Big Data Analytics in Electronic Markets
Special issue of Electronic Markets; Deadline 30 Nov 2015
Special Issue of The Electronic Markets – The International Journal
on Networked Business on Big Data Analytics in Electronic Markets
In the past, the main challenge that businesses faced had to do with operating under conditions of data scarcity. Decision-making was subject to incomplete, insufficient, and time-lapsed data. However, such challenge no longer exists, given the current exponential growth of data available to businesses. Instead, the challenge that businesses now face has to do with the sheer abundance of data. Up until 2003, only 5 exabytes (1018 bytes) of data were available, whereas nowadays the same amount of data can be created within two days (Sagiroglu and Sinanc, 2013). Businesses now have more data than they can effectively use; as a result, a new critical issue is emerging: big data analytics. The term big data refers to “data sets with sizes beyond the ability of common software tools to capture, curate, manage, and process the data within a specific elapsed time” (Bharadwaj, El Sawy, Pavlou and Venkatraman, 2013, p. 447). The ability to manage big data, information, and knowledge to gain competitive advantage becomes increasingly important in enabling data-driven decisions in businesses.
Electronic markets are particularly inseparable from big data analytics, given that the accomplishments fuelled by big data analytics are primarily generated from the electronic market community, as in the case of the product recommender systems introduced by electronic market leaders, such as eBay and Amazon (Chen, Chiang and Storey, 2012). The data of the electronic market are more visible and easier to collect than those of traditional markets because the former can be collected through screen-scraping and agent-based data collection approaches (Chang, Kauffman and Kwon, 2014). Big data analytics has opened opportunities to practitioners of the electronic market to listen to the voice of the market, including customers, employees, investors, and media, through different sources, such as newsgroups and social media sites. For academics, these opportunities represent another broad and encompassing area of research.
To successfully implement big data analytics, businesses must overcome not only technological obstacles, such as data acquisition and management, but also managerial obstacles, such as understanding how to use analytics to improve business performance. Given the importance of the above challenges and issues, big data analytics has increasingly attracted the attention of scholars. The core objective of this special issue is to provide a platform through which academics and practitioners can exchange views, share skills and knowledge, and understand how big data analytics can significantly help businesses in the electronic markets to create added value.
Central issues and themes
Possible topics of submissions include, but are not limited, to the following:
- Big data analytics and mining applications for electronic markets
- Content analysis and network community analysis of blog contents and bloggers’ interaction networks
- Performance analysis of big data tools and their applications in electronic markets
- Development of decision support systems for social media brands and competitive analysis of electronic markets
- Challenges and issues in big data analytics for electronic markets
- Data science and predictive analytics specific to electronic markets
- Organizational impact of big data analytics
- Quantification of the impact of user-generated content on consumers’ good purchase expenditures in electronic markets
We encourage contributions with a broad range of methodological approaches, including conceptual, qualitative and quantitative research. We would also like to welcome authors publishing on the topic of big data analytics in electronic markets.
We also welcome contributions addressing related topics not listed above (please contact the special issue editors in that case to discuss the fit prior to submission).
All papers will be peer reviewed and should conform to Electronic Markets publication standards. Electronic Markets is a SSCI-listed journal and supports methodological and theoretical pluralism, i.e. empirical or theoretical work, qualitative research, design science and/or prototypes are all welcomed by the journal. If you would like to discuss any aspect of the special issue, please contact the guest editors.
Bharadwaj, A., El Sawy, O., Pavlou, P. A., and Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471-482.
Chang, R. M., Kauffman, R. J., and Kwon, Y. (2014). Understanding the paradigm shift to computational social science in the presence of big data. Decision Support Systems, 63, 67-80.
Chen, H., Chiang, R. H. L., and Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188.
Sagiroglu, S. and Sinanc, D. (2013). Big data: A review. In Proceedings of the 2013 International Conference on Collaboration Technologies and Systems (CTS), 42-47
All papers must be original, not published or under review elsewhere. Papers must be submitted via our electronic submission system at http://elma.edmgr.com.
Instructions, templates and general information are available at
Please note the preferred article length must be in a range of 3,500 to 6,500 words.
- Submission Deadline: November 30, 2015
- Ngai, Eric W. T., The Hong Kong Polytechnic University, Hong Kong, China, email@example.com
- Gunasekaran, Angappa, University of Massachusetts Dartmouth, USA, firstname.lastname@example.org
- Fosso Wamba, Samuel, NEOMA Business School, France, Samuel.email@example.com
- Akter, Shahriar, University of Wollongong, Australia, firstname.lastname@example.org
- Dubey, Rameshwar, Symbiosis International University, India, email@example.com