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This paper focusses on effective teaching and learning methods in the context of a larger project that aims to align objectives in higher education with employer requirements in the field of purchasing and supply management (PSM). The reason is that little is known about which specific skills and competencies of PSM professionals are needed outside academia and which learning objective higher education should incorporate to meet the practical PSM requirements of firms and organisations. Practice as well as literature share the understanding that PSM professionals need a well-balanced mixture of knowledge and soft-skills: the merely explicit know-what (codified knowledge), know-why (theory), know-how (method) and inter- & intrapersonal soft skills.
Beyond managing research partnerships: Partnered research as an integrated methodological approach
(2018)
Disruption, Machine Learning, Internet of Things, Augmented Reality, Industry 4.0 and Rapid Prototyping are just a selection of the buzzwords that come up in connection with the rapid changes in the professional world and society brought about by digitalisation. As frequently occurs when buzzwords are used, their exact meaning is unknown, or remains unquestioned, but the use of them is nevertheless excessive. In this way, the buzzword ‘digital native’ assumes that an entire generation has a command of digital skills simply because they were born into this world and use digital media naturally. Which skills profiles this generation, and therefore a majority of today’s students, actually command, remains vague however, and is rarely explored systematically. The same is true of the specific formulation of necessary skills profiles in the digital world for higher education graduates. In the debate around higher education institutions, the description of the swift digital transition (with or without buzzwords) is not usually followed by a revision of existing curricula. This article describes strategic considerations for a better fit between the skills demanded of students and the challenges of the digital world.
Controlling
(2018)
Das Buch erläutert unter dem Oberbegriff digitales Unternehmen die unterschiedlichen Entwicklungen, die für ein Unternehmen im Bereich der digitalen Transformation von Bedeutung sind. Hierzu wird ein Unternehmen in zehn einzelne Elemente wie beispielsweise Geschäftsprozesse, Produkte, Daten, Mitarbeiter, Geschäftsmodell unterteilt. Diese stellen die Eckpfeiler des digitalen Unternehmens dar. Für jedes Element wird die digitale Transformation anhand von Reifegrad-Modellen erklärt, auf deren Basis dann Entscheidungen für die Digitalisierungsschwerpunkte in Unternehmen getroffen werden können. Insbesondere wird herausgestellt, welche Stufen der Transformation tatsächlich neu und welche schon seit vielen Jahren erreicht sind. Dabei werden die oben aufgelisteten Schlagworte eingeordnet und erläutert. Auf diese Weise soll die digitale Transformation greifbar gemacht und konkretisiert werden.
Methoden zur Überwachung und Steuerung von Materialflüssen in einem Produktions- oder Logistiksystem sollen Ziele wie niedrige Kosten und kurze Durchlaufzeiten unterstützen. Die Steuerungsprinzipien der Lean Production zielen auf dezentrale, bedarfsorientierte Selbstorganisation der Prozesse, zum Beispiel in einem Kanban-Regelkreis. Die Ansätze der Industrie 4.0 setzen auf digitale Vernetzung von Maschinen, Produkten und Mitarbeitern sowie den Einsatz von Sensorik. Welcher Steuerungsansatz passt zu welchem Produktportfolio? Lassen sich die Ansätze kombinieren – schlank durch Digitalisierung? Das Crossroads-Modell erklärt anschaulich die Unterschiede der Steuerungsansätze und leitet konkrete Handlungsempfehlungen für die Unternehmenspraxis ab.
How do they do it? Understanding business model innovation in the context of disruptive innovation
(2018)
External sources of knowledge have become a necessary extension to internal innovation activities (Monteiro, Mol and Birkinshaw, 2017; Rosenkopf and Nerkar, 2001). Collaborations with customers, suppliers, universities or even competitors are a promising way to extend the own knowledge base in order to increase the firm´s innovativeness (Felin and Zenger, 2014; Laursen and Salter, 2006). onsidering this potential set of external partners, suppliers seem to have the largest impact on product innovation (Un, Cuervo-Cazurra and Asakawa, 2010). Yet, suppliers’ innovative potential is limited as described in a case study by Gassmann, Zeschky, Wolff, and Stahl (2010), which further shows how a new venture supplier, commonly referred to as “startup”, has succeed at providing a truly innovative idea (a haptic feedback control device for automobiles). Therefore, startups as a specific knowledge provider have received growing attention (Weiblen and Chesbrough, 2015; Zaremba, Bode and Wagner, 2016). By collaborating with startups, corporations hope to benefit from the startups´ entrepreneurial characteristics, such as alertness, creativity, flexibility and willingness to take risks (Audretsch, Segarra and Teruel, 2014; Criscuolo, Nicolaou and Salter, 2012; Marion, Friar and Simpson, 2012).
