Interconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data

Weibl, Johannes (2019): Interconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data. 52th Hawaii International Conference on System Sciences 2019 (HICSS-52), Grand Wailea, Hawaii, January 8-11, 2019. In: Proceedings of the 52rd Hawaii International Conference on System Sciences, University of Hawaii at Manoa, Hamilton Library, ScholarSpace: Honolulu, HI.

Abstract

In recent years, organizations manage an increasing amount of data in order to make better decisions, personalize products, or sell data. By data being combined from various sources, data assets interact with each other. When the interactions are synergistic, they create greater benefits than the sum of the value of the individual data assets. This study explores enablers, mechanisms, and potential outcomes of synergistic interactions among data assets. Based on systems theory and a synthesis of relevant synergy literature, I developed an initial synergy framework in a data context. On this basis, I conducted 14 qualitative interviews to assess the validity of my initial framework. The interview results assisted me in refining and contextualizing a unified conceptual framework of data synergies. The paper reveals that compatibility and contextual relatedness as enablers and informational complementary as a mechanism can lead to super-additive information value among data assets.

• Dokumententyp: Konferenzbeitrag (Paper)
• Fakultät: Betriebswirtschaft > Institut für Digitales Management und Neue Medien
• Themengebiete: 300 Sozialwissenschaften > 330 Wirtschaft
• ISSN: 25726862
• Ort: University of Hawaii at Manoa, Hamilton Library, ScholarSpace
• Bemerkung: ISBN 978-0-9981331-2-6
• Sprache: Englisch