Data Analytics in Accounting: Visualizing Corporate Income Inequality

Seungjae Shin & Kevin L. Ennis

AIS Educator Journal2021https://doi.org/10.3194/1935-8156-16.1.19article
ABDC C
Weight
0.45

What the paper says

Abstract Accounting courses increasingly require students to learn data analytics skills and extract insights from business data. The issue of corporate income inequality (the growing gap between the most- and least-profitable companies) has become relevant in discussions of global economic issues. This project has students use data analytic software tools to gain insight into corporate income inequality by extracting and analyzing accounting data. Students learn to clean, merge, and manipulate financial statement data sets to identify corporate income inequality through visualizations. Students' responses to the post-project questionnaire show that the project provided a positive learning experience and increased their academic performance.

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https://doi.org/https://doi.org/10.3194/1935-8156-16.1.19

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@article{seungjae2021,
  title        = {{Data Analytics in Accounting: Visualizing Corporate Income Inequality}},
  author       = {Seungjae Shin & Kevin L. Ennis},
  journal      = {AIS Educator Journal},
  year         = {2021},
  doi          = {https://doi.org/https://doi.org/10.3194/1935-8156-16.1.19},
}

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Evidence weight

0.45

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.26 × 0.4 = 0.10
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.