Quantifying the Impacts of Sustainability-Oriented Innovation on the Linear Economy

Abstract

Sustainability-oriented innovation is widely promoted, yet rarely quantified in ways that allow meaningful economic, labour, and environmental comparison. Without formal measurement, sustainability transitions risk remaining aspirational rather than actionable. This paper addresses that gap by translating sustainability-oriented innovation into a set of transparent equations designed to evaluate its impacts within a linear economic system.

Introduction:
Sustainability-oriented innovation (SOI) is increasingly promoted as a mechanism for improving economic performance, employment outcomes, and environmental efficiency within traditionally linear economic systems. However, despite extensive conceptual discussion, there remains a lack of unified frameworks that translate SOI into measurable and comparable economic, labour, and environmental impacts.

Methods:
This study adopts a conceptual and analytical approach to develop a formalised model for quantifying the impacts of SOI within a linear economy. Drawing on innovation economics, sustainability science, and systems analysis, the paper constructs an integrated modelling framework based on four interrelated equations. These equations explicitly link SOI investment, technology adoption, labour productivity, and emissions intensity to changes in GDP, employment levels, and environmental outcomes. The model is designed for scenario-based simulation rather than empirical estimation, allowing users to compare outcomes under varying levels of SOI adoption and policy intensity.

Results:
The proposed equations demonstrate how SOI can generate positive economic returns through investment and cost-efficiency channels, influence employment through productivity gains and workforce transition dynamics, and reduce environmental pressure via technological efficiency and market penetration of sustainable products and processes. By incorporating baseline conditions and adjustment parameters, the framework highlights potential trade-offs between short-term transition costs and long-term sustainability gains. The model further enables sensitivity analysis to identify the variables that exert the greatest influence on economic growth, labour restructuring, and emission reduction within a linear economy.

Discussion:
By prioritising formal equations and transparent assumptions, this study advances sustainability research beyond descriptive narratives toward structured quantification. The proposed framework offers policymakers, researchers, and practitioners a practical tool for benchmarking SOI strategies, designing simulation scenarios, and guiding future empirical testing. In doing so, the paper contributes a foundational measurement logic that supports evidence-based transitions toward sustainability within linear economic systems.