Empirical verification of the balanced scorecard
Purpose – The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues. Design/methodology/approach – The research...
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Veröffentlicht in: | Industrial management + data systems 2014-01, Vol.114 (2), p.203-219 |
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description | Purpose
– The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues.
Design/methodology/approach
– The research was performed as a single case study of modelling the BSC for the manufacturing company and founded on complementary use of qualitative and quantitative methods. The central part of the case study is an empirically evaluated layout of the BSC with the Engle-Granger two-step method.
Findings
– The results and findings from empirical analysis showed that the methods used are appropriate for inclusion in the methodological approach as they are complementary. Therefore, it can be asserted that the introduction of quantitative methods of continuous data analysis for the implementation of the BSC improved the established approach. In this research, an approach that represents the basis for further work in the field of research in PMSs of companies, with the use of econometric tools, was empirically tested and developed.
Research limitations/implications
– The generalization of research findings is limited to only one manufacturing company. With the continuation of the research on other case studies, the preliminary lessons learned can be expanded to other organizations.
Originality/value
– Following the research findings, it can be established that the methodology used provides support to organization's decision-making process in real-time and can be used with different strategies scenarios and forecast simulations and thus supports the prioritization of strategic initiatives. In addition, the developed model allows the integration and testing of various performance indicators and the identification and selection of the most appropriate KPIs. |
doi_str_mv | 10.1108/IMDS-04-2013-0195 |
format | Article |
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– The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues.
Design/methodology/approach
– The research was performed as a single case study of modelling the BSC for the manufacturing company and founded on complementary use of qualitative and quantitative methods. The central part of the case study is an empirically evaluated layout of the BSC with the Engle-Granger two-step method.
Findings
– The results and findings from empirical analysis showed that the methods used are appropriate for inclusion in the methodological approach as they are complementary. Therefore, it can be asserted that the introduction of quantitative methods of continuous data analysis for the implementation of the BSC improved the established approach. In this research, an approach that represents the basis for further work in the field of research in PMSs of companies, with the use of econometric tools, was empirically tested and developed.
Research limitations/implications
– The generalization of research findings is limited to only one manufacturing company. With the continuation of the research on other case studies, the preliminary lessons learned can be expanded to other organizations.
Originality/value
– Following the research findings, it can be established that the methodology used provides support to organization's decision-making process in real-time and can be used with different strategies scenarios and forecast simulations and thus supports the prioritization of strategic initiatives. In addition, the developed model allows the integration and testing of various performance indicators and the identification and selection of the most appropriate KPIs.</description><identifier>ISSN: 0263-5577</identifier><identifier>EISSN: 1758-5783</identifier><identifier>DOI: 10.1108/IMDS-04-2013-0195</identifier><identifier>CODEN: IMDSD8</identifier><language>eng</language><publisher>Wembley: Emerald Group Publishing Limited</publisher><subject>Balanced Scorecard ; Balancing ; Case studies ; Computer simulation ; Data management systems ; Empirical analysis ; Error correction & detection ; Hypotheses ; Inclusions ; Indicators ; Industry analysis ; Information & knowledge management ; Information systems ; Managers ; Mathematical models ; Methodology ; Performance evaluation ; Performance measurement ; Qualitative research ; Strategic management</subject><ispartof>Industrial management + data systems, 2014-01, Vol.114 (2), p.203-219</ispartof><rights>Emerald Group Publishing Limited</rights><rights>Copyright Emerald Group Publishing Limited 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-b5bce670e33d640ed14784c93ced6305986147721b280e60bbaa2559cab31c563</citedby><cites>FETCH-LOGICAL-c390t-b5bce670e33d640ed14784c93ced6305986147721b280e60bbaa2559cab31c563</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-04-2013-0195/full/pdf$$EPDF$$P50$$Gemerald$$H</linktopdf><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/IMDS-04-2013-0195/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,776,780,961,11614,21674,27901,27902,52661,52664,53219,53347</link.rule.ids></links><search><creatorcontrib>Janes, Aleksander</creatorcontrib><title>Empirical verification of the balanced scorecard</title><title>Industrial management + data systems</title><description>Purpose
– The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues.
Design/methodology/approach
– The research was performed as a single case study of modelling the BSC for the manufacturing company and founded on complementary use of qualitative and quantitative methods. The central part of the case study is an empirically evaluated layout of the BSC with the Engle-Granger two-step method.
