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Free-floating e-scooter sharing is an upcoming trend in mobility, which has been spreading since 2015 in various German cities. Unlike the more scientifically explorend car sharing, the usage patterns and behaviors of e-scooter sharing customers are yet to be analyzed. This presumably discovers better ways to attract customers as well as adaptions of the business model in order to increase scooter utilization and therefore the profit of the e-scooter providers. As most of the customer's journey, from registration to scooter reservation and the ride itself, is digitally traceable, large datasets are available allowing for understanding of customers' needs and motivations. Based on these datasets of an e-scooter provider operating in a big German city we propose a customer clustering that identifies four different customer segments, which enables multiple conclusions to be drawn for business development and improving the problem-solution fit of the e-scooter sharing model.
With the digital transformation being one of the most discussed topics in the business world today, many enterprises – especially small and medium sized ones – find themselves struggling with the understanding of new digital technologies and thus the potential benefits and risks for their companies. New technologies like the Internet of Things, Blockchain or Machine Learning have great potential for businesses. However, carefully evaluating and selecting purposeful technologies – aligned to the digital strategy – is the key to success. Technologies appear, change and also vanish so rapidly in the digital age, that a proper understanding is crucial for a sustainable technological foundation. Focusing on the characteristic features of technologies, the presented approach promises to create a better technological understanding for decision makers in small and medium-sized enterprises (SMEs) in a playful manner: With a serious game that fosters insight and allays fears of digitalization.
In a time of upheaval and digitalization, new business models for companies play an important role. Decentralized power generation and energy efficiency indicators to achieve climate goals and to reduce global warming are currently forcing energy companies to develop new business models. In recent years, many methods of business model development have been introduced to create new business ideas. But what are the obstacles in implementing these business models in the energy sector to develop new business opportunities? And what challenges do companies face in this respect? To answer this question, a systematic literature review was conducted in this paper. As a result, eight categories were identified which summarise the main barriers for the implementation of new business models in the energy domain.
The energy turnaround, digitalization and decreasing revenues forces enterprises in the energy domain to develop new business models. Business models for renewable energy are compound on different logic than business models for larger scale power plants. Following a design science research approach, we examined the business models of three enterprises in the energy domain in a first step. We identified that these business models result in complex ecosystems with multiple actors and difficult relationships between them. One cause is the fast changing and complicated state regulation in Germany. In order to solve the problem, we captured together with the partners of the enterprises the requirements in a second phase. Further we developed the prototype Business Model Configurator (BMConfig) based on the e3Value Ontology on the metamodelling platform ADOxx. We demonstrate the feasibility of our approach in business model of energy efficiency service based on smart meter data.
The relevance of technology knowledge in digital transformation especially in small and mediumsized enterprises (SMEs) that are still largely dependent on physical human capital has become increasingly obvious. This is due to the rapid revolution in business environment coupled with increased living examples of firms disrupted by advancement in technological knowledge. Consequently, we find it progressively vital for SMEs to spot and mitigate both threats and take advantage of opportunities arising from digital transformation dynamism.
Our study aims at exploring the relevance of technology knowledge in SMEs for digital transformation to uncover the opportunities, roadmaps, and models that SMEs can take advantage of in the digital transformation and gain a competitive edge.
We conclude that irrespective relevance of technology knowledge for digital transformation coupled with its low costs and accessibility, SMEs are yet to realize the full potential of technological knowledge. This is mainly due to technologies appearing, changing and also vanishing so rapidly in the digital age, that gaining proper understanding without dedicated resources is utterly difficult for SMEs - making them less competitive as incumbent large firms in the market.
Small and Medium Enterprises (SMEs) which play substantial role in the development of any economy have been on the rise in the recent periods. Consequently, these enterprises are faced with a myriad of challenges which could potentially be solved through adoption of technology. Nonetheless, it has been observed that the new technological uptake among SMEs remains limited with the majority of them opting to maintain the status quo with regards to technology awareness and innovation strategies.
In a literature review, this paper explores three major dynamics curtailing adoption of new technologies by SMEs in the manufacturing: Knowledge absorptive capacity and management factors, organisational structures as well as technological awareness. Firstly, with regards to knowledge absorptive capacity and management factors, this study shows how these factors drive innovation potentials in SMEs.
