various products were available, but with dwindling quality levels. However, the real task was the choice of a product for upcoming QIP, as it is well known that success heavily depends upon the selection of a particular project. This is also because of the amount of effort in terms of time, money and manpower that is put into a project nowadays. The authors’ objective was to compare three techniques, namely, cost of poor quality (COPQ), conditional probability and fuzzy TOPSIS for selecting the right project based on this specific firm. The pros and cons of these approaches have also been discussed. This study should prove to be instructive for the realization of QIPs in similar types of industry.

4

Machine-learning methods in the classification of water bodies

88%

Sołtysiak M., Blachnik M., Dąbrowska D.

Environmental & Socio-economic Studies

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2016

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vol. 4

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issue 2

34-42

EN

Amphibian species have been considered as useful ecological indicators. They are used as indicators of environmental contamination, ecosystem health and habitat quality., Amphibian species are sensitive to changes in the aquatic environment and therefore, may form the basis for the classification of water bodies. Water bodies in which there are a large number of amphibian species are especially valuable even if they are located in urban areas. The automation of the classification process allows for a faster evaluation of the presence of amphibian species in the water bodies. Three machine-learning methods (artificial neural networks, decision trees and the k-nearest neighbours algorithm) have been used to classify water bodies in Chorzów – one of 19 cities in the Upper Silesia Agglomeration. In this case, classification is a supervised data mining method consisting of several stages such as building the model, the testing phase and the prediction. Seven natural and anthropogenic features of water bodies (e.g. the type of water body, aquatic plants, the purpose of the water body (destination), position of the water body in relation to any possible buildings, condition of the water body, the degree of littering, the shore type and fishing activities) have been taken into account in the classification. The data set used in this study involved information about 71 different water bodies and 9 amphibian species living in them. The results showed that the best average classification accuracy was obtained with the multilayer perceptron neural network.

5

Application of selected data mining techniques in unintentional accounting error detection

75%

Papík M., Papíková L.

Equilibrium. Quarterly Journal of Economics and Economic Policy

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2021

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vol. 16

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issue 1

185-201

EN

Research background: Even though unintentional accounting errors leading to financial restatements look like less serious distortion of publicly available information, it has been shown that financial restatements impacts on financial markets are similar to intentional fraudulent activities. Unintentional accounting errors leading to financial restatements then affect value of company shares in the short run which negatively impacts all shareholders. Purpose of the article: The aim of this manuscript is to predict unintentional accounting errors leading to financial restatements based on information from financial statements of companies. The manuscript analysis if financial statements include sufficient information which would allow detection of unintentional accounting errors. Methods: Method of classification and regression trees (decision tree) and random forest have been used in this manuscript to fulfill the aim of this manuscript. Data sample has consisted of 400 items from financial statements of 80 selected international companies. The results of developed prediction models have been compared and explained based on their accuracy, sensitivity, specificity, precision and F1 score. Statistical relationship among variables has been tested by correlation analysis. Differences between the group of companies with and without unintentional accounting error have been tested by means of Kruskal-Wallis test. Differences among the models have been tested by Levene and T-tests. Findings & value added: The results of the analysis have provided evidence that it is possible to detect unintentional accounting errors with high levels of accuracy based on financial ratios (rather than the Beneish variables) and by application of random forest method (rather than classification and regression tree method).

6

Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

75%

Yukselturk E., Ozekes S., Türel Y. K.

European Journal of Open, Distance and E-Learning

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2014

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vol. 17

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issue 1

118-133

EN

This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies Self-Efficacy Scale, Readiness for Online Learning Questionnaire, Locus of Control Scale, and Prior Knowledge Questionnaire). The collected data included 10 variables, which were gender, age, educational level, previous online experience, occupation, self efficacy, readiness, prior knowledge, locus of control, and the dropout status as the class label (dropout/not). In order to classify dropout students, four data mining approaches were applied based on k-Nearest Neighbour (k-NN), Decision Tree (DT), Naive Bayes (NB) and Neural Network (NN). These methods were trained and tested using 10-fold cross validation. The detection sensitivities of 3-NN, DT, NN and NB classifiers were 87%, 79.7%, 76.8% and 73.9% respectively. Also, using Genetic Algorithm (GA) based feature selection method, online technologies self-efficacy, online learning readiness, and previous online experience were found as the most important factors in predicting the dropouts.

7

Decision Tree Approach to Discovering Fraud in Leasing Agreements

63%

Horvat I., Pejić Bach M., Merkač Skok M.

Business Systems Research Journal

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2014

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vol. 5

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issue 2

61-71

EN

Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories.

8

Cyfryzacja osób będących na emeryturze w krajach europejskich w okresie pandemii COVID-19

63%

Jajko-Siwek A.

