Big Data in Family Firms: A Socioemotional Wealth Perspective

Show simple item record

dc.contributor.author Arzubiaga, U.
dc.contributor.author Diaz-Moriana, V.
dc.contributor.author Bauweraerts, J.
dc.contributor.author Escobar, O.R.
dc.date.accessioned 2022-07-19T06:26:32Z
dc.identifier.uri http://hdl.handle.net/11201/159425
dc.description.abstract [eng] Since about 2010, big data analysis has drastically changed the landscape of information management by becoming a central topic in the academic literature of several fields. Despite the significant contribution of family firms to the economic fabric worldwide and their unique decision-making processes, there is a lack of research investigating big data in family-owned businesses. To address this gap, this article draws on the socioemotional wealth (SEW) perspective and its FIBER model to conceptually investigate its role in family firms' decision to implement big data. We introduce a set of propositions and a framework linking the FIBER dimensions to the likeliness of implementing big data in family firms. Our research thus contributes to a more fine-grained understanding of the decision-making process in family firms.
dc.format application/pdf
dc.relation.isformatof Versió postprint del document publicat a: https://doi.org/10.1016/j.emj.2020.10.006
dc.relation.ispartof European Management Journal, 2020, vol. 39, num. 3, p. 344-352
dc.subject.classification 33 - Economia
dc.subject.other 33 - Economics. Economic science
dc.title Big Data in Family Firms: A Socioemotional Wealth Perspective
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/acceptedVersion
dc.date.updated 2022-07-19T06:26:32Z
dc.date.embargoEndDate info:eu-repo/date/embargoEnd/2026-12-31
dc.embargo 2026-12-31
dc.rights.accessRights info:eu-repo/semantics/embargoedAccess
dc.identifier.doi https://doi.org/10.1016/j.emj.2020.10.006


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Repository


Advanced Search

Browse

My Account

Statistics