From Data Possession to Operations Reconfiguration: Transforming Firm Operations under Big Data - An Integrative Literature Review

Mengfei Xiao; Weixiang Gan

doi:10.62177/jaet.v3i2.1384

Authors

Mengfei Xiao Lincoln University College https://orcid.org/0009-0003-5879-5395
Weixiang Gan Lincoln University College https://orcid.org/0009-0004-5077-1214

DOI:

https://doi.org/10.62177/jaet.v3i2.1384

Keywords:

Firm Operations, Operating Model, Big Data Analytics, Data Governance, Data-Driven Decision Making, Process Transformation, Supply-Chain Analytics, SMEs, Data Platforms

Abstract

This integrative review develops a theory-oriented account of how big data transforms firm operations. Instead of treating big data analytics capability as a direct antecedent of firm performance, it examines how data is institutionalised, translated into decision routines, embedded in workflows, and orchestrated through platforms and ecosystems. Drawing on recent literature published mainly between 2017 and 2026 across management, information systems, operations, supply-chain, governance, and data-platform research, the review shows that operational transformation is not produced by analytics investment alone. Value emerges when firms combine data governance, privacy control, data quality, analytical culture, decision-right redesign, process instrumentation, automation, supply-chain integration, and platformised data architectures. The paper proposes a Data-to-Operations Reconfiguration Framework in which process visibility, decision-latency compression, exception detectability, and cross-boundary coordination explain how data becomes operational value. By moving beyond the conventional capability–performance view, this review positions big data as a socio-technical and institutional mechanism that reconstructs the operating model of the firm. It further identifies propositions around governance-mediated value creation, curvilinear centralisation effects, platform-enabled SME value capture, and resilience-oriented performance under environmental dynamism.

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