Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications

Hazen, Benjamin T.; Boone, Christopher A.; Ezell, Jeremy D.; Jones‐Farmer, L. Allison

doi:10.1016/j.ijpe.2014.04.018

Cited by 661 publications

(411 citation statements)

References 71 publications

(11 reference statements)

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“…We further argue that Big Data and SCM has attracted significant attention from scholars but the Big Data research is in nascent stage and there is urgent need for research to delineate high quality data sets from poor quality data sets (Hazen et al 2014). Furthermore, while analysing Big Data and SCM related research using the perspective of Waller and Fawcett (2013a), we noted that there are gaps in the literature and in particular on machine learning techniques for SCM applications.…”

Section: Contributions To Theorymentioning

confidence: 87%

“…In their study on Big Data analytics (BDA), Bi and Cochran (2014) discussed the impact of Big Data on manufacturing information systems and identified BDA as critical to data acquisition, storage, and analytics in modern manufacturing. In addition, the problem of data quality in SCM was studied by Hazen et al (2014) who emphasized that it is crucial to monitor and control the quality of data in supply chain processes. They also noted that "supply chain professionals are inundated with data, motivating new ways of thinking about how data are produced, organized, and analysed.…”

Section: Big Data and Supply Chain Managementmentioning

confidence: 99%

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Big Data and supply chain management: a review and bibliometric analysis

et al. 2016

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As Big Data has undergone a transition from being an emerging topic to a growing research area, it has become necessary to classify the different types of research and examine the general trends of this research area. This should allow the potential research areas that for future investigation to be identified. This paper reviews the literature on 'Big Data and supply chain management (SCM)', dating back to 2006 and provides a thorough insight into the field by using the techniques of bibliometric and network analyses. We evaluate 286 articles published in the past 10 years and identify the top contributing authors, countries and key research topics. Furthermore, we obtain and compare the most influential works based on citations and PageRank. Finally, we identify and propose six research clusters in which scholars could be encouraged to expand Big Data research in SCM. We contribute to the literature on Big Data by discussing the challenges of current research, but more importantly, by identifying and proposing these six research clusters and future research directions. Finally, we offer to managers different schools of thought to enable them to harness the benefits from using Big Data and analytics for SCM in their everyday work.

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Section: Contributions To Theorymentioning

confidence: 87%

Section: Big Data and Supply Chain Managementmentioning

confidence: 99%

Big Data and supply chain management: a review and bibliometric analysis

et al. 2016

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“…Similar discussions have been produced for other fields (Sonka, 2014;Pugh and Foster, 2014;Hazen et al, 2014).…”

Section: Literaturementioning

confidence: 55%

Big Data versus a Survey

Whitaker

2014

Working Paper (Federal Reserve Bank of Cleveland)

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“…The data quality problem in the context of Supply Chain Management (SCM) was studied; methods for monitoring and controlling data quality were proposed (Hazen et al, 2014). An approach was proposed to provide an analytic infrastructure for companies to incorporate their own competence sets with other companies.…”

Section: Methods and Technology Progress Around Big Datamentioning

confidence: 99%

Big Data Driven Supply Chain Management and Business Administration

Wang

Alexander

2015

American Journal of Economics and Business Administration

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Big Data helps improve visibility throughout the supply chain, provides an integrated view of operational performance and customer interaction and gives businesses real-time insights that help make critical decisions. Big Data also has a potential to yield new management principles. This paper introduces the Big Data concept, its characteristics and some major issues of Big Data in supply chain management and business administration. These issues include supply chain and business data, Big Data benefits and its applications and opportunities. Methods and technology progress about Big Data are presented in this study. General challenges of Big Data and Big Data challenges in supply chain management and business administration are also discussed.

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Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications

Cited by 661 publications

References 71 publications

Big Data and supply chain management: a review and bibliometric analysis

Big Data and supply chain management: a review and bibliometric analysis

Big Data versus a Survey

Big Data Driven Supply Chain Management and Business Administration

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