Mathematics

Research

21 pages, 1466 KiB

Open AccessArticle

Deployment of the Microeconomic Consumer Theory in the Artificial Neural Networks Modelling: Case of Organic Food Consumption

by Ivan Jajić, Tomislav Herceg and Mirjana Pejić Bach

Mathematics 2022, 10(17), 3215; https://doi.org/10.3390/math10173215 - 05 Sep 2022

Viewed by 1700

Abstract

Organic food consumption has become a significant trend in consumer behaviour, determined by various motives, among which the price does not play a major role, thus reflecting the Lancaster approach to the microeconomic consumer theory. Additionally, artificial neural networks (ANNs) have proven to [...] Read more.

Organic food consumption has become a significant trend in consumer behaviour, determined by various motives, among which the price does not play a major role, thus reflecting the Lancaster approach to the microeconomic consumer theory. Additionally, artificial neural networks (ANNs) have proven to have significant potential in providing accurate and efficient models for predicting consumer behaviour. Considering these two trends, this study aims to deploy the Lancaster approach in the emerging area of artificial intelligence. The paper aims to develop the ANN-based predictive model to investigate the relationship between organic food consumption, demographic characteristics, and health awareness attitudes. Survey research has been conducted on a sample of Croatian inhabitants, and ANN models have been used to assess the importance of various determinants for organic food consumption. A Three-layer Multilayer Perceptron Neural Networks (MLPNN) structure has been constructed and validated to select the optimal number of neurons and transfer functions. One layer is used as the first input, while the other two are hidden layers (the first covers the radially symmetrical input, sigmoid function; the second covers the output, softmax function). Three versions of the testing, training, and holdout data structures were used to develop ANNs. The highest accuracy was achieved with a 7-2-1 partition. The best ANN model was determined as the model that was showing the smallest percent of incorrect predictions in the holdout stage, the second-lowest cross-entropy error, the correct classification rate, and the area under the ROC curve. The research results show that the availability of healthy food shops and consumer awareness of these shops strongly impacts organic food consumption. Using the ANN methodology, this analysis confirmed the validity of the Lancaster approach, stating that the characteristics or attributes of goods are defined by the consumer and not by the product itself. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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19 pages, 1505 KiB

Open AccessArticle

New Methodological Approach to Classify Educational Institutions—A Case Study on Romanian High Schools

by Marian Necula, Maria-Magdalena Roșu, Alexandra-Maria Firescu, Cecilia Basu, Andreea Ardelean, Eduard C. Milea and Mihaela Păun

Mathematics 2022, 10(14), 2480; https://doi.org/10.3390/math10142480 - 16 Jul 2022

Viewed by 1447

Abstract

Since 2021, the National Evaluation exam in Romania (the exam aimed to assess 14- to 15-year-old students’ knowledge at the end of lower secondary education and just before high school) has presented a novel examination structure that resembles PISA tests. The current investigation [...] Read more.

Since 2021, the National Evaluation exam in Romania (the exam aimed to assess 14- to 15-year-old students’ knowledge at the end of lower secondary education and just before high school) has presented a novel examination structure that resembles PISA tests. The current investigation analyses the 2021 National Evaluation exam results compared to the results obtained in the previous two years (2019–2020) as an evaluation of upper education institutions’ effectiveness in Romania. The results put forward the same conclusions as proposed by extant literature on Bucharest high schools. Even though the educational institutions show apparent progress and great adaptability to change, a more in-depth analysis reveals great inequality between educational institutions. As in the case of Bucharest, nationally there are only a small number of top-performing high schools in Romania, with the majority of high schools ranking in the lowest category as conceptualised in the study. The current investigation puts together a novel methodology for classification based on the main instruments proposed in literature: a letter grade classification and Turner’s f-index. The results and the methodological proposal are especially relevant considering the latest PISA (2018) conclusions on Romania characterising the national educational system as underperforming. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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17 pages, 5209 KiB

Open AccessArticle

Experiments with Fuzzy Methods for Forecasting Time Series as Alternatives to Classical Methods

by Bogdan Oancea, Richard Pospíšil, Marius Nicolae Jula and Cosmin-Ionuț Imbrișcă

Mathematics 2021, 9(19), 2517; https://doi.org/10.3390/math9192517 - 07 Oct 2021

Cited by 3 | Viewed by 1919

Abstract

Even though forecasting methods have advanced in the last few decades, economists still face a simple question: which prediction method gives the most accurate results? Econometric forecasting methods can deal with different types of time series and have good results, but in specific [...] Read more.

