TY - CHAP A1 - Kellner, Florian A1 - Schroder, Nadine T1 - Location Planning & Analysis Using Uncertain Data T2 - 2021 International Conference on Decision Aid Sciences and Application (DASA), 07-08 December 2021, Sakheer, Bahrain N2 - In today's big data era, a humongous amount of data are collected from various sources. In many cases, these data are incomplete, imprecise, and uncertain. An illustrative example is the OpenStreetMap project, where users all over the world contribute data on a more or less precise and complete level. This research shows whether these data are suited to support management decisions. A real-world example demonstrates the extent to which location decisions of a fast-food restaurant chain can be reproduced using techniques from the field of advanced analytics. The problem deals with classifying potential locations and comparing the predicted locations with the actual ones. The data used for this example are retrieved from the OpenStreetMap project. We find that the OpenStreetMap data are generally suitable for predicting location decisions. However, the choice of the data analytics technique is crucial. In our illustrative example case, boosted trees resulted in the best forecast, thereby outperforming neural networks, classic trees, and logit models. Y1 - 2021 SN - 978-1-6654-1634-4 U6 - https://doi.org/10.1109/DASA53625.2021.9682323 SP - 720 EP - 723 PB - IEEE CY - Piscataway, NJ ER - TY - CHAP A1 - Saßmannshausen, Sean Patrick ED - Faltermeier, Johann Fabian ED - Justus, Xenia T1 - Unternehmertum als Schlüssel der sozio-ökonomischen Entwicklung T2 - Entrepreneurship & Intrapreneurship - Same or Different? 04th and 5th of April 2019, Regensburg N2 - Vor dem Hintergrund von Innovationsdruck und drohenden Strukturbrüchen gewinnt das „Unternehmertum in der Unternehmung“ (kurz Intrapreneurship) zunehmend an Bedeutung. Diese Teildisziplin erklärt unternehmerisch denkende und innovationsbefähigte Mitarbeiterinnen und Mitarbeiter zum Objekt der Entrepreneurship-Forschung. Doch wie lassen sich Entrepreneurship und Intrapreneurship differenzieren? Und wo steht die Entre- und Intrapreneurship-Lehre heute? Und wie kann unternehmerisches Denken und Handeln an Hochschulen und in der Praxis gefördert werden? Wo stehen dabei die Hochschulen und Unternehmen in unserer Region? Y1 - 2019 SN - 978-3-942303-86-6 SP - 3 EP - 14 PB - RAM-Verlag CY - Lüdenscheid ER - TY - CHAP A1 - Saßmannshausen, Sean Patrick A1 - Voigt, Wolfgang A1 - Ojeda Moreno, German Alexander ED - Faltermeier, Johann Fabian ED - Justus, Xenia T1 - Digital Entrepreneurship Education – Verbundprojekt Grow4Digital im Donau-Naab-Regen-Dreieck T2 - Entrepreneurship & Intrapreneurship: Same or Different? Konferenzband N2 - Der durch die Digitalisierung entstehende Struckturwandel bringt neue Herausforderungen mit sich, die es global und insbesondere regional zu bewältigen gilt. Innovative Lösungen sollen durch Entrepreneure und Intrapreneure vorangetrieben werden. Im Rahmen des Verbundprojekts Grow4Digital entstehen an vier ostbayerischen Hochschulen (Ostbayerische Technische Hochschule Regensburg, Ostbayerische Technische Hochschule Amberg-Weiden, Universität Regensburg und Technische Hochschule Deggendorf) neue Studienangebote in der Digital Entrepreneurship Education für eingeschriebene Vollzeitstudierende, hochschulexterne Personen und Masterstudierende. Durch die Konzeption einer Hochschulkooperation im Verbund lassen sich Interessenten in der Region mit einem fachlich breiten Studienangebot erreichen. Dieses Angebot könnten die beteiligten Partnerhochschulen in diesem Umfang alleine nicht anbieten. Die Hochschulen richten sich an den Anforderungen für eine Hochschulqualifizierung der Zukunft aus, um auch den Anforderungen der Wirtschaft und einer sich wandelnden Gesellschaft gerecht zu werden. KW - Digital Entrepreneurship KW - Entrepreneur KW - Intrapreneur KW - Gründungsqualifikation KW - Gründungssensibilisierung KW - Gründungsunterstützung KW - Innovation KW - Grow4Digital KW - Hochschule KW - Masterstudiengang KW - Zertifikat KW - Digitalisierung KW - Bayern Y1 - 2019 SN - 