Early adopters, firm survival, and environmental policy

Dry cleaners in the South Coast Basin of California

Dados Bibliográficos

ID21600180
AutoresPaul M Ong (0000-0002-4953-9109, University of California Los Angeles, Los Angeles, CA, USA), Paul Ong (0000-0002-4358-6297, University of California, Los Angeles), Ward F Thomas (California State University Northridge, Northridge, CA, USA), Ward Thomas (California State University, Northridge, autor correspondente)
Ano2021
Volume64
Fascículo4
Páginas635-648
Data de publicação2021-03-21
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoJournal of Environmental Planning and Management (JOURNAL)
Identificadores do periódicoISSN: 0964-0568 • E-ISSN: 1360-0559
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/09640568.2020.1779674
OpenAlexW3054147160
IdiomaEN
Citações recebidas1
Referências citadas29

This paper examines the relationship between the early adoption of new technologies, the probability of firm survival, and environmental regulations through a case study of dry cleaners in the South Coast Basin of California (SC Basin). Most dry cleaners use machines that use the toxic chemical perchloroethylene (PERC) to clean garments. PERC vapors are emitted into the ambient air during the dry cleaning process and can cause cancer in people who live and work nearby. In 2002, the South Coast Air Quality Management District (AQMD) required all dry cleaners in the region to purchase a costly alternative machine that used a non-toxic cleaning solvent by the year 2020. Using bivariate and multivariate analysis, we found that the timing of the early adoption of non-PERC machines among dry cleaners was optimal, ceteris paribus, and adopting early did not have a negative effect on the probability of surviving

Air quality index · Bivariate analysis · Business · Ceteris paribus · Economics · Geography · Meteorology · Statistics · Structural basin · Waste management · Climate Change Policy and Economics · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Engineering · Environmental Science · Mathematics · Environmental Engineering