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Journal of Business Analytics is a peer-reviewed journal published by Taylor & Francis, covering Big Data and Business Intelligence, Data Quality and Management, Digital Marketing and Social Media.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Journal of Business Analytics 12 (3): 45–58.
Formats any DOI in Journal of Business Analytics style. No sign-up. |
| Publishes research in | Big Data and Business Intelligence Data Quality and Management Digital Marketing and Social Media Customer churn and segmentation Stock Market Forecasting Methods |
| ISSN | 2573-234X |
| Citation impact (2-yr) | 2.22 |
| h-index | 19 |
| i10-index | 35 |
| Total citations | 1,611 |
| Top institutions publishing here | Montclair State University |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Analytics have been employed by companies for several decades, but now many firms are interested in building their capabilities for artificial intelligence (AI). Many AI systems, however, are based on statistics and other forms of analytics. Companies can get a “running start” on AI by building upon their analytical competencies. The focus of this article…
There are plenty of definitions proposed for business analytics – some of them focus on the scope/coverage/problem, some on the nature of the data, and some concentrate on the enabling methods and methodologies. The common denominator of all of these definitions is that business analytics is the encapsulation of all mechanisms that help convert data…
Searches of the Web using Google, and database searches of the academic and practitioner literature, return a large number of differing and varied definitions of the concept of business analytics. This article reviews the growing literature on Business Analytics (BA) using traditional and qualitative research tools. Our searches included using Google Search to identify examples…
Supervised machine learning methods for image analysis require large amounts of labelled training data to solve computer vision problems. The recent rise of deep learning algorithms for recognising image content has led to the emergence of many ad-hoc labelling tools. With this survey, we capture and systematise the commonalities as well as the distinctions between…
Open-ended responses are widely used in market research studies. Processing of such responses requires labor-intensive human coding. This paper focuses on unsupervised topic models and tests their ability to automate the analysis of open-ended responses. Since state-of-the-art topic models struggle with the shortness of open-ended responses, the paper considers three novel short text topic models:…
