Introduction to the handbook of big data research methods

Akter, S; Wamba, SF; Sajib, S; Hossain, S

Introduction to the handbook of big data research methods

Akter, S Wamba, SF Sajib, S

Hossain, S

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Publisher:: Edward Elgar Publishing
Publication Type:: Chapter
Citation:: Handbook of Big Data Research Methods, 2023, pp. 1-10
Issue Date:: 2023-06-20

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Field	Value	Language
dc.contributor.author	Akter, S
dc.contributor.author	Wamba, SF
dc.contributor.author	Sajib, S https://orcid.org/0000-0003-0209-7718
dc.contributor.author	Hossain, S
dc.date.accessioned	2023-12-06T02:22:09Z
dc.date.available	2023-12-06T02:22:09Z
dc.date.issued	2023-06-20
dc.identifier.citation	Handbook of Big Data Research Methods, 2023, pp. 1-10
dc.identifier.isbn	9781800888548
dc.identifier.uri	http://hdl.handle.net/10453/173749
dc.description.abstract	This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics.
dc.language	en
dc.publisher	Edward Elgar Publishing
dc.relation.ispartof	Handbook of Big Data Research Methods
dc.relation.isbasedon	10.4337/9781800888555.00005
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Introduction to the handbook of big data research methods
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
utslib.copyright.status	closed_access	*
dc.date.updated	2023-12-06T02:22:08Z
pubs.publication-status	Published

Abstract:

This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/173749