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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2023

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vol. 67

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issue 1

1-23

EN

The use of digital technologies plays an increasingly important role in the daily lives of all European citizens, regardless of their age, place of residence, gender or health. The article aims to determine whether there has been a change in the level of pensioners’ digital capability in European countries during the COVID-19 pandemic. The article uses data on 14,788 respondents from the SHARE 50+ Corona Survey 2. Changes in the level of digitization were analyzed using classification trees and on the variables related to the acquisition of new technological skills, such as: searching for information on public services, financial management, and buying or selling items or services online. The obtained results indicate that the pensioners’ digital capability during the COVID-19 pandemic increased in the younger age groups, between the ages of 50 and 70, as well as among retirees living in Greece. The change in the level of digitization is related to a greater extent to the frequency of making purchases via internet than to other variables.

PL

Zastosowanie technologii cyfrowych odgrywa coraz większą rolę w codziennym życiu wszystkich mieszkańców Europy niezależnie od ich wieku, miejsca zamieszkania, płci czy stanu zdrowia. Celem artykułu jest przedstawienie zmiany poziomu cyfryzacji emerytów w krajach europejskich w czasie pandemii COVID-19.W artykule wykorzystano dane dotyczące 14 788 respondentów z badania panelowego SHARE 50+ Corona Survey 2. Dokonano analizy zmian w zakresie poziomu cyfryzacji, wykorzystując drzewa klasyfikacyjne oraz zmienne dotyczące nabywania nowych umiejętności technologicznych, takich jak: wyszukiwanie informacji dotyczących usług publicznych, zarządzanie finansami oraz kupowanie lub sprzedaż przedmiotów lub usług online. Uzyskane wyniki wskazują, że poziom cyfryzacji emerytów w czasie pandemii COVID-19 podniósł się w grupach osób młodszych wiekowo, między 50. a 70. rokiem życia, a także wśród emerytów mieszkających w Grecji. Zmiana poziomu cyfryzacji w większym zakresie dotyczyła częstotliwości dokonywania zakupów przez Internet niż pozostałych zmiennych.

9

Modelowanie procesu negocjacji w pośredniczących firmach handlowych

63%

Gromova V., Wilimowska Z.

Metody Ilościowe w Badaniach Ekonomicznych

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2011

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vol. 12

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issue 2

158-167

PL

Cena, tworząc ścisłe relacje między różnymi przedsiębiorstwami i ich jednostkami odgrywa ważną rolę. W artykule rozważają się sytuacje negocjacyjne w pośredniczących przedsiębiorstwach sektora MSP, gdzie zarządzanie ceną jest realizowane przy pomocy zaproponowanego modelu procesu negocjacji przedstawionego w formie drzewa decyzyjnego. Jego głównymi elementami są: cena podstawowa, węzły - ceny produktu (zbioru produktów), uwzględniające opusty (rabaty, bonusy, prolongaty). Proces wyboru odpowiedniej ścieżki w drzewie decyzyjnym uwzględnia losowy charakter występowania sytuacji negocjacyjnych.

EN

Price, as a factor forming close connection with the different business units or companies of the related branches, plays an essential role. In the article attention is paid to the negotiation processes in the commercial intermediary companies, where price decision-making process is introduced in the form of decision tree. It’s basic elements are: basic price, nodes – prices of product or set of products, which consider given discounts, bonuses or adjournment. Process of choosing the appropriate path in a decision tree takes consider stochastic character onset of the defined negotiation situations.

10

Cloud Computing Application for Romanian SMEs

45%

Pistol L., Bucea-Manea Ţoniș R., Bucea-Manea Ţoniș R.

Marketing Instytucji Naukowych i Badawczych

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2017

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issue 3(25)

117-134

EN

The article studies the current economical state of Romanian SMEs and the utility of cloud computing technologies in the process of sustainable open innovation. The study is based on a supply chain adapted for SMEs, on a model of innovation within a network business environment and on a decision tree dedicated for SMEs when starting a new project. Taking into account the statements of the article, a new framework of cloud computing economics can be developed.

PL

Artykuł bada obecną sytuację gospodarczą małych i średnich przedsiębiorstw (MŚP) w Rumunii oraz przydatność technologii chmury obliczeniowej w procesie zrównoważonych otwartych innowacji. Badanie opiera się na koncepcji łańcucha dostaw przystosowanego do potrzeb MŚP, na modelu innowacji w środowisku sieci biznesu oraz na modelu drzewa decyzyjnego opracowanego dla realiów MŚP przy uruchamianiu nowego projektu. Tezy przedstawione w artykule mogą posłużyć do nakreślenia nowych ram ekonomiki chmury obliczeniowej.

Refine search results

Analysis of complex decision problems based on cumulative prospect theory

Energy prosumers: profiling the energy microgeneration market in Lower Silesia, Poland

On the right approach to selecting a quality improvement project in manufacturing industries

Machine-learning methods in the classification of water bodies

Application of selected data mining techniques in unintentional accounting error detection

Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

Decision Tree Approach to Discovering Fraud in Leasing Agreements

Cyfryzacja osób będących na emeryturze w krajach europejskich w okresie pandemii COVID-19

Modelowanie procesu negocjacji w pośredniczących firmach handlowych

Cloud Computing Application for Romanian SMEs