TY - JOUR
T1 - Agile manufacturing practices
T2 - the role of big data and business analytics with multiple case studies
AU - Gunasekaran, Angappa
AU - Yusuf, Yahaya Y.
AU - Adeleye, Ezekiel O.
AU - Papadopoulos, Thanos
N1 - Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/1/17
Y1 - 2018/1/17
N2 - The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four UK organisations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes.
AB - The purpose of this study was to examine the role of big data and business analytics (BDBA) in agile manufacturing practices. Literature has discussed the benefits and challenges related to the deployment of big data within operations and supply chains, but there has not been a study of the facilitating roles of BDBA in achieving an enhanced level of agile manufacturing practices. As a response to this gap, and drawing upon multiple qualitative case studies undertaken among four UK organisations, we present and validate a framework for the role of BDBA within agile manufacturing. The findings show that market turbulence has negative universal effects and that agile manufacturing enablers are being progressively deployed and aided by BDBA to yield better competitive and business performance objectives. Further, the level of intervention was found to differ across companies depending on the extent of deployment of BDBA, which accounts for variations in outcomes.
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U2 - 10.1080/00207543.2017.1395488
DO - 10.1080/00207543.2017.1395488
M3 - Article
AN - SCOPUS:85032702646
SN - 0020-7543
VL - 56
SP - 385
EP - 397
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 1-2
ER -