978-3-942303-86-6 N1 - Diese Publikation entstand an der Ostbayerischen Technischen Hochschule Regensburg im Rahmen des Projekts „Unternehmerische Kompetenzen auf dem tschechisch-bayerischen Arbeitsmarkt" mit der Registrierungsnummer 34, das im Rahmen des „Ziel ETZ 2014 -2020 Freistaat Bayern - Tschechische Republik (INTERREG V)" umgesetzt wird. SP - 63 PB - RAM CY - Lüdenscheid ER - TY - CHAP A1 - Gladbach, Stefan A1 - Saßmannshausen, Sean Patrick T1 - Entrepreneurship Education between Theory and Practice: Case Study Based Teaching as a Method of Creating Future Entrepreneurs T2 - Proceedings of the 8th AGSE International Entrepreneurship Research Exchange, Melbourne, Australia, 01/02/2011 - 04/02/2011 Y1 - 2011 SP - 1121 EP - 1130 ER - TY - CHAP A1 - Kuhn, Birte A1 - Saßmannshausen, Sean Patrick A1 - Zollin, Roxanne T1 - "Entrepreneurial Management" as a Strategic Choice in Firm Behavior T2 - Proceedings of the High technology Small Firms Conference Y1 - 2010 ER - TY - CHAP A1 - Saßmannshausen, Sean Patrick A1 - Blumberg, Boris F. A1 - Hofmann, Monica T1 - THE ETHICS OF EUROPEAN ENTREPRENEURS: 20 NATIONS CROSS-COMPARATIVE EMPIRICAL ANALYSES OF ATTITUDES AND BEHAVIOR OF ENTREPRENEURS, MANAGERS AND THE REMAINING POPULATION T2 - AGSE International Entrepreneurship Research Exchang N2 - This paper has three main objectives. First, it attempts to develop testable, theoretical sounded hypotheses explaining ethics of entrepreneurs. Therefore it builds upon studies exploring potential drivers for ethical attitudes and behavior. Second, these hypotheses are tested with a large and representative cross national data set, i.e. data from the European Social Survey (ESS). Third, our study is two-level comparative: The sample includes entrepreneurs, managers of sme's and large incorporations, and a representative number of populations excluding the two groups mentioned before. By this, we can compare ethics in attitudes and behavior between those three groups of profession as well as we can test for differences in ethical attitudes and behavior across 20 European countries. Our results show that many theoretical hypotheses do not meet empirical proof and that entrepreneurs seem to be significantly less ethical than the other groups. Y1 - 2008 UR - https://www.researchgate.net/publication/239279253_THE_ETHICS_OF_EUROPEAN_ENTREPRENEURS_20_NATIONS_CROSS-COMPARATIVE_EMPIRICAL_ANALYSES_OF_ATTITUDES_AND_BEHAVIOR_OF_ENTREPRENEURS_MANAGERS_AND_THE_REMAINING_POPULATION SP - 585 EP - 599 ER - TY - CHAP A1 - Gladbach, Stefan A1 - Saßmannshausen, Sean Patrick T1 - Zielgruppenspezifische Methoden in Entrepreneurship T2 - Methoden und Qualität in Gründungslehre, Gründungscoaching und Gründungsberatung : Interventionen und Innovationen N2 - Seitdem in den 1990er Jahren eine neue Förderkultur für Unternehmensgründungen in Deutschland entstand legt auch die Wissenschaft einen Fokus auf die Ausbildung von Unter-nehmensgründern, also auf die Entrepreneurship Education. Diese umfasst alle didaktischen Anstrengungen, die jeweilige Zielgruppe für eine potenzielle selbstständige Tätigkeit zu sen-sibilisieren und zielt auf den Erwerb spezifischer Kenntnisse und Fähigkeiten, die in grün-dungsrelevanten Handlungs- und Entscheidungsfeldern ausgerichtet sind (Uebelacker 2005). Doch welche Methodiken eignen sich im Besonderen dazu, diese umfangreichen und kom-plexen Kenntnisse und Fähigkeiten zu vermitteln? Nach Meinung der Verfasser ist die Fall-studien-Methodik besonders dazu geeignet, diese schwierige Aufgabe zu bewerkstelligen. Die Bezeichnung als „besonders dazu geeignet“ impliziert dabei keinesfalls die Behauptung einer alleinigen oder ausschließlichen Eignung. Die Verfasser befürworten vielmehr einen Methodenpluralismus in der Lehre, fokussieren im vorliegenden Beitrag aber auf Fallstudien, da diese Methode in Deutschland eher unterbewertet wird. Y1 - 2011 SP - 87 EP - 98 PB - Eul CY - Köln ER - TY - CHAP A1 - Günther, Swen A1 - Liubenova Popova, Silvia A1 - Falter, Thomas T1 - Indicators for Knowledge and Technology Transfer: Mapping, Measuring, and Managing T2 - Academic and Practitioner, Proceedings