Production, Manufacturing and LogisticsSupplier-initiated outsourcing: A methodology to exploit synergy in transportation
Introduction
A Logistics Service Provider (LSP) is defined as a provider of logistics services that performs logistics functions on behalf of his customers (cf. Coyle et al. (1996)). In recent years, LSPs have had to cope with stricter requirements of customers in terms of speed, quality, flexibility and price. In addition, because of broader product assortments and shorter life cycles, streams through the LSPs’ networks became highly fragmented. This causes load factors and, by consequence, profit margins to drop. To cope with these heavy market conditions, LSPs are on a continuous search for opportunities to increase their efficiency and discern themselves from competitors (cf. Langley et al. (2005)). In parallel, manufacturers are outsourcing their non-core competences, which raises the demand for transportation in the LSP market.
Razzaque and Sheng (1998) define logistics outsourcing or third party logistics as the provision of a single or multiple logistics services by a vendor on a contractual basis. It has been estimated that about 40% of global logistics is outsourced, and increasing numbers of shippers consider it an attractive alternative to the traditional logistics service mode (cf. Wong et al., 2000, Hong et al., 2004).
For their turnover, LSPs heavily depend on the extent to which producers or retailers outsource their logistics activities. In the remainder of this paper, producers and retailers who might outsource their logistics activities to an LSP will be referred to as ‘shippers’. Wilding and Juriado (2004) provide a literature review of empirical papers on outsourcing, investigating which activities are typically outsourced and what are the most important reasons for doing so. Table 1 shows the top-5 reasons for outsourcing.
The outsourced activities can be related to Transportation and Shipment, Warehousing and Inventory, Information Systems and Value Added Services. It turns out that the most basic logistics functions of transportation, warehousing and inventory are outsourced most frequently.
The general idea behind outsourcing is a focus of companies on their core businesses. For example, customers of an LSP benefit from the LSP’s larger economies of scale that enable him to perform transportation and warehousing more efficiently than his customers. Traditionally, the initiative for outsourcing lies with the shippers: once it is reckoned by management that logistics activities can better be performed by a third party, an invitation to submit a tender is sent out to a number of pre-selected LSPs. Based on this invitation, the LSPs then propose a price for their services.
The subject of this paper is the reverse mode of operation, where the initiative for the contract lies with the LSP. To stress the contrast between the traditional push approach of outsourcing, and the here proposed pull approach where the service provider is the initiator of the shift of logistics activities from the shipper to the LSP, in the remainder of this paper we will refer to supplier-initiated outsourcing as insinking.
The advantage of insinking over outsourcing is that it enables LSPs to gain maximum synergetic effects by tendering for multiple shippers whose distribution networks can be merged very efficiently. We observe that there exist promising business opportunities for insinking in practice. One example is the introduction of the so-called transport-arrangements in the Dutch Randstad metropolis. In this project, a Dutch LSP offers prominent shippers in the fashion sector to perform the distribution to their shops in the city centers against very competitive tariffs. These tariffs are low because of the strong synergies the LSP can benefit from in case it replenishes multiple fashion outlets in the same city center. The Dutch branch organization for fashion companies, actively participates in this project by stimulating their members to accept the offer. Engaging in the transport-arrangements project is beneficial for the individual producers because transportation costs are reduced and customer satisfaction is likely to increase since the number of visits per shop decreases when multiple shippers make use of the transport-arrangements. As a result, trucks interrupt store personnel less frequently. Moreover, congestion in the city center will decrease as a result of the smaller number of vehicle movements. Apart from the time investments that all partners in this project are making, the financial risk rests solely with the LSP. After all, the tariff offers are based on the expectation that a certain minimum number of shippers will participate. So when only 1 or 2 shippers accept the offer, the required synergies to break even may not be attained. When the behavior of potential customers is highly unpredictable, this risk might be prohibitive for the LSP. The phenomenon is also a potential reason why initiatives in for example City Logistics, where LSPs also take the lead, sometimes fail. To resolve this issue, this paper offers a methodology for LSPs to apply insinking while eliminating this financial risk.
