Abstract
Different data sources and analytical methodologies can be used to establish a ranking of enterprises according to several performance measures including their reputation, financial health, and future growth potential. Such a ranking can be extremely useful for third enterprises interested in creating alliances, outsourcing some activities, or simply contracting services offered by external firms. This paper reviews well-established methodological approaches that have been employed to generate such rankings, which are typically applied on reduced sets of large enterprises. We discuss the need to extend these ranking practices to large sets of small and medium enterprises, which do not usually provide publicly-available data. In consideration of present digital age, we support the following concepts: 1) citation indicators - such as those generated by search engines - can be employed to automate the fast generation of rankings; 2) when properly validated, these 'agile' rankings can be used as proxies for a reputation ranking.
| Original language | English |
|---|---|
| Pages (from-to) | 265-290 |
| Number of pages | 26 |
| Journal | International Journal of Data Analysis Techniques and Strategies |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Data analytics
- Decision sciences
- Digital age
- Management science
- Ranking enterprises
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