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Big data reduction framework for value creation in sustainable enterprises

Big data reduction framework for value creation in sustainable enterprises
Big data reduction framework for value creation in sustainable enterprises
Value creation is a major sustainability factor for enterprises, in addition to profit maximization and revenue generation. Modern enterprises collect big data from various inbound and outbound data sources. The inbound data sources handle data generated from the results of business operations, such as manufacturing, supply chain management, marketing, and human resource management, among others. Outbound data sources handle customer-generated data which are acquired directly or indirectly from customers, market analysis, surveys, product reviews, and transactional histories. However, cloud service utilization costs increase because of big data analytics and value creation activities for enterprises and customers. This article presents a novel concept of big data reduction at the customer end in which early data reduction operations are performed to achieve multiple objectives, such as a) lowering the service utilization cost, b) enhancing the trust between customers and enterprises, c) preserving privacy of customers, d) enabling secure data sharing, and e) delegating data sharing control to customers. We also propose a framework for early data reduction at customer end and present a business model for end-to-end data reduction in enterprise applications. The article further presents a business model canvas and maps the future application areas with its nine components. Finally, the article discusses the technology adoption challenges for value creation through big data reduction in enterprise applications.
sustainable enterprises, value creation, big data analytics, data reduction, business model
0268-4012
917-928
Rehman, Muhammad Habib ur
25006c6a-ac68-424c-9764-2da7cafa152d
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Batool, Aisha
aa839c50-e075-42af-944e-95348b1853c1
Teh, Ying Wah
6144dd02-d140-4b58-80e7-109b973ce395
Rehman, Muhammad Habib ur
25006c6a-ac68-424c-9764-2da7cafa152d
Chang, Victor
a7c75287-b649-4a63-a26c-6af6f26525a4
Batool, Aisha
aa839c50-e075-42af-944e-95348b1853c1
Teh, Ying Wah
6144dd02-d140-4b58-80e7-109b973ce395

Rehman, Muhammad Habib ur, Chang, Victor, Batool, Aisha and Teh, Ying Wah (2016) Big data reduction framework for value creation in sustainable enterprises. International Journal of Information Management, 36 (6), 917-928. (doi:10.1016/j.ijinfomgt.2016.05.013).

Record type: Article

Abstract

Value creation is a major sustainability factor for enterprises, in addition to profit maximization and revenue generation. Modern enterprises collect big data from various inbound and outbound data sources. The inbound data sources handle data generated from the results of business operations, such as manufacturing, supply chain management, marketing, and human resource management, among others. Outbound data sources handle customer-generated data which are acquired directly or indirectly from customers, market analysis, surveys, product reviews, and transactional histories. However, cloud service utilization costs increase because of big data analytics and value creation activities for enterprises and customers. This article presents a novel concept of big data reduction at the customer end in which early data reduction operations are performed to achieve multiple objectives, such as a) lowering the service utilization cost, b) enhancing the trust between customers and enterprises, c) preserving privacy of customers, d) enabling secure data sharing, and e) delegating data sharing control to customers. We also propose a framework for early data reduction at customer end and present a business model for end-to-end data reduction in enterprise applications. The article further presents a business model canvas and maps the future application areas with its nine components. Finally, the article discusses the technology adoption challenges for value creation through big data reduction in enterprise applications.

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big_data_framework_IJIM_accepted.pdf - Accepted Manuscript
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More information

Accepted/In Press date: 14 May 2016
Published date: 1 December 2016
Keywords: sustainable enterprises, value creation, big data analytics, data reduction, business model
Organisations: Electronics & Computer Science, Electronic & Software Systems

Identifiers

Local EPrints ID: 394442
URI: http://eprints.soton.ac.uk/id/eprint/394442
ISSN: 0268-4012
PURE UUID: 87f15215-9831-46e8-b0e7-64240b9613c4

Catalogue record

Date deposited: 15 May 2016 14:46
Last modified: 07 Oct 2020 04:55

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