Shippers who are active in the same sector, such as the fashion producers in the transport-arrangements example, will sell products with roughly the same characteristics and ordering dynamics (time windows, order sizes, conditioning, etc.). This opens up possibilities for synergy, because the LSP can operate the same truck types and sometimes even the same routes to service multiple shippers. As discussed in Cruijssen et al. (2007a), the actual synergy potential then depends on the complementarity of order sizes, time windows and the precise demand locations. When such shippers are served on the same route, insinking creates a situation of so-called ‘co-opetition’ (cf. Brandenburger and Nalebuff, 1996, Zineldin, 2004). Although the shippers are competitors on their core businesses, they tacitly cooperate with each other on the non-core domain of transportation, since they agree that their products are distributed in a single shipment with their competitors’ products. Transportation, the area where the cooperation takes place, is not visible to customers. Bengtsson and Kock (2000) consider visibility for the customer as the most important characteristic for determining whether competition or cooperation should take place on a certain activity. For example, if there is cooperation on transportation activities, competition and differentiation can remain unchanged on other domains such as product prices and product assortments. Particularly in transportation and logistics, where there are almost no unique technologies, companies must often rely on applying innovative concepts such as co-opetition to achieve growth. Whereas co-opetition is already in place for some time in industries where for example Express transport is heavily used and sourced by consortia of multiple (competing) companies, it is now also quickly gaining momentum in the grocery industry. Examples of co-opetition in the consumer goods industry can be found in Bahrami, 2003, LeBlanc et al., 2007.
With co-opetition, issues of fairness and stability of the cooperation are important impediments. In particular, guaranteeing a fair allocation is essential. Mistrust about the fairness of the applied allocation rule for the savings has caused many logistics co-opetition initiatives among shippers to marginalize or disintegrate (cf. Cruijssen et al., 2007b).
In practice, a plethora of allocation rules for cooperation among shippers can be observed. Most often these are simple rules of thumb that distribute savings proportionally to a single indicator of either size or contribution to the synergy. Some examples are:
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Proportional to the total load shipped.
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Proportional to the number of customers served.
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Proportional to the transportation costs before the cooperation.
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Proportional to distance traveled for each shipper’s orders
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based on inter-drop distances of constructed joint routes,
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based on direct distances from depot to outlet.
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Proportional to the number of orders.
Because these rules are easy and transparent and since each embodies a construct that arguably represents the importance of an individual shipper to the group, they are likely to appeal to practitioners initially. However, in the long run, some participants will inevitably get frustrated since their true contribution to the group’s success is undervalued. For example, if gain sharing takes place according to the number of drop points, a certain customer firm with many end consumers in a small geographical region will get a large share of the benefits, while his de facto contribution to the attained synergy is negligible when the other participants serve only few drop points in this area.
To ensure a fair gain sharing mechanism, the true contributions of each shipper to the total gain have to be accurately quantified. The insinking approach uses these true contributions to the group’s synergy to calculate customized prices that fairly distribute the monetary savings that are attained by consolidating flows of multiple shippers. In our approach, the applied methodology is explained to the shippers and the LSP’s cost structure is deliberately made transparent.
It is illustrated above that practical rules of thumb might not always be the best choice for fair gain sharing. Our proposal is to employ solution procedures from cooperative game theory instead. Cooperative game theory models the negotiation process within a group of cooperating agents (in this case shippers) and allocates the generated savings. This field has proved capable of solving fairness issues in many fields. Some logistics related examples are: (Vertical) Supply Chain Coordination (cf. Dawande et al. (2006)), Hub-and-Spoke network formation (cf. Matsubayashi et al. (2005)), Outsourcing (cf. Elitzur and Wensley (1997)), Inventory pooling (cf. Anupindi et al., 2001, Bartholdi and Kemahlioğlu-Ziya, 2004), and Machine scheduling (Heydenreich et al. (2007)). Other sectors where game theoretical methods have been successfully applied in practice include among others: Automotive (cf. Cachon and Lariviere (2005)), Retail (cf. Sayman et al. (2002)), Telecommunication (cf. van den Nouweland et al. (1996)), Aviation (cf. Adler (2001)), and Health Care (cf. Ford et al. (2004)). Cooperating companies in these sectors benefit from game theoretical methods that objectively take into account each player’s impact within the group as a whole and produce compromise allocations that distribute the benefits of cooperation based on clear cut fairness properties. Different fairness properties are represented by well-known allocation rules such as the Shapley value (Shapley (1953)), the nucleolus (Schmeidler (1969)) and the tau-value (Tijs (1981)).
