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In the context of Industry 4.0, intralogistics faces an increasingly complex and dynamic environment driven by a high level of product customisation and complex manufacturing processes. One approach to deal with these changing conditions is the decentralised and intelligent connectivity of intralogistics systems. However, wireless connectivity presents a major challenge in the industry due to strict requirements such as safety and real-time data transmission. In this context, the fifth generation of mobile communications (5G) is a promising technology to meet the requirements of safety-critical applications. Particularly, since 5G offers the possibility of establishing private 5G networks, also referred to as standalone non-public networks. Through their isolation from public networks, private 5G networks provide exclusive coverage for private organisations offering them high intrinsic network control and data security. However, 5G is still under development and is being gradually introduced in a continuous release process. This process lacks transparency regarding the performance of 5G in individual releases, complicating the successful adoption of 5G as an industrial communication. Additionally, the evaluation of 5G against the specified target performance is insufficient due to the impact of the environment and external interfering factors on 5G in the industrial environment. Therefore, this paper aims to develop a technical decision-support framework that takes a holistic approach to evaluate the practicality of 5G for intralogistics use cases by considering two fundamental stages. The first of these analyses technical parameters and characteristics of the use case to evaluate the theoretical feasibility of 5G. The second stage investigates the application's environment, which substantially impacts the practicality of 5G, for instance, the influence of surrounding materials. Finally, a case study validates the proposed framework by means of an autonomous mobile robot. As a result, the validation proves the proposed framework's applicability and shows the practicality of the autonomous mobile robot, when integrating it into a private 5G network testbed.
On the design of an urban data and modeling platform and its application to urban district analyses
(2020)
An integrated urban platform is the essential software infrastructure for smart, sustainable and resilitent city planning, operation and maintenance. Today such platforms are mostly designed to handle and analyze large and heterogeneous urban data sets from very different domains. Modeling and optimization functionalities are usually not part of the software concepts. However, such functionalities are considered crucial by the authors to develop transformation scenarios and to optimized smart city operation. An urban platform needs to handle multiple scales in the time and spatial domain, ranging from long term population and land use change to hourly or sub-hourly matching of renewable energy supply and urban energy demand.
This paper generalizes the theory of policy uncertainty with the new literature on rational inattention. First, the model demonstrates that inattention is dependent on the signal variance and the policy parameter. Second, I discover a novel trade-off showing that a policy instrument mitigates attention. Third, the policy instrument is non-linear and reciprocal to both the size and variance of the signal. The unifying theory creates new implications to economic theory and public policy alike.
Customer relationship management (CRM) is one of the most frequently adopted management tools and has received much attention in the literature. From a company-wide perspective, CRM is viewed as a complex process requiring interventions in different company areas. Previous research has already highlighted the pitfalls and failures related to a partial and incomplete view of CRM. This study advances research on CRM by investigating the impact of the relative implementation time according to which interventions are implemented in different areas (customer management, CRM technology, organizational alignment, and CRM strategy) on CRM performance. The results of the empirical study reveal that compared to other critical CRM activities, a later implementation of organizational alignment activities has a negative impact on performance. Further, our results show that CRM implementations do not equally address the areas of customer acquisition, growth, and loyalty, since this clearly depends on company objectives and also on geographical differences.
Marketing channels are among the most important elements of any value chain. This is because the bulk of a nation´s manufacturing output flows through them. The intermediaries (e.g., distributors, wholesalers, retailers) constituting marketing channels perform specific distribution functions,such as transportation, storage, sales, financing, and relationship building, better than most manufacturers. Over his distinguished career, Louis P. Bucklin investigated many questions about the structuring and functioning of marketing channels using conceptual, empirical, and microeconomics model-based methodologies. Today, the academic marketing literature contains hundreds of articles that have employed these three broad classes of methodologies to investigate issues of channel intermediaries´ interorganizational relationships, for example, power-dependence, relational outcomes, conflict and negotiations, and manufacturing firms´ channel strategy, for example, channel structure, selection, coordination and control. So far, however, there has been no review of how the three different methodologies have contributed to advancing knowledge across this set of channels research domains.