The traffic moved between two cities by a long-haul carrier is commonly termed a lane. The purpose of this study is to demonstrate methods to assess the profitability of individual lanes. To tackle the problem of lane profitability, one needs to have accurate and valid data of revenue and costs. In view of the importance of properly prepared data, a secondary purpose of this study is to recommend accounting procedures to record data in a usable form for further studies of this kind. The concept of revenue for a lane is not difficult to understand. However, the concept of cost for a lane raises some difficult questions. Since a terminal handles traffic from a variety of lanes, the crux of the problem is to disaggregate the terminal costs to each individual lane. Statistical costing is the main tool used in this study. It is not the most accurate method but is less costly than most other methods. Thus, it is often an indeal substitution for detailed engineering studies. Statistical methods have applicability when direct observation of the relationship between cost and output is difficult or impossible. To this end, regression analysis was proposed extensively in the study to examine the behaviour of different cost elements. With a good grasp of the relationship between terminal costs and terminal output (activities) one can apportion the related terminal costs to the lanes of interest. This study presents a normative model. To construct the model, the examination of a common motor carrier's operation has provided much insight regarding (1) the kinds of data that are generally available, (2) how the available data can be improved, and (3) how the constructed model relates to the motor carrier examined. To appreciate the subtleties inherent in this study, a general understanding of the industry as well as the daily operation of a motor carrier is required. To assess the profitability relating to different lanes, one requires some workable methods, and above all, workable data. / Business, Sauder School of / Graduate

Air pollution is a threat to the environment and human health. Freight trucking in particular is the main source of freight transportation emissions. Heavy-duty trucks emit large amounts of toxic air pollutants that cause serious diseases and harm public health. In addition, heavy-duty trucks emit great amounts of greenhouse gas (GHG), which is the leading cause of global warming. Despite increased environmental restrictions on air pollution and rising trucking greenhouse gas emissions in the past decades, no economic study has examined the potential GHG and air pollution reductions in the trucking sector and the associated private abatement costs to the industry. This study accounts for GHG emissions and toxic air pollutants in measuring and evaluating efficiency and productivity for the trucking industry in the 48 contiguous states. Moreover, the private costs of abatement to the industry were also estimated. When only GHG was incorporated in the production model, the results showed that each state could expand desirable output and reduce GHG by an average of 11 percent per year between 2000 and 2007. The Malmquist-Luenberger productivity indexes showed that omitting or ignoring GHG in trucking service production yielded biased estimates. On the other hand, due to increased environmental regulations, most of the toxic air pollutants decreased dramatically between 2002 and 2005. The analytical results showed that inefficiency decreased during this period. The private costs of abatement averaged $73 million per state in 2005. When GHG and six toxic air pollutants were incorporated in the production model, the estimated private abatement cost was $76 million per state, which was equivalent to 0.7 percent of the industry output in 2005.