Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/88463
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorPavlidou, Ien_US
dc.creatorPapagiannidis, Sen_US
dc.creatorTsui, Een_US
dc.date.accessioned2020-11-26T09:27:45Z-
dc.date.available2020-11-26T09:27:45Z-
dc.identifier.issn0263-5577en_US
dc.identifier.urihttp://hdl.handle.net/10397/88463-
dc.language.isoenen_US
dc.publisherEmerald Group Publishing Limiteden_US
dc.rights© Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher’.en_US
dc.rightsThe following publication Pavlidou, I., Papagiannidis, S. and Tsui, E. (2020), "Crowdsourcing: a systematic review of the literature using text mining", Industrial Management & Data Systems, Vol. 120 No. 11, pp. 2041-2065 is published by Emerald and is available at https://dx.doi.org/10.1108/IMDS-08-2020-0474en_US
dc.subjectCrowdsourcingen_US
dc.subjectCrowdfundingen_US
dc.subjectCrowd venturingen_US
dc.subjectSystematic literature reviewen_US
dc.subjectInnovationen_US
dc.subjectNewproduct developmenten_US
dc.subjectPlatformsen_US
dc.subjectProjectsen_US
dc.subjectCollective intelligenceen_US
dc.subjectWisdom of the crowden_US
dc.titleCrowdsourcing : a systematic review of the literature using text miningen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2041en_US
dc.identifier.epage2065en_US
dc.identifier.volume120en_US
dc.identifier.issue11en_US
dc.identifier.doi10.1108/IMDS-08-2020-0474en_US
dcterms.abstractPurpose: This study is a systematic literature review of crowdsourcing that aims to present the research evidence so far regarding the extent to which it can contribute to organisational performance and produce innovations and provide insights on how organisations can operationalise it successfully.en_US
dcterms.abstractDesign/methodology/approach: The systematic literature review revolved around a text mining methodology analysing 106 papers.en_US
dcterms.abstractFindings: The themes identified are performance, innovation, operational aspects and motivations. The review revealed a few potential directions for future research in each of the themes considered.en_US
dcterms.abstractFindings: The themes identified are performance, innovation, operational aspects and motivations. The review revealed a few potential directions for future research in each of the themes considered.en_US
dcterms.abstractOriginality/value: This study employed quantitative content analysis in order to identify the main research themes with higher reliability and validity. It is also the first review on crowdsourcing that incorporates the relevant literature on crowdfunding as a value-creation tool.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIndustrial management and data systems, 2020, v. 120, no. 11, p. 2041-2065en_US
dcterms.isPartOfIndustrial management and data systemsen_US
dcterms.issued2020-
dc.identifier.eissn1758-5783en_US
dc.description.validate202011 bcrcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0480-n01en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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