Exploring Novelty Differences between Industry and Academia: A Knowledge Entity-centric Perspective

TL;DR

This study compares the novelty of research outputs between academia and industry by analyzing knowledge entities and their semantic distances, revealing academia's higher novelty, especially in patents, with limited impact from collaborations.

Contribution

Introduces a novel entity-based semantic distance method to quantify and compare research novelty across academia and industry.

Findings

Academia shows higher research novelty, especially in patents.

Both sectors focus on method-driven advancements; industry excels in datasets.

Collaboration enhances patent novelty but has limited effect on papers.

Abstract

Academia and industry each possess distinct advantages in advancing technological progress. Academia's core mission is to promote open dissemination of research results and drive disciplinary progress. The industry values knowledge appropriability and core competitiveness, yet actively engages in open practices like academic conferences and platform sharing, creating a knowledge strategy paradox. Highly novel and publicly accessible knowledge serves as the driving force behind technological advancement. However, it remains unclear whether industry or academia can produce more novel research outcomes. Some studies argue that academia tends to generate more novel ideas, while others suggest that industry researchers are more likely to drive breakthroughs. Previous studies have been limited by data sources and inconsistent measures of novelty. To address these gaps, this study conducts an analysis using four types of fine-grained knowledge entities (Method, Tool, Dataset, Metric), calculates semantic distances between entities within a unified semantic space to quantify novelty, and achieves comparability of novelty across different types of literature. Then, a regression model is constructed to analyze the differences in publication novelty between industry and academia. The results indicate that academia demonstrates higher novelty outputs, which is particularly evident in patents. At the entity level, both academia and industry emphasize method-driven advancements in papers, while industry holds a unique advantage in datasets. Additionally, academia-industry collaboration has a limited effect on enhancing the novelty of research papers, but it helps to enhance the novelty of patents. We release our data and associated codes at https://github.com/tinierZhao/entity_novelty.