Secondly, with regards to technological awareness factors, this study documents how perceived usefulness, costs, network and infrastructure, education and skills, training and attitude as well as knowledge influence adoption of new technologies among SMEs in the world. Lastly, the study concludes by analysing how organisational structures drive innovation potentials of SMEs in the wake of swift and profound technological changes in the market.
46 Prozent der Arbeitsplätze in der Automobilindustrie sind bis 2030 durch Automatisierung und Digitalisierung bedroht – die Tätigkeiten werden dann nicht mehr von Menschen, sondern von intelligenten Robotern und Systemen erledigt. Das ist das zentrale Ergebnis unserer Studie „Digitale Transformation – Der Einfluss der Digitalisierung auf die Workforce in der Automobilindustrie“, die wir gemeinsam mit dem Herman Hollerith Lehr- und Forschungszentrum an der Hochschule Reutlingen erstellt haben.
Decentralized energy systems are characterized by an ad hoc planing. The missing integration of energy objectives into business strategy creates difficulties resulting in inefficient energy architectures and decisions. Practice-proven methods such as balanced scorecard, enterprise architecture management and value network approach supports the transformation path towards an effective decentralized system. The methods are evaluated based on a case study. Managing multi-dimensionality, high complexity and multiple actors are the main drivers for an effective and efficient energy management system. The underlying basis to gain the positive impacts of these methods on decentralized corporate energy systems is digitization of energy data and processes.
Managing decentralized corporate energy systems is a challenging task for enterprises. However, the integration of energy objectives into business strategy creates difficulties resulting in inefficient decisions. To improve this, practice-proven methods such as the balanced scorecard and enterprise architecture management are transferred to the energy domain. The methods are evaluated based on a case study. Managing multi-dimensionality and high complexity are the main drivers for an effective and efficient energy management system. Both methods show a positive impact on managing decentralized corporate energy systems and are adaptable to the energy domain.
War Anfang des Jahrtausends der Wertbeitrag der IT zum Unternehmenserfolg noch umstritten, so negieren diesen heute nur noch die wenigsten Geschäftsführer. Wie Wertschöpfung durch Alignment von Unternehmens- und IT-Strategie mittels passender IT-Architekturen erzeugt wird, scheint für kleine und mittlere Unternehmen (KMU) verschiedenster Branchen noch immer mysteriös. Besonders fatal ist diese Lücke in den KMU der Kultur- und Kreativwirtschaft, die klassischen Industriesektoren als Innovationslieferanten dienen. An dieser Stelle setzt der vorliegende Bericht an. Er baut auf den Ergebnissen des Forschungsprojekts KonfIT-SSC auf, das in den vergangenen Jahren die Möglichkeit erforschte, mit Produktkonfiguratoren den „strategical fit“ zwischen Business und IT-Strukturen zu bewerkstelligen. Die zentrale Herausforderung bei diesem Vorhaben war es, Daten über Informationssystemstrukturen und die sie bestimmenden Ökosysteme so zu erheben, dass sie einer formalen Modellierung von Regelwerken und der Konfiguration von Geschäftsarchitekturen zugänglich werden. Der vorliegende Bericht liefert Antworten auf die Fragen, wie sich passende IT-Service Strategien für Unternehmen der Kultur- und Kreativwirtschaft erreichen lassen, welchen Beitrag Produktkonfiguratoren dabei liefern können und mit welchen Methoden sich Daten gewinnen lassen, um generische IT-Architekturen für KMU der Kreativbranche definieren zu können. Dabei werden im Verlauf neben den Antworten auf die wissenschaftlichen Fragestellungen auch die Ergebnisse der einzelnen Schritte zur Lösung der Aufgabenstellung in Form eines handelsüblichen Konfigurators dokumentiert. Als Methoden im Rahmen des Vorgehens kommen dabei zur Datengewinnung ein klassischer Literature Review, eine Online-Befragung sowie fünf Fallstudien in kleinen und mittleren Unternehmen der Werbebranche, aber auch Interviews mit Experten zum Einsatz. Bei der Analyse der Daten werden die Modellierung von Wertschöpfungsnetzen (e3value und i*), aber auch die Referenzmodellierung von Unternehmensarchitekturen verwendet. Abschließend wird das Vorgehen bei der Entwicklung der Konfigurationsmodelle (Regelwerke) und der Implementierung erläutert.
