TY - THES A1 - Brzoska, Jan T1 - Market forecasting in China: An Artificial Neural Network approach to optimize the accuracy of sales forecasts in the Chinese automotive market T1 - Marktprognosen in China: Einsatz eines Künstlichen Neuronalen Netzes zur Optimierung der monatlichen Absatzprognosequalität im chinesischen Automobilmarkt N2 - Sales forecasts are an essential determinant of operational planning in entrepreneurial organizations. However, in China, as in other emerging markets, monthly sales forecasts are particularly challenging for multinational automotive enterprises and suppliers. A chief reason for this is that conventional approaches to sales forecasting often fail to capture the underlying market dynamics. To that end, this dissertation investigates the application of Artificial Neural Networks with an implemented backpropagation algorithm as a more “unconventional” sales forecasting method. A key element of statistical modelling is the selection of superior leading indicators. These indicators were collected as part of the researcher’s expert interviews with multinational enterprises and state associations in China. The economic plausibility of all specified indicators is critically explored in qualitative-quantitative pre-selection procedures. The overall objective of the present study was to improve the accuracy of monthly sales forecasts in the Chinese automotive market. This objective was achieved by showing that the forecasting error could be lowered to a new benchmark of less than 10% in an out-of-sample forecasting application. N2 - Absatzprognosen sind ein zentraler Bestandteil der operativen Unternehmensplanung. In China, wie auch in anderen Schwellenländern, stellen vor allem monatliche Prognosen jedoch eine besondere Herausforderung für multinationale Automobilhersteller und deren Zulieferer dar. Ein Grund hierfür ist, dass konventionelle Prognoseverfahren der außergewöhnlich hohen Marktdynamik nicht ausreichend gerecht werden. In der vorliegenden Dissertationsschrift werden Künstliche Neuronale Netze mit integriertem Backpropagation-Algorithmus als alternatives Marktprognoseverfahren eingehend beleuchtet. Erprobt vor allem in hochvolatilen Finanzmarktanwendungen ist diese Form künstlicher Intelligenz imstande, hochkomplexe Zusammenhänge zu entschlüsseln und selbständig aus Prognosefehlern zu lernen. Ein Kernelement der statistischen Modellierung ist die Auswahl von geeigneten Frühwarnindikatoren, die unter anderem durch Experteninterviews in chinesischer Sprache bei Regierungsablegern erhoben wurden. Die ökonomische Plausibilität der genannten Indikatoren wird in qualitativ-quantitativen Vorauswahlverfahren kritisch reflektiert. Grundlegendes Ziel des Forschungsprojektes war es, die Güte der monatlichen Absatzprognosen im chinesischen Automobilmarkt zu verbessern. Dieses Ziel konnte mit Unterschreitung der entscheidenden 10%-Prognosefehlerschwelle im Validierungsdatensatz erreicht werden. KW - China KW - Kraftfahrzeugindustrie KW - Marktprognose KW - Neuronales Netz KW - Automotive industry KW - Chinese economy KW - Market forecasts KW - Artificial Neural Networks KW - Backpropagation Learning KW - Leading indicators KW - Institutional voids KW - Emerging markets KW - Resource-based view KW - International business strategy KW - Wirtschaft KW - Prognosen KW - Autoindustrie KW - Neuronale Netze Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-203155 ER - TY - RPRT A1 - Krause, Theresa A1 - Fischer, Doris T1 - Data as the new driver for growth? European and Chinese perspectives on the new factor of production T1 - Sind Daten der neue Wachstumstreiber? Europäische und chinesische Perspektiven auf den neuen Produktionsfaktor N2 - Amidst an emerging international systemic competition between China and the Western world, China’s sustained high economic growth rates, technological innovations and successful control of the corona pandemic have raised doubts over the West’s systemic capabilities. In this context, data resources and regimes play an increasing role. This research note looks at data as present and future driver of innovation and economic growth in more detail. It compares the Chinese and the European perspective on data as well as their respective (planned) policy measures in order to draw tentative conclusions about their different approaches' implications. T3 - CBE Research Note - 1/2021 KW - China KW - Europa KW - Wirtschaftspolitik KW - drivers of growth KW - China KW - data economics KW - European Union KW - growth KW - economic policy KW - data KW - Europe Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-229794 ER - TY - RPRT A1 - Fischer, Doris A1 - Schaper, Anna-Katharina T1 - Does Gender Matter for the Entrepreneurship Fairy Tale? An Analysis of Chinese Unicorn Start-ups T2 - CBE Research Notes N2 - Start-up ecosystems around the world have created a large number of successful and innovative unicorn companies in recent years. Our research note focuses on the case of China and offers a global comparative perspective on the current status of Chinese unicorn start-ups and their founding structure. We identify a predominantly male unicorn founding structure and illustrate a worrying decline of female entrepreneurship in China. T3 - CBE Research Note - 2/2021 KW - female entrepreneurs KW - unicorns KW - China KW - economics KW - entrepreneurship KW - Women entrepreneurs KW - Start-up Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-244415 SN - 2747-8661 ER -