Browsing by Subject "Comparative Analysis"
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Item Restricted How Machine Learning Models were Affected by the Corona Crisis(2023) Paul Immanuel Scrima von der Goltz; Artinger, Florian; Koç, Hasan; Faculty of Business Administration; Berlin International University of Applied SciencesAI-GENERATED ABSTRACT: Abstract: The COVID-19 crisis has had a profound impact on various industries worldwide, including the airline and movie sectors. Machine learning models, which play a crucial role in predicting outcomes and optimizing operations in these industries, have also been affected by the pandemic. This comparative literature review aims to explore and analyze the performance of machine learning models in the airline and movie industries during and after the COVID-19 crisis. By conducting a comprehensive analysis of relevant scholarly articles, conference papers, and industry reports, this review aims to provide insights into the challenges, adaptations, and advancements made in machine learning models pre- and post-pandemic. The relevant papers and sources were selected based on being pre- and post-pandemic. These two categories of sources were then compared for both industries to illustrate the effects of the pandemic on machine learning models in both industries, and how they have developed since this global event. The findings demonstrated that machine learning has been in use for decades in both industries. In the movie industry, the algorithms were mainly used for forecasting revenue or predicting movie success pre-pandemic, while in the airline industry, machine learning models predicted flight patterns/delays or ticket prices. While the algorithms and models in both industries struggled initially in the new dynamic environments, key differences can be synthesized between the developments since. While the airline industry continues to grow and utilizes ML as a globally demanded and necessary industry, the movie industry has still not fully recovered since COVID-19 as many consumers move to digital alternatives like streaming platforms. The findings of this review will contribute to a deeper understanding of the implications of the COVID-19 crisis on machine learning applications and provide insights for researchers, practitioners, and decision-makers in these industries. Keywords: COVID-19 Impact, Machine Learning Models, Airline Industry, Movie Industry, Predictive Analytics, Pandemic Adaptations, Comparative Analysis, Algorithm Performance, Industry Recovery, Digital TransformationItem Restricted Navigating Cross-cultural Differences : Opportunities, Challenges, and Success for International Immigrant Entrepreneurs at a Berlin Start-up Incubator(2023) Nikhilesh Kalyana Kumar; Ülker, Barış; Villegas, Erick Behar; Faculty of Business Administration; Berlin International University of Applied SciencesAI-GENERATED ABSTRACT: Abstract: To understand the perceptions and experiences of the immigrant entrepreneurs this study was conducted, spotlighting on their challenges, experiences, motivation and factors which succeed them. This research also shows the effort of the Berlin startup incubators in order to support the immigrant entrepreneurs. The study is set on the bigger context of global trends in entrepreneurship and migration, the significance of the topic in today's socio-economic landscape was addressed. The presentation of the results of this study was provided in detailed manner, which also includes the entrepreneur's demographic information, their self-motivation to start a business in foreign country, their experience with the Berlin startup incubator, challenges faced by the entrepreneurs and strategies implemented to pass them, and factors which succeed them. Complete analysis and comparison were done by using the findings from interviews with Berlin startup incubator official and immigrant entrepreneurs, which showed some differences and similarities in their perceptions and experiences. The key points of the research were summarized, a comprehensive understanding of the experiences and perceptions of immigrant entrepreneurs were provided and in the supporting role the startup incubator acted well. Keywords: immigrant entrepreneurs, startup incubators, Berlin, entrepreneurship, global migration, socio-economic impact, challenges, motivation, business strategy, comparative analysis