How Big Data Analytics Enables Service Innovation: Materiality, Affordance, and the Individualization of Service

Christiane Lehrer, Alexander Wieneke, Jan vom Brocke, Reinhard Jung, Stefan Seidel

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The article reports on an exploratory, multisite case study of four organizations from the insurance, banking, telecommunications, and e-commerce industries that implemented big data analytics (BDA) technologies to provide individualized service to their customers. Grounded in our analysis of these four cases, a theoretical model is developed that explains how the flexible and reprogrammable nature of BDA technologies provides features of sourcing, storage, event recognition and prediction, behavior recognition and prediction, rule-based actions, and visualization that afford (1) service automation and (2) BDA-enabled human-material service practices. The model highlights how material agency (in the case of service automation) and the interplay of human and material agencies (in the case of human-material service practices) enable service individualization, as organizations draw on a service-dominant logic. The article contributes to the literature on digitally enabled service innovation by highlighting how BDA technologies are generative digital technologies that provide a key organizational resource for service innovation. We discuss implications for research and practice.
Original languageEnglish
JournalJournal of Management Information Systems
Volume35
Issue number2
Pages (from-to)424-460
Number of pages37
ISSN0742-1222
DOIs
Publication statusPublished - 2018
Externally publishedYes

Keywords

  • Affordances
  • Agency
  • Big data analytics
  • Digital innovation
  • Materiality
  • Service-dominant logic
  • Service innovation
  • Services

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