Machine Economy Index (MEI) and Legal Rail Readiness Score (LRRS): Methodology Documentation

Methodology documentation for the Machine Economy Index (MEI) and its legal component, the Legal Rail Readiness Score (LRRS), methodology version 1.3 (20 October 2026). The record contains the conceptual and mathematical specification of the index framework, inclusion criteria, normalization bounds methodology, legal-coverage scoring rules, and versioning protocol. The MEI tracks machine-economy activity across payments, physical infrastructure, and legal readiness, plus a macro demand component, combined with a geometric mean. The LRRS measures GDP-weighted legal coverage across 48 jurisdictions and five categories. The public methodology overview is available at https://machineeconomy.ai/methodology. Files are restricted; access is available from the author on request. Integrity record: an archive of the full project repository at Git commit 468bf155da9e7e187598458cc65325a709dd280d has the SHA-256 digest 02019ba5f4523e3d8b611d7a52ac87cc56ddba8b80749493f9d180f72cbe0199, timestamped via OpenTimestamps on the Bitcoin blockchain and signed with a qualified electronic signature on 2 November 2026.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-09
DOI
https://doi.org/10.5281/zenodo.24093685
Primary Topic
Digital Economy and Transformation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Machine Economy Index (MEI) and Legal Rail Readiness Score (LRRS): Methodology Documentation

Muhammad Suleiman
Zenodo (CERN European Organization for Nuclear Research)
Digital Economy and Transformation
article

Machine Economy Index (MEI) and Legal Rail Readiness Score (LRRS): Methodology Documentation

Muhammad Suleiman
article en

Abstract

Methodology documentation for the Machine Economy Index (MEI) and its legal component, the Legal Rail Readiness Score (LRRS), methodology version 1.3 (20 October 2026). The record contains the conceptual and mathematical specification of the index framework, inclusion criteria, normalization bounds methodology, legal-coverage scoring rules, and versioning protocol. The MEI tracks machine-economy activity across payments, physical infrastructure, and legal readiness, plus a macro demand component, combined with a geometric mean. The LRRS measures GDP-weighted legal coverage across 48 jurisdictions and five categories. The public methodology overview is available at https://machineeconomy.ai/methodology. Files are restricted; access is available from the author on request. Integrity record: an archive of the full project repository at Git commit 468bf155da9e7e187598458cc65325a709dd280d has the SHA-256 digest 02019ba5f4523e3d8b611d7a52ac87cc56ddba8b80749493f9d180f72cbe0199, timestamped via OpenTimestamps on the Bitcoin blockchain and signed with a qualified electronic signature on 2 November 2026.

Zenodo (CERN European Organization for Nuclear Research)
Digital Economy and Transformation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon