Statistinių metodų taikymo edukologiniuose tyrimuose klaidos

Januškevičius, Romanas; Pumputis, Dalius

doi:10.15388/actpaed.2011.27.2969

Cited by 3 publications

(6 citation statements)

References 2 publications

(2 reference statements)

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“…The main objective of cluster analysis is to group objects in such a way that differences within clusters are minimised, and differences between clusters maximised. Based on the steps and formulas are presented below (Bileviciene & Jonusauskas, 2011). Stages of cluster analysis:…”

Section: Methodsmentioning

confidence: 99%

Assessing Circular Textile Industry Development

Silobrit,

Jureviciene

2023

Economics and Culture

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Research purpose. Identify the main textile exporters in the global world that would have the greatest impact on the development of geared textiles. Design / Methodology / Approach. TOPSIS analysis has been applied as the most widely used efficiency measurement technique. The six criteria in the current research have been selected to describe the leading players in textiles globally and are available in a public database. In addition to the TOPSIS analysis, a clustering method has been employed to identify distinct groups among the countries under examination. Through this clustering analysis, countries with similar characteristics and practices. Findings. The analysis of the textile and clothing industry has revealed the top ten economies that make the most significant contributions to global textile production. Through a comprehensive assessment based on predetermined criteria, these economies have been closely scrutinised, resulting in the European Union securing the leading position, followed by Malaysia in second place and China in the third. The leading position of the European Union can be attributed to its robust economic infrastructure, strong policy frameworks promoting sustainability, and a growing commitment to circular economy principles within the textile sector. Malaysia's second-place position may be influenced by its strategic investments in the textile industry, favourable business environment, and initiatives to foster sustainable practices. China's third-place ranking can be attributed to its substantial textile manufacturing capacity, extensive supply chains, and efforts to integrate circular economy principles into its textile production. The research findings indicate that several factors influence the rankings, including the level of economic development, technological advancements, population size, availability of cheap labour, and the influence of fashion trends, among others. Originality / Value / Practical implications. The circular textile industry is a relatively new field, with the European Commission announcing the EU Strategy for Sustainable and Circular Textiles in 2022. This strategic initiative aims to propel the development and adoption of circular textile practices throughout the European Union, setting a benchmark for other regions to follow. It is important to underline that the study was carried out on a global scale in order to assess the world's main textile exporters. In order to assess the progress of circular textiles, we employ the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method. This approach allows us to rank and assess countries based on their implementation of strategies and initiatives for developing a circular textile industry. Furthermore, we utilise a clustering method to identify distinct groups or patterns within the data, enabling a deeper understanding of the similarities and differences among countries in their circular textile. This clustering analysis helps identify clusters of countries that exhibit similar characteristics or practices, facilitating the identification of best practices, knowledge sharing, and collaboration among countries within each cluster. The findings of this study hold significant value and practical implications for policymakers, industry stakeholders, and researchers.

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Section: Methodsmentioning

confidence: 99%

Assessing Circular Textile Industry Development

Silobrit,

Jureviciene

2023

Economics and Culture

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“…Tada taikomas daugialypės tiesinės regresijos modelis ir daugialypė koreliacinė analizė. Daugialypės regresijos modelis (6 formulė) yra tiesinio (paprastojo) regresijos modelio apibendrinimas atvejui, kai nepriklausomųjų kintamųjų yra daugiau nei vienas (Bilevičienė ir Jonušauskas, 2011): .. reikšmes. Daugialypė tiesinė regresija yra efektyviausias būdas išspręsti problemą, kuri priklauso nuo daugybės kintamųjų (Didar, 2019).…”

Section: Carunclassified

“…Šis koeficientas nurodo ir identifikuoja vieną požymį, kurio bendro kitimo dalis paaiškina kito požymio kintamųjų kitimą. Determinacijos koeficientas R 2 esant tiesinei priklausomybei yra lygus koreliacijos tarp kintamųjų (požymių) X ir Y koeficiento kvadratui (Bilevičienė ir Jonušauskas, 2011).…”

Section: Carunclassified

Evaluation of the Impact of Financial Technologies on the Financial Efficiency of Commercial Banks

Bitinas,

Burkšaitienė

2024

Science - Future of Lithuania

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The topic of financial technologies (Fintech), which has attracted enormous interest in the last decade, has become one of the most promising niches that allow participants providing services in the payment market to improve the efficiency of financial activity systems. Financial industry players such as commercial banks have begun to pay special attention to the development of this new niche. In order to maintain or occupy higher market positions, they must take into account the potential of financial technologies and their possible exploitation by integrating new solutions into already functioning banking systems. This article aims to reveal the influence of financial technologies on the financial efficiency of commercial banks. After highlighting the importance of financial technologies for commercial banks in the theoretical part of the study, the analytical part examines the financial indicators of Lithuanian commercial banks (SEB, Swedbank, Šiaulių bankas, and Citadelė) in the period 2017–2021. Correlation and regression analysis will be used to determine the impact of financial technologies on the financial efficiency of commercial banks. The results of this study determines how financial technology impacts the financial performance of commercial banks.

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“…On the contrary, a perfect negative relationship indicates -1; when one variable changes, the other variables change in the opposite direction. Finally, there is no relationship between variables if the value of the correlation coefficient is 0 (Bilevičienė & Jonušauskas, 2011). The next step is to assess the impact of the enabling environment for the development of the sharing economy on the level of use of the sharing economy platforms in different clusters.…”

Section: Selected Methods For Evaluating Factors Influencing the Shar...mentioning

confidence: 99%

“…If it is high enough, the regression equation includes the main factors that influence the dependent variable. If R² < 0.25, the fit of the linear regression model is highly questionable (Bilevičienė & Jonušauskas, 2011). The adequacy of the model with the real situation is checked by Fisher's F statistic for a confidence level of 0.05.…”

Section: Selected Methods For Evaluating Factors Influencing the Shar...mentioning

confidence: 99%

Evaluation of factors having an impact on the development of the sharing economy

Grybaitė¹

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Vilnius 2023 4 Disertacija rengta 2016-2023 metais Vilniaus Gedimino technikos universitete. (Disertacija ginama eksternu). Mokslinis konsultantas prof. dr. Jelena STANKEVIČIENĖ (Vilniaus Gedimino technikos universitetas, ekonomika -S 004). Vilniaus Gedimino technikos universiteto Ekonomikos mokslo krypties disertacijos gynimo taryba: Pirmininkas prof. habil. dr. Romualdas GINEVIČIUS (Vilniaus Gedimino technikos universitetas, ekonomika -S 004). Nariai: doc. dr. Viktorija SKVARCIANY (Vilniaus Gedimino technikos universitetas, ekonomika -S 004), prof. dr. Dalia ŠTREIMIKIENĖ (Vilniaus universitetas, ekonomika -S 004), prof. dr. Rima TAMOŠIŪNIENĖ (Vilniaus Gedimino technikos universitetas, ekonomika -S 004), prof. dr. Jelena TITKO (Latvijos mokslų akademija, ekonomika -S 004). Disertacija bus ginama viešame Ekonomikos mokslo krypties disertacijos gynimo tarybos posėdyje 2023 m. balandžio 3 d. 14 val. Vilniaus Gedimino technikos universiteto senato posėdžių salėje.

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Statistinių metodų taikymo edukologiniuose tyrimuose klaidos

Cited by 3 publications

References 2 publications

Assessing Circular Textile Industry Development

Assessing Circular Textile Industry Development

Evaluation of the Impact of Financial Technologies on the Financial Efficiency of Commercial Banks

Evaluation of factors having an impact on the development of the sharing economy

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