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The purpose of this paper is to model the tradeoffs among fatalities, CO₂ emissions and value generated by the truck transportation portion of supply chains with the goal of determining if efforts to reduce CO₂ emissions increase transportation‐related fatalities.

The joint production of CO₂, fatalities, and truck transport value in the 50 US states during 2002‐2007 is modeled using data envelopment analysis. The directional output distance function is estimated under two assumptions: strong and weak disposability of CO₂ emissions. This provides the means of calculating shadow prices that estimate the cost of reducing CO₂ emissions.

The authors' findings indicate that the transfer of resources to the reduction of CO₂ emissions will result in a statistically significant increase in fatalities and a statistically significant decrease in value of transport from truck transport.

The model presented is based on secondary data from the Federal Highway Statistics Series, the Fatality Analysis Reporting System, and the Bureau of Economic Analysis.

The model developed demonstrates tradeoffs among sustainability‐related variables.

The model presented in the paper uses shadow prices to assess sustainability‐related tradeoffs in supply chains. While this method has been used in other fields, this is its first use in supply chain studies.

Develops and estimates efficiency and productivity measures in the US trucking and warehousing industry in the 48 contiguous states during the years 1994‐2000. The model, estimated via data envelopment analysis, accounts for both desirable outputs and undesirable outputs produced by a given vector of inputs. The model establishes an efficient frontier of operation for each year studied and can be used to determine, on an annual basis, which of the 48 states operate on the frontier. The findings indicate that the trucking and warehousing industry does not operate efficiently in all 48 states during the period studied. If the industry were to operate on the frontier of the feasible output set by using inputs to produce outputs efficiently, it could eliminate three to four fatal traffic accidents per state per year, while simultaneously increasing industry income by between $38 to $47 million per state per year. In addition, finds that traditional techniques of estimating efficiency that ignore traffic fatalities bias estimates of efficiency and total factor productivity growth.

The purpose of this paper is to analyze trends in fatal law enforcement officer (LEO) traffic collisions and describes prior research approaches and industry responses. It reviews the issue from historical and contemporary perspectives and details its problems for public policy.

Descriptive statistics are applied to data primarily covering the period 1995 to 2010 contained in the Federal Bureau of Investigation Crime in the USA and LEO Killed and Assaulted reports and the National Highway Transportation Safety Administration Fatality Analysis Reporting System database. Trends are established and comparisons are offered between groups.

Traffic collisions are the leading cause of death for LEOs. Traffic fatalities in the general public have steadily decreased in past decades. This has not been the trend among LEOs. This issue has been studied from several disciplinary perspectives in the social, cognitive, biological, engineering, and natural sciences. While the law enforcement industry has documented the trend, concerted efforts to mitigate the issue have been limited until recently.

Law enforcement practitioners and policymakers should take note of research findings and pursue training, policy, and practice changes to limit LEO traffic fatalities and effect an improvement trend consistent with the national reduction in highway deaths.

This paper brings together previously uncoupled data sources and prior research to identify problematic trends and contextualize LEO traffic fatalities as a subset of all traffic fatalities. It provides law enforcement policymakers a stark and revealing assessment of the most dangerous aspect of their field.

The purpose of this paper is to investigate variability in law enforcement officer (LEO) traffic fatality rates among states in order to identify policy-relevant areas of opportunity to reduce deaths.

Differences in state highway spending, regulatory policy, law enforcement training, LEO and general public traffic fatalities, and other state-level variables are explored through cross-sectional regression analysis and qualitative content analysis. Data were used from the Federal Bureau of Investigation Crime in the USA and LEOs Killed and Assaulted reports, and the National Highway Transportation Safety Administration Fatality Analysis Reporting System, among other sources.

There are a number of significant state-level variables and trends that contribute to differences in LEO traffic fatality rates. Maximum highway speed limits and general population traffic fatalities are found to be statistically significant predictors. Thematic factors relating to LEO exceptionalism, agency sovereignty, training, and external control loci, emerged through qualitative analysis.

Limitations included differences in definition, consistency, and reporting among data sources. Qualitative analysis of some variables were limited and future research should pursue more robust and repeated/longitudinal measures.

Policymakers have an opportunity to review significant factors contributing to higher/lower collision involvement rates and make changes to police practices to reduce collision involvement and improve safety for LEOs.

No prior study has offered a national, cross-case analysis of LEO traffic fatalities by state. This paper offers law enforcement policymakers empirical examples of successful LEO traffic safety policies.

