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Calibrating the factors of management quality in banking performance: a mixed method approach
Purpose This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance. Design/methodology/approach The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated...
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Published in: | Measuring business excellence 2018-09, Vol.22 (3), p.242-257 |
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creator | Chatterjee, Debmallya Dhaigude, Amol S |
description | Purpose
This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Design/methodology/approach
The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated fuzzy cognitive map (FCM) and Matrices’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) approach. Scenario analysis is carried out on the proposed model to study the behavior in a dynamic setting.
Findings
The main finding of this study is the prioritization of FMQD in evaluating banking performance. The cohesive model obtained by FCM-MICMAC integrated approach demonstrates that the interlinked factors can be grouped into independent, autonomous, dependent and relay clusters. The results suggest that internal control system is the most influential factor, whereas the business per employee is the most sensitive one in modeling management quality.
Research limitations/implications
This study models the FMQD through expert opinions, and hence, individual bias may influence the results. This study can be further validated through statistical analysis.
Practical implications
The study suggests that practitioners may focus more on these select factors and their mutual interactions to enhance management quality for improving the performance of the banks. The study emphasizes that better clarity and efficient designing of internal processes are the key to management soundness.
Originality/value
This is the first study to explore and model FMQD in banking performance using FCM-MICMAC approach. Validation of the proposed model in a dynamic setting is also relatively new in the banking performance literature. |
doi_str_mv | 10.1108/MBE-08-2017-0052 |
format | article |
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This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Design/methodology/approach
The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated fuzzy cognitive map (FCM) and Matrices’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) approach. Scenario analysis is carried out on the proposed model to study the behavior in a dynamic setting.
Findings
The main finding of this study is the prioritization of FMQD in evaluating banking performance. The cohesive model obtained by FCM-MICMAC integrated approach demonstrates that the interlinked factors can be grouped into independent, autonomous, dependent and relay clusters. The results suggest that internal control system is the most influential factor, whereas the business per employee is the most sensitive one in modeling management quality.
Research limitations/implications
This study models the FMQD through expert opinions, and hence, individual bias may influence the results. This study can be further validated through statistical analysis.
Practical implications
The study suggests that practitioners may focus more on these select factors and their mutual interactions to enhance management quality for improving the performance of the banks. The study emphasizes that better clarity and efficient designing of internal processes are the key to management soundness.
Originality/value
This is the first study to explore and model FMQD in banking performance using FCM-MICMAC approach. Validation of the proposed model in a dynamic setting is also relatively new in the banking performance literature.</description><identifier>ISSN: 1368-3047</identifier><identifier>EISSN: 1758-8057</identifier><identifier>DOI: 10.1108/MBE-08-2017-0052</identifier><language>eng</language><publisher>Bradford: Emerald Publishing Limited</publisher><subject>Asset liability management ; Banking ; Banking industry ; Banks ; Camelids ; Data envelopment analysis ; Decision making ; Economic development ; Expenditures ; Financial institutions ; Information technology ; Liquidity ; Literature reviews ; Mixed methods research ; Money laundering ; Performance evaluation ; Profits ; Quality ; Ratings & rankings ; Researchers</subject><ispartof>Measuring business excellence, 2018-09, Vol.22 (3), p.242-257</ispartof><rights>Emerald Publishing Limited</rights><rights>Emerald Publishing Limited 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c311t-3781b6381b095709197c4ac90198ebf7a5d33610e83f3aa9adba7c9afe5130e23</citedby><cites>FETCH-LOGICAL-c311t-3781b6381b095709197c4ac90198ebf7a5d33610e83f3aa9adba7c9afe5130e23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2108111504/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2108111504?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11688,27924,27925,36060,44363,74767</link.rule.ids></links><search><creatorcontrib>Chatterjee, Debmallya</creatorcontrib><creatorcontrib>Dhaigude, Amol S</creatorcontrib><title>Calibrating the factors of management quality in banking performance: a mixed method approach</title><title>Measuring business excellence</title><description>Purpose
This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Design/methodology/approach
The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated fuzzy cognitive map (FCM) and Matrices’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) approach. Scenario analysis is carried out on the proposed model to study the behavior in a dynamic setting.
Findings
The main finding of this study is the prioritization of FMQD in evaluating banking performance. The cohesive model obtained by FCM-MICMAC integrated approach demonstrates that the interlinked factors can be grouped into independent, autonomous, dependent and relay clusters. The results suggest that internal control system is the most influential factor, whereas the business per employee is the most sensitive one in modeling management quality.
Research limitations/implications
This study models the FMQD through expert opinions, and hence, individual bias may influence the results. This study can be further validated through statistical analysis.
Practical implications
The study suggests that practitioners may focus more on these select factors and their mutual interactions to enhance management quality for improving the performance of the banks. The study emphasizes that better clarity and efficient designing of internal processes are the key to management soundness.
