arbiter
JournalsAccount

Using Data Analytics to Analyze Wind Turbine Upgrade Decisions: An ESG Case

Diane J. Janvrin & Cynthia Jeffrey

Journal of Emerging Technologies in Accounting2025https://doi.org/10.2308/jeta-2024-046article
AJG 1ABDC B
Weight
0.50

Abstract

To meet the demand of regulators and investors, companies are working to reduce their carbon emissions with alternative energy sources. Further, the recent state regulations and the European Corporate Sustainability Reporting Directive requiring companies to disclose information about climate risks and carbon emissions increase the need for relevant instructional cases. In this business case emphasizing analytics skill development, students are employed by a fictitious utility company that needs to replace its existing wind turbine infrastructure. Management is debating between buying new turbines or retrofitting the turbines and wants to conduct an environmental analysis of their competitors’ turbines before proceeding with its buy versus retrofit decision. To complete this analysis, students use a data analytics tool of their choice to clean and analyze the dataset. Students use this information in decision-making. The case is designed for an undergraduate or graduate environmental, social, and governance (ESG), managerial accounting, or accounting analytics course.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.2308/jeta-2024-046

Or copy a formatted citation

@article{diane2025,
  title        = {{Using Data Analytics to Analyze Wind Turbine Upgrade Decisions: An ESG Case}},
  author       = {Diane J. Janvrin & Cynthia Jeffrey},
  journal      = {Journal of Emerging Technologies in Accounting},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.2308/jeta-2024-046},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Using Data Analytics to Analyze Wind Turbine Upgrade Decisions: An ESG Case

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
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.