Wirtschaft (MSB)
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The financial services sector is undergoing a digital transformation. But the emerging picture is very different from the innovation-driven revolution that was initially expected.
Due to the variety of challenges, banks and mostly young financial technology companies (fintechs) are increasingly cooperating instead of competing. Yet despite the rapidly growing importance of bank-fintech cooperation, there is still a lack of empirical evidence on the determinants. We use an explorative research design and conduct semi-structured interviews to contribute to this research field. Our findings illustrate that banks are primarily concerned with access to innovation, while fintechs mainly focus on balancing their resource constraints.
An- und Auslaufmanagement
(2008)
Attainment of higher quality for innovative ideas by systematic utilisation of external sources
(2008)
Beschaffungsprozesse - Aufgaben und methodische Unterstützung im Zeitalter der Internetökonomie.
(2003)
Collective dynamic capabilities in innovation ecosystems - an analysis of the multi-actor process
(2023)
Complementor relationship management for Data-driven B2B platforms: Towards a Holistic approach
(2021)
In the so-called ecosystem economy, new platform-based business models evolve rapidly based on the prospects of digital technology. Especially in the B2B context, data-driven platforms are highly relevant. Thus far, little research has been conducted on the supply side of data-driven platforms and especially on service providers, the so-called complementors. Therefore, this paper offers insights into the various facets of complementor relationship management (CoRM). The paper aims to develop a framework for the management of complementors of data-driven B2B platforms. For empirical evidence, we draw on 14 semi-structured expert interviews with platform managers and complementors. The findings outline two big areas of CoRM and discuss distinct characteristics of partner management and technology management. For partner management the differentiation into open and closed platform needs to be taken into account for complementor relationship management. Moreover, our study reveals the key factors of technology management which lead from platform infrastructure to digital applications like digital twins or predictive maintenance.
Particularly in times of disruptive changes, companies need an early warning system for risks in their supply chains to gain relevant information in a timely manner. Furthermore, they require suitable action plans and strategies to help react when a risk occurs. Based on an in-depth case study at an automotive parts supplier producing electronic systems and lighting components, this paper develops a holistic supply chain risk management framework. After investigating the specific supply chain risks to support critical parts management, standardised processes and procedures are developed to improve the preventive supply chain risk strategy cycle, as well as the reactive critical parts management cycle.
Buying firms lack transparency about the supplier relationships in their networks. The applica-tion of dedicated tools such as Supply Network Mapping (SNM) can help to visualize and analyze these relationships. However, the impact of such tools on the purchasing performance has not been explored yet. Moreover, companies with different competitive strategies might have different motivations to use these tools. Therefore, this paper tests the impact of supplier relationship information and SNM on the purchasing performance on a large sample of 624 purchasers. A multi-group analysis in structural equation modeling estimates the impact of a cost leadership versus a differentiation strategy on cost saving and innovation performance. We show that information quality and SNM indeed improve the purchasing performance. Moreover, cost leaders use SNM if they know their supplier relationships with sub-suppliers, while innovation leaders use it if they know their supplier relationships with other customers. Hence, our results prove the usefulness of the SNM tool and give recommendations for its use depending on a company’s competitive strategy.
To increase maturity within purchasing and supply management (PSM), future purchasing skills are needed based on the technological development towards Industry 4.0. Past research, eg, the work of Bals, Schulze, Kelly, and Stek (2019), started to address this issue based on literature review and interview studies. However, a detailed description of these skills is missing. Utilizing a real-time Delhi study with 45 experts within the PSM field, nine future purchasing skills have been elaborated. Identified skills connect to the maturing and emerging technologies within purchasing and provide a guideline towards Industry 4.0 in purchasing based on a human-centric perspective.
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.