Sena, Vania and Bhaumik, Sumon and Sengupta, Abhijit and Demirbag, Mehmet (2019) Big Data and Firm Performance: What Can Management Research Tell Us? British Journal of Management, 30 (2). pp. 219-228. DOI https://doi.org/10.1111/1467-8551.12362
Sena, Vania and Bhaumik, Sumon and Sengupta, Abhijit and Demirbag, Mehmet (2019) Big Data and Firm Performance: What Can Management Research Tell Us? British Journal of Management, 30 (2). pp. 219-228. DOI https://doi.org/10.1111/1467-8551.12362
Sena, Vania and Bhaumik, Sumon and Sengupta, Abhijit and Demirbag, Mehmet (2019) Big Data and Firm Performance: What Can Management Research Tell Us? British Journal of Management, 30 (2). pp. 219-228. DOI https://doi.org/10.1111/1467-8551.12362
Abstract
The special issue focuses on the theory and evidence linking the use of Big Data related technologies by businesses with their performance. Here we connect the papers accepted for the special issue to the overarching theme of Big Data as an emerging concept within the business management literature. We present two prominent case studies examining the use Big Data technologies on performance and strategy, followed by a discussion on how themes around Big Data and Performance may be examined from a theoretical perspective. Finally, based on a synthesis of papers in the current issue, we discuss the emerging issues and trends within the academic literature, relevant for future research.
Item Type: | Article |
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Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 14 Mar 2019 19:27 |
Last Modified: | 30 Oct 2024 16:17 |
URI: | http://repository.essex.ac.uk/id/eprint/24209 |
Available files
Filename: Big Data Editorial BJM.pdf