Data analytics management capability and strategies for interorganisational collaborations: a survey research

Drawing on the dynamic capabilities perspective, we propose a research model that explains how data analytics management capability (DAMC) impacts interorganisational collaboration and business performance. Our model incorporates DA strategy as a moderator of the relationship between DAMC and collab...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of business analytics 2023-10, Vol.ahead-of-print (ahead-of-print), p.1-21
Hauptverfasser: Daneshvar Kakhki, Mohammad, Shrivastava, Utkarsh
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 21
container_issue ahead-of-print
container_start_page 1
container_title Journal of business analytics
container_volume ahead-of-print
creator Daneshvar Kakhki, Mohammad
Shrivastava, Utkarsh
description Drawing on the dynamic capabilities perspective, we propose a research model that explains how data analytics management capability (DAMC) impacts interorganisational collaboration and business performance. Our model incorporates DA strategy as a moderator of the relationship between DAMC and collaboration. We test our model with a survey of 508 practitioners. Our findings suggest that while the DA innovator strategy fosters collaboration, it does not improve performance. In contrast, a more conservative DA strategy leads to higher strategic and operational performance. Our work highlights how leveraging DAMC facilitates effective interorganisational collaborations.
doi_str_mv 10.1080/2573234X.2023.2204159
format Article
fullrecord <record><control><sourceid>econis_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1080_2573234X_2023_2204159</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1860741134</sourcerecordid><originalsourceid>FETCH-LOGICAL-c367t-4fb836f15709413bd658713bd524efbf6c7349fd30d66c3bab611a7d7bceab663</originalsourceid><addsrcrecordid>eNp9kN1KAzEQhYMoWGofQcgLtOZvs1uvlPoLBW8UerdMskmN7G5KEpV9e7O26p0XYc4kc86QD6FzShaUVOSCFSVnXGwWjDC-YIwIWiyP0GS8nzNeVMe_WmxO0SzGN0IIGw-nE9TdQAIMPbRDcjriLsut6UyfsIYdKNe6NOT3BscUIJmtMxFbH7Drkwk-bKF3EZLzOQFr37agfPju4yUGHN_DhxlwMNFA0K9n6MRCG83sUKfo5e72efUwXz_dP66u13PNZZnmwqqKS0uLkiwF5aqRRVWOtWDCWGWlLrlY2oaTRkrNFShJKZRNqbTJWvIpKva5OvgYg7H1LrgOwlBTUo_Y6h9s9YitPmDLPrz3Ge3zv_5clSSloJSLPHK1H3F9xtDBpw9tUycYWh9sgF5nG_9_yxflq4HZ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Data analytics management capability and strategies for interorganisational collaborations: a survey research</title><source>Alma/SFX Local Collection</source><creator>Daneshvar Kakhki, Mohammad ; Shrivastava, Utkarsh</creator><creatorcontrib>Daneshvar Kakhki, Mohammad ; Shrivastava, Utkarsh</creatorcontrib><description>Drawing on the dynamic capabilities perspective, we propose a research model that explains how data analytics management capability (DAMC) impacts interorganisational collaboration and business performance. Our model incorporates DA strategy as a moderator of the relationship between DAMC and collaboration. We test our model with a survey of 508 practitioners. Our findings suggest that while the DA innovator strategy fosters collaboration, it does not improve performance. In contrast, a more conservative DA strategy leads to higher strategic and operational performance. Our work highlights how leveraging DAMC facilitates effective interorganisational collaborations.</description><identifier>ISSN: 2573-234X</identifier><identifier>EISSN: 2573-2358</identifier><identifier>DOI: 10.1080/2573234X.2023.2204159</identifier><language>eng</language><publisher>Taylor &amp; Francis</publisher><subject>business performance ; collaboration ; cooperation ; coordination ; Data analytics management capability ; data analytics strategy</subject><ispartof>Journal of business analytics, 2023-10, Vol.ahead-of-print (ahead-of-print), p.1-21</ispartof><rights>2023 The Operational Research Society 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-4fb836f15709413bd658713bd524efbf6c7349fd30d66c3bab611a7d7bceab663</citedby><cites>FETCH-LOGICAL-c367t-4fb836f15709413bd658713bd524efbf6c7349fd30d66c3bab611a7d7bceab663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Daneshvar Kakhki, Mohammad</creatorcontrib><creatorcontrib>Shrivastava, Utkarsh</creatorcontrib><title>Data analytics management capability and strategies for interorganisational collaborations: a survey research</title><title>Journal of business analytics</title><description>Drawing on the dynamic capabilities perspective, we propose a research model that explains how data analytics management capability (DAMC) impacts interorganisational collaboration and business performance. Our model incorporates DA strategy as a moderator of the relationship between DAMC and collaboration. We test our model with a survey of 508 practitioners. Our findings suggest that while the DA innovator strategy fosters collaboration, it does not improve performance. In contrast, a more conservative DA strategy leads to higher strategic and operational performance. Our work highlights how leveraging DAMC facilitates effective interorganisational collaborations.