Skip to main content

An Exploratory Study of Biomass Harvesting among Logging Firms in Virginia and North Carolina

Buy Article:

$21.50 plus tax (Refund Policy)

Logging firms in the United States will need to harvest and transport woody biomass if national wood-based renewable energy production goals are to be achieved. Expansion of associated biomass markets could provide important revenue opportunities for logging firms and potentially alter the sector. To study biomass harvesting behavior among logging firms, a logistic regression model was developed using a backward likelihood ratio procedure and 114 Virginia and North Carolina logging firms that operate in proximity to established woody biomass markets. The sample was identified from a larger pool of firm owners who participated in a Virginia Sustainable Harvesting and Resource Professional (SHARP) Logger Program survey. Hypothesized predictors included logging operation and owner variables. Confirmatory factor analysis was used to verify the underlying structure of summated latent constructs. The model correctly classified biomass harvesting 78% of the time, exhibited acceptable fit, and contained normally distributed residual error. Significant predictors included firm mechanization, haul distance, and owner perspectives regarding job security satisfaction and attitudes about biomass harvesting. Analysis of variance and χ2 were used to test for differences between significant predictors when factored across a three-point biomass market-action variable—no market, market/no harvest, and market/harvest. The follow-on market-action evaluations included firms from the SHARP Logger Program survey that share county-level centers of operation for which at least one of the firms noted proximity to a woody biomass market. Implications for logging sector research are discussed, along with practical considerations for regions where wood-based renewable energy initiatives are on the rise.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Keywords: diffusion of innovations; job security; logistic regression; renewable energy; woody biomass

Document Type: Research Article

Publication date: 2011-10-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
  • Submit a Paper
  • Membership Information
  • Author Guidelines
  • Podcasts
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more