Managing supply chain resources with Big Data Analytics: a systematic review

被引:76
|
作者
Barbosa, Marcelo Werneck [1 ,2 ]
de la Calle Vicente, Alberto [3 ]
Ladeira, Marcelo Bronzo [1 ]
Valadares de Oliveira, Marcos Paulo [4 ]
机构
[1] Univ Fed Minas Gerais, Dept Adm, Belo Horizonte, MG, Brazil
[2] Pontificia Univ Catolica Minas Gerais, Dept Software Engn & Informat Syst, Belo Horizonte, MG, Brazil
[3] Univ Deusto, Dept Ind Technol, Bilbao, Spain
[4] Univ Fed Espirito Santo, Dept Adm, Vitoria, Brazil
关键词
Big Data Analytics; Business Analytics; Supply Chain Analytics; Supply Chain Intelligence; supply chain management; Resource-based View; BUSINESS INTELLIGENCE; PREDICTIVE ANALYTICS; KNOWLEDGE MANAGEMENT; DYNAMIC-CAPABILITIES; DATA INITIATIVES; DECISION-MAKING; DATA SCIENCE; PERFORMANCE; CHALLENGES; INTEGRATION;
D O I
10.1080/13675567.2017.1369501
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Big Data Analytics (BDA) has the potential to improve demand forecasting, communications and better manage supply chain resources. Despite such recognised benefits and the increase of BDA research, little is known about the general approaches used to investigate BDA in the context of supply chain management (SCM). In the light of the Resource-based View, the main goal of this study was, by means of a systematic literature review, to comprehend how BDA has been investigated on SCM studies, which resources are managed by BDA as well as which SCM processes are involved. Our study found out that the predictive and prescriptive approaches are more frequently used and organisational, technological and human resources are often managed by BDA. It was observed a focus on Demand Management and Order Fulfilment processes and a lack of studies on Returns Management, which indicates an open research area that should be exploited by future studies.
引用
收藏
页码:177 / 200
页数:24
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