Logistics and transportation issues in supply chain

The logistics function in supply chain is conceptualized as a service function because its output is not a product but a performance, such as just-in-time delivery of the right amount of goods at the right place (Heskett et al. 1990). Logistics is also a strategic level challenge in a supply chain. In literature of supply chain management, there is a lot of studies have conducted the role of transportation and logistics functions in a supply chain. van Hoek and van Dierdonck (2000) aimed at assessing whether or not final manufacturing activities are actually being postponed and placed in the distribution channel. Based on a survey among 782 companies, the difference in size

and scope of applications between manufacturers, wholesalers and logistics service providers are assessed. The results showed that high value adding manufacturing activities are still the primary domain of manufacturers and there are not often outsourced to logistics service providers. Morash and Clinton (1997) investigated and compared supply chain organizational structures and integrative capabilities of approximately two thousand firms from the United States, Japan, Korea, and Australia.

Country differences in both supply chain structures and transportation capabilities were identified.

Lai et al. (2002) aimed to investigate the construct of, and develop a measurement instrument for, supply chain performance in transport logistics. A 26-item supply chain performance measurement instrument was constructed, reflecting service effectiveness for shippers, operations efficiency for transport logistics service providers, and service effectiveness for consignees. Mason et al. (2003) demonstrated the potential for integrating the warehousing and transportation functions and so improve customer service through reduced costs and reduced lead-time variability. Thomas and Hackman (2003) analyzed a supply chain environment where a distributor facing price-sensitive demand has the opportunity to contractually commit to a delivery quantity at regular intervals over a finite horizon in exchange for a per-unit cost reduction for units acquired via committed delivery.

Chopra (2003) described a framework for designing the distribution network in a supply chain. In the paper, there are six distinct distribution network designs, such as:

(1) manufacturer storage with direct shipping; (2) manufacturer storage with direct shipping and in-transit merge; (3) distributor storage with package carrier delivery; (4) distributor storage with last mile delivery; (5) manufacturer/distributor storage with customer pickup; and (6) retail storage with customer pickup. The strengths and

weakness of these designs and various factors influencing the choice of distribution network are also described.

Ambrosino and Scutellà (2005) studied complex distribution network design problems, which involve facility location, warehousing, transportation and inventory decisions. The main contribution of this study is the statement of two kinds of mathematical programming formulations: some formulations aimed at warehouse location-routing problems and other formulations are based on flow variables and constraints. Eskigun et al. (2005) formulated an integer linear programming (ILP) model, which considered the design of an outbound supply chain network for vehicle distribution centers, considering lead times, location of distribution facilities and choice of transportation mode. A Lagrangian heuristic was developed to solve this large-scale integer linear programming model. Results of the scenario analyses indicate that as the lead-time gains importance, the use of trucks increases significantly to deliver the vehicle directly from plants to demand areas in shorter lead-time.

Motivated by observing the chemical industries, where manufacturing often takes place only after the order has been received, Kiesmüller et al. (2005) presented a dual supply model taking into account that the replenishment cycle involves not only the physical distribution of goods, but also the manufacturing of products. This study also investigated a class of order-up-to policies and showed how to compute the optimal policy parameters. The results showed that especially in cases where the manufacturing lead time is long and the difference in cost between fast and slow modes is big and the lead time difference is large, the added value of including the manufacturing lead time for the model is substantial. In industries such as the chemical industry using the models would imply a dramatic shift from road transport to rail or barge transport.

Though the importance of logistic functions to the supply chain efficiency has been demonstrated and discussed included in supply chain design problems. The shipping frequency and shipment size between different combinations of suppliers and manufacturing plants and of manufacturing plants and customers in different regions have not been discussed yet. Furthermore, shipping economies inhering in the supply chain are seldom discussed when design a supply chain network.

A great deal of analytical research has been conducted on solving the physical distribution problems (e.g. Burns et al., 1985; Blumenfeld et al., 1985). Hall (1987) proposed a critical flow concept, that is to say, shipping economies arise when the shipment size exceeds the critical flow. Blumenfeld et al. (1985) pointed out that the optimal shipping route depends on the geographical combinations of production sites, warehouses, and customers. From these studies, the following conclusions can be drawn: a less frequent strategy is suggested when two locations are distant from each other; otherwise, a converse strategy is preferred. Furthermore, according to Daganzo (1991), some cost components may not be paid by the manufacture, e.g. the key-component shipping fee and the inventory cost of the final products at customers.

However, an optimization without these costs tends to transfer the burden of the operation from the manufacturer to the customers and the suppliers, since their costs are not being considered. In other words, the customers and suppliers may be less willing to participate in the operation. Table 2.3 summarizes main issues and features and important results in the existing literature on logistics issues in the supply chain.

Summary:

Past literature has demonstrated the importance of logistics functions on the efficiency of a supply chain. However, the shipping frequency and shipment size between different combinations of suppliers and manufacturing plants and of

manufacturing plants and customers in different regions have not been discussed yet.

Furthermore, shipping economies inhering in the supply chain are seldom discussed when design a supply chain network. The impact of spatial distance on the optimal shipping frequency although having been studied in logistics literature, has not been integrated into the design of supply chain networks.

Table 2.3 Main issues, features and results in literature on logistics issues in the supply chain

Authors Main issues and features Important results van Dierdonck

(2000)

Assess whether or not final manufacturing activities are actually being postponed and placed in the distribution channel

High value adding

manufacturing activities are still the primary domain of

manufaturers

Manson et al.

(2003) Integrate the warehousing and transportation functions of the supply chain

Demonstrate the potential for integrated paradigm to improve customer service through improved efficiencies, reduced costs and reduced lead-time variability

Ambrosino and

Scutellà (2005) Consider complex distribution

design problems The main contribution is the statement of two kinds of mathematical programming formulations

Eskigun et al.

(2005) Design an outbound distribution network for vehicle distribution centers

As the lead-time gains importance, the use of trucks increases significantly to deliver the vehicle directly from plants to demand areas in shorter lead-time

Kiesmüller et al.

(2005) Present a dual supply model taking into account that the replenishment cycle involves not only the physical

distribution of goods, but also the manufacturing of products.

When the manufacturing lead time is long and the difference in cost between fast and slow modes is big and the lead time difference is large, the added value of including the

manufacturing lead time for the model is substantial

Hall (1987)

Propose analytical research on solving the physical distribution problems

Propose a critical flow concept, i.e. shipping economies arise when the shipment size exceeds the critical flow.

Blumenfeld et al.

(1985)

Propose analytical research on solving the physical distribution problems

The optimal shipping route depends on the geographical combinations of production sites, warehouses, and customers.

Source: this study