TY  - CHAP
A1  - Buchholz, Wolfgang
A1  - Meiners, Daniel
T1  - Attainment of higher quality for innovative ideas by systematic utilisation of external sources
T2  - Attainment of higher quality for innovative ideas by systematic utilisation of external sources
Y1  - 2008
CY  - Hamburg
ER  - 
TY  - CHAP
A1  - Buchholz, Wolfgang
T1  - Borderless business - Bridging the gaps between fairly contrastive management concepts
T2  - Baaken, T./Teczke, J. [Edit.]: Managing Disruption and Destabilisation
Y1  - 2014
SN  - 978-3-938137-49-9
SP  - 143
EP  - 156
PB  - International Management Foundation
CY  - Cracow
ER  - 
TY  - CHAP
A1  - Engelking, Bastian
A1  - Buchholz, Wolfgang
A1  - Köhne, Frank
T1  - Design Principles for the Application of Machine Learning in Supply Chain Risk Management: An Action Design Research Approach
T2  - Supply Management Research / Ed. Christoph Bode
N2  - 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.
Y1  - 2020
SP  - 1
EP  - 28
PB  - Springer
CY  - Berlin
ER  - 
TY  - CHAP
A1  - Buchholz, Wolfgang
A1  - De Bie, Holger
T1  - Managing the Supply-side of Digital  Platforms: Framework, Categorisation  and Selection of Complementors for  Industrial IoT- and Financial Services Platforms
T2  - Supply Management Research: Aktuelle Forschungsergebnisse 2021 (Advanced Studies in Supply Management) / Hrsg. Christof Bode
N2  - 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.
Y1  - 2021
SN  - 978-3-658-35448-0
U6  - http://dx.doi.org/10.1007/978-3-658-35449-7
SP  - 233
EP  - 256
PB  - Springer
CY  - Berlin
ER  -