Startups have the potential to transform industries as they follow partly divergent business strategies and have the ability to develop new innovative products. The evolving fields of digitalization, sustainability and urbanization highlight the direction of change. Due to enormous time pressure and lack of knowledge, corporations rely heavily on external sources of knowledge to increase innovativeness. Therein, startups take a special role. Joint R&D projects, investments or strategic buyer-supplier agreements with startups grant corporations access to their innovative technologies. This paper gives insights into the organization of search processes to identify innovative startups and highlights approaches to initiate collaborations. Therefore, a multiple-case study among automotive OEMs and suppliers was conducted. The research ends with organizational structures, an identification process, and various instruments developed for the identification of startup innovations. Furthermore, propositions are made for a successful collaboration between startups and established corporations, displaying the role of purchasing in startup management, the need to take fast decisions, secure technical support by experts within their organization and build strong relationships with partners within their supply chain and new partners, as for example venture capitalists.
Investitionscontrolling
(2018)
Der Abschlussbericht fasst die Ergebnisse des Forschungs- und Entwicklungsprojektes 2017/2018 im Studiengang Master of Science Wirtschaftsinformatik (FH Münster) zur Themenstellung "IoT trifft Blockchain" zusammen. Ausgehend von der entwickelten Vision eines „digitalen Scheckheftes“, das die Nutzungsdaten von Fahrzeugen und industriellen Anlagen fälschungssicher erfasst und diese für cloud-basierte Analysen bereitstellt, wurden folgende Fragestellungen betrachtet: - Wie lassen sich personenbezogene Daten in einer öffentlichen Blockchain ablegen und Zugriffsrechte hierauf individuell steuern? - Wie lassen sich Firmware-Updates für IoT-Geräte durch den Einsatz einer Blockchain und eines dezentralen Dateisystems besser schützen? - Welcher Ansatz eignet sich, um erfasste Maschinendaten redundant in verteil-ten Edge Devices zu sichern? - Welche Vor- und Nachteile hat die Inhouse-Verarbeitung gegenüber einer externen IoT-Cloud-Lösung? Wie lassen sich Inhouse-Lösungen in die Angebote von Cloud-Anbietern migrieren? - Welche Möglichkeiten zur Integration und Verarbeitung von IoT-Daten bieten die IoT-Plattformen Amazon Web Services und Microsoft Azure? Wie grenzen sich diese voneinander ab? Die Ergebnisse der Untersuchungen wurden in Form von eigenständigen Beiträgen verfasst und in diesem Abschlussbericht zusammengetragen.
Globalization, digitalization and increasingly shortened lifecycles of consumer and business goods require companies to be continuously innovative. Under these domains of innovation, disruptive innovation has developed as a popular term amongst scholars and practitioners alike (Christensen, Raynor, & McDonald, 2015). In fact, the concept of disruptive technolo-gies was introduced to explain the failure of incumbent businesses in times of change (Bower & Christensen, 1995). Later, research broadened the concept towards disruptive innovations thereby going beyond technologies alone (Yu & Hang, 2010). Indeed, recent literature stresses the embracing business model that needs to be designed appropriately to make use of the technology and push it forward in the process of disruption. Subse-quently, current research concludes that disruption in its core is a “business model problem, not a technology problem” (Christensen, 2006).
Despite the recognition of the relevance of a firm’s business model for disruption, a clarifi-cation of the business model concept in the disruptive innovation process appears to be necessary in two dimensions. First, there is only limited knowledge regarding the actual design of (potential) disruptive business models. Second, from a dynamic perspective, less is known about how organizations manage the process of disruptive innovation until their business model yields a disruptive effect in the market.
The PhD research project aims at shedding light on the role of the firm’s business model in regard to the concept of disruptive innovation. Insights from this research project will not only add to a deeper understanding of disruptive innovation from a theoretical perspective but also deliver guidance for managers facing an increasingly changing environment.