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 - THES A1 - Hauser, Anna Si-Lu T1 - A comparative approach to local organisation of the energy transition N2 - In recent years, numerous renewable energy cities were established worldwide, piloting different pathways to transition to clean energy. With the ability to address local needs more precisely in their unique geographic, social and economic contexts, cities play a vital role in implementing overall climate mitigation goals on the local level. In China, many renewable energy cities have emerged as well. However, official documents suggest that Chinese government authorities establish such renewable energy cities strategically, which leads to the assumption that the impulse to become renewable is different from other countries, where bottom-up initiatives are more common. Hence, this thesis explores answer to the question why and how the Chinese government promotes the energy transition of Chinese cities and regions. To explore the dynamics of local energy transition projects, this thesis adopts two frameworks from the field of sustainability transitions, the multi-level perspective and strategic niche management, and applies them to seven European and two Chinese case studies. The European sample includes the cities Graz, Güssing, Freiburg, and Helsinki as well as the communities Feldheim, Jühnde and Murau. The Chinese sample consists of the bottom-up initiative Shaanxi Sunflower Project and the demonstration project Tongli New Energy Town. A comparative analysis evaluates in how far the cases correspond to the multi-level perspective or strategic niche management. The comparison of the case studies reveals that the development of renewable energy cities in China goes beyond a top-down vs. bottom-up logic. In the Chinese context, strategic niche management should be understood as experimentation under hierarchy, which serves at pretesting different approaches before rolling them out nationwide. In addition, the analysis shows that both the multi-level perspective and strategic niche management have their advantages and disadvantages for niche development. Niches following the logic of the multi-level perspective may result in higher stakeholder acceptance, whereas strategic niche management can in turn accelerate niche development. However, since natural niche development cannot be steered intentionally, decision-makers who intend to induce local renewable energy projects have no other option but to resort to strategic niche management. To increase stakeholder acceptance and thus to improve the project outcome, decision-makers are advised to accommodate sufficient room for stakeholder participation in the project design. KW - China KW - multi-level perspective KW - strategic niche management KW - energy transition KW - top down KW - bottom up Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-202109 ER - TY - RPRT A1 - Angnide, Enarile A1 - Bielitska, Iryna A1 - Borchert, Leon A1 - Braun, Louisa A1 - Bühler, Pascal A1 - Chen, Xinyue A1 - Ho, Katherina A1 - Hofmann, Lena A1 - Kebekus, Melvin A1 - Kubsch, Torbjörn A1 - Li, Alexander A1 - Lin, Simon A1 - Mischer, Andreas A1 - Mogus, Mateja A1 - Schmid, Fabian A1 - Schneidawind, Luisa A1 - Voss, Manuela A1 - Wilson, Claire A1 - Wieteska, Filip A1 - Yu, Linda ED - Lindner, Jonas ED - Fischer, Doris T1 - Chinese Entanglements in Lower Franconian Business BT - A student research project by the Chair of China Business and Economics at the University of Würzburg N2 - Using own survey data and interviews, this study analyzes how businesses in Lower Franconia (Unterfranken) are entangled with China. Starting with a bird's-eye-view of the current situation, the study goes on to provide valuable insights from five specific industries. The study shows that a majority of the analyzed firms have some sort of ties to China, be it through Chinese customers, import/export activities, or else. KW - China KW - Unterfranken KW - China KW - Lower Franconia KW - Unterfranken KW - business KW - entanglement KW - Handel Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-209876 ER -