Even though forecasting methods have advanced in the last few decades, economists still face a simple question: which prediction method gives the most accurate results? Econometric forecasting methods can deal with different types of time series and have good results, but in specific cases, they may fail to provide accurate predictions. Recently, new techniques borrowed from the soft computing area were adopted for economic forecasting. Starting from the importance of economic forecasts, we present an experimental study where we compared the accuracy of some of the most used econometric forecasting methods, namely the simple exponential smoothing, Holt and ARIMA methods, with that of two new methods based on the concept of fuzzy time series. We used a set of time series extracted from the Eurostat database and the R software for all data processing. The results of the experiments show that despite not being fully superior to the econometric techniques, the fuzzy time series forecasting methods could be considered as an alternative for specific time series. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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19 pages, 1196 KiB

Open AccessArticle

Hybrid Model for Unemployment Impact on Social Life

by Claudiu-Ionuţ Popîrlan, Irina-Valentina Tudor, Constantin-Cristian Dinu, Gabriel Stoian, Cristina Popîrlan and Daniela Dănciulescu

Mathematics 2021, 9(18), 2278; https://doi.org/10.3390/math9182278 - 16 Sep 2021

Cited by 7 | Viewed by 1771

Abstract

In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, we analyze the effect of unemployment on two of the main aspects of social life: social exclusion and life satisfaction. First, we predict [...] Read more.

In this paper, we want to examine how unemployment impacts social life, and, by using datasets from six European countries, we analyze the effect of unemployment on two of the main aspects of social life: social exclusion and life satisfaction. First, we predict unemployment rates using the Auto Regressive Integrated Moving Average (ARIMA) model and the results are further used in a linear regression model alongside social exclusion and life satisfaction data, thus obtaining the hybrid model. With the help of the point prediction method, we use the hybrid model to predict new values for the two aspects of social life for the upcoming three years and we analyze the results obtained in order to better understand their interconnection. The results suggest that unemployment has particularly adverse effects on the subjective perception of life satisfaction, furthermore increasing the social exclusion percentage. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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35 pages, 1427 KiB

Open AccessArticle

On the Reachability of a Feedback Controlled Leontief-Type Singular Model Involving Scheduled Production, Recycling and Non-Renewable Resources

by Manuel De la Sen, Asier Ibeas and Santiago Alonso-Quesada

Mathematics 2021, 9(17), 2175; https://doi.org/10.3390/math9172175 - 06 Sep 2021

Cited by 3 | Viewed by 1481

Abstract

This paper proposes and studies the reachability of a singular regular dynamic discrete Leontief-type economic model which includes production industries, recycling industries, and non-renewable products in an integrated way. The designed prefixed final state to be reached, under discussed reachability conditions, is subject [...] Read more.

This paper proposes and studies the reachability of a singular regular dynamic discrete Leontief-type economic model which includes production industries, recycling industries, and non-renewable products in an integrated way. The designed prefixed final state to be reached, under discussed reachability conditions, is subject to necessary additional positivity-type constraints which depend on the initial conditions and the final time for the solution to match such a final prescribed state. It is assumed that the model may be driven by both the demand and an additional correcting control in order to achieve the final targeted state in finite time. Formal sufficiency-type conditions are established for the proposed singular Leontief model to be reachable under positive feedback, correcting controls designed for appropriate demand/supply regulation. Basically, the proposed regulation scheme allows fixing a prescribed final state of economic goods stock in finite time if the model is reachable. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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19 pages, 577 KiB

