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Oregon Business Decisions for Environmental Management Selected Summary Statistics and Effects of Voluntary Environmental Programs. Cody Jones Master of Environmental Management Portland State University February 2, 2007. Description and Objectives.
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Oregon Business Decisions for Environmental ManagementSelected Summary Statistics and Effects of Voluntary Environmental Programs Cody Jones Master of Environmental Management Portland State University February 2, 2007
Description and Objectives • Environmental issues are gaining attention and importance for stakeholders • Current regulatory framework is not proving effective for certain global issues (CO2, nonpoint sources) • U.S. Environmental Protection Agency (EPA) Science to Achieve Results (STAR) grant • Three universities: PSU, OSU, UIUC • Comprehensive survey of environmental management in Oregon • Environmental management: influences and barriers • Environmental practices: training, voluntary programs • Environmental performance: actual outcomes, regulatory compliance, changes in impacts • Informing public policy to foster voluntary environmental management efforts at for-profit organizations
Voluntary Environmental Programs • VEPs • Unilateral — Industry or firm action with no government involvement (Responsible Care) • Bilateral — Industry and government partnerships (Green Permits, Performance Track) • Government initiatives — Government sponsored and managed (WasteWise) • Program types: • Specific impact (ENERGY STAR) • Industry specific (Smartway Transportation Partnership) • General (The Oregon Natural Step Network)
Survey and Sample • Survey: Tailored Design Method (Dillman 2000) • Designed with expert consultation and pretested • Specific respondents were identified (environmental manager or other environmental decision-maker) • Self-administered by mail, with followups • Survey period: Calendar year 2004 (mailed in fall 2005) • SESRC, WSU, Pullman, WA • Sample: Oregon Employment Department (OED) facility–level data • Facilities with 10 employees in Oregon • Six sectors • Manufacturing: food, wood, electronics • Others: construction, transport, accommodation • Range of environmental impacts, environmental regulations, and voluntary approaches • Prominent economically: numerous facilities, high employment, substantial revenues • Random sample of 1,964 facilities
689 responses 35.1% response rate Construction: 34.3% Food: 37.1% Wood: 37.2% Electronics: 34.2% Transport: 37.3% Accommodation: 29.9% 31 of 36 counties represented Small facilities 89% privately held 79% independent 100 87 85 84 83 83 81 80 60 40 Study sample Washington 20 Montana Oregon Idaho U.S. 0 Respondent Characteristics Establishments (facilities) with <100 employees (2000 Census)
Energy 8% 6% Green building 42% 7% Recycling 13% Industry Climate 16% Water 30% General 20% Participate Do not participate 80% Program Participation
Participant Characteristics • Participants reported higher revenues • Participants had more employees • Participants were located in 27 counties 35 30% 30 25 22% 20% 20% 20 16% 15 10 5% 5 0 Food (311) Electronics (334) Construction (236) Transport (484) Hotels (721) Wood (321)
M = 2.14, SD = 1.27 Interest Groups M = 2.65, SD = 1.38 Customers M = 2.69, SD = 1.36 Competition M = 2.98, SD = 1.45 Investors and Lenders M = 3.25, SD = 1.40 Regulations M = 3.70, SD = 1.05 Upper Management Parent Company M = 3.86, SD = 1.12 Influences and Perceptions 0 1 2 3 4 5
Barriers High upfront expense M = 3.63, SD = 1.36 M = 3.29, SD = 1.28 High day-to-day costs M = 3.21, SD = 1.26 Upfront time commitment M = 3.11, SD = 1.33 Uncertain future benefits M = 2.86, SD = 1.40 Risk of downtime or interruptions M = 2.77, SD = 1.23 Knowledgeable staff M = 2.36, SD = 1.29 Employee appraisals M = 2.30, SD = 1.29 Employee rewards 0 1 2 3 4 5
Performance • Impacts queried • Wastewater and dewatering discharge • Solid waste and recycling • Hazardous or toxic wastes • Carbon dioxide (CO2) emissions • Hazardous air emissions (all except construction) • Electricity and natural gas (manufacturing and accommodation) • Green building and energy efficient installations (construction) • Diesel and biodiesel use (transport) • Three measures: outcomes, compliance, changes • 95% responded to compliance questions • 70% responded to change questions • 56% responded to outcome questions
Performance - Outcomes • Facilities reported recycling 49% on average • VEP participants averaged 59% • Nonparticipants averaged 44% • Construction installed 38% energy efficient equipment on average • VEP participants averaged 54% • Nonparticipants averaged 32% • Construction built 29% of buildings to “green” standards on average • VEP participants averaged 28% • Nonparticipants averaged 9% • Few facilities were tracking CO2 and those that did used inconsistent standards
Performance – Compliance and Changes • 35% reported overcompliance on at least one impact • 57% of VEP participants • 30% of nonparticipants • 4% reported working toward regulation on at least one impact • 59% reported improvements in at least one area • 80% of VEP participants reported improvements • 54% of nonparticipants reported improvements • Most changes were minimal • Hazardous waste and hazardous air emissions very slightly decreased (~1%) • Electricity and natural gas use slightly increased (1-3%) • Recycling slightly increased (1-3%) • Energy efficient equipment installations and green building slightly increased (~3%)
Summary • Role for regulation • Regulatory influences were rated the most important external influence • Complying with current regulations was highest rated external influence • Majority of facilities reported meeting regulatory requirements as opposed to exceeding them • Opportunities for increased voluntary environmental management • Overall, facilities agreed with the idea that facilities have responsibilities to protect the environment • One-third of respondents reported exceeding regulatory requirements • VEPs may be viable mechanism • Participants reported more practices, greater rates of overcompliance, and greater rates of impact improvements • The bottom line is a major driver of behavior • Investors were a high priority • Costs and time investments were the greatest barriers
Limitations and Future Research • Limitations • Characterization not an analysis • Subjective data • Limited bias testing • Good geographic representation and reasonable consistency with other estimates where available • No apparent bias based on size • Potential exists for underreporting of noncompliance and outcomes, overreporting of overcompliance and improvements • Secondary data on permits, inspections, infractions, and emissions from the DEQ, DOT, OSHA, EPA • Future research: Stay tuned
Acknowledgements U.S. EPA Project Team: David Ervin, Madhu Khanna, Patricia Koss, Junjie Wu, Cameron Speir, Terry Wirkkala, Beth Minor Committee: David Ervin, Cory Ann Wind, Joe Maser Agencies: DEQ, OED, SESRC Survey Respondents