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This paper deals with the development of an automated procedure for selecting motor carriers to minimize transportation cost prepaid by a shipper. To test the effectiveness of the decision support system (DSS), an empirical study was conducted, in which the freight carriers actually chosen by the traffic manager at a large manufacturing company over a period of time were compared with those recommended by the computer program and the difference between the two total transportation costs was computed. It was found that, while the human decisions based on experience and intuition were generally sound and good, substantial savings in shipping expenses were achievable with the aid of a DSS such as the one described here, especially when the logistical operations become more complex and the time horizon is longer. Limitations of the present study are delineated and directions for future research are discussed.

To present a decision support system (DSS) enabling the analysis of the cost‐effectiveness of direct‐shipping long‐haul road transport policies, including full truck load (FTL) and less than truck load (LTL) modes, and to select the optimal carrier.

Analytical estimation of transportation costs is provided in a framework including an interactive computer procedure and a dedicated database structure capable of characterizing the logistics system.

Main criticalities of manual logistic planning are: sub‐optimal selection of carrier and excessive use of LTL transport, while the optimal FTL vs LTL trade‐off is not fully explored in practice.

This is an analysis tool of user‐defined scenarios and does not provide the automatic synthesis of shipments planning. Admittedly, this model does not attempt to optimize the shipping strategy, but to quantitatively assess the effects of the adopted decisions.

Alternative shipping policies can be compared to perform what‐if analyses and explore the outcome of alternative decisions (FTL vs LTL shipping modes) even in terms of transportation expenditures. Allows rapid selection of the optimal motor carrier and assesses the extra cost due to a sub‐optimal choice. Gives the experienced manager a framework for critical assessment of shipping decisions, suggesting improvement areas for cost reduction.

With respect to other software tools for carrier selection provides explicit analysis of extra costs incurred by manual planning, thus becoming a strategic tool for logistic decision making. Furthermore, enables managerial insights to be gained and makes manual planning more effective.