{"id":{"repo_id":"middlesex","oai_identifier":"oai:repository.mdx.ac.uk:105082"},"canonical_url":"https://search.dev.ndltd.org/etd/middlesex/oai:repository.mdx.ac.uk:105082","repository":{"repo_id":"middlesex","name":"Middlesex University","base_url":"https://repository.mdx.ac.uk/oai2"},"display":{"title":"Konzeption eines mehrdimensionalen Human-Capital-Kennzahlen-Dashboards am Fallbeispiel eines Medien- und Technologieunternehmens","abstract":"As a contribution to applied business studies, the dissertation is situated within human resource management studies. The dissertation addresses the challenges of human capital measurement with the aim of empirically conceptualising a human capital dashboard for an existing media and technology company. These challenges include data analysis methods, where academic procedures are often too complex to be used in business practice. In addition, Human Resources (HR) often occupies a lower position in the corporate hierarchy than other departments such as Controlling or Sales. As a result, HR is not recognised for its contribution to human capital as these achievements are attributed to managers in other departments. In addition, key information (e.g. employee satisfaction indices) may be lacking or require significant effort to quantify (e.g. motivation levels). Accordingly, based on a review of the literature, the paper explores how human capital can be measured for applied and operational HR management. To this end, the methodological controversy surrounding the Saarbrücker formula is addressed, as well as the description of fourteen other measurement methods. Within a clustering of methods into quarters (monetary/non-monetary and uni-/multidimensional) a research gap can be identified. The hypothesis is that there is no tool (dashboard) that includes quantitative, financial and qualitative data equally. However, meta-analyses have shown that this multidimensionality is critical for success. Thus, the key finding of this work is that the three dimensions must be given equal weight in the applied measurement of human capital. In terms of creating a multidimensional human capital tool, the findings from the expert interviews in the empirical part of the dissertation are as follows: • The interaction of data categories forms the basis for measurement. • Measuring human capital adds value. • The use of elaborate methods does not lead to any advanced knowledge. • Human capital can be measured using HR dashboards.","abstract_html":"As a contribution to applied business studies, the dissertation is situated within human resource management studies. The dissertation addresses the challenges of human capital measurement with the aim of empirically conceptualising a human capital dashboard for an existing media and technology company. These challenges include data analysis methods, where academic procedures are often too complex to be used in business practice. In addition, Human Resources (HR) often occupies a lower position in the corporate hierarchy than other departments such as Controlling or Sales. As a result, HR is not recognised for its contribution to human capital as these achievements are attributed to managers in other departments. In addition, key information (e.g. employee satisfaction indices) may be lacking or require significant effort to quantify (e.g. motivation levels). Accordingly, based on a review of the literature, the paper explores how human capital can be measured for applied and operational HR management. To this end, the methodological controversy surrounding the Saarbrücker formula is addressed, as well as the description of fourteen other measurement methods. Within a clustering of methods into quarters (monetary/non-monetary and uni-/multidimensional) a research gap can be identified. The hypothesis is that there is no tool (dashboard) that includes quantitative, financial and qualitative data equally. However, meta-analyses have shown that this multidimensionality is critical for success. Thus, the key finding of this work is that the three dimensions must be given equal weight in the applied measurement of human capital. In terms of creating a multidimensional human capital tool, the findings from the expert interviews in the empirical part of the dissertation are as follows: • The interaction of data categories forms the basis for measurement. • Measuring human capital adds value. • The use of elaborate methods does not lead to any advanced knowledge. • Human capital can be measured using HR dashboards.","abstract_has_math":false,"creators":["Eckert, T."],"institution":"Middlesex University / KMU Akademie & Management AG","degree_name":null,"degree_level":"DBA thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023","date_published":"2023","updated_at":"2026-07-24T03:03:48Z","subjects":["Human Capital Management (HCM)","HC Key Figures","HC Controlling","HC Dashboard"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:105082"],"render_values":[{"text":"oai:repository.mdx.ac.uk:105082","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Eckert, T."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023"]},{"key":"dc:date.issued","label":"Date","values":["2023"]},{"key":"dc:publisher","label":"Institution","values":["Middlesex University Research Repository"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Business School"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Middlesex University / KMU Akademie & Management AG"]},{"key":"dc:relation","label":"Dc Relation","values":["https://repository.mdx.ac.uk/item/105082"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://repository.mdx.ac.uk/item/105082"]},{"key":"dc:type","label":"Dc Type","values":["Thesis or dissertation"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["DBA thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Human Capital Management (HCM)","HC Key Figures","HC Controlling","HC Dashboard"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:repository.mdx.ac.uk:105082"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://repository.mdx.ac.uk/download/028b62877a54c4466eb88e754ec2b976707f067ee20ab47c0d51d90b4286e198/4783412/TEckert%20thesis.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["As a contribution to applied business studies, the dissertation is situated within human resource management studies. 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However, meta-analyses have shown that this multidimensionality is critical for success. Thus, the key finding of this work is that the three dimensions must be given equal weight in the applied measurement of human capital. In terms of creating a multidimensional human capital tool, the findings from the expert interviews in the empirical part of the dissertation are as follows: • The interaction of data categories forms the basis for measurement. • Measuring human capital adds value. • The use of elaborate methods does not lead to any advanced knowledge. • Human capital can be measured using HR dashboards."]},{"key":"dc:title","label":"Title","values":["Konzeption eines mehrdimensionalen Human-Capital-Kennzahlen-Dashboards am Fallbeispiel eines Medien- und Technologieunternehmens"]}]}],"canonical_facts":{"dc:creator":["Eckert, T."],"dc:date":["2023"],"dc:date.issued":["2023"],"dc:description":["As a contribution to applied business studies, the dissertation is situated within human resource management studies. The dissertation addresses the challenges of human capital measurement with the aim of empirically conceptualising a human capital dashboard for an existing media and technology company. 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Within a clustering of methods into quarters (monetary/non-monetary and uni-/multidimensional) a research gap can be identified. The hypothesis is that there is no tool (dashboard) that includes quantitative, financial and qualitative data equally. However, meta-analyses have shown that this multidimensionality is critical for success. Thus, the key finding of this work is that the three dimensions must be given equal weight in the applied measurement of human capital. 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In addition, Human Resources (HR) often occupies a lower position in the corporate hierarchy than other departments such as Controlling or Sales. As a result, HR is not recognised for its contribution to human capital as these achievements are attributed to managers in other departments. In addition, key information (e.g. employee satisfaction indices) may be lacking or require significant effort to quantify (e.g. motivation levels). Accordingly, based on a review of the literature, the paper explores how human capital can be measured for applied and operational HR management. To this end, the methodological controversy surrounding the Saarbrücker formula is addressed, as well as the description of fourteen other measurement methods. Within a clustering of methods into quarters (monetary/non-monetary and uni-/multidimensional) a research gap can be identified. The hypothesis is that there is no tool (dashboard) that includes quantitative, financial and qualitative data equally. 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