Browsing by Subject "Electronic negotiation"

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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, Annika
Standardised 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.
Opportunities and challenges of blockchain technology for negotiation support systems
(2025) Witt, Josepha; Schoop, Mareike; Knaus, Konstantin
Blockchain Technology (BCT) is the backbone of the next generation of the internet and thus affects how electronic business (e-business) is conducted. While the usage of BCT for the initiation and transaction phases in e-business has been studied, the negotiation aspect has not been considered in a comprehensive manner. The current literature on the utilisation of BCT in electronic negotiations (e-negotiations) primarily focuses on autonomous agents and lacks research on the support of e-negotiations conducted by human negotiators using negotiation support systems (NSSs). This results in the issue that the consequences of a transition to Web3.0-based NSSs are unclear, while other areas of e-business already apply Web3.0 technologies. We address this lack of knowledge following a design-oriented approach in three steps exploring the opportunities and challenges of using BCT for e-negotiations via NSSs. Firstly, the well-established negotiation support system Negoisst is extended by BCT features resulting in the development of a Web3.0-based NSS called NegoisstBCT to demonstrate the technical feasibility of this approach. Secondly, the potential opportunities and challenges of a Blockchain-based NSS are analysed referring to its technical architecture. Thirdly, a generalised view of the application of Web3.0-based NSSs in different settings is taken, discussing future research on BCT in e-negotiations. The present research thus fosters the application of Blockchain-based NSSs in e-negotiations and of NSSs in BCT application areas.
Sentiment analysis in electronic negotiations
(2017) Körner, Michael; Schoop, Mareike
The 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.