of the 2022 UIIN Conference Series: Challenges and Solutions for Fostering Entrepreneurial University-Industry Engagement, Entrepreneurial & Innovative Universities and Collaborative Innovation, June 13-15, 2022, Amsterdam N2 - The university research landscape in Germany has been repeatedly criticised for the fact that the excel-lent scientific output is insufficiently transferred to economically usable applications. In order to un-cover the weaknesses of knowledge and technology transfer, an effective measurement and indicator system is required. For this reason, research activities in this area have increased recently, especially funded by state institutions such as the Federal Ministry of Education and Research (BMBF). Relevant publications and studies contain a large number of proposals for key figures and indicators. These are intended to provide as comprehensive a picture of the transfer process as possible. The point of view of the transfer provider, i.e. the university, is often in the foreground. Until the present moment, transfer recipients such as economy and society have received less attention. The analysis of these sub-systems was part of the cross-university research project ‘Transfer_i: Transfer Indicators’. In this paper we describe an effective approach for mapping, measuring, and managing of transfer pro-cesses by using key performance indicators (KPI). Therefore, a systematic analysis and description of the (research-based) transfer processes at the subsystem level were carried out. The main causal rela-tionships in knowledge and technology transfer were determined for each sub-system, e.g. state, re-search, economy, society. The results were aggregated on the basis of a multidimensional model. Y1 - 2022 UR - https://www.researchgate.net/publication/362158728_Indicators_for_Knowledge_and_Technology_Transfer_Mapping_Measuring_and_Managing_in_UIIN_ed_Academic_and_Practitioner_Proceedings_of_the_2022_UIIN_Conference_Series_June_13-15_2022_Amsterdam_pp_52-64 SP - 52 EP - 64 ER - TY - CHAP A1 - Günther, Swen A1 - Falter, Thomas A1 - Brucksch, Michael A1 - Beckmann, Wilhelm A1 - Lang, Gabriele A1 - Findeisen, Vivien A1 - Bormann, Paula-Marie T1 - Relevance of transfer processes and indicators in practice - Results of a cross-subsystem expert survey in Germany T2 - Academic and Practitioner Proceedings of the 2023 UIIN Conference Series, Challenges and Solutions for Fostering Entrepreneurial University-Industry Engagement, Entrepreneurial & Innovative Universities and Collaborative Innovation, Budapest KW - Innovation Systems KW - Knowledge and Technology Transfer KW - Transfer Indicators KW - Processes KW - Subsystems Y1 - 2023 UR - https://www.uiin.org/product/2023-uiin-conference-proceedings/ SN - 9789-491-901-614 PB - University Industry Innovation Network B.V. CY - Amsterdam ER - TY - CHAP A1 - Kellner, Florian A1 - Otto, Andreas A1 - Busch, Andreas ED - Ivanov, Dimitri ED - Sokolov, Boris ED - Käschel, Joachim T1 - Distribution Networks - Rigid Investments In Dynamic Environments T2 - Flexibility and adaptability of global supply chains - Proceedings of the 7th German-Russian Logistics Workshop (DR-LOG 2012) Y1 - 2012 SP - 103 EP - 111 CY - Sankt Petersburg ER - TY - CHAP A1 - Günther, Swen A1 - Falter, Thomas A1 - Brucksch, Michael A1 - Beckmann, Wilhelm A1 - Lang, Gabriele A1 - Findeisen, Vivien A1 - Bormann, Paula-Marie T1 - Relevance of transfer processes and indicators in practice 3 Results of a cross-subsystem expert survey in Germany T2 - Academic and Practitioner Proceedings of the 2023 UIIN Conference Series, June 9-11, 2023, Budapest Y1 - 2023 SP - 104 EP - 119 PB - UIIN ER - TY - CHAP A1 - Liebetruth, Thomas T1 - Megatrends, recent developments, its impact on logistics processes and possible reactions - a bavarian perspective T2 - Carpathian Logistics Congress, CLC : November 4th-6th 2015, Priessnitz Spa, Jesenik, Czech Republic, EU : congress proceedings N2 - Megatrends have a high impact on logistics processes. Nevertheless some companies are still hesitating to start initiatives to react to it. Therefore this paper gives an overview