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The purpose of this paper is to investigate the issue of efficiency in the Brazilian motor carrier industry, which has undergone significant transformations since the economy deregulation in the mid-1990s. The main research objective is to determine whether or not different types of cargoes and geographic regions serviced significantly impact trucking managerial efficiency levels.

Research objectives are accomplished by applying a two-stage data envelopment analysis model with bootstrapped estimates. Based on an unbalanced panel model, secondary data from the annual study published by Transporte Moderno (years 2002-2010) were collected and analyzed.

Results support anecdotal evidence regarding a heterogeneous impact of cargo mix and route mix on efficiency levels.

A major limitation of this work concerns the fact of working with secondary data instead of primary data, especially with respect to the set of inputs and outputs used in the analysis, which may not cover all aspects relevant to building an efficiency frontier. Despite this limitation, the study has made an important contribution in its use of panel data to demonstrate the impacts of different types of cargoes and geographic regions serviced on managerial efficiency levels in the trucking industry.

Managerial impacts in terms of mergers and acquisitions are addressed.

The contribution of this study is twofold. On the theoretical side, a valuable scale for the measurement of managerial efficiency was built and validated, representing an index toward the most productive cargo/route mix. On the other hand, the managerial implication of this possibility of measuring the efficiency levels is that motor carriers can use it as a basis for establishing future action plans.

Brazil, DEA, Longitudinal study, Efficiency drivers, Trucking industry, Unbalanced panel

 Research paper

El estudio investiga el tema de la eficiencia en la industria del transporte Brasileña, la cual ha experimentado cambios significativos desde la desregulación de la economía a mediados de los años noventa. El objetivo principal de la investigación es determinar si los diferentes tipos de cargas y regiones geográficas que han recibido los servicios impactan significativamente o no los niveles de eficiencia administrativa de las empresas de camiones.

Los objetivos de la investigación se lograron usando un modelo DEA de dos etapas con estimaciones bootstrap. Basado en un modelo de panel no balanceado, se obtuvieron y analizaron datos secundarios del estudio anual publicados por Transporte Moderno (años 2002-2010).

Los resultados apoyan la evidencia anécdota en lo relacionado con el impacto heterogéneo de mezcla de cargas y una combinación de rutas en los niveles de eficiencia.

La limitación más grande de este trabajo es el hecho de trabajar con datos secundarios en vez de usar datos primarios, especialmente en relación con el set de inputs y outputs usados en este análisis, que podrían no cubrir todos los aspectos relevantes en la construcción de una frontera eficiente. A pesar de esta limitación, este estudio hace una importante contribución al usar datos de panel para demostrar los impactos de los diferentes tipos de cargas y regiones geográficas atendidas, en los niveles de eficiencia de la administración de la industria de transporte de camiones.

Se discuten los impactos de administración en términos fusiones y adquisiciones.

La contribución de este estudio es doble. Por el lado teórico, una escala relevante para medir la eficiencia de la administración fue construida y validada, que representa un índice hacia la combinación carga/ruta más efectiva. Por otro lado, las implicaciones administrativas de la posibilidad de medir niveles de eficiencia es que las empresas de transportes pueden usarloa como base para establecer planes futuros de acción.

Estudio longitudinal, Industria camionera, Brasil, DEA, Promotores de eficiencia, Panel no balanceado

 Trabajo de investigación

A pesquisa investiga o tema da eficiência na indústria brasileira de transporte rodoviário, a qual tem experimentado mudanças significativas desde a desregulamentação da economia em meados dos anos noventa. O objetivo principal da pesquisa é determinar se os diferentes tipos de cargas e de regiões geográficas atendidas impactam significativamente ou não nos níveis de eficiência na gestão de cargas rodoviárias.

Os objetivos da pesquisa foram atingidos usando um modelo DEA de dois estágios com estimativas bootstrap. Baseados em um modelo de painel, foram recolhidos e analisados dados secundários publicados no estudo anual da publicação Transporte Moderno (anos 2002-2010).

Os resultados apoiam a evidência baseada no senso comum relacionada ao impacto heterogêneo do mix de cargas e do mix de rotas nos níveis de eficiência.

