Leveraging Big Data and Business Analytics [Guest editors' introduction]
Open accessAbstract
Big data projects and programs provide tremendous opportunity for organizations looking to transform their operations, innovate in their markets, and better serve their customers; however, these initiatives must be based on sound approaches and principles and not fads or empty vendor claims. This special issue aims to promote a better understanding of big data to foster wider deployment of big data approaches and a new era of business analytics capabilities.
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Existing research largely focuses on anecdotal evidence in proposing the relationship between BDAC and firm performance.
“The existing research largely focuses on anecdotal evidence in proposing the relationship between BDAC and firm performance (FPER) (Agarwal and Dhar, 2014;Mithas et al., 2013).”
From How to improve firm performance using big data analytics capability and business strategy alignment? (2016) · cites this paper as Mithas et al., 2013
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Research works printed but not linked: 2
- K. Gillon et al., "Panel-Business Analytics: Radical Shift or Incremental Change?" Proc. 32nd Int'l Conf. Information Systems, Assoc. Information Systems, 2012; http://aisel.aisnet.org/icis2012/proceedings/ Panels/4.
- "Survey: What IT Teams Want Their CIOs to Know About Enterprise Big Data," InfoChimps, press release, 24 Jan. 2013; www.infochimps.com/press/ survey-what-it-teams-want-their-cios-to-know-about- enterprise-big-data.
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How to improve firm performance using big data analytics capability and business strategy alignment?
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.08.018 · Cited by 1,624 · see citing works
Big data consumer analytics and the transformation of marketing
Erevelles, S., Fukawa, N., & Swayne, L. (2016) · Journal of Business Research · doi:10.1016/j.jbusres.2015.07.001 · Cited by 1,377 · see citing works
Big data analytics in E-commerce: a systematic review and agenda for future research
Akter, S., & Wamba, S. F. (2016) · Electronic Markets · doi:10.1007/s12525-016-0219-0 · Cited by 684 · see citing works
Sharma, R., Mithas, S., & Kankanhalli, A. (2014) · European Journal of Information Systems · doi:10.1057/ejis.2014.17 · Cited by 516 · see citing works
Self-citationHow Organisations Leverage Big Data: A Maturity Model
Comuzzi, M., & Patel, A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-12-2015-0495 · Cited by 191 · see citing works
Education and training for successful career in big data and business analytics
Dubey, R., & Gunasekaran, A. (2015) · Industrial and Commercial Training · doi:10.1108/ict-08-2014-0059 · Cited by 94 · see citing works
- Authors
- Mithas, S., Lee, M. R., Earley, S., Murugesan, S., & Djavanshir, R.
- Affiliations
- University of Maryland, College Park (US)
- Shih Chien University (TW)
- Johns Hopkins University (US)
- Venue
- IT Professional
- Published
- 2013-11
- Volume
- 15
- Issue
- 6
- Pages
- 18-20
- ISSN
- 1520-9202 (ISSN-L)
- OpenAlex
- W2041613553
- Cited by
- 82
- References
- 0
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 2 · 2023: 5 · 2022: 5 · 2021: 10 · 2020: 7 · 2019: 10 · 2018: 14 · 2017: 6 · 2016: 9 · 2015: 7 · 2014: 1
- FWCI
- 11.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- IT Professional (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Digital Innovation in Industries
- Keywords
- big data, business analytics, big data adoption, organizational change, analytics capability, data-driven decision making
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