Open AccessArticle

Analysis of the Tax Compliance in the EU: VECM and SEM

by Marius-Răzvan Surugiu, Cristina-Raluca Mazilescu and Camelia Surugiu

Mathematics 2021, 9(17), 2170; https://doi.org/10.3390/math9172170 - 05 Sep 2021

Cited by 2 | Viewed by 2816

Abstract

Tax compliance is an important indicator for the proper functioning of the tax authority, influencing the budget revenue level. In this study, a Vector Error Correction Model (VECM) analysis was developed to identify the long-term relationships between the compliance in individual income taxation [...] Read more.

Tax compliance is an important indicator for the proper functioning of the tax authority, influencing the budget revenue level. In this study, a Vector Error Correction Model (VECM) analysis was developed to identify the long-term relationships between the compliance in individual income taxation (taxpayer’s behavior), public trust in politicians (trust in authorities), and rule of law (power of the authorities), using unbalanced panel data for the European Union (EU28) during the 2007–2017 period. The results underline the causality of the long-run relationships between the variables. The results of the VECM analysis underline the need for various support measures for voluntary tax compliance, with the trust variable having an important impact on tax compliance. In addition, a Structural Equation Modeling (SEM) analysis was employed using an improved data set with variables such as the compliance in corporation taxation (taxpayer’s behavior), wastefulness of government spending, and quality of the education system. The results of the SEM analysis underline the positive and significant influences of the variables on tax compliance. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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22 pages, 1825 KiB

Open AccessArticle

A Non-Parametric Analysis of the Relationship between Business Experience and Entrepreneurial Intention of Final-Year University Students

by Oana Simona Hudea, Sorin-George Toma and Marin Burcea

Mathematics 2021, 9(16), 1955; https://doi.org/10.3390/math9161955 - 16 Aug 2021

Cited by 2 | Viewed by 1760

Abstract

Last decades have witnessed that exposure to business activities, through family and direct experience, positively influences students’ entrepreneurial intention (EI). The paper aims to present and analyze the relationship between business experience (BE) and EI in the case of final-year university students, specialized [...] Read more.

Last decades have witnessed that exposure to business activities, through family and direct experience, positively influences students’ entrepreneurial intention (EI). The paper aims to present and analyze the relationship between business experience (BE) and EI in the case of final-year university students, specialized in business administration and marketing, resorting to this end to a standardized questionnaire, developed by the authors and finalized following a pilot survey. The hypotheses considered, centered on the study of the existence of any contingency or correlational relationship between the BE of students, and their EI, based on related coefficients applicable in such case, have been confirmed, in line with similar studies. Theoretically, this paper contributes to the enrichment of the literature on students’ EI in higher education institutions (HEIs). Practically, students’ EI can be stimulated and encouraged by a deeper involvement of HEIs in entrepreneurship education, thereby creating a challenging entrepreneurial academic environment through a plethora of measures, such as establishing university spin-offs and closer relationships with their specific external stakeholders (e.g., entrepreneurs, businessmen). Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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15 pages, 694 KiB

Open AccessArticle

Understanding Consumer Stockpiling during the COVID-19 Outbreak through the Theory of Planned Behavior

by Maria-Magdalena Roșu, Rodica Ianole-Călin, Raluca Dinescu, Anca Bratu, Răzvan-Mihail Papuc and Anastasia Cosma

Mathematics 2021, 9(16), 1950; https://doi.org/10.3390/math9161950 - 15 Aug 2021

Cited by 12 | Viewed by 3403

Abstract

We use the theory of planned behavior (TPB) to investigate determinants of stockpiling behavior during the COVID-19 lockdown. We analyzed 518 responses to an online survey and used Partial Least Squares Path Modeling (PLS-PM) techniques to estimate relationships between variables. Negative attitude (perceived [...] Read more.

