Wirtschaft (MSB)
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- Wirtschaft (MSB) (116) (remove)
Tactical planning measures for sustainable and efficient international transportation networks
(2021)
Strategic Marketing of Higher Education Institutions: Missions' and Customers' Identification
(2011)
On the Compatibility of Value at Risk, Other Risk Concepts, and Expected Utility Maximization
(1996)
Managing University-Business-Collaboration through Formalisation: The Moderating Role of Fairness
(2016)
In the so-called ecosystem economy, new platform-based business models evolve rapidly based on the prospects of digital technology. Thus far, little research has been conducted on the supply side of digital platforms which also explains the lack of empirical evidence. We develop a framework, categorise complementors, and analyse the main factors of influence for the evaluation and selection of complementors. For our analysis, we consider both industrial IoT platforms as well as financial services platforms. In addition, we use an explorative research design and conduct semi-structured interviews to contribute to this research field. Top-level managers of digi-tal platforms in both industries were interviewed as experts. In addition, the study also considered secondary data to increases the overall reliability and validity in terms of triangulation. As a result, our study reveals both a number of similarities and differences with regard to complementor management for industrial IoT- and financial services platforms.
Integrating Context-Free and Context-Dependent Attentional Mechanisms for Gestural Object Reference
(2003)
An important, often overlooked group of workers that HR managers have trouble reaching are those intentionally disconnected from personal digital devices. That is, workers in manufacturing facilities, distribution centers, secure areas, or locations where employers ban workers from bringing their own devices. We explore the engagement problem for these intentionally disconnected workers. We outline a disruptive HR strategy in these work contexts. We then focus on implementation, testing a simple digital platform prototype that can serve as an entry for existing, disruptive HR management engagement tools (e.g. chatbots, HR analytics) in these settings. Our exploratory findings suggest engagement is a problem for these workers and these simple tools can be an effective strategy to help HR managers improve engagement. We conclude that simple digital solutions aimed at engaging this underserved segment of the workforce can have disruptive yet positive effects for workers, HR managers and shareholders.
Effects on Risk Taking Resulting from Limiting the Value at Risk or the Lower Partial Moment One
(1997)
The opportunity to anticipate delivery failures, shortages or delays in company’s upstream supply chains at an early stage facilitates to take preventive countermeas-ures to mitigate potential damage. However, data-driven predictive technologies such as machine learning (ML) are rarely examined in supply chain risk management (SCRM). The purpose of the following paper is to present a framework of design principles for the application of ML in SCRM. The foundation of this framework is an action design research (ADR) project, which is performed in collaboration with the SCRM department of an automotive company. A predictive ML model is developed and evaluated in collaboration with the company. Based on the findings and observa-tions made during the project, general design principles are derived and grouped by the three interrelated elements of organisation, development and operation, which are to be considered when applying ML in SCRM. Finally, the derived elements and the corresponding design principles are discussed and justified with reference to the literature.