Unpacking task-technology fit to explore the business value of big data analytics

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

20 Sitaatiot (Scopus)
74 Lataukset (Pure)

Abstrakti

Understanding how the application of big data analytics (BDA) generates business value is a persistent challenge in information systems (IS) research. Improving understanding of how BDA realizes business value requires unpacking theories to study the phenomenon. This study unpacks the task-technology fit (TTF) theory toward generating new and improved insights into the business value of BDA. Extant studies on TTF have mainly focused on traditional IT which is different from digital technologies like BDA that are malleable and dynamic. While TTF has primarily focused on how the technology meets task requirements, this study contends that tasks can also be structured to fit the functionality of technology. This study proposes a 2 × 2 matrix framework to explain how BDA and tasks interact. The framework indicates how the reconfigurability of tasks and the editability of BDA impact the fit between tasks and BDA. Future research should explore how the fit between tasks and BDA changes over time.

AlkuperäiskieliEnglanti
Artikkeli102619
Sivumäärä8
JulkaisuInternational Journal of Information Management
Vuosikerta69
Varhainen verkossa julkaisun päivämäärä29 jouluk. 2022
DOI - pysyväislinkit
TilaJulkaistu - huhtik. 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Julkaisufoorumi-taso

  • Jufo-taso 3

!!ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Marketing
  • Library and Information Sciences
  • Artificial Intelligence

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