Carbon Footprints of Global Tourism Enterprises with Firm-Level MRIO Data

Global firm-level data and code supporting a study on the carbon footprints of tourism enterprises. The repository contains processed data for figures and tables, cluster labels, and decomposition outputs from the EMERGING MRIO database. It was authored by Qingyu Hao and last updated in June 2026.

Use Cases

• Validate K-means clustering results based on the provided validation metrics and final cluster labels.
• Perform LMDI (Logarithmic Mean Divisia Index) decomposition analysis using the supplied calculation notes and outputs.
• Replicate firm-level MRIO (Multi-Regional Input-Output) attribution analysis using the included scripts.
• Analyze carbon footprint patterns across global tourism enterprises based on the processed data underlying the study's figures.

Strengths

• Includes processed data specifically supporting Figs. 1–4 and Table 1 of the associated manuscript.
• Provides analysis scripts for firm-level MRIO attribution and K-means validation.
• Released under a permissive CC-BY-4.0 license for reuse.

Limitations

• Raw firm-level financial and operational data from S&P Capital IQ are not included due to licensing restrictions.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Processed from the EMERGING MRIO database and licensed S&P Capital IQ data (not redistributed).

Collection Method

Firm-level MRIO assessment and K-means clustering, as described in the supporting manuscript.

Freshness

Last updated 2026-06-03 08:05:39; freshness should be verified.

Geography

Global