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Die vorliegende Ausarbeitung beschäftigt sich mit der Frage, ob weibliche Führungskräfte aufgrund spezieller Führungskompetenzen auf den langfristigen Unternehmenserfolg einzahlen. Besondere Beachtung findet hierbei der Faktor der Emotionalen Intelligenz. Nach wie vor ist der Anteil weiblicher Führungskräfte auf deutschen Managementebenen auffallend gering. Um ein Verständnis für die Hintergründe dieser Thematik zu entwickeln, werden zunächst die Ursachen geschlechtsbedingter Differenzierungen erläutert. Die wesentlichen Erkenntnisse entstammen dem Bereich der Geschlechterforschung. Im Anschluss werden diese im Kontext der Führung beleuchtet. Ein besonderes Augenmerk liegt auf der Frage, ob und inwiefern sich ein potentieller weiblicher Führungsstil von der als männlich geltenden Führung unterscheidet. Im weiteren Verlauf des Artikels wird das Phänomen der Emotionalen Intelligenz im Detail betrachtet. Dieses gilt im Kontext der Führung seit geraumer Zeit als Erfolgsfaktor. Ob und inwiefern diese Annahme tatsächlich Bestand hat, soll daher zunächst herausgestellt werden. Abschließend wird geprüft, ob es sich bei der Emotionalen Intelligenz um eine vorwiegend weibliche Kompetenz handelt
This research paper discusses how RFID technology could improve current deposit bottle logistic processes in food retailing and which obstacles impede successful implementations. Research Methodology include desk research: Library, EBSCOhost, wiso.net, Google Scholar, Scientific Journals, Statista, SpringerLink. Implementation of RFID is potentially beneficial, but same obstacles remain outlook. To validate the conclusion further studying and practical proof of concept are necessary. Contributions: supply chain management, return logistics, food retail, beverage industry
In recent years, the retail virtual store has become the main trend in social services. More and more people tend to shop in retail virtual stores. With the development of 3D virtual reality, this trend is getting stronger and stronger. Therefore, the development prospect of virtual retail stores has attracted much attention. This paper examines the impact of companies' and users' popularization of helmet gadgets on in-store traffic and analyzes how virtual reality (VR) could enhance the customer experience throughout the shopping trip. A qualitative research design has been used, which also included conversations with both professionals and consumers. Moreover, this paper seeks to break new ground by attempting to use the current literature to help predict future directions and trends for online shopping.
Der Erbbauzins ist bei kommunalen Erbbaurechten sowohl eine zentrale Stellgröße für die Wirtschaftlichkeit als auch von kommunalwirtschafts- und beihilferechtlicher Relevanz. Er wird zumeist ermittelt, indem ein geeigneter Erbbauzinssatz auf den Bodenwert angelegt wird. Der Erbbauzinssatz sollte dabei marktgerecht sein. Sowohl die Ableitung des Erbbauzinssatzes aus dem Primärmarkt (erstmalige Ausgabe von Erbbaurechten) wie aus dem Sekundärmarkt (Weiterverkäufe) ist aber zumindest bei Erbbaurechten für Mehrfamilienhäuser derzeit kaum sinnvoll zu diesem Zwecke durchzuführen. Auch der Liegenschaftszinssatz ist ungeeignet, da er aus einem Modell für Volleigentum mit einer vollkommen anderen Risiko-/Rendite-Konstellation abgeleitet wird. Daher wird für eine stärkere Anwendung ökonomisch basierter Verfahren plädiert und hierbei ein kapitalmarktorientiertes Mark-to-Model-Verfahren dargestellt. Erste überschlägige Ermittlungen legen zudem die Orientierung an langfristigen Baufinanzierungssätzen als Daumenregel nahe. Regelmäßig dürften von Kommunen für die Ermittlung von marktgerechten Erbbauzinssätzen öffentlich bestellte und vereidigte oder zertifizierte Grundstückssachverständige betraut werden, denen die betreffenden Verfahren jedoch oftmals fremd sind. Auch stellt sich die Frage nach der Zulässigkeit, da sie sich als Best Practice-Verfahren bislang nicht etabliert haben. Daher wäre dem Gesetz- bzw. Verordnungsgeber anzuraten, die Ermittlung marktgerechter Erbbauzinssätze ausdrücklich zu regeln und dabei jenseits von Mark-to-Market-Verfahren weitere geeignete ökonomisch gestützte Methoden wie auch empirisch abgesicherte „Daumenregeln“ zuzulassen.
Thailand’s power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand’s Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels.