We use the theory of planned behavior (TPB) to investigate determinants of stockpiling behavior during the COVID-19 lockdown. We analyzed 518 responses to an online survey and used Partial Least Squares Path Modeling (PLS-PM) techniques to estimate relationships between variables. Negative attitude (perceived barriers) and others’ behavior (descriptive social norms) were revealed as significant predictors for both intention to over-purchase and the actual stockpiling behavior. The lack of significance obtained for perceived behavioral control (PBC) is also an important result, strengthening the evidence that factors’ contribution to TPB’s predictive power is strongly context-dependent, respectively that PBC is less relevant in settings dominated by uncertainty. The lack of significance is especially compelling when stockpiling behavior is regarded as deviant conduct from effective consumption. Our findings expand the understanding on the applicability of TPB and offer informed practical suggestions for improving managerial strategies, public and private ones, during extreme events when self-regulation and cognitive control are expedient but hard to achieve. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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19 pages, 1279 KiB

Open AccessArticle

On the Connection between the GEP Performances and the Time Series Properties

by Alina Bărbulescu and Cristian Ștefan Dumitriu

Mathematics 2021, 9(16), 1853; https://doi.org/10.3390/math9161853 - 05 Aug 2021

Cited by 3 | Viewed by 1245

Abstract

Artificial intelligence (AI) methods are interesting alternatives to classical approaches for modeling financial time series since they relax the assumptions imposed on the data generating process by the parametric models and do not impose any constraint on the model’s functional form. Even if [...] Read more.

Artificial intelligence (AI) methods are interesting alternatives to classical approaches for modeling financial time series since they relax the assumptions imposed on the data generating process by the parametric models and do not impose any constraint on the model’s functional form. Even if many studies employed these techniques for modeling financial time series, the connection of the models’ performances with the statistical characteristics of the data series has not yet been investigated. Therefore, this research aims to study the performances of Gene Expression Programming (GEP) for modeling monthly and weekly financial series that present trend and/or seasonality and after the removal of each component. It is shown that series normality and homoskedasticity do not influence the models’ quality. The trend removal increases the models’ performance, whereas the seasonality elimination results in diminishing the goodness of fit. Comparisons with ARIMA models built are also provided. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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24 pages, 6933 KiB

Open AccessArticle

Q or R Factor Analysis for Subjectiveness Measurement in Consumer Behavior? A Study Case on Durable Goods Buying Behavior in Romania

by Manuela Rozalia Gabor and Nicoleta Cristache

Mathematics 2021, 9(10), 1136; https://doi.org/10.3390/math9101136 - 17 May 2021

Cited by 3 | Viewed by 2590

Abstract

The complexity of consumer behavior requires new research methods to overcome the limitations of conventional evident-based research. The aim of this paper is the comparison between two types of factor analyses, Q and R (PCA and cluster analysis) for subjectiveness measurement in the [...] Read more.

The complexity of consumer behavior requires new research methods to overcome the limitations of conventional evident-based research. The aim of this paper is the comparison between two types of factor analyses, Q and R (PCA and cluster analysis) for subjectiveness measurement in the case of durable goods buying behavior in Romanian households with different levels of education and occupancy. Our study explores different subjective patterns of stimulus of 30 statements (Q-sample) by 30 Romanian households (P-sample) using the Q-sort method for collecting data. For the Q-sample inputs, results from the literature were used. Based on the 30 Q-sorts, we discovered four factors for both Q and R factor analysis, mostly different according to specific results from different methods. For the Q method, we used the labels “pragmatic”, “modern”, “traditionalist”, and “innovator. For R factor analysis and cluster, we used “traditional Romanian brands”, “real needs and power purchasing”, “sceptic versus optimistic subjectiveness”, and “negative subjectiveness”. This paper suggests the Q methodology as a structured and transparent approach to consumer behavior research by combining the in-depth subjectivity of qualitative methods and statistical rigor of factor analysis to identify groups in consumers. The research provides useful suggestions for selecting and approaching target consumer segments in the Romanian durable goods industry. Full article

(This article belongs to the Special Issue Analysis and Mathematical Modeling of Economic - Related Data)

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