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Patent Value Characterization -- An Empirical Analysis of Elevator Industry Patents

Yuhang Guan, Runzheng Wang, Lei Fu, Huanle Zhang

TL;DR

The paper tackles how to quantify patent value to support elevator-industry financing amid rising global patent activity. It introduces a 14-indicator patent evaluation framework and constructs a Patent Value Classification Prediction (PVCP) model based on a decision tree with cross-validation. Applied to elevator patents, it reports that coastal Chinese provinces dominate filings, foreign patents often command higher values, and that features such as Number of Document Pages and Number of Citing Patents correlate with higher value, while Publication Date tends to be negatively related. The results yield actionable guidance for patent financing institutions and demonstrate the value of interpretable AI methods for asset valuation.

Abstract

The global patent application count has steadily increased, achieving eight consecutive years of growth.The global patent industry has shown a general trend of expansion. This is attributed to the increasing innovation activities, particularly in the fields of technology, healthcare, and biotechnology. Some emerging market countries, such as China and India, have experienced significant growth in the patent domain, becoming important participants in global patent activities.

Patent Value Characterization -- An Empirical Analysis of Elevator Industry Patents

TL;DR

The paper tackles how to quantify patent value to support elevator-industry financing amid rising global patent activity. It introduces a 14-indicator patent evaluation framework and constructs a Patent Value Classification Prediction (PVCP) model based on a decision tree with cross-validation. Applied to elevator patents, it reports that coastal Chinese provinces dominate filings, foreign patents often command higher values, and that features such as Number of Document Pages and Number of Citing Patents correlate with higher value, while Publication Date tends to be negatively related. The results yield actionable guidance for patent financing institutions and demonstrate the value of interpretable AI methods for asset valuation.

Abstract

The global patent application count has steadily increased, achieving eight consecutive years of growth.The global patent industry has shown a general trend of expansion. This is attributed to the increasing innovation activities, particularly in the fields of technology, healthcare, and biotechnology. Some emerging market countries, such as China and India, have experienced significant growth in the patent domain, becoming important participants in global patent activities.
Paper Structure (21 sections, 1 equation, 12 figures, 2 tables)

This paper contains 21 sections, 1 equation, 12 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related work
  3. Patent Application
  4. Patent Evaluation
  5. Basic Theory and Research Design
  6. Basic Theory and Methods
  7. Traditional Methods
  8. AI Methods
  9. Research Design
  10. Patent Data Collection
  11. Feature Selection
  12. Feature and Correlation Analysis
  13. Construction of PVCP Model
  14. Experimental Implementation
  15. Data Preprocessing
  16. ...and 6 more sections

Figures (12)

  • Figure 1: The Global Annual Number of Patent Applications
  • Figure 2: Data preprocessing process
  • Figure 3: Distribution of the Proportion and Average Value of Patents by Country
  • Figure 4: Proportion and Average Value of Patents by Province of China
  • Figure 5: Average Patent Value by Publication Date
  • ...and 7 more figures