Resource management in big data initiatives: Processes and dynamic capabilities

详细信息    查看全文

• 作者：Ashley Braganza^a ; ^{ashley.braganza@brunel.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Laurence Brooks^b ; ^{laurence.brooks@dmu.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Daniel Nepelski^c ; ^{daniel.nepelski@ec.europa.eu" class="auth_mail" title="E-mail the corresponding author} ; Maged Ali^d ; ^{maaali@essex.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Russ Moro^a ; ^{russ.moro@brunel.ac.uk" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Big data ; Resource based theory ; Dynamic capabilities ; Business processes ; European Poles Of Excellence
• 刊名：Journal of Business Research
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：70
• 期：Complete
• 页码：328-337
• 全文大小：958 K

文摘

Effective management of organizational resources in big data initiatives is of growing importance. Although academic and popular literatures contain many examples of big data initiatives, very few are repeated in the same organization. This suggests either big data delivers benefits once only per organization or senior managers are reluctant to commit resources to big data on a sustained basis. This paper makes three contributions to the Special Issue's theme of enhancing organizational resource management. One is to establish an archetype business process for big data initiatives. The second contribution directs attention to creating a dynamic capability with big data initiatives. The third identifies drawbacks of resource based theory (RBT) and it's underpinning assumptions in the context of big data. The paper discusses lessons learnt and draws out implications for practice and business research. The paper's intellectual and practical contributions are based on an in-depth case study of the European ICT Poles of Excellence (EIPE) big data initiative and evidence from the extant literature.