To understand whether telecommuting could be part of the policy solutions for greenhouse gas reduction in the transportation sector, this study uses Instrumental Variable Tobit models and data from 2001 and 2009 National Household Travel Surveys to explore whether telecommuting reduces or increases the daily work and non-work vehicle miles traveled. Our findings suggest telecommuters have more vehicle miles traveled for both daily work and non-work trips than non-telecommuters. Adding the findings that telecommuting has no impact on other non-working household member's daily total (nonwork) trips, we can possibly argue that households with telecommuter(s) tend to have higher daily total vehicle miles traveled. Our estimated marginal effect of telecommuting on worker's daily total trips indicates that, a telecommuter on average travels 38 vehicle miles more on a daily basis in 2001 and 45 vehicle miles more in 2009 compared with a non-telecommuter. These increases in vehicle miles traveled translate into a rather large increase in greenhouse gas emissions in the U.S. equivalent to adding 7,248,845 cars in 2001 and 8,808,165 in 2009 to the road. Moreover, the difference of this marginal effect between 2001 and 2009 suggests the impact of telecommuting on worker's daily total vehicle miles traveled had increased over time. With the emerging work arrangements to work from home, telecommuting has been welcomed in this changing environment, not only by individual workers and employers but also policymakers. But the outcomes seem to be opposite to what policy makers may have expected for GHG emission reductions.

This is an author-produced, peer-reviewed version of this article.

This study aims to improve how human performance improvement (HPI) practitioners manage attributes of change. While there have been numerous studies addressing various aspects of change management, few have examined how the characteristics of the change itself contribute to adoption. This study addresses a change scenario of current importance and interest. Researchers coded applicable survey responses from a previous study and performed factor analysis to identify barriers and incentives to green building, including Leadership in Energy and Environmental Design (LEED) certification, for construction industry professionals in the Pacific Northwest, and how those professionals feel about adopting “green” building practices—among them, the LEED rating system. Findings suggest that (a) the qualities of some changes have far more influence on adoption than others, such as difficulty of transition, and (b) other characteristics combine to exert their influence in concert with one another. Finally, a user\u27s perception of the value of the change was significant. The article\u27s conclusion addresses how HPI practitioners can integrate the findings into green building adoption specifically, as well as within the greater context of change management and implementation practices in general

This article provides empirical evidence that the factors of context and social climate are the most influential for achieving green building. Using both chi-squared analysis and factor analysis findings indicate that providing the context and social climate which can reduce transaction costs influence green building. Specifically, through policies and guidelines, having the local expertise and support to make the outcomes occur are all important factors. Additionally, central cities were much more likely to engage in green building than suburban or non-metropolitan areas. This has implications for matters of collective action.

We present a novel approach to understanding distance as a barrier to cycling and its use as a dependent variable in multinomial logistic regression. In doing so, this study explores distances in relation to spatially and relevant human factors such as gender and propensity to cycle among college students. College students (N= 949) participated in a health survey and stated possible predictors of cycling based on their cycle usage and preferences in the previous 30 days. While utilizing GIS in a bicycle-friendly network, we created geo-statistical GISgroupings and performed multinomial logistic regression analysis. We examined college students to discover how their demographic and personal characteristics may mediate the deterrent properties of distance when considered as a dependent variable in cycling to a college campus. Age and propensity for cycling for transportation mediate the negative effect of distance on the likelihood of cycling. The findings also suggest that infrastructure improvements could lessen the impact of distance as a barrier to cycling and increase the likelihood of cycling for commuting.