Physical distribution networks are integral parts of modern supply chains. When faced with a question of which node in a network is more important, cost immediately jumps to mind. However, in a world of uncertainty, there are other significant factors which should be considered when trying to answer such a question. The integrity of a network, as well as its robustness are factors that we consider, in making a judgement of importance. We develop algorithms to measure several properties of a class of networks. To accelerate the optimization of multiple related linear programs, we develop a modification of the revised simplex method, which exploits several key aspects to gain efficiency. We combine these algorithms and methods, to give rankings of the relative importance of nodes in networks. In order to better understand the usefulness of our method, we analyse the effect parameter changes have on the relative importance of nodes. We present a large, realistic network, whose nodes we rank in importance. We then vary the network's parameters and observe the impact of each change.

Risk management is one of the critical issues in supply chain management. Supply chain disruptions negatively impact on the performance and the business continuity of a firm, and the disruptions should be managed proactively if possible. One of the approaches for supply disruption management is to raise the level of inventory: supply disruptions can be reduced by simply increasing the safety stock level. However, inventory costs will be increased at the same time. Therefore it is assumed that having extra safety stock when and where needed is better than keeping a high safety stock all of the time. In this thesis, the concept of dynamic inventory management by supplier behavior monitoring is suggested and explored. Key to the concept is the assumption that out-of-control situations at a supplier can be causal triggers for stockouts, and that these triggers can be potentially predicted by using statistical monitoring tools. In the suggested approach, the statistical process control approach of using run tests is employed to monitor and evaluate the supplier behavior. The supplier’s yield rate is monitored as the performance measure, and the receiver’s safety stock level is increased when the supplier’s performance is detected to be potentially out-of-control (or about to reach an out-of-control situation). The simulation results under different yield rates indicate that stockouts can be reduced by monitoring the supplier behavior and dynamically adjusting inventory policy when production capacity is relatively loose and enough variability can be seen in the performance measure.

This thesis studies the influence of horizontal competition on supply chain performance. Unlike most of the existing literature which focuses on horizontal competition between echelon levels, we look at both the supply chain and the individual company??s performance with the presence of supply chain to supply chain competition. Specifically, this thesis is composed of three individual research papers. The first paper deals with chain-to-chain horizontal competition and considers price competition among an arbitrary number of supply chains by comparing two cases. In the first case each supply chain is vertically integrated, while in the second, decentralised, case the manufacturers and retailers act independently. We explore the effect of varying the level of price competition on the profitts of the industry participants and demonstrate the important role played by the spread of underlying market shares. The coefficient of variation of these market shares determines whether decentralised supply chains can outperform integrated supply chains with an appropriate level of competition. The second and third papers focus on in-chain horizontal competition with capacity constraints. In the second paper, we look at a supply chain with one manufacturer and two downstream retailers. Based on total capacity available, the manufacturer needs to find ways to best use the capacity by determining whether or not to release the capacity information to retailers. The third paper looks at competition in a more complicated supply chain structure. A retailer buys three brands of products from two manufacturers. One manufacturer produces both branded and private label products, and the other one manufactures a branded product only. With our model, we are able to determine the profits of each supply chain agent. At the end of the paper, we use data from the Australian milk industry and discuss a problem in which a manufacturer needs to decide how to allocate capacity between the national brand and the private label when there is a capacity shortage.

Doctor of Philosophy / Buyer-supplier relationships have been increasingly considered a critical part of contemporary supply chain management. In response to dynamic and unpredictable market changes, buyers and suppliers enter into cooperative relationships to pursue individual goals and joint goals for better economic and non-economic performance of the supply chain. On the other hand, cooperation between channel members is surrounded by uncertainty, which can create a detrimental impact on the performance of a supply chain. Previous research has focused on various aspects of uncertainty that could affect supply chain member behaviour. The present research contends that relationship behavioural factors play an important role in increasing or mitigating channel members’ perceived uncertainty in their supply or purchase decision-making. Specifically, the purpose of this research is to investigate the impact of retailer-supplier cooperation and retailer/supplier’s decision-making uncertainty (DMU) on retail supply chain performance from the perspectives of both the retailer and the supplier. A holistic model was developed as the theoretical framework for this conceptualisation. A sample of 202 retailers and 64 suppliers in the sporting goods retail business in Taiwan was used to separately test a number of hypothesised relationships by using structural equation modelling (SEM). The findings indicate that both cooperation and DMU are the key determinants of retail supply chain performance, including financial performance and non-financial performance (i.e., supply flexibility and customer service). Financial performance is positively affected by retailer-supplier cooperation and negatively affected by DMU in both the retailer model and the supplier model. The five dimensions of retailer-supplier cooperation (i.e. trust, guanxi, dependence, coercive power and non-coercive power) have significant effects on cooperation. However, apart from guanxi with the retailer/supplier, neither other relationship dimensions nor retailer-supplier cooperation have any influence on retailer’s DMU or supplier’s DMU. The results also indicate that differences and similarities exist across retailers and suppliers with respect to the effects of several relationship dimensions on cooperation and uncertainty. 2 The holistic empirical model developed for this research contributes further to understanding the links, which have been lacking in the extant channel relationship literature and supply chain management literature, between buyer-supplier relationships, DMU, and supply chain performance. The findings that a retailer/supplier’s DMU can erode the performance of a supply chain in various aspects highlight the need for improvement in some areas of supply chain efficiency and effectiveness, through cooperation-enhancing actions between the retailer and the supplier. From a managerial perspective, the performance improvement in the supply chain, in turn, will motivate more reciprocal commitment and efforts from the retailer and the supplier to maintain their working relationship. As such, mutual trust and enriched guanxi, dependence and non-coercive power help both the retailer and the supplier to have less uncertainty in their purchase/supply decision-making process. It creates a win-win position for both parties in the supply chain.

Zugl.: München, Univ., Diss., 2005

Zugl.: Darmstadt, Techn. Univ., Diss., 2005

Zugl.: Cranfield, Univ., Diss., 2006

Zugl.: Köln, Univ., Diss., 2005 u.d.T.: Poluha, Rolf G.: Analyse der Supply Chain von Unternehmen mittels des Supply Chain Operations Reference (SCOR)-Modells

Zugl.: Kassel, Univ., Diss., 2005

Zugl.: Köln, Univ., Diss., 2005 u.d.T.: Poluha, Rolf G.: Analyse der Supply Chain von Unternehmen mittels des Supply Chain Operations Reference (SCOR)-Modells