Findings
– The results and findings from empirical analysis showed that the methods used are appropriate for inclusion in the methodological approach as they are complementary. Therefore, it can be asserted that the introduction of quantitative methods of continuous data analysis for the implementation of the BSC improved the established approach. In this research, an approach that represents the basis for further work in the field of research in PMSs of companies, with the use of econometric tools, was empirically tested and developed.
Research limitations/implications
– The generalization of research findings is limited to only one manufacturing company. With the continuation of the research on other case studies, the preliminary lessons learned can be expanded to other organizations.
Originality/value
– Following the research findings, it can be established that the methodology used provides support to organization's decision-making process in real-time and can be used with different strategies scenarios and forecast simulations and thus supports the prioritization of strategic initiatives. In addition, the developed model allows the integration and testing of various performance indicators and the identification and selection of the most appropriate KPIs.</description><subject>Balanced Scorecard</subject><subject>Balancing</subject><subject>Case studies</subject><subject>Computer simulation</subject><subject>Data management systems</subject><subject>Empirical analysis</subject><subject>Error correction & detection</subject><subject>Hypotheses</subject><subject>Inclusions</subject><subject>Indicators</subject><subject>Industry analysis</subject><subject>Information & knowledge management</subject><subject>Information systems</subject><subject>Managers</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>Performance evaluation</subject><subject>Performance measurement</subject><subject>Qualitative research</subject><subject>Strategic 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scorecard</title><author>Janes, Aleksander</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-b5bce670e33d640ed14784c93ced6305986147721b280e60bbaa2559cab31c563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Balanced Scorecard</topic><topic>Balancing</topic><topic>Case studies</topic><topic>Computer simulation</topic><topic>Data management systems</topic><topic>Empirical analysis</topic><topic>Error correction & detection</topic><topic>Hypotheses</topic><topic>Inclusions</topic><topic>Indicators</topic><topic>Industry analysis</topic><topic>Information & knowledge management</topic><topic>Information systems</topic><topic>Managers</topic><topic>Mathematical models</topic><topic>Methodology</topic><topic>Performance evaluation</topic><topic>Performance measurement</topic><topic>Qualitative research</topic><topic>Strategic management</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Janes, Aleksander</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>Computer and Information Systems Abstracts</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>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology 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Global</collection><collection>Computing Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</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 China</collection><collection>ProQuest Central Basic</collection><jtitle>Industrial management + data systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Janes, Aleksander</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Empirical verification of the balanced scorecard</atitle><jtitle>Industrial management + data systems</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>114</volume><issue>2</issue><spage>203</spage><epage>219</epage><pages>203-219</pages><issn>0263-5577</issn><eissn>1758-5783</eissn><coden>IMDSD8</coden><abstract>Purpose
– The development and empirical verification of the balanced scorecard (BSC) model are key parts of the research of a case study on the performance measurement system (PMS) of the Ydria Motors LL Company (YM). The paper aims to discuss these issues.
Design/methodology/approach
– The research was performed as a single case study of modelling the BSC for the manufacturing company and founded on complementary use of qualitative and quantitative methods. The central part of the case study is an empirically evaluated layout of the BSC with the Engle-Granger two-step method.
Findings
– The results and findings from empirical analysis showed that the methods used are appropriate for inclusion in the methodological approach as they are complementary. Therefore, it can be asserted that the introduction of quantitative methods of continuous data analysis for the implementation of the BSC improved the established approach. In this research, an approach that represents the basis for further work in the field of research in PMSs of companies, with the use of econometric tools, was empirically tested and developed.
Research limitations/implications
– The generalization of research findings is limited to only one manufacturing company. With the continuation of the research on other case studies, the preliminary lessons learned can be expanded to other organizations.
Originality/value
– Following the research findings, it can be established that the methodology used provides support to organization's decision-making process in real-time and can be used with different strategies scenarios and forecast simulations and thus supports the prioritization of strategic initiatives. In addition, the developed model allows the integration and testing of various performance indicators and the identification and selection of the most appropriate KPIs.</abstract><cop>Wembley</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/IMDS-04-2013-0195</doi><tpages>17</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Balanced Scorecard Balancing Case studies Computer simulation Data management systems Empirical analysis Error correction & detection Hypotheses Inclusions Indicators Industry analysis Information & knowledge management Information systems Managers Mathematical models Methodology Performance evaluation Performance measurement Qualitative research Strategic management |
title | Empirical verification of the balanced scorecard |
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