A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | RAM. Revista de Administração Mackenzie |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712019000400202 |
Resumo: | ABSTRACT Purpose: The article presents the development of a framework to analyze the use of big data and analytics in organizations. The framework is based on affordance theory and actor-network theory (ANT). Originality/value: Big data and analytics are a set of tools and techniques that are not new, but recently have received much attention from the media and academia. The media promotes big data and analytics while the academia addresses the fact that there are still implementation obstacles and the process of using big data analytics is not well understood. Design/methodology/approach: We used a qualitative approach, in the form of a theoretical essay. We analyzed papers that related affordance theory with IT and, in particular, with big data and analytics. Further, in order to create the resulting framework, an illustrative case study was conducted. Findings: Affordance theory, allied to the translation concept of ANT, can be useful when analyzing the process of using big data and analytics in organizations, because it contemplates individual and organizational aspects, covering the perception of utility, necessary sociotechnical transformations in processes, people and structures, actual use and organizational effects. As the main contribution, we proposed a framework that includes elements of translation to guide future research. |
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A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSALBig dataAnalyticsAffordancesActor-network theoryFrameworkABSTRACT Purpose: The article presents the development of a framework to analyze the use of big data and analytics in organizations. The framework is based on affordance theory and actor-network theory (ANT). Originality/value: Big data and analytics are a set of tools and techniques that are not new, but recently have received much attention from the media and academia. The media promotes big data and analytics while the academia addresses the fact that there are still implementation obstacles and the process of using big data analytics is not well understood. Design/methodology/approach: We used a qualitative approach, in the form of a theoretical essay. We analyzed papers that related affordance theory with IT and, in particular, with big data and analytics. Further, in order to create the resulting framework, an illustrative case study was conducted. Findings: Affordance theory, allied to the translation concept of ANT, can be useful when analyzing the process of using big data and analytics in organizations, because it contemplates individual and organizational aspects, covering the perception of utility, necessary sociotechnical transformations in processes, people and structures, actual use and organizational effects. As the main contribution, we proposed a framework that includes elements of translation to guide future research.Editora MackenzieUniversidade Presbiteriana Mackenzie2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712019000400202RAM. Revista de Administração Mackenzie v.20 n.4 2019reponame:RAM. Revista de Administração Mackenzieinstname:Universidade Presbiteriana Mackenzie (UPM)instacron:MACKENZIE10.1590/1678-6971/eramr190182info:eu-repo/semantics/openAccessSTRAUSS,LUISA M.HOPPEN,NORBERTOeng2019-08-22T00:00:00Zoai:scielo:S1678-69712019000400202Revistahttps://www.scielo.br/j/ram/https://old.scielo.br/oai/scielo-oai.phprevista.adm@mackenzie.br1678-69711518-6776opendoar:2019-08-22T00:00RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)false |
dc.title.none.fl_str_mv |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
title |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
spellingShingle |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL STRAUSS,LUISA M. Big data Analytics Affordances Actor-network theory Framework |
title_short |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
title_full |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
title_fullStr |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
title_full_unstemmed |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
title_sort |
A FRAMEWORK TO ANALYZE AFFORDANCES WHEN USING BIG DATA AND ANALYTICS IN ORGANIZATIONS: A PROPOSAL |
author |
STRAUSS,LUISA M. |
author_facet |
STRAUSS,LUISA M. HOPPEN,NORBERTO |
author_role |
author |
author2 |
HOPPEN,NORBERTO |
author2_role |
author |
dc.contributor.author.fl_str_mv |
STRAUSS,LUISA M. HOPPEN,NORBERTO |
dc.subject.por.fl_str_mv |
Big data Analytics Affordances Actor-network theory Framework |
topic |
Big data Analytics Affordances Actor-network theory Framework |
description |
ABSTRACT Purpose: The article presents the development of a framework to analyze the use of big data and analytics in organizations. The framework is based on affordance theory and actor-network theory (ANT). Originality/value: Big data and analytics are a set of tools and techniques that are not new, but recently have received much attention from the media and academia. The media promotes big data and analytics while the academia addresses the fact that there are still implementation obstacles and the process of using big data analytics is not well understood. Design/methodology/approach: We used a qualitative approach, in the form of a theoretical essay. We analyzed papers that related affordance theory with IT and, in particular, with big data and analytics. Further, in order to create the resulting framework, an illustrative case study was conducted. Findings: Affordance theory, allied to the translation concept of ANT, can be useful when analyzing the process of using big data and analytics in organizations, because it contemplates individual and organizational aspects, covering the perception of utility, necessary sociotechnical transformations in processes, people and structures, actual use and organizational effects. As the main contribution, we proposed a framework that includes elements of translation to guide future research. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712019000400202 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712019000400202 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-6971/eramr190182 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Editora Mackenzie Universidade Presbiteriana Mackenzie |
publisher.none.fl_str_mv |
Editora Mackenzie Universidade Presbiteriana Mackenzie |
dc.source.none.fl_str_mv |
RAM. Revista de Administração Mackenzie v.20 n.4 2019 reponame:RAM. Revista de Administração Mackenzie instname:Universidade Presbiteriana Mackenzie (UPM) instacron:MACKENZIE |
instname_str |
Universidade Presbiteriana Mackenzie (UPM) |
instacron_str |
MACKENZIE |
institution |
MACKENZIE |
reponame_str |
RAM. Revista de Administração Mackenzie |
collection |
RAM. Revista de Administração Mackenzie |
repository.name.fl_str_mv |
RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM) |
repository.mail.fl_str_mv |
revista.adm@mackenzie.br |
_version_ |
1752128650185015296 |