Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

THE STANCE LOGISTICS: An Attempt to Adapt Logistics Principles on Human and Inter-human Movement Behaviors

The broad span of Logistics Management encompasses control of time, place, movement, energy (efforts, labor), as well as the positioning, stance and movement of products, materials, commodities, and people. This study coins the term Stance Logistics to focus on the stance and movement of people within the range of Logistics principles. The philosophy behind this is to enhance the required sensitivity with respect to management and control of time, place, movement, motion, stance and energy in material and nonmaterial exchanges and in all types of human encounters. Stance Logistics includes not only the “on foot” (pedestrian) or “in-vehicle” (automated) movements and public behaviour in stopping, standing, and positioning, but also individual predisposition of physical and mental response, and awareness (aesthesia). This essay describes the application of the scientific principles of Logistics to the personal experiences of people. Current Logistics literature includes mostly models developed on pedestrian and evacuation movement behaviour. To the author’s knowledge, however, there is nothing documented on the issue of personal individual Logistics Stance. Behaviours, especially that of blocking other people’s ways and passages, intervening, rudeness and queue-jumping in various environmental settings have not been extensively studied, if at all, whether during walking, pausing, stopping, face-to-face encounters, standing or waiting in lines and lanes or waiting for an elevator or metro train door to open. This study seeks underlying clues to increase sensitivity and awareness of people’s movement particularly in public areas by shedding light on Logistics behaviours of people. When combined with applicable models of pedestrian movements and integrated with the general principles of Logistics, Stance Logistics can serve as an important guide to facilitate the daily activities of many people. It is believed that, this exploratory study will pave the way for further research to produce promising results on the aspects of this new concept of Stance Logistic

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (1/4)

Technical report about sustainable urban freight solutions, part 1 of

From Big Data To Knowledge – Good Practices From Industry

Recent advancements in data gathering technologies have led to the rise of a large amount of data through which useful insights and ideas can be derived. These data sets are typically too large to process using traditional data processing tools and applications and thus known in the popular press as ‘big data’. It is essential to extract the hidden meanings in the available data sets by aggregating big data into knowledge, which may then positively contribute to decision making. One way to engage in data-driven strategy is to gather contextual relevant data on specific customers, products, and situations, and determine optimised offerings that are most appealing to the target customers based on sound analytics. Corporations around the world have been increasingly applying analytics, tools and technologies to capture, manage and process such data, and derive value out of the huge volumes of data generated by individuals. The detailed intelligence on consumer behaviour, user patterns and other hidden knowledge that was not possible to derive via traditional means could now be used to facilitate important business processes such as real-time control, and demand forecasting. The aim of our research is to understand and analyse the significance and impact of big data in today’s industrial environment and identify the good practices that can help us derive useful knowledge out of this wealth of information based on content analysis of 34 firms that have initiated big data analytical projects. Our descriptive and network analysis shows that the goals of a big data initiative are extensible and highlighted the importance of data representation. We also find the data analytical techniques adopted are heavily dependent on the project goals

A Model of Adoption of AR-based Self-service Technologies: A two Country Comparison

Purpose This paper proposes a model that extends the technology acceptance model (TAM) by identifying factors that influence consumers' acceptance of augmented reality (AR) self-service technologies (AR-based SSTs) in the retail sector, resulting in the Augmented Reality in Retail Model (ARiR Model). Design/methodology/approach This study is based on an online questionnaire responded to by 284 makeup-using women from Nicaragua and the USA. It is based on an AR mobile app used to shop in retail stores. Partial least squares-structural equation modelling was used to validate the ARiR model and test the hypotheses. Findings Aesthetics and navigation are significant predictors of perceived usefulness and perceived ease of use (PEOU), and self-efficacy also explains perceived ease of use. Technology readiness and the need for personal interaction were not found to be influencing factors. A cross-cultural comparison indicated that both countries have similar overall attitudes towards AR-based SSTs. Research limitations/implications This paper provides insights into the perceived value of, and motives for customer acceptance of, AR-based SSTs, which can serve as guidelines for their future implementation. Furthermore, it validates and confirms the application of the proposed ARiR model for technology acceptance in both developed and developing countries. Practical implications The paper provides new insights for retailers on the implementation of AR at the point of sale. Originality/value The model extends the original TAM to AR and introduces five new constructs: need for personal interaction, aesthetics, navigation, self-efficacy and technology readiness. It was tested in both a developing and a developed country

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

A Tutorial on Geographic Information Systems: A Ten-year Update

This tutorial provides a foundation on geographic information systems (GIS) as they relate to and are part of the IS body of knowledge. The tutorial serves as a ten-year update on an earlier CAIS tutorial (Pick, 2004). During the decade, GIS has expanded with wider and deeper range of applications in government and industry, widespread consumer use, and an emerging importance in business schools and for IS. In this paper, we provide background information on the key ideas and concepts of GIS, spatial analysis, and latest trends and on the status and opportunities for incorporating GIS, spatial analysis, and locational decision making into IS research and in teaching in business and IS curricula

Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

Artificial Intelligence Applied to Supply Chain Management and Logistics: Systematic Literature Review

The growing impact of automation and artificial intelligence (AI) on supply chain management and logistics is remarkable. This technological advance has the potential to significantly transform the handling and transport of goods. The implementation of these technologies has boosted efficiency, predictive capabilities and the simplification of operations. However, it has also raised critical questions about AI-based decision-making. To this end, a systematic literature review was carried out, offering a comprehensive view of this phenomenon, with a specific focus on management. The aim is to provide insights that can guide future research and decision-making in the logistics and supply chain management sectors. Both the articles in this thesis and that form chapters present detailed methodologies and transparent results, reinforcing the credibility of the research for researchers and managers. This contributes to a deeper understanding of the impact of technology on logistics and supply chain management. This research offers valuable information for both academics and professionals in the logistics sector, revealing innovative solutions and strategies made possible by automation. However, continuous development requires vigilance, adaptation, foresight and a rapid problem-solving capacity. This research not only sheds light on the current panorama, but also offers a glimpse into the future of logistics in a world where artificial intelligence is set to prevail