Browsing by Person "Schoop, Mareike"
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Publication A hybrid model of electronic negotiation : integration of negotiation support and automated negotiation models(2008) Rehman, Moez ur; Schoop, MareikeElectronic business negotiations are enabled by different electronic negotiation models: automated negotiation models for software agents, negotiation support models for human negotiators, and auction models for both. To date, there is no electronic negotiation model that enables bilateral multi-issue negotiations between a human negotiator and a negotiation agent?an important task in electronic negotiation research. In this thesis, a model is presented that integrates the automated negotiation model and the negotiation support model. The resulting hybrid negotiation model paves the way for human-agent business negotiations. The integration of two models is realised at the levels of negotiation process, communication support and decision making. To this end, the negotiation design, negotiation process, negotiation decision making, and negotiation communication in negotiation support systems (NSSs) and agent negotiation systems (ANSs) are studied and analysed. The analyses on these points help in strengthening the motivation behind hybrid negotiation model and setting aims for the integration of an NSS and an ANS in hybrid negotiation model. We mainly propose a human-agent negotiation design, negotiation process protocols to support the design, a hybrid communication model for human-agent interaction, an agent decision-making model for negotiation with human, and a component for interoperability between NSS and ANS. The agent decision-making model is composed of heuristic and argumentation-based negotiation techniques. It is proposed after analysing different automated negotiation models for different human negotiation strategies. The proposed communication model supports human negotiator and negotiation agent to understand and process negotiation messages from each other. This communication model consists of negotiation ontology, a wrapper agent, and a proper selection of an agent communication language (ACL) and a content language. The wrapper agent plays a role for interoperability between agent system and NSS by providing a communication interface along with the negotiation ontology. The negotiation ontology, ACL and agent content language make the communication model of negotiation agent in ANS. The proposed hybrid model is realised by integrating an ANS into NSS Negoisst. The research aim is to show that a hybrid negotiation system, composed of two heterogeneous negotiation models, can enable human-agent multi-issue integrative negotiations.Publication Data quality and information loss in standardised interpolated path analysis : quality measures and guidelines(2019) Schoop, Mareike; Witt, Josepha; Schmid, Andreas; Melzer, Philipp; Kaya, Muhammed; Lenz, AnnikaStandardised interpolated path analysis (SIPA) is a method to investigate negotiation processes making different negotiation histories comparable. Due to its interpolation approach, researchers employing SIPA must take data quality and potential information loss into account to maximise the method’s explanatory power. This paper presents quality measures and applies them to two negotiation datasets for deriving meaningful boundaries. Using these quality measures enables researchers to compare SIPA across segmentations, variables, and datasets also providing outlier analysis.Publication Doctoral Consortium of the 17th International Conference on Group Decision and Negotiation(2017) Schoop, MareikePublication Electronic negotiation support systems and their role in business communication : an exploratory evaluation of auction use(2007) Köhne, Frank; Schoop, MareikeElectronic communication media and electronic commerce have become substantial components of economic interaction. Buyers and consumers are increasingly integrated in processes of product and service specification. More and more coordination processes are conducted digitally or partly automated. Buyer-supplier relationships change. In the post-hype phase regarding online-auctions long term relationships prevail ? however, the electronic communication via e-mail as well as the different types of reverse auction have been established as business processes. The dissertation contributes to an understanding of the appropriation and use processes of electronic procurement auctions, i.e. the only form of electronic negotiation with sufficient market-penetration for a field study. Consequently, it explicates the effects of the technology in its application context. The focus of the study is on an aspect, which is hardly suitable for experimental analysis: the identification and contextualisation of organisational communication effects. It shows how auction systems can generate efficiencies as well as relational threats and communicative barriers. The latter is mainly achvied through references to the theory of Habermas. Based on the field study, conclusions for the adequate design and choice of negotiation support technology are drawn.Publication Proceedings of RSEEM 2006 : 13th Research Symposium on Emerging Electronic Markets(2006) Schoop, MareikeElectronic markets have been a prominent topic of research for the past decade. Moreover, we have seen the rise but also the disappearance of many electronic marketplaces in practice. Today, electronic markets are a firm component of inter-organisational exchanges and can be observed in many branches. The Research Symposium on Emerging Electronic Markets is an annual conference bringing together researchers working on various topics concerning electronic markets in research and practice. The focus theme of the13th Research Symposium on Emerging Electronic Markets (RSEEM 2006) was ?Evolution in Electronic Markets?. Looking back at more than 10 years of research activities in electronic markets, the evolution can be well observed. While electronic commerce activities were based largely on catalogue-based shopping, there are now many examples that go beyond pure catalogues. For example, dynamic and flexible electronic transactions such as electronic negotiations and electronic auctions are enabled. Negotiations and auctions are the basis for inter-organisational trade exchanges about services as well as products. Mass customisation opens up new opportunities for electronic markets. Multichannel electronic commerce represents today?s various requirements posed on information and communication technology as well as on organisational structures. In recent years, service-oriented architectures of electronic markets have enabled ICT infrastructures for supporting flexible e-commerce and e-market solutions. RSEEM 2006 was held at the University of Hohenheim, Stuttgart, Germany in September 2006. The proceedings show a variety of approaches and include the selected 8 research papers. The contributions cover the focus theme through conceptual models and systems design, application scenarios as well as evaluation research approaches.Publication Proceedings of the 17th International Conference on Group Decision and Negotiation(2017) Schoop, MareikePublication Sentiment analysis in electronic negotiations(2017) Körner, Michael; Schoop, MareikeThe thesis analyzes the applicability