Big data analytics and enterprises: a bibliometric synthesis of the literature

Abstract

Understanding the developmental trajectories of big data analytics in the corporate context is highly relevant for information systems research and practice. This study presents a comprehensive bibliometric analysis of applications of big data analytics in enterprises. The sample for this study contained a total of 1727 articles published between 2009 and 2019 as indexed by the Scopus database.The sample represents contributions from 4342 authors, 3515 organizations, 89 countries, and 763 journals on this research topic. The sample was analysed with techniques such as bibliographic coupling, citation analysis, co-word analysis, and co-authorship analysis. Four major thematic areas in the extant literature emerged from the co-citation analysis. The thematic areas were inputs for strategic decision-making, concept development for big data analytics, trends in applications of big data analytics, and efficient supply chain management. The evolution of these thematic areas was documented with dynamic co-citation analysis. The results provide insights into the extant research on big data analytics and can guide future research efforts in this area.

Education and Diet in the Scientific Literature: A Study of the Productive, Structural, and Dynamic Development in Web of Science

“…This study followed a bibliometric research methodology, taking as reference other previous studies of high impact literature [39][40][41][42][43][44]. The reason why this research technique was used is reflected in the potentialities that Scientometrics reports have in aspects related to quantifying, evaluating, and estimating the scientific evolution of the field of knowledge in question [45].…”

Big data analytics in healthcare: a systematic literature review

“…The concept of BDA overarches several data-intensive approaches to the analysis and synthesis of large-scale data (Galetsi, Katsaliaki, and Kumar 2020;Mergel, Rethemeyer, and Isett 2016). Such large-scale data derived from information exchange among different systems is often termed 'big data' (Bahri et al 2018;Khanra, Dhir, and Mäntymäki 2020). Although it is referred to as 'big' data, its importance is associated with its ability to capture small details about the subject being studied (George, Haas, and Pentland 2014;McAfee et al 2012).…”

“…To determine the appropriate keywords, a search was performed on Google Scholar with the phrase 'big data analytics in healthcare.' The most commonly related terms were identified from the first 100 search results (Khanra, Dhir, and Mäntymäki 2020). We identified from the co-occurrence of keywords that the term 'predictive analytics' was frequently used to refer to 'big data analytics,' following an approach adapted by Khanra, Dhir, and Mäntymäki (2020).…”

“…The most commonly related terms were identified from the first 100 search results (Khanra, Dhir, and Mäntymäki 2020). We identified from the co-occurrence of keywords that the term 'predictive analytics' was frequently used to refer to 'big data analytics,' following an approach adapted by Khanra, Dhir, and Mäntymäki (2020). Raghupathi and Raghupathi (2014) highlighted applications of big data analytics in healthcare, including analysis of patient profiles with predictive modelling to identify suitable treatments, prediction of outcomes of different treatments, and percipience of the most clinically and cost-effective treatments for the patient.…”

Managing digital transformation of smart cities through enterprise architecture – a review and research agenda

“…Thus, digitisation is the procedure of representing information as '0ʹ or '1ʹ that is utilised by computers for storage, processing and transmission as information (Boratyńska 2019). Digitisation is also referred to as change of analog task to digital operations or can be conceptualised as the integration of IT to facilitate existing tasks, and generally, as the enabler or development of cost-efficient resource configurations utilising IT (Verhoef et al 2019;Khanra, Dhir, and Mäntymäki 2020). In summary, digitisation defines the process of converting information from analog to digital which can results to changes in existing business model to provide value to stakeholders (Heilig, Lalla-Ruiz, and Voß 2017; Boratyńska 2019).…”