This study tests whether a simplified neural-network computational model can make routing decisions in a logistics facility more efficiently than five ׳intelligent׳ routing heuristics from the logistics literature. The experiment uses a real-world simulation scenario based on the Hamburg Harbor Car Terminal, a logistic site faced with managing approximately 46,500 car-routing decisions on a yearly basis. The simulation environment has been built based on a data set provided by the Terminal operator to reflect a real-world case. The simulation results show that the percent-improvement of the neural-net model׳s performance is 48% better than that of the best routing heuristic tested in previous studies. To test the applicability of the method with more complex logistic scenarios, we relaxed the sequence constraints for routing in a subsequent simulations study. If logistic complexity in terms of more freedom in decision-making is increased, the neural net model׳s percent-improvement performance of routing decisions is around three times better than the best-performing heuristic.

In the idea contest for technological solutions, cost-efficient processes and customer-oriented mobility services for the usage of electric mobility the phase of a realistic estimation concerning the threats and opportunities can be identified with the help of the hype cycle. Therefore, the research question arises about the steps which lead towards the slope of enlightenment. In this regard, the paper intends to discuss the questions in the following categories for getting an extensive overview: How did the market structures change? How did the business models change? How will the service strategies change? As a result, the paper contributes to the research about future concepts of mobility by providing an overview of different strategic perspectives.

Through the competition over technological possibilities, cost-efficient realizations and innovative concepts for the usage of Electric Mobility the automotive industry stands at a strategic crossroad. Hereby, the question is to a lesser extent whether new driving technologies will penetrate the market. Moreover, it is the question of substance, which determinants for the diffusion process of Electric Mobility will become apparent; what are enablers and disablers and what are their resulting strategic implications? For this, the article intends to discuss—inter alia—the following questions: How will the competing forces position themselves? Which potentials for the positioning and standing out on the market will arise? How will the structures and processes of the global value creation networks change? As a result, it will be assumed that an increased complexity will only lead to bounded changes in the strategic behavior in the long-term so that the “rules of the game” will stay mostly the same.

Companies involved in the electric mobility sector such as car manufacturers, battery producers or infrastructure providers are confronted with risks of technological and institutional path dependencies and resulting lock-in situations. One approach that might enable these companies to avoid and cope with such lock-ins is the idea of knowledge-based dynamic capabilities. Accordingly, companies need to be able to replicate their organizational resources through knowledge codification and transfer, and to reconfigure their resources through knowledge abstraction and absorption. This chapter reveals exemplary effects that result from such knowledge-based activities on the abilities to maintain or increase their technological and strategic flexibility. Accordingly, companies in the electric mobility sector have e.g. the chance to reduce risks of path dependent developments through transferring their knowledge internally and between each other in order to trigger a combination of knowledge resources, which in turn increase the varieties of their decision alternatives.

This paper aims for a logical deductive literature-based generation of hypotheses regarding the robustness of complex adaptive logistics systems (CALS) based on self-healing processes. Therefore, the increasing necessity for supply networks to gain and maintain robustness in order to ensure a high reliability of their logistics services is shown. Additionally, the concept of CALS is presented in order to deduce the outcomes that result from a technology-based increase of the CALS characteristics. Finally, a set of hypotheses is developed that link the outcomes of CALS with the evolvement of self-healing processes in supply networks in order to deduce implications for their robustness. Hence, a starting point for further empirical and simulation-based research is presented, on which basis an operationalization of the outcomes of CALS and their self-healing abilities can be conducted.

Based on the introductory chapter, five elements can be distinguished that are all part of the concept of SCSM. First at all (1), since various concepts already exist in the literature, the necessity of developing a new concept for the management of risk and uncertainty factors in company spanning supply chains has to be emphasized. Then (2), risk and uncertainty factors threatening a supply chain’s safety have to be identified and analyzed. Following this, adequate action measures have to be taken: Preventive action measures aim at eliminating the source of risk and uncertainty factors and therefore make contribution to a supply chain’s protection (3). Reactive action measures, by contrast, aim at minimizing the detrimental impact resulting from risk and uncertainty factors that already have occurred and therefore make contribution to a supply chain’s resilience (4). Finally, a management process has to be implemented enabling a supply chain to improve it’s overall preparedness (5).

Manufacturing systems are subject to the risk of path dependencies and resulting lock- in situations. In order to avoid and cope with them, they need manufacturing flexibilities. A management approach that triggers strategic flexibilities is the concept of dynamic capabilities. Therefore, a knowledge-based conceptualization of dynamic capabilities—i.e. knowledge codification, transfer, abstraction and absorption—is taken and analyzed regarding its contributions and limitations to flexibilize manufacturing systems on the basic or component as well as the system and the aggregated level.

Logistics systems have to cope with different challenges like unforeseeable machine failures leading to an increase of dynamics and complexity. Accordingly, a system’s robustness (i.e. the ability to resist against a number of endangering environmental influences and the ability to restore its operational reliability after being damaged) might be decreased. Thus, this paper aims to answer the following research question: How do selected exemplarily heuristics (Minimum Queue-length Estimation, Minimum Cumulative Processing, Simple Rule-based, Holonic, Ant Pheromone, and Neural Net) contribute to a real world Hamburg Harbour Car Terminal’s robustness? Thereby, the research focus in this investigation is on throughput time. As a main result it could be shown that all selected heuristics could contribute to a positive development of the system’s robustness in case of machine failures. Thus, from a practical view potentials for the improvement of real-world scenarios might be assumed.

The production of electric mobility can be considered as a network of networks, because of the internal linkages of industry-wide value creation chains, the international linkages of suppliers with several car manufacturers and the international linkages between car manufacturers due to different forms of cooperation. As a result, a classification approach for the structural relations is needed to better analyze e.g. the robustness of efficiency of cooperative partnerships, because these are not adequately formalized in the logistics and supply chain management literature. For this reason, the paper introduces a systematic classification approach based on the methodology of complex network sciences and a three-dimensional matrix notation for the production of electric vehicles.

Der Paradigmenwechsel vom Verbrennungs- hin zum Elektromotor stellt für die Akteure in den internationalen Wertschöpfungsnetzwerken der Automobilindustrie eine große Herausforderung dar [1]. Diese besteht zum Beispiel in der strategischen Bewertung der Ambidextrie (d. h. Management der Beidhändigkeit) beim Übergang zur Elektromobilität [2] und ergibt sich z. B. aus der Frage nach den Marktein- und -austritten von Akteuren in den Markt für Elektromobilitätstechnologien und damit der Dynamik – bestimmt durch die Strukturen und Prozesse – und ihrer Turbulenz in Wertschöpfungsnetzwerken [3]. Ein genaues Verständnis der Dynamik ist aus diesem Grund wichtig für das Management, weil bspw. Kooperationen in den Industrienetzwerken entlang verschiedener Wertschöpfungsstufen die Prozesse effizienter gestalten und damit das eigene Leistungsspektrum erweitern lassen. Daraus ergibt sich die Frage der Adaption von Prozessen und wie diese durch das gegenseitige Lernen zu Wertschöpfungsvorteilen für jedes einzelnen Unternehmen führen können [4]. Damit bedarf es zur strategischen Bewertung der Ambidextrie und dem Markterfolg der Elektromobilität einer Analyse der Dynamik in internationalen Wertschöpfungsnetzwerken.

Companies face a variety of risks resulting from cost reduction strategies, rationalization measures, global sourcing, and outsourcing activities. Due to the large number of actors involved, extremely