Exploring the path to big data analytics success in healthcare
Although big data analytics have tremendous benefits for healthcare organizations, extant research has paid insufficient attention to the exploration of its business value. In order to bridge this knowledge gap, this study proposes a big data analytics-enabled business value model in which we use th...
Gespeichert in:
| Veröffentlicht in: | Journal of business research 2017-01, Vol.70, p.287-299 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 299 |
|---|---|
| container_issue | |
| container_start_page | 287 |
| container_title | Journal of business research |
| container_volume | 70 |
| creator | Wang, Yichuan Hajli, Nick |
| description | Although big data analytics have tremendous benefits for healthcare organizations, extant research has paid insufficient attention to the exploration of its business value. In order to bridge this knowledge gap, this study proposes a big data analytics-enabled business value model in which we use the resource-based theory (RBT) and capability building view to explain how big data analytics capabilities can be developed and what potential benefits can be obtained by these capabilities in the health care industries. Using this model, we investigate 109 case descriptions, covering 63 healthcare organizations to explore the causal relationships between the big data analytics capabilities and business value and the path-to-value chains for big data analytics success. Our findings provide new insights to healthcare practitioners on how to constitute big data analytics capabilities for business transformation and offer an empirical basis that can stimulate a more detailed investigation of big data analytics implementation. |
| doi_str_mv | 10.1016/j.jbusres.2016.08.002 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1847486709</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0148296316304891</els_id><sourcerecordid>1847486709</sourcerecordid><originalsourceid>FETCH-LOGICAL-c401t-d602c445e7c2f249171eb1044861c4be7e6f16e84dd5164837d6d2c1ef7eb6443</originalsourceid><addsrcrecordid>eNqFkM9LwzAYhoMoOKd_ghDw4qU1SbMkvSgi8wcMvOg5pOnXNaVrZ5KK--_N2E5ePH188LwvvA9C15TklFBx1-VdNQUPIWfpzYnKCWEnaEaVLDJZSnWKZoRylbFSFOfoIoSOJIIQNUP3y59tP3o3rHFsAW9NbHEcceXWuDbRYDOYfhedDThM1kII2A24BdPH1hoPl-isMX2Aq-Odo8_n5cfTa7Z6f3l7elxllhMas1oQZjlfgLSsYbykkkJFCedKUMsrkCAaKkDxul5QwVUha1EzS6GRUAnOizm6PfRu_fg1QYh644KFvjcDjFPQVHGZyiQpE3rzB-3GyacZe6qQqiwLxRK1OFDWjyG5a_TWu43xO02J3lvVnT5a1XurmiidnKXcwyEHae23A6-DdTBYqJ0HG3U9un8afgFGUoG3</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1837899382</pqid></control><display><type>article</type><title>Exploring the path to big data analytics success in healthcare</title><source>Access via ScienceDirect (Elsevier)</source><creator>Wang, Yichuan ; Hajli, Nick</creator><creatorcontrib>Wang, Yichuan ; Hajli, Nick</creatorcontrib><description>Although big data analytics have tremendous benefits for healthcare organizations, extant research has paid insufficient attention to the exploration of its business value. In order to bridge this knowledge gap, this study proposes a big data analytics-enabled business value model in which we use the resource-based theory (RBT) and capability building view to explain how big data analytics capabilities can be developed and what potential benefits can be obtained by these capabilities in the health care industries. Using this model, we investigate 109 case descriptions, covering 63 healthcare organizations to explore the causal relationships between the big data analytics capabilities and business value and the path-to-value chains for big data analytics success. Our findings provide new insights to healthcare practitioners on how to constitute big data analytics capabilities for business transformation and offer an empirical basis that can stimulate a more detailed investigation of big data analytics implementation.</description><identifier>ISSN: 0148-2963</identifier><identifier>EISSN: 1873-7978</identifier><identifier>DOI: 10.1016/j.jbusres.2016.08.002</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Big Data ; Big data analytics ; Business value ; Capability building view ; Causality ; Data analysis ; Health care industries ; Health care industry ; Information technology source management ; Resource-based theory ; Studies ; Valuation</subject><ispartof>Journal of business research, 2017-01, Vol.70, p.287-299</ispartof><rights>2016 Elsevier Inc.</rights><rights>Copyright Elsevier Sequoia S.A. Jan 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c401t-d602c445e7c2f249171eb1044861c4be7e6f16e84dd5164837d6d2c1ef7eb6443</citedby><cites>FETCH-LOGICAL-c401t-d602c445e7c2f249171eb1044861c4be7e6f16e84dd5164837d6d2c1ef7eb6443</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jbusres.2016.08.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Wang, Yichuan</creatorcontrib><creatorcontrib>Hajli, Nick</creatorcontrib><title>Exploring the path to big data analytics success in healthcare</title><title>Journal of business research</title><description>Although big data analytics have tremendous benefits for healthcare organizations, extant research has paid insufficient attention to the exploration of its business value. In order to bridge this knowledge gap, this study proposes a big data analytics-enabled business value model in which we use the resource-based theory (RBT) and capability building view to explain how big data analytics capabilities can be developed and what potential benefits can be obtained by these capabilities in the health care industries. Using this model, we investigate 109 case descriptions, covering 63 healthcare organizations to explore the causal relationships between the big data analytics capabilities and business value and the path-to-value chains for big data analytics success. Our findings provide new insights to healthcare practitioners on how to constitute big data analytics capabilities for business transformation and offer an empirical basis that can stimulate a more detailed investigation of big data analytics implementation.