Sascha Bioly

Simulation der Interaktion von Elektrofahrzeugdaten und Navigationsdaten

Alternative Antriebssysteme sollen das Ende der Abhangigkeit von fossilen Ressourcen ermoglichen [1], [13], [16]. Nachdem Elektroantriebe bereits im PKW-Bereich Einzug halten, sollen sie zukunftig ihr Potenzial im Nutzfahrzeugbereich zeigen.Beispielsweise zahlt das Modell ‚Vito‘ von Mercedes-Benz zu den ersten Transportern mit Elektroantrieb und wird aktuell von Unternehmen wie beispielsweise DHL erprobt [5], [6].

Human Resource and Knowledge Management

Future innovations in logistics and supply chain management are driven by technological, regional, economic and social changes as well as sustainability and resource restrictions. They will not occur without sufficient attention for the human contribution, in particular the qualification, competence and motivation of the workforce in the logistics domain. Worldwide, about 50 million people—or the entire population of South Korea—are employed in the SCM, logistics and transportation sectors. Consequently, human resource and knowledge management plays an important role, more so when considering demographic developments (ageing, migration) and increasing globalization. Whereas in the past, many blue-collar jobs in logistics such as truck driving merely required a basic school education and rudimentary qualification levels, these jobs now require increased competences due to improved technology interaction, e.g., barcode and RFID systems, fleet management or toll and truck steering concepts and finally artificial intelligence applications. The same is true for many white-collar jobs in logistics, exemplified by the increasing number of university graduates employed in the sector. This is especially true for specific fields such as logistics information technology, contract logistics and supply chain innovation and design, which in turn leads to the question of how to assess qualitative and quantitative competence levels in the SCM and logistics sector. Such an analysis example is provided here with the Berufswertigkeit concept (reference framework for competence levels). This may lead to a new paradigm in HR and knowledge management for SCM and logistics: whereas past education was mainly driven by formal qualifications and therefore personnel groups (white-collar/blue-collar), future concepts may focus on an individual analysis of gaps and potentials based on elaborate evaluations. In addition, modern concepts like edugaming are outlined as examples for future qualification and training concepts for logistics personnel.

Logistics Dynamics and Demographic Change

Change and dynamics in logistics are interestingly driven at the same time by external as well as internal forces. This contribution outlines a big data literature review methodology to overview recognizable external changes and analyzes the interaction of one major trend—demographic change—further in order to allow for change management and adaption concepts for successful logistics. Therefore, this may be a first blueprint of how to analyze and react to specific trends in a holistic manner embedded into a context and environment of trends and changes. This may allow logistics dynamics concepts also to be possibly more sustainable in terms of applicable for a longer period of time—and not to be overcome by other trends.

Future Transport Volume and Demographic Change—An Intermodal GAMS Approach

Prognosis of future transport volumes and modal split scenarios are a research field with major implications in transport policy and business practice alike. Therefore major decision frameworks as e.g. infrastructure investments or policy concepts as for example the EU commission white book are based on expectations regarding transport volume developments. But these calculations are mainly based on transport demand and only in very limited approaches on transport supply, assuming that in the very competitive transport markets there will always be capacity for supply adjustments to demand changes. Expected demographic changes in European countries as for example Germany will probably render this paradigm invalid—as already today i.e. truck drivers are sought but not readily found. Therefore this contribution outlines a first quantitative approach in transport simulation including demographic change restrictions e.g. regarding the number of available truck drivers. Implications on the modal split are tested and reported with a cost-minimizing GAMS model in order to explore expected implications on transport markets.

Demografie und Urbanisierung in der Logistikwirtschaft

Der Beitrag diskutiert die Frage, welche Entwicklungen und Innovationen insbesondere im Schnittfeld von demografischer Entwicklung, Urbanisierung und Logistiksystemen erwartet werden konnen. Dazu werden neben den Beschreibungen der drei Bereiche insbesondere demografieabhangige Forschungsthemen der Logistik wie die Elektromobilitat oder die „neue“ City-Logistik vorgestellt und auf ihr Innovationspotenzial hin analysiert. Daraus werden Gestaltungsthesen abgeleitet: Nachhaltigkeit und Elektromobilitat hangen ins-besondere in urbanen Raumen von „added service“-Angeboten fur altere Menschen ab; interaktive „social transport networks“ auf Web 2.0-Basis werden die Stadte erobern; der stadtische Einzelhandel wird sich rund um Online-Auslieferungen neu organisieren; der urbane Raum wird weiterhin Impulsgeber fur Transport und Innovationssysteme sein.

Potenziale eines GPS-Trackingsystems

Kurzfassung Der vorliegende Artikel stellt den Ansatz eines stetigen Tracking & Tracing-Konzepts mit der Hilfe von Trackingmodulen auf der Basis von GPS vor. Zunächst wird der Stand der Technik im Bereich der Sendungsverfolgung dargestellt und die Einsatzmöglichkeiten von GPS-basiertem Tracking erörtert, um die angesprochenen Anforderungen an die Logistikdienstleister zu erfüllen. Im Anschluss wird das am Institut für Logistik- & Dienstleistungsmanagement (ild) der FOM Hochschule für Oekonomie & Management vorhandene GPS-Ortungssystem GPS.LAB vorgestellt und die Ergebnisse einer getrackten Tour abgebildet. Darauf aufbauend wird beispielhaft eine CO2- Emissionsberechnung für eine verfolgte Sendung durchgeführt, bevor es zu einem Ausblick der Forschungsaktivitäten kommt.