Purpose: The purpose of this paper is to scrutinize and classify the literature linking Big Data analytics and management phenomena. Design/methodology/approach: An objective bibliometric analysis is conducted, supported by subjective assessments based on the studies focused on the intertwining of Big Data analytics and management fields. Specifically, deeper descriptive statistics and document co-citation analysis are provided. Findings: From the document co-citation analysis and its evaluation, four clusters depicting literature linking Big Data analytics and management phenomena are revealed: theoretical development of Big Data analytics; management transition to Big Data analytics; Big Data analytics and firm resources, capabilities and performance; and Big Data analytics for supply chain management. Originality/value: To the best of the authors’ knowledge, this is one of the first attempts to comprehend the research streams which, over time, have paved the way to the intersection between Big Data analytics and management fields.
A bibliometric analysis of research on Big Data analytics for business and management / Ardito, Lorenzo; Scuotto, Veronica; Del Giudice, Manlio; Messeni Petruzzelli, Antonio. - In: MANAGEMENT DECISION. - ISSN 0025-1747. - STAMPA. - 57:8(2019), pp. 1993-2009. [10.1108/MD-07-2018-0754]
A bibliometric analysis of research on Big Data analytics for business and management
Lorenzo Ardito;Antonio Messeni Petruzzelli
2019-01-01
Abstract
Purpose: The purpose of this paper is to scrutinize and classify the literature linking Big Data analytics and management phenomena. Design/methodology/approach: An objective bibliometric analysis is conducted, supported by subjective assessments based on the studies focused on the intertwining of Big Data analytics and management fields. Specifically, deeper descriptive statistics and document co-citation analysis are provided. Findings: From the document co-citation analysis and its evaluation, four clusters depicting literature linking Big Data analytics and management phenomena are revealed: theoretical development of Big Data analytics; management transition to Big Data analytics; Big Data analytics and firm resources, capabilities and performance; and Big Data analytics for supply chain management. Originality/value: To the best of the authors’ knowledge, this is one of the first attempts to comprehend the research streams which, over time, have paved the way to the intersection between Big Data analytics and management fields.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.