</description><subject>business performance</subject><subject>collaboration</subject><subject>cooperation</subject><subject>coordination</subject><subject>Data analytics management capability</subject><subject>data analytics strategy</subject><issn>2573-234X</issn><issn>2573-2358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kN1KAzEQhYMoWGofQcgLtOZvs1uvlPoLBW8UerdMskmN7G5KEpV9e7O26p0XYc4kc86QD6FzShaUVOSCFSVnXGwWjDC-YIwIWiyP0GS8nzNeVMe_WmxO0SzGN0IIGw-nE9TdQAIMPbRDcjriLsut6UyfsIYdKNe6NOT3BscUIJmtMxFbH7Drkwk-bKF3EZLzOQFr37agfPju4yUGHN_DhxlwMNFA0K9n6MRCG83sUKfo5e72efUwXz_dP66u13PNZZnmwqqKS0uLkiwF5aqRRVWOtWDCWGWlLrlY2oaTRkrNFShJKZRNqbTJWvIpKva5OvgYg7H1LrgOwlBTUo_Y6h9s9YitPmDLPrz3Ge3zv_5clSSloJSLPHK1H3F9xtDBpw9tUycYWh9sgF5nG_9_yxflq4HZ</recordid><startdate>20231002</startdate><enddate>20231002</enddate><creator>Daneshvar Kakhki, Mohammad</creator><creator>Shrivastava, Utkarsh</creator><general>Taylor &amp; Francis</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20231002</creationdate><title>Data analytics management capability and strategies for interorganisational collaborations: a survey research</title><author>Daneshvar Kakhki, Mohammad ; Shrivastava, Utkarsh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-4fb836f15709413bd658713bd524efbf6c7349fd30d66c3bab611a7d7bceab663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>business performance</topic><topic>collaboration</topic><topic>cooperation</topic><topic>coordination</topic><topic>Data analytics management capability</topic><topic>data analytics strategy</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Daneshvar Kakhki, Mohammad</creatorcontrib><creatorcontrib>Shrivastava, Utkarsh</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><jtitle>Journal of business analytics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Daneshvar Kakhki, Mohammad</au><au>Shrivastava, Utkarsh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data analytics management capability and strategies for interorganisational collaborations: a survey research</atitle><jtitle>Journal of business analytics</jtitle><date>2023-10-02</date><risdate>2023</risdate><volume>ahead-of-print</volume><issue>ahead-of-print</issue><spage>1</spage><epage>21</epage><pages>1-21</pages><issn>2573-234X</issn><eissn>2573-2358</eissn><abstract>Drawing on the dynamic capabilities perspective, we propose a research model that explains how data analytics management capability (DAMC) impacts interorganisational collaboration and business performance. Our model incorporates DA strategy as a moderator of the relationship between DAMC and collaboration. We test our model with a survey of 508 practitioners. Our findings suggest that while the DA innovator strategy fosters collaboration, it does not improve performance. In contrast, a more conservative DA strategy leads to higher strategic and operational performance. Our work highlights how leveraging DAMC facilitates effective interorganisational collaborations.</abstract><pub>Taylor &amp; Francis</pub><doi>10.1080/2573234X.2023.2204159</doi><tpages>21</tpages></addata></record>
fulltext fulltext
identifier ISSN: 2573-234X
ispartof Journal of business analytics, 2023-10, Vol.ahead-of-print (ahead-of-print), p.1-21
issn 2573-234X
2573-2358
language eng
recordid cdi_crossref_primary_10_1080_2573234X_2023_2204159
source Alma/SFX Local Collection
subjects business performance
collaboration
cooperation
coordination
Data analytics management capability
data analytics strategy
title Data analytics management capability and strategies for interorganisational collaborations: a survey research
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T05%3A09%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-econis_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Data%20analytics%20management%20capability%20and%20strategies%20for%20interorganisational%20collaborations:%20a%20survey%20research&rft.jtitle=Journal%20of%20business%20analytics&rft.au=Daneshvar%20Kakhki,%20Mohammad&rft.date=2023-10-02&rft.volume=ahead-of-print&rft.issue=ahead-of-print&rft.spage=1&rft.epage=21&rft.pages=1-21&rft.issn=2573-234X&rft.eissn=2573-2358&rft_id=info:doi/10.1080/2573234X.2023.2204159&rft_dat=%3Ceconis_cross%3E1860741134%3C/econis_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true