A maior limitação de esta pesquisa concerne ao fato de trabalhar com dados secundários em vez de dados primários, especialmente em relação com a série de inputs e outputs utilizados na análise, que não puderam cobrir todos os aspectos relevantes para definição da fronteira de eficiência. Apesar dessa limitação, esta pesquisa traz uma importante contribuição ao utilizar dados de painel para demonstrar os impactos dos diferentes tipos de cargas e de regiões geográficas atendidas sobre os níveis de eficiência na gestão do transporte de cargas rodoviárias.

Os impactos da gestão em termos de fusão e aquisição são abordados.

A contribuição deste estudo é dupla. Pelo lado teórico, foi construída e validada uma escala relevante para medir a eficiência de gestão de cargas rodoviárias, que indica um índice para a combinação mais efetiva da combinação entre cargas e rotas. Por outro lado, quanto às implicações gerenciais, a possibilidade de medir os níveis de eficiência criam a possibilidade das empresas de transportes utilizá-los como base para futuros planos de ação.

Estudo longitudinal, Setor de transporte rodoviário, Brasil, DEA, Condutores de eficiência, Dados em painel

 Trabalhos de pesquisa

Traditionally, economic production models consider pollution as bads that may be modeled as either outputs or inputs in economic models. The purpose of this paper is to examine the implications of these modeling choices on the measurements of productive efficiency and private costs of pollution control.

The authors apply the hyperbolic distance functions to measure trucking efficiency and the private costs of pollution control.

The results show: (i) regardless of the choice of modeling, when only one bad was incorporated in hyperbolic distance functions, the efficiency loss and private abatement cost measures derived from the two models were equivalent, but potential pollution reduction and good output expansion differed; (ii) when more than one bad were introduced, the equivalence of efficiency loss measure in (i) did not hold; and (iii) the potential amounts of pollution reduction and good output expansion were larger when bads were modeled as inputs. With multiple bads, private abatement costs varied considerably under the two modeling treatments.

From a policy standpoint, the results suggest that one should consider the modeling options with caution when multiple economic bads are involved, because the resulting measures of economic burden of pollution control differ.

The paper shows that the traditional conceptual framework for modeling pollution in hyperbolic distance functions could yield inconsistent results.

This study aims to explore the challenges of truck-sharing and effective ways of dealing with those in achieving supply chain collaboration and collaboration in transportation management (e.g. transport collaboration) for transport capacity expansion, and reducing carbon emission and traffic congestion for integrating environmental and social sustainability issues. This paper also reveals insights into successful shared-transportation and a reduction in empty trips.

This exploratory qualitative study was conducted by means of interviewing road carriers from the container transportation industry.

In a truck-sharing initiative, technical issues (e.g. carrying capacity) arise, some of which involve the container truck and some involving constraints that cannot be controlled, such as driving restrictions, seaport operating hours, and the presence of the large number of container categories pertaining to the industry. Therefore, a significant amount of “structural empty running” may always prevail. It should also be noted that some, seemingly vital, constraints can actually be changed, treated, or modified for better truck-sharing outcomes, such as building a foundation of trust and establishing coordination among road carriers.

A probable solution to the problem of increasing hinterland transport capacity is to make appropriate use of the huge number of idle truck slots that exist; this could be achieved by encouraging the acceptance of the challenges of truck-sharing realistically and suggesting an approach to handling them.

To broaden its appeal, truck-sharing initiatives must be able to overcome challenges by combining theoretical insight with an understanding of the practical aspects of such an endeavor. This original research fosters knowledge that is unique and which also has real-life applications in maritime logistics studies and supply chain literature for both port authorities and container road carriers.

Due to mounting fiscal pressures, the federal government as well as many state and municipal governments in the USA have had to re-examine their transportation policies. Tax increases and/or spending cuts which aim to trim budget deficits are preoccupations of most policy makers and legislative bodies nowadays. With regard to the task of building new or rehabilitating old bridges, highways, and toll gates, cost-benefit analysis and economic impact studies are often undertaken by various government entities to rank and prioritize spending in the hopes of maximizing fiscal efficiency and road usage benefits. Since most highway construction and maintenance expenditures are absorbed by state governments, it is mostly up to state policy makers to decide transportation priorities. Not much research to date has been conducted to evaluate the comparative efficiency of state road provision to commuters and shippers. Such research would be useful to a state government’s budgetary allocation, road planning, and spending plans. The paper aims to discuss these issues.

