An analysis of algorithmic capability and organizational impact

George Papachristos, Scott W. Cunningham

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Organizations face ever more complex environments and the need to adapt and increase their performance. A well-known trade-off lies between the convergence of performance-related factors to an organization’s strategic orientation that produces inertia versus the need to sense opportunity and change in the environment and make the necessary internal changes. The advent of the algorithms has given rise to algorithmic governance and the notion that this trade-off can be addressed through the large-scale implementation of algorithms for data mining of Big Data. This chapter addresses the implementation aspects of data governance programs in terms of the two sides of this trade-off. It may enable improvements in organizational performance but at the same time it is necessary to managing unwanted effects inside and beyond the organization.
Original languageEnglish
Title of host publicationThe Human Element of Big Data
Subtitle of host publicationIssues, Analytics, and Performance
EditorsGeetam S. Tomar, Narendra S. Chaudhari, Robin Singh Bhadoria, Ganesh Chandra Deka
Place of PublicationNew York
Chapter5
Pages93-118
Number of pages26
Edition1
ISBN (Electronic)9781315368061
DOIs
Publication statusPublished - 26 Oct 2016

    Fingerprint

Keywords

  • big data
  • algorithmic capability
  • organizational impact

Cite this

Papachristos, G., & Cunningham, S. W. (2016). An analysis of algorithmic capability and organizational impact. In G. S. Tomar, N. S. Chaudhari, R. S. Bhadoria, & G. C. Deka (Eds.), The Human Element of Big Data: Issues, Analytics, and Performance (1 ed., pp. 93-118). New York. https://doi.org/10.1201/9781315368061