The Evaluation of Bank Performance Using a Multicriteria Decision Making Model: A Case Study on Lithuanian Commercial Banks

Stankevičienė, Jelena; Mencaitė, Evelina

doi:10.3846/20294913.2012.668373

Cited by 41 publications

(31 citation statements)

References 29 publications

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“…In particular, this is true for Lithuania in the field of finance. Lithuanian scientists pay some attention to the problem of evaluating domestic banks by MCDA methods (Brauers, Ginevicius, Podviezko, 2012;Zavadskas, Kaklauskas, Banaitis, Kvederyte, 2004;Ginevicius, Podvezko, 2008a;Ginevicius, Podvezko, Novotny, 2010;Ginevicius, Podvezko, Podviezko, 2012;Zvirblis, Buracas, 2010;Podviezko, Ginevicius, 2010;Stankeviciene, Mencaite, 2012).…”

Section: Introductionmentioning

confidence: 99%

The Evaluation of Financial Stability and Soundness of Lithuanian Banks

Ginevičius

Podviezko

2013

Economic Research-Ekonomska Istraživanja

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The successful development of economy is based on effective and stable performance of commercial banks. The evaluation of stability and soundness of banks is a complex task, involving a considerable number of multidimensional criteria. It is an idiosyncratic task because of a complicated internal business structure of banks, intertwined cash flows and strong influence of market conditions on soundness levels. In this paper, soundness and stability dynamics of commercial banks registered in Lithuania was evaluated by using several multiple criteria methods from simpler ones to the more sophisticated PROMETHEE method. The results obtained indicate that the levels of soundness and stability of banks operating in the developing Lithuanian market of commercial banks noticeably fluctuate. A comparison of the obtained results reveals the causes of the fluctuations. A simultaneous use of different multiple criteria methods for evaluating the soundness and stability of commercial banks increases the robustness of the evaluation. ARTICLE INFO

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Section: Introductionmentioning

confidence: 99%

The Evaluation of Financial Stability and Soundness of Lithuanian Banks

Ginevičius

Podviezko

2013

Economic Research-Ekonomska Istraživanja

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“…One of the best-performing indicators that evaluates (compares) the return on investment is Sharpe ratio [5]. The higher the Sharpe ratio is; the sooner the fund compensates for the risks involved [18]. The Sharpe ratio is calculated from the investment return rate minus the risk-free rate of return and dividing the result by the average standard deviation of the investment risk:…”

Section: Methodology For the Assessment Of Wheelset Wheel Weariness Amentioning

confidence: 99%

Research on metal fatigue of rail vehicle wheel considering the wear intensity of rolling surface

Vaičiūnas¹,

Бурейка²,

Steišūnas³

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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The article overviews scientific research studies that examine the interaction between railway vehicle wheel and rail, and the phenomena of wear on wheel rolling surface. Unique experimental research has been conducted, in which regularity of weariness on rolling surface of exploitable locomotive wheel and phenomena of metal fatigue on wheel were researched. A hypothesis is made, that according to the differences in weariness intensity of wheel rolling surface it is possible to determine the start of metal fatigue. The inequality of wear intensity of different locomotive wheels is assessed by the Sharpe ratio, adapting it to describe the wheel wear intensity criteria. Based on the results of research, the authors propose a simplified and reliable methodology for determining metal fatigue on locomotive wheels at initial stages. The uneven wear on rolling surface of different wheels of wheelset inevitably changes the values of Sharpe ratio, which can accurately describe the conditions in which the critical metal fatigue on wheels begins to emerge.

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“…Indeed, in what concerns bank branch service quality in particular, there is a significant amount of research showing that despite the progress achieved, most of the limitations discussed above are still present (see also Ferreira et al 2011b;Stankevičiene and Mencait_ e 2012). Athanassopoulos (1997), for instance, highlighted the major limitations of Data Envelopment Analysis (DEA) as a nonparametric technique; Lee et al (2011) and Oliveira and von Hippel (2011) reported on several types of sample limitation; and Karatepe et al (2005) argued the need for more studies to address the issues discussed above.…”

Section: Related Workmentioning

confidence: 96%

Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

et al. 2015

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Using fuzzy cognitive mapping, this study aims to create a holistic framework whereby the determinants of bank branch service quality and their cause-and-effect relationships can be identified and dynamically analyzed. The methodology is applied using a group of experts from the banking industry in Portugal. Our results not only indicate the applicability and usefulness of the proposed approach, but identify human resource characteristics (which include collaborators' personal and professional training) and management team technical skills as particularly relevant driving forces of bank branch service quality. The proposal holds great potential for the operational planning and improvement of bank branch service quality, which is a prime concern for bank administrators, bank branch collaborators, and society at large. Advantages and shortcomings of the framework are also reported.

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The Evaluation of Bank Performance Using a Multicriteria Decision Making Model: A Case Study on Lithuanian Commercial Banks

Cited by 41 publications

References 29 publications

The Evaluation of Financial Stability and Soundness of Lithuanian Banks

The Evaluation of Financial Stability and Soundness of Lithuanian Banks

Research on metal fatigue of rail vehicle wheel considering the wear intensity of rolling surface

Understanding the dynamics behind bank branch service quality in Portugal: pursuing a holistic view using fuzzy cognitive mapping

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