
@book{abdollahpouriPersonalizationResearchDirections2019,
  abstract = {Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes. As the reach of recommender systems has extended, it has become apparent that the single-minded focus on the user common to academic research has obscured other important aspects of recommendation outcomes. Properties such as fairness, balance, profitability, and reciprocity are not captured by typical metrics for recommender system evaluation. The concept of multistakeholder recommendation has emerged as a unifying framework for describing and understanding recommendation settings where the end user is not the sole focus. This article describes the origins of multistakeholder recommendation, and the landscape of system designs. It provides illustrative examples of current research, as well as outlining open questions and research directions for the field.},
  author = {Abdollahpouri, Himan and Adomavicius, Gediminas and Burke, Robin and Guy, Ido and Jannach, Dietmar and Kamishima, Toshihiro and Krasnodebski, Jan and Pizzato, Luiz},
  date = {2019-05-01},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\YXJISA5R\\Abdollahpouri et al_2019_Beyond Personalization.pdf},
  shorttitle = {Beyond {{Personalization}}},
  title = {Beyond {{Personalization}}: {{Research Directions}} in {{Multistakeholder Recommendation}}}
}

@inproceedings{andrzejakSoftwareConfigurationDiagnosis2018,
  abstract = {As software systems become more complex and featurerich, configuration mechanisms are needed to adapt them to different execution environments and usage profiles. As a consequence, failures due to erroneous configuration settings are becoming more common, calling for effective mechanisms for diagnosis, repair, and prevention of such issues. In this paper, we survey approaches for diagnosing software configuration errors, methods for debugging these errors, and techniques for testing against such issues. In addition, we outline current challenges of isolating and fixing faults in configuration settings, including improving fault localization, handling the case of multi-stack systems, and configuration verification at runtime.},
  author = {Andrzejak, Artur and Friedrich, Gerhard and Wotawa, Franz},
  booktitle = {Proceedings~of~ the~20th~{{International~Configuration~Workshop}}},
  date = {2018},
  eventtitle = {20th {{International Workshop}} on {{Configuration}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\9Z76QC7P\\Andrzejak et al. - Software Conﬁguration Diagnosis – A Survey of Exis.pdf},
  langid = {english},
  pages = {85-92},
  title = {Software {{Configuration Diagnosis}} \textendash{} {{A Survey}} of {{Existing Methods}} and {{Open Challenges}}},
  url = {http://confws.ist.tugraz.at}
}

@article{article,
  author = {Mendon{\c c}a, Marc\'ilio and Cowan, Donald and Malyk, William and Oliveira, Toacy},
  date = {2008-01},
  journaltitle = {JSW},
  pages = {69-82},
  title = {Collaborative Product Configuration: Formalization and Efficient Algorithms for Dependency Analysis.},
  volume = {3}
}

@inproceedings{atasItemRecommendationUsing2017,
  abstract = {The intensity of domain knowledge exchange among group members is an important factor that directly influences group decision quality. The more frequent information is exchanged among group members, the higher the quality of the corresponding decision. In this paper we present results of an empirical study conducted with groups of students \textendash{} the task of each group was to take a decision regarding the exam topics the group prefers. This group decision had to be taken on the basis of a group decision support environment with included recommendation functionality and a discussion forum that allows for information exchange among group members. Depending on the included variant of the group recommendation algorithm, groups received recommendations that varied in terms of recommendation diversity. The results of the study show that increased recommendation diversity leads to an increased degree of information exchange among group members.},
  author = {Atas, M\"usl\"um and Felfernig, Alexander and Stettinger, Martin and Tran, Thi Ngoc Trang},
  booktitle = {Social {{Informatics}}},
  date = {2017},
  doi = {10.1007/978-3-319-67256-4_29},
  editor = {Ciampaglia, Giovanni Luca and Mashhadi, Afra and Yasseri, Taha},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\JEFM2ATK\\Atas et al_2017_Beyond Item Recommendation.pdf},
  isbn = {978-3-319-67256-4},
  keywords = {Decision quality,Group decision making,Group recommender systems,Information exchange},
  langid = {english},
  location = {{Cham}},
  pages = {368-377},
  publisher = {{Springer International Publishing}},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  shorttitle = {Beyond {{Item Recommendation}}},
  title = {Beyond {{Item Recommendation}}: {{Using Recommendations}} to {{Stimulate Knowledge Sharing}} in {{Group Decisions}}}
}

