Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Challenges with big data analytics in service supply chains in the UAE

Challenges with big data analytics in service supply chains in the UAE The purpose of this paper is to study the challenges associated with big data analytics (BDA) in service supply chains in the United Arab Emirates (UAE).Design/methodology/approachA comprehensive questionnaire has been developed based on semi-structured interviews with different administrators and IT experts. In the second phase, data (n=164) are collected from procurement, operations, administration and customer service staff in the UAE. In the third phase, responses are examined using principal component analysis to identify eight major challenges for big data. A structural model is developed to examine the significance of these dimensions to the notion of big data challenges in supply chains.FindingsThe statistical model shows 66 percent variance of response to BDA, which is caused by technical, cultural, ethical, operational, tactical, procedural, functional and organizational challenges. These are positively correlated measurement challenges with BDA in service supply chains.Research limitations/implicationsService supply chain professionals and stakeholders believe that catering to the challenges with BDA must be a multi-faceted approach and not limited to specific practices.Practical implicationsThe challenges with BDA should be taken into planning and implementation from a holistic perspective. The framework in this paper can have both theoretical and practical implications.Originality/valueThe contribution of this paper is to advance the understanding of BDA in service sector by viewing it from the perspective of different stakeholders. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Decision Emerald Publishing

Challenges with big data analytics in service supply chains in the UAE

Khan, Mehmood
Management Decision , Volume 57 (8): 24 – Sep 20, 2019
Download PDF
24 pages

Loading next page...
 
/lp/emerald-publishing/challenges-with-big-data-analytics-in-service-supply-chains-in-the-uae-68BKTIs0Ow

References (146)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0025-1747
DOI
10.1108/md-06-2018-0669
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to study the challenges associated with big data analytics (BDA) in service supply chains in the United Arab Emirates (UAE).Design/methodology/approachA comprehensive questionnaire has been developed based on semi-structured interviews with different administrators and IT experts. In the second phase, data (n=164) are collected from procurement, operations, administration and customer service staff in the UAE. In the third phase, responses are examined using principal component analysis to identify eight major challenges for big data. A structural model is developed to examine the significance of these dimensions to the notion of big data challenges in supply chains.FindingsThe statistical model shows 66 percent variance of response to BDA, which is caused by technical, cultural, ethical, operational, tactical, procedural, functional and organizational challenges. These are positively correlated measurement challenges with BDA in service supply chains.Research limitations/implicationsService supply chain professionals and stakeholders believe that catering to the challenges with BDA must be a multi-faceted approach and not limited to specific practices.Practical implicationsThe challenges with BDA should be taken into planning and implementation from a holistic perspective. The framework in this paper can have both theoretical and practical implications.Originality/valueThe contribution of this paper is to advance the understanding of BDA in service sector by viewing it from the perspective of different stakeholders.

Journal

Management Decision – Emerald Publishing

Published: Sep 20, 2019

Keywords: Service supply chains; UAE; Analytics; Big data; Challenges

There are no references for this article.