dc.contributor.author | Terziyan, Vagan | |
dc.contributor.author | Kaikova, Olena | |
dc.date.accessioned | 2015-08-26T04:31:56Z | |
dc.date.available | 2016-08-31T21:45:05Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Terziyan, V., & Kaikova, O. (2015). The ‘magic square’: A roadmap towards emotional business intelligence. <i>Journal of Decision Systems</i>, <i>24</i>(3), 255-272. <a href="https://doi.org/10.1080/12460125.2015.969592" target="_blank">https://doi.org/10.1080/12460125.2015.969592</a> | |
dc.identifier.other | CONVID_24011029 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/46707 | |
dc.description.abstract | Emotions are known to be an important driver in human behaviour and decision-making. In the business world, there is a growing belief that emotions are not an obstacle but rather an enabler for a successful business. Business intelligence (by providing analytical processing and convenient presentation of a business data) traditionally supports rational decision-making. However, opposite to former opinion that all decisions should be ‘cleansed’ of emotions, there are more and more indicators of the need for solutions supporting also emotional decision-making. The domain of emotional business intelligence, suggested in this paper, concerns emotional and emotion-aware decisions, intuition, innovation and creativity. We present the new domain as an integration of popular, emerging and evolving domains of emotional business, emotional intelligence and business intelligence. We argue the objectives of emotional business intelligence and discuss the needed technological basis, models and methods for its roadmapping. | en |
dc.language.iso | eng | |
dc.publisher | Taylor & Francis | |
dc.relation.ispartofseries | Journal of Decision Systems | |
dc.subject.other | decision-making | |
dc.subject.other | emotion | |
dc.subject.other | emotional business | |
dc.subject.other | rational vs. emotional | |
dc.subject.other | semantic technology | |
dc.title | The ‘magic square’: A roadmap towards emotional business intelligence | |
dc.type | research article | |
dc.identifier.urn | URN:NBN:fi:jyu-201508252751 | |
dc.contributor.laitos | Tietotekniikan laitos | fi |
dc.contributor.laitos | Department of Mathematical Information Technology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.date.updated | 2015-08-25T09:15:03Z | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 255-272 | |
dc.relation.issn | 1246-0125 | |
dc.relation.numberinseries | 3 | |
dc.relation.volume | 24 | |
dc.type.version | acceptedVersion | |
dc.rights.copyright | © Taylor & Francis. This is a final draft version of an article whose final and definitive form has been published by Taylor & Francis. | |
dc.rights.accesslevel | openAccess | fi |
dc.type.publication | article | |
dc.subject.yso | tunneäly | |
dc.subject.yso | business intelligence | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p6731 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p9225 | |
dc.relation.doi | 10.1080/12460125.2015.969592 | |
dc.type.okm | A1 | |