of the impact of megatrends on logistics processes. It then gives examples of innovative logistical solutions, how companies can react to these trends and even improve processes and thus create a competitive advantage with a special focus on Bavarian political, industrial and academic initiatives. KW - Digitalization KW - Collaborative Robotics KW - Bavaria KW - Globalization KW - Industry 4.0 KW - Virtual Reality KW - Supply Chain Management KW - Process Improvement KW - Megatrends KW - Logistics KW - Global Sourcing Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-80451 UR - https://www.confer.cz/clc/2015/2755-megatrends-recent-developments-its-impact-on-logistics-processes-and-possible-reactions-a-bavarian-perspective SN - 978‐80‐87294‐61-1 SN - 2694-9318 SP - 10 EP - 14 PB - TANGER Ltd. CY - Ostrava ER - TY - CHAP A1 - Hauser, Florian A1 - Staufer, Susanne A1 - Röhrl, Simon A1 - Nadimpalli, Vamsi Krishna A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Mottok, Jürgen A1 - Falter, Thomas ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - LEVERAGING FIVE QUESTIONNAIRES TO ANALYZE STUDENT LEARNING STRATEGIES AND GENERATE AI-POWERED INDIVIDUALIZED LEARNING PATHS T2 - ICERI2025 Proceedings N2 - Background: The COVID-19 pandemic has significantly accelerated the shift toward online and blended learning in higher education, placing renewed emphasis on the individualization of learning content to meet diverse student needs. Even high-quality learning materials may fail to engage learners if they do not align with students’ personal preferences and learning styles. Identifying these learner preferences, therefore, emerges as a critical challenge. Objectives: This paper presents ongoing work within a larger research project aimed at employing artificial intelligence to recommend optimal learning path for students in specific courses. Beyond mere optimization, the goal is to ensure the best possible fit between learning materials and individual learners. Sample & Methods: A total of 27 students from technical degree programs took part in this survey. All participation was voluntary, and data were handled in full compliance with GDPR regulations. Although our broader project integrates fine-grained learning analytics from Moodle, the present abstract focuses exclusively on the self-report questionnaire results. Participants completed five instruments: 1. Index of Learning Styles (ILS) 2. LIST-K (Learning and Study Strategies Inventory – Short version) 3. BFI-10 (Big Five Inventory – 10 items) 4. Custom Preferences Instrument, capturing preferences for specific learning elements (e.g. instructional videos, lecture notes, summaries) and basic demographic data 5. Motivational Value Systems Questionnaire (MVSQ), piloted last semester to assess value orientations and motivational drivers Results: Preliminary analyses of the questionnaire data reveal: - Learning Styles (ILS): The majority lean toward the visual learning type (M = 5.740, SD = 3.430). - Learning Strategies (LIST-K): High scores on metacognitive strategies (M = 3.000; SD = 0.520) and collaboration with peers (M = 3.190; SD = 0.540). - Preferred Learning Elements: Summaries, overviews, and self-checks are most favored. - Value Orientations (MVSQ): Students are primarily driven by the pursuit of personal achievement (M = 4.400; SD = 11.140). Conclusion & Significance: By integrating these five standardized questionnaires, we gain valuable insights into student learning preferences—insights that complement our Moodle analytics in the broader project. Observed trends suggest that learning materials should be concise and designed to facilitate peer interaction and knowledge deepening. These findings will guide the refinement of our AI-driven recommendation engine, enhancing its ability to deliver personalized learning paths that boost both engagement and effectiveness. KW - AI in higher education KW - learning management system KW - adaptive learning KW - personalized learning paths KW - online and blended learning Y1 - 2025 U6 - https://doi.org/10.21125/iceri.2025.0658 SP - 1775 EP - 1784 PB - IATED ER -