The growth of companies as a function of total assets

Total Assets determines the size of the companies and allows classifying them by economic relevance in every industry. However, the path of company growth, measured by Total Assets, might be different depending on the type of industry and the size of companies. Accordingly, this research focuses on...

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Autores:
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/23497
Acceso en línea:
https://repository.urosario.edu.co/handle/10336/23497
Palabra clave:
Company size
Financial statements
Industry classification
Total assets
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network_acronym_str EDOCUR2
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repository_id_str
spelling 2883306002020-05-26T00:02:32Z2020-05-26T00:02:32Z2018Total Assets determines the size of the companies and allows classifying them by economic relevance in every industry. However, the path of company growth, measured by Total Assets, might be different depending on the type of industry and the size of companies. Accordingly, this research focuses on identifying the trend in Total Assets growth across industries and company size by finding a function that fits industries-company-size combinations. The method is analytical, deductive and empirical; it is a cross-sectional analysis with six industries in two years (three for every year) with four different company sizes, based on Total Assets, grouped into the categories of micro, small, medium or big companies, for a total of 24 industry-company-size-year combinations. Every combination of industry-company-size is analyzed to see which function yields the best fit. The functions are: 1) Linear, 2) Logarithmic, 3) Inverse, 4) Quadratic, 5) Cubic, 6) Compound, 7) Power, 8) S, 9) Growth, 10) Exponential, and 11) Logistic. The test consists of statistical regression analysis, ANOVA significance test and explained variance. The cubic function gives the best results in all industry-company-size combination for the two years. Other functions are relevant in some, but not all, combinations of categories. The conclusion is that cubic function provides the best fit for Total Assets company growth across industry-company-size combinations for the two years. Cubic function properties are described for future applications. © 2018, World Scientific and Engineering Academy and Society. All rights reserved.application/pdf11099526https://repository.urosario.edu.co/handle/10336/23497engWorld Scientific and Engineering Academy and Society310301WSEAS Transactions on Business and EconomicsVol. 15WSEAS Transactions on Business and Economics, ISSN:11099526, Vol.15,(2018); pp. 301-310https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052553230&partnerID=40&md5=ca8cacc89642601c3c5c18df50fa41f7Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCompany sizeFinancial statementsIndustry classificationTotal assetsThe growth of companies as a function of total assetsarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Juárez, Fernando10336/23497oai:repository.urosario.edu.co:10336/234972022-05-02 07:37:16.684912https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv The growth of companies as a function of total assets
title The growth of companies as a function of total assets
spellingShingle The growth of companies as a function of total assets
Company size
Financial statements
Industry classification
Total assets
title_short The growth of companies as a function of total assets
title_full The growth of companies as a function of total assets
title_fullStr The growth of companies as a function of total assets
title_full_unstemmed The growth of companies as a function of total assets
title_sort The growth of companies as a function of total assets
dc.subject.keyword.spa.fl_str_mv Company size
Financial statements
Industry classification
Total assets
topic Company size
Financial statements
Industry classification
Total assets
description Total Assets determines the size of the companies and allows classifying them by economic relevance in every industry. However, the path of company growth, measured by Total Assets, might be different depending on the type of industry and the size of companies. Accordingly, this research focuses on identifying the trend in Total Assets growth across industries and company size by finding a function that fits industries-company-size combinations. The method is analytical, deductive and empirical; it is a cross-sectional analysis with six industries in two years (three for every year) with four different company sizes, based on Total Assets, grouped into the categories of micro, small, medium or big companies, for a total of 24 industry-company-size-year combinations. Every combination of industry-company-size is analyzed to see which function yields the best fit. The functions are: 1) Linear, 2) Logarithmic, 3) Inverse, 4) Quadratic, 5) Cubic, 6) Compound, 7) Power, 8) S, 9) Growth, 10) Exponential, and 11) Logistic. The test consists of statistical regression analysis, ANOVA significance test and explained variance. The cubic function gives the best results in all industry-company-size combination for the two years. Other functions are relevant in some, but not all, combinations of categories. The conclusion is that cubic function provides the best fit for Total Assets company growth across industry-company-size combinations for the two years. Cubic function properties are described for future applications. © 2018, World Scientific and Engineering Academy and Society. All rights reserved.
publishDate 2018
dc.date.created.spa.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2020-05-26T00:02:32Z
dc.date.available.none.fl_str_mv 2020-05-26T00:02:32Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.issn.none.fl_str_mv 11099526
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/23497
identifier_str_mv 11099526
url https://repository.urosario.edu.co/handle/10336/23497
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 310
dc.relation.citationStartPage.none.fl_str_mv 301
dc.relation.citationTitle.none.fl_str_mv WSEAS Transactions on Business and Economics
dc.relation.citationVolume.none.fl_str_mv Vol. 15
dc.relation.ispartof.spa.fl_str_mv WSEAS Transactions on Business and Economics, ISSN:11099526, Vol.15,(2018); pp. 301-310
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052553230&partnerID=40&md5=ca8cacc89642601c3c5c18df50fa41f7
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv World Scientific and Engineering Academy and Society
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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