</description><subject>Big Data</subject><subject>Big data analytics</subject><subject>Business value</subject><subject>Capability building view</subject><subject>Causality</subject><subject>Data analysis</subject><subject>Health care industries</subject><subject>Health care industry</subject><subject>Information technology source management</subject><subject>Resource-based theory</subject><subject>Studies</subject><subject>Valuation</subject><issn>0148-2963</issn><issn>1873-7978</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFkM9LwzAYhoMoOKd_ghDw4qU1SbMkvSgi8wcMvOg5pOnXNaVrZ5KK--_N2E5ePH188LwvvA9C15TklFBx1-VdNQUPIWfpzYnKCWEnaEaVLDJZSnWKZoRylbFSFOfoIoSOJIIQNUP3y59tP3o3rHFsAW9NbHEcceXWuDbRYDOYfhedDThM1kII2A24BdPH1hoPl-isMX2Aq-Odo8_n5cfTa7Z6f3l7elxllhMas1oQZjlfgLSsYbykkkJFCedKUMsrkCAaKkDxul5QwVUha1EzS6GRUAnOizm6PfRu_fg1QYh644KFvjcDjFPQVHGZyiQpE3rzB-3GyacZe6qQqiwLxRK1OFDWjyG5a_TWu43xO02J3lvVnT5a1XurmiidnKXcwyEHae23A6-DdTBYqJ0HG3U9un8afgFGUoG3</recordid><startdate>201701</startdate><enddate>201701</enddate><creator>Wang, Yichuan</creator><creator>Hajli, Nick</creator><general>Elsevier Inc</general><general>Elsevier Sequoia S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope></search><sort><creationdate>201701</creationdate><title>Exploring the path to big data analytics success in healthcare</title><author>Wang, Yichuan ; Hajli, Nick</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c401t-d602c445e7c2f249171eb1044861c4be7e6f16e84dd5164837d6d2c1ef7eb6443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Big Data</topic><topic>Big data analytics</topic><topic>Business value</topic><topic>Capability building view</topic><topic>Causality</topic><topic>Data analysis</topic><topic>Health care industries</topic><topic>Health care industry</topic><topic>Information technology source management</topic><topic>Resource-based theory</topic><topic>Studies</topic><topic>Valuation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Yichuan</creatorcontrib><creatorcontrib>Hajli, Nick</creatorcontrib><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Journal of business research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Yichuan</au><au>Hajli, Nick</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring the path to big data analytics success in healthcare</atitle><jtitle>Journal of business research</jtitle><date>2017-01</date><risdate>2017</risdate><volume>70</volume><spage>287</spage><epage>299</epage><pages>287-299</pages><issn>0148-2963</issn><eissn>1873-7978</eissn><abstract>Although big data analytics have tremendous benefits for healthcare organizations, extant research has paid insufficient attention to the exploration of its business value. In order to bridge this knowledge gap, this study proposes a big data analytics-enabled business value model in which we use the resource-based theory (RBT) and capability building view to explain how big data analytics capabilities can be developed and what potential benefits can be obtained by these capabilities in the health care industries. Using this model, we investigate 109 case descriptions, covering 63 healthcare organizations to explore the causal relationships between the big data analytics capabilities and business value and the path-to-value chains for big data analytics success. Our findings provide new insights to healthcare practitioners on how to constitute big data analytics capabilities for business transformation and offer an empirical basis that can stimulate a more detailed investigation of big data analytics implementation.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><doi>10.1016/j.jbusres.2016.08.002</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0148-2963 |
| ispartof | Journal of business research, 2017-01, Vol.70, p.287-299 |
| issn | 0148-2963 1873-7978 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1847486709 |
| source | Access via ScienceDirect (Elsevier) |
| subjects | Big Data Big data analytics Business value Capability building view Causality Data analysis Health care industries Health care industry Information technology source management Resource-based theory Studies Valuation |
| title | Exploring the path to big data analytics success in healthcare |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T13%3A24%3A20IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Exploring%20the%20path%20to%20big%20data%20analytics%20success%20in%20healthcare&rft.jtitle=Journal%20of%20business%20research&rft.au=Wang,%20Yichuan&rft.date=2017-01&rft.volume=70&rft.spage=287&rft.epage=299&rft.pages=287-299&rft.issn=0148-2963&rft.eissn=1873-7978&rft_id=info:doi/10.1016/j.jbusres.2016.08.002&rft_dat=%3Cproquest_cross%3E1847486709%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1837899382&rft_id=info:pmid/&rft_els_id=S0148296316304891&rfr_iscdi=true |