Big Data is now poised to mutate decision-making systems. Indeed, the decision is no longer based solely on the structured information that was hitherto collected and stored by the organization, but also on all data not structured outside the corporate straitjacket. The cloud and the information it contains impacts decisions and the industry is witnessing the emergence of business intelligence 3.0. With the growth of the internet, social networks, connected objects and communication information are now more abundant than ever before, along with rapid and substantial growth in their production. In 2012, 2.5 exabytes of data (one exabyte representing a million gigabytes of data) came every day to swell the ranks of big data (McAfee et al., 2012), which should weigh more than 40 zettabytes from 2020 (Valduriez, 2014) for 30 billion connected devices (The Internet Of Nothings, 2014) and 50 billion sensors (Davenport & Soulard, 2014). One of the most critical aspects of all of this information flow is the impact these will have on the way decisions are made. Indeed, in the part of an environment in which data was scarce and difficult to obtain, it was logical to let decision-making be conditioned by the intuition of the experienced decision-maker (Klein, Phillips, Rall, & Peluso, 2007). However, since information and knowledge are now available to everyone, the role of experts and decision-makers is gradually changing. Big data, in particular, makes it possible for analytical and decision-making systems to base their decision-making on global models. However, considering all the dimensions of the situations encountered, it was not until now that these systems were not within the reach of man, but were rationally limited (Simon & Newell, 1971). Big data and however, the processing of unstructured data requires modifying the architecture of decision support systems (DSS) of organizations. This paper is an inventory of developments undergone by aid systems decision-making, under the pressure of big data. Finally, it opens the debate on ethical questions raised by these new technologies, and it is observed that now, data analysis of personal data has become more debatable than in the past.
The integration of genetic algorithms to optimize the networks of value chains could enormously improve the performance of supply chains. For this reason, this paper describes in more detail the application of genetic algorithms in the value chains of the automotive industry. For this purpose, a theoretical model is built up to evaluate whether the application of the model can optimize the value chain. This option is described, analyzed and its restrictions are shown. Instead of looking at the entire network, individual finished goods and their bill of material are used as a basis for optimization, which greatly reduces the complexity of the original problem. The original complexity of the supply chain networks can thus be reduced and considered based on the bill of material.
For a detailed discussion of process mining, the objective of this paper is the analysis of the successful implementation of process mining in the practical fields of supply chain management. The research comprises the investigation of use cases in companies that are already actively using process mining.
Purpose: This research aims to highlight the applicability of process mining in the supply chain management business field.
Research Methodology: In order to examine the applicability of process mining in supply chain management a research study was conducted among experts in this business field. Further, theoretical findings were compared to the results and evaluated.
Results: Process Mining can be applied very well in the SCM area. The advantages that arise primarily reflect significant potential benefits and improved process throughput times. The information that can be gained from the operational areas supported by process mining is suitable for reliable decisions, both in the tactical and strategic areas.
Limitations: The results on the application of process mining show a certain generalization and have to be adapted and adjusted to the respective application case.
Contribution: This study is useful, especially for the purchasing and logistics business area.
A study of industry 4.0 technologies in the John Deere and Company and their impact on company operations is presented in this paper. Deere and Company’s implementation of Industry 4.0 to its factories and its factors was the focus of the research. The literature review with the systematic approach as well as a comprehensive review of current John Deere and Company’s developments is used in the current study. Also, it relied on freely available information on the company website. Public and investor relations have also been used as credible sources of information. An analysis found that adopting industry 4.0 technologies to agriculture manufacturing results in higher quality products, increased productivity, safety, and wider acceptance among stakeholders. This study assumes full implementation of these technologies in all agriculture manufacturing companies, and it also emphasizes up-to-date technologies. Studying this topic can be useful for engineers in mechanical and agricultural fields, managers in business, and marketers.
The aim of the study is to find out how SMEs used Social Media during Corona and how customers received it, to determine what should be continued or avoided by SMEs in the future. In this study, an interpretivist approach was adopted through problem-centred interviews with three SMEs. The second part of the study used an objectivist approach, where an online-based survey with a purpose sampling was conducted. The results were evaluated by means of thematic analysis.The SMEs interviewed considered Social Media essential during Corona. This was due to limited resources and the feeling of being overwhelmed by the situation. For customers a Social Media presence is also considered indispensable, and that the followership is based on the desire for the latest information. However, it also became clear that the survey participants do not believe the information on Social Media and prefer information on the website or at the location itself. No answers could be found about how the experts would answer sans or post Corona. Furthermore, due to anonymisation efforts, it was not possible to clarify the attitude of the survey participants specifically to the individual SMEs.