Originality/value
This is the first study to explore and model FMQD in banking performance using FCM-MICMAC approach. Validation of the proposed model in a dynamic setting is also relatively new in the banking performance literature.</description><subject>Asset liability management</subject><subject>Banking</subject><subject>Banking industry</subject><subject>Banks</subject><subject>Camelids</subject><subject>Data envelopment analysis</subject><subject>Decision making</subject><subject>Economic development</subject><subject>Expenditures</subject><subject>Financial institutions</subject><subject>Information technology</subject><subject>Liquidity</subject><subject>Literature reviews</subject><subject>Mixed methods research</subject><subject>Money laundering</subject><subject>Performance evaluation</subject><subject>Profits</subject><subject>Quality</subject><subject>Ratings & rankings</subject><subject>Researchers</subject><issn>1368-3047</issn><issn>1758-8057</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNptkD1PwzAQhi0EEqWwM1piNr2L6zhhg6p8SEUsMCLr4thtSpO0TirRf4-jsiCx3HvD895JD2PXCLeIkE1eH-YCMpEAagGgkhM2Qq0ykYHSp3GXaSYkTPU5u-i6NQCmKtUj9jmjTVUE6qtmyfuV455s34aOt57X1NDS1a7p-W4fsf7Aq4YX1HwN8NYF34bIWHfHidfVtyt57fpVW3LabkNLdnXJzjxtOnf1m2P28Th_nz2LxdvTy-x-IaxE7IXUGRapjANypSHHXNsp2Rwwz1zhNalSyhTBZdJLopzKgrTNyTuFElwix-zmeDe-3e1d15t1uw9NfGmSKAcRFUwjBUfKhrbrgvNmG6qawsEgmEGiiRJNjEGiGSTGyuRYiRoCbcr_Gn-0yx9oWXKn</recordid><startdate>20180918</startdate><enddate>20180918</enddate><creator>Chatterjee, Debmallya</creator><creator>Dhaigude, Amol S</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8AO</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F~G</scope><scope>K6~</scope><scope>K8~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20180918</creationdate><title>Calibrating the factors of management quality in banking performance: a mixed method approach</title><author>Chatterjee, Debmallya ; Dhaigude, Amol S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c311t-3781b6381b095709197c4ac90198ebf7a5d33610e83f3aa9adba7c9afe5130e23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Asset liability management</topic><topic>Banking</topic><topic>Banking industry</topic><topic>Banks</topic><topic>Camelids</topic><topic>Data envelopment analysis</topic><topic>Decision making</topic><topic>Economic development</topic><topic>Expenditures</topic><topic>Financial institutions</topic><topic>Information technology</topic><topic>Liquidity</topic><topic>Literature reviews</topic><topic>Mixed methods research</topic><topic>Money laundering</topic><topic>Performance evaluation</topic><topic>Profits</topic><topic>Quality</topic><topic>Ratings & rankings</topic><topic>Researchers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chatterjee, Debmallya</creatorcontrib><creatorcontrib>Dhaigude, Amol S</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Business Collection</collection><collection>DELNET Management Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global (ProQuest)</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Measuring business excellence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chatterjee, Debmallya</au><au>Dhaigude, Amol S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Calibrating the factors of management quality in banking performance: a mixed method approach</atitle><jtitle>Measuring business excellence</jtitle><date>2018-09-18</date><risdate>2018</risdate><volume>22</volume><issue>3</issue><spage>242</spage><epage>257</epage><pages>242-257</pages><issn>1368-3047</issn><eissn>1758-8057</eissn><abstract>Purpose
This paper aims to explore and model the factors of management quality dimension (FMQD) in evaluating banking performance.
Design/methodology/approach
The FMQD in evaluating banking performance are explored through the review of literature. The identified factors are modeled using integrated fuzzy cognitive map (FCM) and Matrices’ Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC) approach. Scenario analysis is carried out on the proposed model to study the behavior in a dynamic setting.
Findings
The main finding of this study is the prioritization of FMQD in evaluating banking performance. The cohesive model obtained by FCM-MICMAC integrated approach demonstrates that the interlinked factors can be grouped into independent, autonomous, dependent and relay clusters. The results suggest that internal control system is the most influential factor, whereas the business per employee is the most sensitive one in modeling management quality.
Research limitations/implications
This study models the FMQD through expert opinions, and hence, individual bias may influence the results. This study can be further validated through statistical analysis.
Practical implications
The study suggests that practitioners may focus more on these select factors and their mutual interactions to enhance management quality for improving the performance of the banks. The study emphasizes that better clarity and efficient designing of internal processes are the key to management soundness.
Originality/value
This is the first study to explore and model FMQD in banking performance using FCM-MICMAC approach. Validation of the proposed model in a dynamic setting is also relatively new in the banking performance literature.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/MBE-08-2017-0052</doi><tpages>16</tpages></addata></record> |
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subjects | Asset liability management Banking Banking industry Banks Camelids Data envelopment analysis Decision making Economic development Expenditures Financial institutions Information technology Liquidity Literature reviews Mixed methods research Money laundering Performance evaluation Profits Quality Ratings & rankings Researchers |
title | Calibrating the factors of management quality in banking performance: a mixed method approach |
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