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Unprecedented endeavors have been made to take autonomous trucks to the open road. This study aims to provide relevant information on autonomous truck technology and to help logistics managers gain insight into assessing optimal shipment sizes for autonomous trucks.

Empirical data of estimated autonomous truck costs are collected to help revise classic, conceptual models of assessing optimal shipment sizes. Numerical experiments are conducted to illustrate the optimal shipment size when varying the autonomous truck technology cost and transportation lead time reduction.

Autonomous truck technology can cost as much as 70% of the price of a truck. Logistics managers using classic models that disregard the additional cost could underestimate the optimal shipment size for autonomous trucks. This study also predicts the possibility of inventory centralization in the supply chain network.

The findings are based on information collected from trade articles and academic journals in the domain of logistics management. Other technical or engineering discussions on autonomous trucks are not included in the literature review.

Logistics managers must consider the latest cost information when deciding on shipment sizes of road freight for autonomous trucks. When the economies of scale in autonomous technology prevail, the classic economic order quantity solution might again suffice as a good approximation for optimal shipment size.

This study shows that some models in the literature might no longer be applicable after the introduction of autonomous trucks. We also develop a new cost expression that is a function of the lead time reduction by adopting autonomous trucks.

This paper studies the frequency and the average size of export shipments at the firm–product–destination level.

This paper sets up a theoretical model about the shipping frequency and the shipment size of exports to a given market from individual exporters. Then it confronts the predictions of the model with trade data.

This paper shows that patterns of export shipments are determined by (1) a product's export potential in a market, which is the exports revenue when the firm delivers the exports of the product to the market in a single shipment in each period; and (2) factors related to the firm's efficiency of managing shipments of the product exported to the market.

This paper reveals some important patterns of export shipments. It provides a theoretical model that explains the patterns.

The purpose of this paper is to develop a transport portfolio framework (TPF) and explore its use as a decision support tool for shippers wanting to improve their transport system in terms of reducing their carbon footprint.

The TPF has been designed on the basis relevant theoretical frameworks in logistics and thereafter tested and further developed by the use of empirical data from a case study. Quantitative methods are used to find patterns in the shipment statistics for import flows obtained from a food retailer and carriers.

The TPF highlights different avenues for decreasing the carbon footprint, by identifying the product flow characteristics that might affect modal split and load factor, and it is believed that these can help shippers’ intent on analysing the largest potential for improvement. This potential is estimated based on how the key variables, modal split and load factor, can be improved.

Shippers can use the TPF as a decision support tool in their efforts to reduce their carbon footprint by: structuring complexity, managing data and finding effective solutions.

Reducing emissions is an increasingly important priority for shippers and the TPF helps them to direct their efforts towards approaches that have a substantial impact.

The TPF provides an opportunity to match different approaches for improving the environmental performance with the potential for reducing carbon footprint in shippers’ transportation networks, by taking into account the complexity of logistics network.

Addresses a number of issues relating to determining whether products should be ordered independently and therefore shipped as a single‐product order, or co‐ordinated and shipped as a group, or multiproduct, order from a single source. Factors which might influence the decision include the level or volume of demand, the distribution of demand across products, the weight of items and the attractiveness of the quantity discount offered. Uses an optimal inventory‐theoretic model, that incorporates transport weight breaks and quantity discounts, to assess when product orders should be combined and what products should be ordered separately. The effects of these decisions on the order interval, the number of order groupings, the proportion of items ordered independently, the proportion of attractive discounts forgone in favour of consolidation, and the relative cost savings, are examined using an extensive set of simulated data that are based on a firm in the automobile industry supply chain.

Due to the growing percentage share of urban dwellers, the physical distribution of products faces altering conditions. This research explores the effects that urbanization has on the performance of a fast-moving consumer goods distribution network. A focus is set on changes in distribution cost, the cost-minimal network design, and greenhouse gas emissions.

The analyses are based on a quantitative distribution network model of an existing manufacturer of consumer goods.

The results indicate that the foreseen population shift will affect the network's economic and environmental performance. Effects are, among others, due to differences in the efficiency of supplying urban and nonurban regions. The combined effects of urbanization and the development of the population size will even more affect the network's performance.

Research dealing with distribution logistics and urbanization primarily focuses on city logistics. In this paper, the object of analysis is the entire distribution system.

Although some recent articles have extended the traditional economic order quantity models to JIT purchasing, their value is limited by the simplistic nature of the underlying assumptions. Implementation of JIT procurement is a lengthy and complex process and it is important to recognize the interrelationships between the investments in the different subsystems of the procurement system to suit JIT and the resultant cost and lead time structures. It is also important o consider the variability in demand and lead time. Presents an inventory‐theoretical model that takes these considerations into account and illustrates its application with a numerical example. This model facilitates the choice of an optimal combination of the investment and the shipment lot size to minimize the total annual cost in each period as a firm progressively adopts JIT procurement.

Business to consumer (B‐2‐C) e‐commerce offers many potential benefits to firms, including access to geographically dispersed markets across international borders and enabling direct supply chain relationships with consumers. Language and currency differences, consumer liability implications and customs and inspection fees represent barriers to the expansion of international e‐commerce. Comparisons are presented of customs fees for regular and e‐commerce sized shipments of four food products from Canada to the USA. As these fees are largely charged on a flat rate basis, they place e‐commerce shipments at a considerable competitive disadvantage relative to traditional truckload sized shipments. The lack of agreement internationally on how to revise or harmonise customs regulations means that customs fees remain geared towards large shipments. Although the existing system was acceptable when most shipments crossing borders were large truck or container loads, the development of e‐commerce provides a strong incentive for change.

Freight consolidation across time and customers, use of warehouses, and direct LTL distribution systems are compared on distribution costs and delivery times for selected product characteristics and demand patterns. The results can assist managers in determining whether using freight consolidation is a viable alternative to direct shipments from plants or warehouses.

There is need for a new, more precise, more integrated system for logistics costing. The integration of purchasing, transportation (traffic) and storage operations throughout the vertical stream, from source of materials to the consumer is discouragingly complex. It cannot be accomplished by departmentalising logistics functions, performing average and joint commodity costing, and dealing primarily with direct costs. The volume of records may be representative, but there is a very apparent lack of costing systems to facilitate logistics planning. The volume of shipment is the key to logistics cost analysis, just as volume of production is the independent variable in conventional economic analysis. Logistics costs vary with changes in the volume of shipment. Cost per hundredweight is the unit for cost analysis under the Cellular Flow Planning System. It is measured on a specific commodity, between specific points. Purchase price, transport rate, linear increasing costs, constant and single payment decreasing costs are the five classes of costs used to compare competitive volumes of shipment. All significant logistics costs can be so classified. This article presents only the rationale behind the unit for cost measurement, the classification of costs, and the means of comparison.