of methods of Sentiment Analysis and Predictive Analytics on textual communication in electronic negotiation transcripts. In particular, the thesis focuses on examining whether an automatic classifier can predict the outcome of ongoing, asynchronous electronic negotiations with sufficient accuracy. When combined with influencing factors leading to the specific classification decision, such a classification model could be incorporated into a Negotiation Support System in order to proactively intervene in ongoing negotiations it judges as likely to fail and then to give advice to the negotiators to prevent negotiation failure. To achieve this goal, an existing data set of electronic negotiations was used in a first study to create a Sentiment Lexicon, which tracks verbal indicators for utterances of positive and, respectively, negative polarity. This lexicon was subsequently combined with a simplified, feature-based representation of electronic negotiation transcripts which was then used as training data for various machine learning classifiers in order to let them determine the outcome of the negotiations based on the transcripts in a second study. Here, complete negotiation transcripts were classified as well as partial transcrips in order to assess classification quality in ongoing negotiations. The third study of the thesis sought to refine the classification model with respect to sentence-based granularity. To this end, human coders were classifying negotiation sentences regarding their subjectivity and polarity. The results of this content analysis approach were then used to train sentence-level subjectivity and polarity classifiers. The fourth and final study analyzed different aggregation methods for these sentence-level classification results in order to support the classifiers on negotiation granularity. Different aggregation and classification models were discussed, applied to the negotiation data and subsequently evaluated. The results of the studies show that it is possible to a certain degree to use a sentiment-based representation of negotiation data to automatically determine negotiation outcomes. In combination with the sentence-based classification models, negotiation classification quality increased further. However, this improvement was only found to be significant for complete negotiation transcripts. If only partial transcripts are used – specifically to simulate an ongoing negotiation scenario – the models tend to behave more erratic and classifcation quality depletes. This result yields the assumption that polarized utterances (positive as well as negative) only carry unequivocal information (with respect to the outcome) towards the end of the negotiation. During the negotiation, the influence of these utterances becomes more ambiguous, hence decreasing classification accuracy on models using a representation based on sentiments. Regarding the original goal of the thesis, which is to provide a basic means to support ongoing negotiations, this means that supporting mechanisms employed by a Negotiation Support System should focus on moderation techniques and resolving of potentially conflicting situations. Approaches that could be used to employ further conflict diagnosis in interaction with the negotiators are given in the final chapter of the thesis, as well as a discussion of potential recommendations and advice the system could give and lastly, approaches to visualize the classification data to the negotiators.Publication Unlocking the power of generative AI models and systems such asGPT-4 and ChatGPT for higher education(2023) Vandrik, Steffen; Urbach, Nils; Gimpel, Henner; Hall, Kristina; Decker, Stefan; Eymann, Torsten; Lämmermann, Luis; Mädche, Alexander; Röglinger, Maximilian; Ruiner, Caroline; Schoch, Manfred; Schoop, MareikeGenerative AI technologies, such as large language models, have the potential to revolutionize much of our higher education teaching and learning. ChatGPT is an impressive, easy-to-use, publicly accessible system demonstrating the power of large language models such as GPT-4. Other compa- rable generative models are available for text processing, images, audio, video, and other outputs – and we expect a massive further performance increase, integration in larger software systems, and diffusion in the coming years. This technological development triggers substantial uncertainty and change in university-level teaching and learning. Students ask questions like: How can ChatGPT or other artificial intelligence tools support me? Am I allowed to use ChatGPT for a seminar or final paper, or is that cheating? How exactly do I use ChatGPT best? Are there other ways to access models such as GPT-4? Given that such tools are here to stay, what skills should I acquire, and what is obsolete? Lecturers ask similar questions from a different perspective: What skills should I teach? How can I test students’ competencies rather than their ability to prompt generative AI models? How can I use ChatGPT and other systems based on generative AI to increase my efficiency or even improve my students’ learning experience and outcomes? Even if the current discussion revolves around ChatGPT and GPT-4, these are only the forerunners of what we can expect from future generative AI-based models and tools. So even if you think ChatGPT is not yet technically mature, it is worth looking into its impact on higher education. This is where this whitepaper comes in. It looks at ChatGPT as a contemporary example of a conversational user interface that leverages large language models. The whitepaper looks at ChatGPT from the perspective of students and lecturers. It focuses on everyday areas of higher education: teaching courses, learning for an exam, crafting seminar papers and theses, and assessing students’ learning outcomes and performance. For this purpose, we consider the chances and concrete application possibilities, the limits and risks of ChatGPT, and the underlying large language models. This serves two purposes: • First, we aim to provide concrete examples and guidance for individual students and lecturers to find their way of dealing with ChatGPT and similar tools. • Second, this whitepaper shall inform the more extensive organizational sensemaking processes on embracing and enclosing large language models or related tools in higher education. We wrote this whitepaper based on our experience in information systems, computer science, management, and sociology. We have hands-on experience in using generative AI tools. As professors, postdocs, doctoral candidates, and students, we constantly innovate our teaching and learning. Fully embracing the chances and challenges of generative AI requires adding further perspectives from scholars in various other disciplines (focusing on didactics of higher education and legal aspects), university administrations, and broader student groups. Overall, we have a positive picture of generative AI models and tools such as GPT-4 and ChatGPT. As always, there is light and dark, and change is difficult. However, if we issue clear guidelines on the part of the universities, faculties, and individual lecturers, and if lecturers and students use such systems efficiently and responsibly, our higher education system may improve. We see a greatchance for that if we embrace and manage the change appropriately.