Functionality Versus “Typical Product” Measures of Technological Progress A Case Study of Semiconductor Manufacturing

• Published in: Journal of industrial ecology Vol. 15; no. 1; pp. 108 - 121
• Main Authors: Deng, Liqiu, Williams, Eric D.
• Format: Journal Article
• Language: English
• Published: New Haven Wiley Subscription Services, Inc 01.02.2011
• Subjects: Case studies; Energy consumption; Environmental management; Product life cycle; Semiconductors; Studies; Transistors; Trends
• ISSN: 1088-1980; 1530-9290
• DOI: 10.1111/j.1530-9290.2010.00306.x

Technological progress and adoption are fundamentally interconnected with environmental challenges faced by society. At the product level, researchers often explore the interplay between technological change and the environment by tracking trends in impacts per unit functionality - for example, gasoline consumed per distance traveled by a vehicle. In this article, we explore an alternative measure: typical product. A typical product measure accounts for changes in consumers' demand and use of products as product quality improves - for example, gasoline consumed for a typical driving pattern for a vehicle. We compare and contrast functionality and typical product measures through a case study of electricity use to fabricate Intel desktop microprocessors from 1995 to 2006. The functionality normalization is measured in terms of electricity use per transistor produced. Results show rapid and sustained exponential decrease. The typical product measures electricity use per typical desktop microprocessor of a given year (e.g., a Pentium II in 1998, a Pentium IV in 2002). Results show that, despite fluctuations, energy use per typical microprocessor is roughly constant over the 12-year period. The explanation of this result is that although technological progress dramatically reduces the energy needed per transistor, it also induces demand for more powerful chips, which contain many more transistors. The typical product measure has applications in defining functional units in life cycle assessment, characterizing rebound effects, and measuring energy efficiency trends.