Chilling Out Data Chaos: Leveraging Cold Chain Principles and the Triple Helix Framework

Abstract

As big data increasingly influences decision-making, ensuring data consistency and reliability has become essential. This paper explores how the cold chain’s singular focus on temperature can serve as a model for building unified, high-quality, and sustainable data systems. Despite the primary emphasis on machine learning of literature, this grounded in theory research, investigates how big data quality impacts technological execution and decision-making across industries. Drawing on 65 expert interviews, the study’s final discussion highlights the potential of the Triple Helix model—collaboration between government, industry, and society—as a framework for creating unified data systems. The cold chain, with its focus on temperature as the sole variable, exemplifies how such collaboration can enhance data reliability. Key challenges identified include data governance, operational inconsistencies, and barriers to collaboration. The paper proposes solutions such as professional training and the development of collaborative infrastructures to improve data dependability and support sustainable decision-making across industries