FOR some time it has been recognized that the greater part of all passenger fatalities in air transportation were the result of impact in crash landings. Since in the majority of cases the crash landing was followed by fire, it was popularly believed that the majority of the deaths were occasioned by incineration. This Command, anxious to better an already excellent safety record, was fully aware of this problem, as were all other operators of transport aircraft.

The purpose of this paper is to provide an overview of the literature pertaining to occupational health disparities experienced by Latino immigrant workers in the USA and to advance a general framework based on systems science to inform epidemiological and intervention research.

Using papers and other sources from 2000 to the present, the authors examined the employment conditions and health outcomes of Latino immigrant workers and critically analyzed the pervasive evidence of health disparities, including causal mechanisms and associated intervention programs.

The occupations, including the work environment and resultant living conditions, frequently performed by Latino immigrants in the USA represent a distinct trigger of increased injury risk and poor health outcomes. Extant intervention programs have had modest results at best and are in need of more comprehensive approaches to address the complex nature of health disparities.

An integrated, systems-based framework concerning occupational health disparities among Latino immigrant workers allows for a holistic approach encompassing innovative methods and can inform high-leverage interventions including public policy.

Reductionist approaches to health disparities have had significant limitations and miss the complete picture of the many influences. The framework the authors have provided elucidates a valuable method for reducing occupational health disparities among Latino immigrant workers as well as other populations.

In the United States, many arguments for mass transport often focus on its benefits to the environment or in terms of congestion relief. This chapter instead looks at direct micro-scale and meso-scale economic and social benefits by identifying occupations, industries, and demographic groups that are both growing and can benefit from transit. In using this form of local-scale identification of unique economic circumstances, government planners, elected officials, and academics can create a practical, GIS-focused approach to increase the utility and acceptance of mass transportation in the United States.

Using a GIS-based approach with US Census and US Labor Department data, the chapter focuses on local growth sectors in the economy, then identifying their transit-usage patterns. Additionally some GIS are used to identify concentration areas of both occupations and transit usage, along with areas of likely employment for those individuals. Locally this creates “micro-climates” or hot spots for favorable views and usage of transport. These micro-climates can be duplicated in other similar areas to increase utilization, and therefore return on investment, of public transportation.

For denser areas, affluent downtowns, and areas which are accessible to hospitals and universities, the primary growth engines of the current US labor market, transit has a positive correlated relationship. Additionally, recent immigrant groups, particularly those with limited English speaking ability, have also shown a correlated growth in transit usage. By identifying these areas with GIS, transit can better align its services to needs and improve it return on investment.

The United States has had a fifty-year-long negative view of public transport outside of major urban areas. By identifying groups with positive correlated use of transit, the return on investment and public perception of its use and environmental sustainability can mesh with land use planning and perceived quality of the service. In so doing, transit use may be encouraged.

The United States is faced with very high petrol prices relative to its history, and somewhat lesser incomes among its sub-age-30 work cohorts. This has encouraged density. However, in order to provide for this increased demand, there must be an increase in both supply and politically perceived value in its investment. This chapter seeks to be an early pragmatic model in valuing public transport at a local level.

The purpose of this paper is to examine the past 50 years of driver research from a historical context linked to the political and economic developments of the US motor carrier industry.

A comprehensive literature review was conducted and studies were targeted that exemplified eras of historic change pertaining to trucking published within the top-tier logistics journals.

Distinctive categorizations of driver research emerged: organizing era from 1930 to 1949, era of the collective mind from 1950 to 1979, era of the individual from 1980 to 2009 and the era of the driver as extension of the firm from 2010 to present. Research streams are highly influenced by current industry developments, economic conditions and the political landscape.

The chronological framework of research established specific time-based eras. An alternative framework or other emerging eras may be conceived as scholars consider factors in addition to those explored within this research.

Managers within developing countries may leverage the research within a specific era to help resolve driver problems that have already been researched in the USA. Scholars are encouraged to further study truck drivers as critical extensions of the firm in light of the advances in autonomous vehicles, drones and other technology impacting the motor carrier industry.

For nearly a half century, the turnover of truck drivers has been a major issue. This research provides driver managers with the knowledge to better understand and to more adequately provide for the needs and welfare of truck drivers.

This research is the first to fully connect the research and developments pertaining to the motor carrier industry, the occupation of truck driving and the historical developments of US policy and the economy.