658 Allgemeines Management
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Der vorliegende Artikel beleuchtet die grundsätzlichen Möglichkeiten der Integration von Funktionalitäten der sozialen Medien in Unternehmen. Darauf aufbauend wird Social Commerce als zentraler Gegenstand der Unternehmensführung hergeleitet. Dabei stehen der kundenseitige Kaufprozess und dessen Schnittstellen zu Kommunikationsinstrumenten des Social Webs im Vordergrund. Gezeigt wird die Beeinflussung des individuellen Kaufprozesses durch Social Media. Diese Wirkungsdynamiken sind nachfolgend die Grundlage für die Deskription von möglichen strategischen Einsatzfeldern und Bereichen des Social Commerce in der Unternehmensführung.
The EU funded project RobLog recently developed a system able to autonomously unload coffee sacks from a standard container. Being the first of its kind, a further development is needed in order for the system to be competitive against manual labor. Financing this development entails a risk, hence a justified skepticism, which can be overcome by the longsighted view of the existing market potential. This paper presents a method to estimate the market potential of autonomous unloading systems for heavy deformable goods. Starting from the analysis of the coffee trade, first the current coffee traffic is investigated in order to calculate the number of autonomous systems needed to handle the imported sacks; Results are validated and the method is extended for the calculation of the potential of other market segments, where the same unloading technology can be applied.
Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
Die Wahl einer Klinik ist typischerweise dem stellvertretenden Kaufverhalten zuzuordnen – Kunden suchen vertrauenswürdige, persönliche Quellen zur Unterstützung der Entscheidung. Weiterempfehlungsverhalten kann durch Anreize unterstützt werden – grundlegende Voraussetzung für ehrliche Weiterempfehlung ist jedoch Kundenzufriedenheit. Kundenzufriedenheit entsteht durch den Abgleich zwischen erwarteter und empfundener Leistung – das erwartete Leistungsniveau wird häufig durch Unternehmen anderer Branchen determiniert. Individuen sind nicht in der Lage, die Bestandteile einer Erfahrung isoliert zu bewerten, sondern vermengen sie (Halo-Effekt) - Inkonsistenzen führen zu einer Abwertung der Gesamterfahrung. Darum ist im ersten Schritt die Identifikation der Gesamterfahrung (Kundenreise) erforderlich – diese beginnt vor und endet nach der unmittelbaren Interaktion des Kunden mit dem Unternehmen / der Klinik. Im zweiten Schritt sind die Zufriedenheitstreiber und die Interdependenzen zwischen den Einzelerfahrungen zu ermitteln um dann die Optimierung der Kundenreise zu planen und umzusetzen.
When forecasting sales figures, not only the sales history but also the future price of a product will influence the sales quantity. At first sight, multivariate time series seem to be the appropriate model for this task. Nontheless, in real life history is not always repeatable, i.e. in the case of sales history there is only one price for a product at a given time. This complicates the design of a multivariate time series. However, for some seasonal or perishable products the price is rather a function of the expiration date than of the sales history. This additional information can help to design a more accurate and causal time series model. The proposed solution uses an univariate time series model but takes the price of a product as a parameter that influences systematically the prediction. The price influence is computed based on historical sales data using correlation analysis and adjustable price ranges to identify products with comparable history. Compared to other techniques this novel approach is easy to compute and allows to preset the price parameter for predictions and simulations. Tests with data from the Data Mining Cup 2012 demonstrate better results than established sophisticated time series methods.
Industry 4.0 predicts that industrial processes, technological infrastructure and all corresponding Business processes, with the help of information and communication technology (ICT), will advance to integrated, ad-hoc interconnected and decentralized Cyber-Physical Production Systems (CPPS) with real-time capabilities of selfoptimization and adaptability. Considering this change, the human being will remain in a dominant role, because it is not expected that the human factor with its characteristics and capabilities will be substituted entirely by autonomously acting technology in the foreseeable future. The mechanical intelligence, for instance, is limited to the selection of predefined options, while human creativity, flexibility, the ability to learn and to improve are required to design and configure systems, processes and products. Humans have the expertise and experience to analyze, assess and solve - even in exceptional situations. However, the amount of purely manual tasks for shop floor workers will decrease. Their role will change from a manually executing to a proactive preconceiving worker with increased responsibility. Due to the growing degree of digitalization and interconnectedness, also the tasks and responsibilities for planning and design personnel will continuously expand and become more complex. The work in versatile ad-hoc networks with advanced ICT-Tools and assistance systems will lead to increased requirements regarding the knowledge, capability and capacity of the respective employees. The on-going pervasion of IT and emergence of systems with unprecedented complexity specifically require significantly improved capabilities in analysis, abstraction, problem solving and decision making from future labour. Accordingly, the industry is asking for graduates that are educated interdisciplinary and practice-oriented. Some universities already meet these expectations, using learning factories for realistic, action-oriented classes and trainings. Lecturers are confronted with the challenge to identify future job profiles and correlated qualification requirements, especially regarding the conceptualization and implementation of CPPS, and to adapt and enhance their education concepts and methods adequately and consequently. For the new, virtual world of manufacturing a proper understanding of engineering as well as Computer sciences is essential. Industry 4.0 implies this interdisciplinary split. Integrated competencies for product and process planning and design, methodological competencies for systematical idea and innovation management as well as a holistic system and Interface competence will be crucial to achieve interconnection of physical and digital processes and machines. The Vienna University of Technology and the ESB Reutlingen committed to integrate key aspects of Industry 4.0 into their respective learning factories successively. Thus, the students will act as the coordinators of the CPPS and thereby remain in the center of all learning and implementation activities.