2018
DOI: 10.18488/journal.aefr.2018.81.22.37
|View full text |Cite
|
Sign up to set email alerts
|

Do Human Capital and Cost Efficiency Affect Risk and Capital of Commercial Banks? An Empirical Study of a Developing Country

Abstract: Article History JEL Classification:C2, G17, D22, G28, F20.As a striking force and operational optimization, human capital and cost efficiency of commercial banks are worth considering factors in decision making. Using simultaneous equation models this study delves the interrelationship between bank risk, capital and efficiency of a sample developing country-Bangladesh incorporating new dimension human capital efficiency along with existing cost efficiency through Stochastic Frontier Analysis (SFA). The empiric… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
9
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 9 publications
(10 citation statements)
references
References 31 publications
1
9
0
Order By: Relevance
“…Indeed, many investigations concur that the motivation behind the adoption and implementation of AI-driven social media marketing has been to understand human psychology, with organizations such as startup businesses or SMEs being unexceptional [5][6][7]. Through social media marketing automation, some studies contend further that the resultant outcome involves AI leveraging [7,8], with the latter trend observed further to aid in understanding and tracking the user behaviors' multiple aspects [8][9][10]. Some of the specific user behavior aspects that have been observed to attract the adoption of AISMM include the aim of individuals to use social media, the types of social media platforms on which the individuals are likely to spend more time interacting, and the amount of time that individuals spend interacting online [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Indeed, many investigations concur that the motivation behind the adoption and implementation of AI-driven social media marketing has been to understand human psychology, with organizations such as startup businesses or SMEs being unexceptional [5][6][7]. Through social media marketing automation, some studies contend further that the resultant outcome involves AI leveraging [7,8], with the latter trend observed further to aid in understanding and tracking the user behaviors' multiple aspects [8][9][10]. Some of the specific user behavior aspects that have been observed to attract the adoption of AISMM include the aim of individuals to use social media, the types of social media platforms on which the individuals are likely to spend more time interacting, and the amount of time that individuals spend interacting online [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…The possible cause for this statement is the increase of NPLs, which silently deteriorates future earnings. Again, Altunbas, Carbo, Gardener, and Molyneux (2007), Zheng, Gupta, and Moudud-Ul-Huq (2018) found that inefficiency is positively related to the risk-taking behaviour of banks which is also supported by the moral hazard hypothesis (MHH). Liquidity means the loan to deposit ratio is used to measure the ability of banks to cover withdrawals made by its customers.…”
Section: Variable Definitionmentioning
confidence: 66%
“…Inspiring from the study of A. Kasman and Carvallo (2014), Gupta and Moudud-Ul-Huq (2020), and Zheng et al (2018a), we also use Cost efficiency measure through Stochastic Frontier Analysis (SFA) to represent the efficiency of banks. Using the Software FRONTIER version 4.1 from banks level data, we measure the efficiency cost.…”
Section: Efficiency Measurementioning
confidence: 99%
“…The simultaneous equations are drawn to judge the "back and forth" causation of variables applies. System GMM suggested by Arellano and Bover (1995) and Blundell and Bond (2000), is applied for our dynamic panel data to address the endogeneity and unobserved heteroskedasticity and autocorrelation problems of the model (Baselga-Pascual et al, 2018;Gupta & Moudud-Ul-Huq, 2020;Moudud-Ul-Huq et al, 2018;Zheng et al, 2018a). The empirical model of the study is structured as follows:…”
Section: Empirical Research Frameworkmentioning
confidence: 99%
See 1 more Smart Citation