@inproceedings{13587,
  author       = {{Gutt, Dominik and Neumann, Jürgen and Jabr, W. and Kundisch, Dennis}},
  booktitle    = {{Proceedings of the 40th International Conference on Information Systems (ICIS)}},
  location     = {{Munich, Germany}},
  title        = {{{The App Updating Conundrum: Implications of Platform’s Rating Resetting on Developers’ Behavior}}},
  year         = {{2019}},
}

@inproceedings{2660,
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
  booktitle    = {{Conference Abstracts of the Symposium on Statistical Challenges in Electronic Commerce Research (SCECR)}},
  location     = {{Rotterdam, Netherland}},
  title        = {{{The Traveling Reviewer Problem - Exploring the Relationship Between Offline Locations and Online Rating Behavior}}},
  year         = {{2018}},
}

@inproceedings{4520,
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
  booktitle    = {{Workshop on IS Design and Economic Behavior (ISDEB)}},
  location     = {{Lüneburg, Germany}},
  title        = {{{The Traveling Reviewer Problem - Exploring the Relationship Between Offline Locations and Online Rating Behavior}}},
  year         = {{2018}},
}

@inproceedings{4364,
  author       = {{Neumann, Jürgen}},
  booktitle    = {{INFORMS Conference on Information Systems and Technology (CIST)}},
  location     = {{Phoenix, Arizona, USA}},
  title        = {{{The Economics of Online Reviews in Markets with Variety-Seeking Consumers}}},
  year         = {{2018}},
}

@inproceedings{1060,
  abstract     = {{With a growing number of online reviews, it becomes increasingly important for customers and online review platforms to find groups of reviewers who write useful reviews. Customers who review local offline businesses such as restaurants can identify themselves as locals or travelers and thus implicitly assign themselves to a specific reviewer group. This study investigates the relationship between identifying as a local and the perceived usefulness of their online reviews. Using data from Yelp.com, we empirically test hypotheses derived from attribution theory. Our results suggest that neutral and negative reviews by locals tend to be perceived as more useful than reviews by travelers. Positive reviews by locals, however, are not perceived as more useful. These findings provide significant practical implications for online review platforms and local offline businesses.}},
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis and van Straaten, Dirk}},
  booktitle    = {{Proceedings of the Multikonferenz Wirtschaftsinformatik 2018 (MKWI), Lüneburg, Germany}},
  title        = {{{When Local Praise Becomes Cheap Talk - Analyzing the Relationship between Reviewer Location and Usefulness of Online Reviews}}},
  year         = {{2018}},
}

@inproceedings{2683,
  author       = {{Kundisch, Dennis and Neumann, Jürgen and Schlangenotto, Darius}},
  booktitle    = {{Proceedings der 15. e-Learning Fachtagung Informatik (DELFI 2017)}},
  location     = {{Chemnitz}},
  title        = {{{Bitte stimmen Sie jetzt ab! - Ein Erfahrungsbericht über das Audience Response System PINGO}}},
  year         = {{2017}},
}

@inproceedings{53,
  abstract     = {{Amongst the growing body of literature on the drivers of online ratings, the influence of
customers’ local offline environment on their ratings has largely been neglected. This
study examines the relationship between ratings made outside of a customer’s home area
and the magnitude of online ratings. We employ a data-driven identification of a
customer’s geographic home area and use variation in this variable to identify the
consequences for the magnitude of ratings. In line with our theory, we find that customers
who rate while traveling give, on average, higher ratings than locals. However, this
relationship is moderated by the posting time of a review relative to consumption, as
travelers post more negative ratings during or shortly after consumption. These
relationships are most pronounced for customers who travel and rate less frequently. Our
results come with substantial implications for a business’s average rating and for
customer decision making. }},
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
  booktitle    = {{Proceedings of the 38th International Conference on Information Systems (ICIS)}},
  location     = {{Seoul, South Korea}},
  title        = {{{The Traveling Reviewer Problem – Exploring the Relationship Between Offline Locations and Online Rating Behavior}}},
  year         = {{2017}},
}

@inproceedings{54,
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
  booktitle    = {{INFORMS Annual Meeting}},
  location     = {{Houston, USA}},
  title        = {{{The Traveling Reviewer Problem – Exploring the Relationship between Offline Locations and Online Rating Behavior}}},
  year         = {{2017}},
}

@inproceedings{126,
  abstract     = {{Optimal price setting in peer-to-peer markets featuring online ratings requires incorporating interactions between prices and ratings. Additionally, recent literature reports that online ratings in peer-to-peer markets tend to be inflated overall, undermining the reliability of online ratings as a quality signal. This study proposes a two-period model for optimal price setting that takes (potentially inflated) ratings into account. Our theoretical findings suggest that sellers in the medium-quality segment have an incentive to lower first-period prices to monetize on increased second-period ratings and that the possibility on monetizing on second-period ratings depends on the reliability of the rating system. Additionally, we find that total profits and prices increase with online ratings and additional quality signals. Empirically, conducting Difference-in-Difference regressions on a comprehensive panel data set from Airbnb, we can validate that price increases lead to lower ratings, and we find empirical support for the prediction that additional quality signals increase prices. Our work comes with substantial implications for sellers in peer-to-peer markets looking for an optimal price setting strategy. Moreover, we argue that our theoretical finding on the weights between online ratings and additional quality signals translates to conventional online markets.}},
  author       = {{Neumann, Jürgen and Gutt, Dominik}},
  booktitle    = {{Proceedings of the 25th Conference on Information Systems (ECIS)}},
  location     = {{Guimaraes, Portugal}},
  title        = {{{A Homeowner’s Guide to Airbnb: Theory and Empirical Evidence for Optimal Pricing Conditional on Online Ratings}}},
  year         = {{2017}},
}

@inproceedings{127,
  author       = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
  location     = {{Houston, USA}},
  title        = {{{A Homeowner’s Guide to Airbnb: Theory and Empirical Evidence for Optimal Pricing Conditional on Online Ratings}}},
  year         = {{2017}},
}

@article{2467,
  author       = {{Bach, Christoph and Kundisch, Dennis and Neumann, Jürgen and Schlangenotto, Darius and Whittaker, Michael}},
  journal      = {{HMD Praxis der Wirtschaftsinformatik}},
  number       = {{4}},
  pages        = {{486--498}},
  title        = {{{Dokumentenorientierte NoSQL-Datenbanken in skalierbaren Webanwendungen - Eine Analyse am Beispiel von MongoDB und der Webanwendung PINGO}}},
  volume       = {{53}},
  year         = {{2016}},
}

@inproceedings{2755,
  author       = {{Kundisch, Dennis and Herrmann, Philipp and Whittaker, Michael and Neumann, Jürgen and Magenheim, J. and Reinhardt, W. and Beutner, Marc and Zoyke, A.}},
  booktitle    = {{Proceedings of the Design Science Research in Information Systems and Technologies 2013 (DESRIST)}},
  location     = {{Helsinki, Finland}},
  publisher    = {{Springer}},
  title        = {{{Designing a Web-Based Classroom Response System}}},
  volume       = {{7939}},
  year         = {{2013}},
}