The Link Between Large Scientific Collaboration and Productivity. Rethinking How to Estimate the Monetary Value of Publications

TL;DR

This paper develops a new method to assign monetary value to scientific publications, especially in large collaborations, revealing significantly higher valuations and emphasizing the importance of considering coauthorship in research impact assessment.

Contribution

It introduces a generalized Marginal Cost of Production model that accounts for collaboration effects, improving valuation accuracy for multi-author scientific outputs.

Findings

Collaborative adjustments can increase valuation estimates by up to 1000 times.

High-value papers are associated with high research quality.

The methodology is applicable across various scientific fields and impact assessment frameworks.

Abstract

This paper addresses how to assign a monetary value to scientific publications, particularly in the case of multi-author papers arising from large-scale research collaborations. Contemporary science increasingly relies on extensive and varied collaborations to tackle global challenges in fields such as life sciences, climate science, energy, high-energy physics, astronomy, and many others. We argue that existing literature fails to address the collaborative nature of research by overlooking the relationship between coauthorship and scientists productivity. Using the Marginal Cost of Production (MCP) approach, we first highlight the methodological limitations of ignoring this relationship, then propose a generalised MCP model to value co-authorship. As a case study, we examine High-Energy Physics (HEP) collaborations at the Large Hadron Collider (LHC) at CERN, analysing approximately half a million scientific outputs by over 50,000 authors from 1990 to 2021. Our findings indicate that collaborative adjustments yield monetary valuations for subsets of highly collaborative papers up to 3 orders of magnitude higher than previous estimates, with elevated values correlating with high research quality. This study contributes to the literature on research output evaluation, addressing debates in science policy around assessing research performance and impact. Our methodology is applicable to authorship valuation both within academia and in large-scale scientific collaborations, fitting diverse research impact assessment frameworks or as self-standing procedure. Additionally, we discuss the conditions under which this method may complement survey-based approaches.