Jörn-Henrik Thun

Managing uncertainty – an empirical analysis of supply chain risk management in small and medium-sized enterprises

Uncertainty and the need for lean processes forces manufacturing companies to intensively deal with supply chain risk issues. The purpose of this article is the empirical investigation of supply chain risk management in small and medium-sized enterprises (SMEs). Using data from 67 manufacturing plants from the German automotive industry, differences between large-scale enterprises and SMEs are identified. After addressing the general question whether SMEs consider their supply chain as vulnerable, the key drivers of supply chain risks are analysed. Furthermore, instruments of supply chain risk management are investigated in terms of their suitability for creating a resilient supply chain by comparing SMEs with large-scale companies. Finally, this article examines existing differences with respect to how companies deal with risk. The analyses show that SMEs predominantly focus on reactive instruments that absorb risks through the creation of redundancies instead of preventing risks.

From waste to value – a system dynamics model for strategic decision-making in closed-loop supply chains

Although the field of closed-loop supply chain management has attracted a lot of attention in recent years and the management of reverse logistics processes has become a major field of supply chain management, there is still a lack of research conducting analyses using a comprehensive approach that takes the complexity of problems of reverse logistics processes into account. Hence, the purpose of this paper is to develop a model that allows an original equipment manufacturer in the electronics industry to test different value recovery strategies for business-to-business products in a closed-loop supply chain setting. For this purpose system dynamics is used because this approach enables one to capture the high complexity of reverse logistics processes and is suitable, contrary to traditional optimisation approaches, for analysing the dynamic behaviour of closed-loop supply chains comprehensively. The simulation analysis identifies leverage points for the improvement of decisions concerning reverse logistics. In particular, the simulation runs conducted highlight the high complexity and connectivity inherited with various value recovery processes. The paper contributes to a better understanding of supply chain dynamics, the impact of product backflow, and reverse logistics.

Empowering Kanban through TPS-principles – an empirical analysis of the Toyota Production System

The purpose of this paper is the empirical investigation of the Toyota Production System in order to test existing relationships as they are proposed in theory. The underlying model consists of seven factors reflecting the key practices of the Toyota Production System. Using data from 188 manufacturing plants participating in the High Performance Manufacturing research project, the models measurement characteristics were validated through confirmatory factor analysis. Path analysis of the model showed that the majority of the relationships can be confirmed. Furthermore, a comparison of mean analysis based on a conducted cluster analysis indicates that plants with a higher implementation degree of the practices of the Toyota Production System also show a higher perceived performance in terms of the key criteria of production, i.e. time, cost, quality, and flexibility.

Surplus division and investment incentives in supply chains: A biform-game analysis

In this paper, we use a biform-game approach for analyzing the impact of surplus division in supply chains on investment incentives. In the first stage of the game, firms decide non-cooperatively on investments. In the second stage, the surplus is shared according to the Shapley value. We find that all firms have inefficiently low investment incentives which, however, depend on their position in the supply chain. Cross-subsidies for investment costs can mitigate, but not eliminate the underinvestment problem. Vertical integration between at least some firms.yields efficient investments, but may nevertheless reduce the aggregated payoff of the firms. We show how the size of our effects depends on the structure of the supply chain and the efficiency of the investment technology. Various extensions demonstrate that our results are qualitatively robust.

Loading and sequencing heuristics for job scheduling on two unrelated parallel machines with long, sequence-dependent set-up times

The purpose of this paper is to develop and test intelligible heuristics for the scheduling of production orders that can easily be used in practice. Grounded in a case study, this paper examines the combined effects of assignment and sequencing heuristics on commonly used performance indicators. Discrete event simulation is used in the analysis to adequately capture the complexity found in the case study: production orders differing in many aspects, two unrelated parallel machines with varying and product-specific speed, and set-up times that depend on the (dis)similarity of successive orders. Evaluating 108 strategy–scenario combinations including the base case derived from the case study, it is found that a loading heuristic based on order quantity and scheduled capacity in combination with the shortest set-up heuristic performs best. When compared to the heuristic approach used by the case company, this strategy saves about 13.9% of total machine busy time and increases service level by 10.2%. In addition, using a reduced set of 40 production orders we are able to demonstrate that the best heuristic strategies comes close to results generated in a two-stage optimisation. The gap to optimality is only 3.1% in total busy time on average over all scenarios.