This paper uses data envelopment analysis under both constant and variable returns-to-scale and then to explain variations in efficiency ratings by using Tobit regression analysis.

The authors discovered that the greater the level of state resident income and/or the warmer the weather, the higher the road or mass transit provision efficiency on average. The authors also found that greater urbanization in a state had little to do with efficiencies with respect to road provision.

This paper is one of the first to assess and evaluate the comparative efficiency of road provision across 50 states in the USA and then set a benchmark for utilizing state financial resources to improve road infrastructure. More importantly, this paper helps transportation planners and public policy makers better allocate their limited financial resources to public goods in time of budget cutbacks and shortfalls.

Mahindra Trucks and Bus Division (MTBD) of Mahindra & Mahindra is at an interesting stage of its evolution. Having gone through a bad patch with a product that was not quite up to the mark, it appears to have got the product right by early 2018 and truck sales had been going up in the country for the previous four years. While Mahindra & Mahindra as a company is a large firm with revenues of more than USD 15 billion, MTBD itself is a small player (INR 2400 crore, USD 350 million) within the firm and in an Indian truck industry that is dominated by goliaths, Tata Motors and Ashok Leyland that between them had more than 81% market share and a customer mindset that was loath to leave the comfort of a known brand. The case provides data on product specifications, prices, marketing communication, channels, positioning, the context and competition. The intention is to use the case to go through the steps involved in evaluating and developing and creating a marketing plan for MTBD to increase its market share from the 4% in 2018 to an intended 8% in 2022.

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.

A seaport is an essential part of a supply chain, but many ports experience truck shortages, creating pressure for port authorities from shippers who need more trucks that move cargo. This study explores and ranks the motives for adopting a truck-sharing concept (where shippers share the same truck for delivery) as a mechanism to improve transport capacity.

This study adopts a multi-method approach – both interviews and surveys. Interviews are first conducted with shippers to explore truck-sharing usage motives. Next, quantitative surveys of both shippers and carriers are conducted to rank those motives.

The study identifies five motives (operational efficiency goal, quick transport solution, sustainability policy, convenience-seeking behavior and secure transport process) for truck-sharing, four critical transport attributes (lower charges for freight, distance travelled, full capacity utilization and environmental recognition), four psychological consequences (monetary savings, greater safety, instant availability of trips and clarification of environmental values), and six core values (secure transport process, being careful of money, ease of doing business, sustainability, status in the community and recognition by customers of shippers).

The qualitative results will help researchers better understand how usage motives influence shippers' willingness to share a truck for transport needs. The quantitative results are useful for ranking truck-sharing motives by their importance.

Based on the findings, managers of carriers can categorize shippers according to their specific needs and thereby customize promotions to attract more shippers.

The findings provide the first, exploratory insights into shippers' motives.

WHERE are we going? The aim is to double our standard of living in the next 25 years and, as Sir Alexander Fleck, K.B.E., Chairman of Imperial Chemical Industries Ltd., so aptly staled recently, ‘The man who knows where he is going is the one who is most likely to arrive.’ One might venture to expand this statement by adding that he is still more likely to arrive if the cluttering debris of inefficient methods and movements are cleared away.

The purpose of this paper is to propose a scheme to estimate the technical efficiency of trucks engaged in logistics and to analyze the properties of efficiency. The objectives are to determine individual‐truck level technical efficiency using both radial and non‐radial measures for freight trucks, to calculate the degree of input overuse.

Data envelopment analysis is employed in this paper because it does not require the assumption of the functional specification between input and output factors and also includes multiple outputs unlike stochastic frontier model. Data for empirical analysis in this paper come from a survey of truck drivers.

The result of technical efficiency estimation shows that there exists a substantial opportunity for improvement in technical efficiency of trucks engaged in logistics and also the heterogeneity in the technical efficiency among trucks based on their capacity and age. For scale efficiency, it is also possible to confirm the existence of improvement opportunity and heterogeneity among truck and that trucks with large capacity are more scale‐efficient than those with small capacity.

The paper analyzes the properties of technical efficiency scores of trucks engaged in logistics and finds some managerial insights which can help them improve their efficiency.