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Big Data Challenges for Performance Measurement and Management: A critical reflection
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- Ask, Urban, 1956 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för tillämpad informationsteknologi (GU),Department of Applied Information Technology (GU)
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- Bredmar, Krister, 1967 (author)
- Gothenburg University,Göteborgs universitet,Företagsekonomiska institutionen, Redovisning,Department of Business Administration, Accounting
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- Magnusson, Johan, 1976 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för tillämpad informationsteknologi (GU),Department of Applied Information Technology (GU)
- (creator_code:org_t)
- 2015
- 2015
- English.
- In: Proceedings in the 8th conference on performance measurement and management control. - 2295-1660.
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- Big Data is starting to permeate the field of performance measurement and management. With data being referred to as the “new oil of the 21st century” and organizations more and more striving for utilizing this to their advantage, the notion of Big Data has become a hallmark for the modern decision maker. We argue that albeit promising for performance measurement and management, there are several aspects that need to be addressed within research. This paper builds on a literature review of extant research, and, a case study, and raises issues that if left unchecked could have negative impacts on the field of performance measurement and management. Despite the many positive aspects associated with Big Data, there is a need for a sound, critical perspective. The findings are discussed in relation to the three Vs regarded as a the core definition of Big Data (volume, variety and velocity) and illustrated by a case study.
Subject headings
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv -- Företagsekonomi (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business -- Business Administration (hsv//eng)
Keyword
- Performance measurement and management
- big data
- critical reflection
Publication and Content Type
- ref (subject category)
- kon (subject category)
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