With the insinking procedure, the LSP establishes fair gain sharing by means of customized pricing. This enables the LSP to explicitly incorporate participants’ marginal contributions to the group’s synergy potential. The business opportunities offered by intelligent pricing strategies are being increasingly recognized in Marketing (cf. Desiraju and Shugan (1999)) and Psychology (cf. Hermann et al. (2004)). The advent of Information and Communication Technology (ICT) in the last decade has opened up a vast array of new pricing possibilities (cf. Dixit et al. (2005)). The most important challenge of such information enhanced pricing strategies is to be perceived by customers as fair. Perceived fairness depends on comparisons to past prices, competitor prices, and perceived cost of the product or service (cf. Bolton et al. (2003)). Although these factors come from a Business-to-Consumer setting, we hypothesize that the same constructs are relevant for the Business-to-Business situation that we consider in this paper.
An important aspect of fair pricing is the principle of dual entitlement (cf. Kahneman et al. (1986)). This means that a profit increase by the selling firm (the LSP) is only accepted when it does not harm the customer’s interest. This egalitarian principle sometimes conflicts with the utilitarian principle of cost-based pricing. Under cost-based pricing, an LSP will charge the total costs plus a ‘reasonable’ percentage. Dixit et al. (2005) argue that dissatisfaction about fairness of prices could be avoided by proper implementation and communication of price composition. Therefore, openness of information is an important aspect of insinking and, as will become clear in the next section, both the egalitarian and utilitarian principles mentioned above are satisfied. In particular, this means that no potential participants will have an incentive to provide false information, since gain sharing is conducted during the operation based on the true contribution of the participant has brought to the group.
Despite its obvious business opportunities, only few firms take full advantage of intelligent pricing. The vast majority still uses pricing strategies based on historical cost benchmarks, whereas more forward-looking and clientele-oriented pricing is likely to be more promising (cf. Noble and Gruca (1999)). Especially in the very competitive and low-margin transportation sector, smart pricing offers LSPs an excellent opportunity to gain a competitive edge.
The remainder of this paper is organized as follows. In the next section the insinking procedure for exploiting synergy in transportation will be explained and illustrated by means of a small hypothetical example. In Section 3, the applicability of the procedure is established by means of a practical example based on real-life data from the Dutch grocery transportation sector. Finally, Section 4 concludes.
Section snippets
The insinking procedure
The insinking procedure builds on customized pricing by an LSP. These prices (or: tariffs) are induced by the varying claims of shippers’ order sets on the LSP’s resources. Among other properties, order sets may differ in the number of orders, the geographical spread of the drop points, the location of the shipper’s warehouse(s), the tightness of time windows, and the average and standard deviation of the order sizes. In Cruijssen et al. (2007a) it is shown that each of these aspects has a
An example based on real-life data
Many grocery retailers are not performing well and have been facing a loss of profitability in recent years. Together with the complexity and dynamism inherent to the grocery industry, this has made it difficult for retailers to survive in isolation of their competitors (cf. Ballou et al. (2000)). There is growing empirical evidence that retailers as a result turn to co-opetive behavior to construct win–win situations together with their competitors. For example, Kotzab and Teller (2003),
Conclusions
In this paper we have introduced the so-called insinking procedure that LSPs can use to attract new customers and improve their market power. The given format minimizes the LSP’s financial risks, while making sure that it offers very competitive tariffs to each potential customer. These customized prices are based on each shipper’s actual contribution to the total synergy and accomplish a fair allocation of the monetary savings resulting from the cooperation. The procedure uses an operations
Acknowledgements
The authors thank Olli Bräysy for his helpful comments on applying the VRPTW heuristic (Bräysy et al., 2004) and the editors and referees for their helpful comments.
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