@inproceedings{atasLiquidDemocracyGroupbased2018,
  abstract = {Group-based configuration systems support scenarios where a group of users configures a product/service. In those groupbased configuration scenarios where the knowledge of some group members regarding items is insufficient, an advice of experts is necessary in order to help members to evaluate products or services. This paper introduces a novel approach which takes advantage of the concept of liquid democracy that allows the delegation of group member votes to experts. Concerning the application of liquid democracy, we propose a new approach based on Multi-attribute Utility theory (MAUT)-based evaluation used to calculate the utility of configurable items. Compared to the traditional approach, the proposed MAUT-based evaluation focuses on the role of experts by assigning higher weights to them. Additionally, the respective expertise level of the experts is taken into account. Consequently, the main contribution of this paper consists in the improvement of group-based configuration by taking liquid democracy aspects into consideration.},
  author = {Atas, Muesluem and Tran, Thi Ngoc Trang and Samer, Ralph and Felfernig, Alexander and Stettinger, Martin and Fucci, Davide},
  date = {2018},
  eventtitle = {{{ConfWS}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\95YRVV9G\\Atas et al. - Liquid Democracy in Group-based Conﬁguration.pdf},
  langid = {english},
  pages = {93-98},
  title = {Liquid {{Democracy}} in {{Group}}-Based {{Configuration}}}
}

@inproceedings{atasSociallyAwareDiagnosisConstraintBased2019,
  abstract = {Constraint-based group recommender systems support the identification of items that best match the individual preferences of all group members. In cases where the requirements of the group members are inconsistent with the underlying constraint set, the group needs to be supported such that an appropriate solution can be found. In this paper, we present a guided approach that determines socially-aware diagnoses based on different aggregation functions. We analyzed the prediction quality of different aggregation functions by using data collected in a user study. The results indicate that those diagnoses guided by the Least Misery aggregation function achieve a higher prediction quality compared to the Average Voting, Most Pleasure, and Majority Voting. Moreover, another major outcome of our work reveals that diagnoses based on aggregation functions outperform basic approaches such as Breadth First Search and Direct Diagnosis.},
  author = {Atas, Muesluem and Samer, Ralph and Felfernig, Alexander and Tran, Thi Ngoc Trang and Erdeniz, Seda Polat and Stettinger, Martin},
  booktitle = {Proceedings of the 27th {{ACM Conference}} on {{User Modeling}}, {{Adaptation}} and {{Personalization}}  - {{UMAP}} '19},
  date = {2019},
  doi = {10.1145/3320435.3320436},
  eventtitle = {The 27th {{ACM Conference}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\3CYBXHM5\\Atas et al. - 2019 - Socially-Aware Diagnosis for Constraint-Based Reco.pdf},
  langid = {english},
  location = {{Larnaca, Cyprus}},
  pages = {121-129},
  publisher = {{ACM Press}},
  title = {Socially-{{Aware Diagnosis}} for {{Constraint}}-{{Based Recommendation}}}
}

@thesis{benzMoeglichkeitenIntelligenterEmpfehlungssysteme2017,
  author = {Benz, Daniel},
  date = {2017-09-14},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\8HENYXLR\\Benz - Karlsruhe, 13. September 2017.pdf},
  institution = {{Hochschule Karlsruhe \textendash{} Technik und Wirtschaft}},
  langid = {german},
  location = {{Kalrsruhe}},
  pagetotal = {115},
  title = {M\"oglichkeiten intelligenter Empfehlungssysteme in der Produktkonfikuration},
  type = {Master's thesis}
}

@article{bonnerEffectsMemberExpertise2002,
  abstract = {This study assesses the effects of member expertise on group decision-making and group performance. Three-person cooperative groups and three independent individuals solved either an easy or moderately difficult version of the deductive logic game Mastermind. Experimental groups were given veridical performance information, i.e., the members' rankings on prior individual administrations of the task. Control groups were not provided with this information. Results supported the predictions of this study: (1) groups gave more weight to the input of their highest performing members with the group decision-making process being best approximated by post hoc ``expert weighted'' social decision schemes and (2) groups performed at the level of the best of an equivalent number of individuals. \'O 2002 Elsevier Science (USA). All rights reserved.},
  author = {Bonner, Bryan L and Baumann, Michael R and Dalal, Reeshad S},
  date = {2002-07},
  doi = {10.1016/S0749-5978(02)00010-9},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\EQHEQVEN\\Bonner et al. - 2002 - The effects of member expertise on group decision-.pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  number = {2},
  pages = {719-736},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  title = {The Effects of Member Expertise on Group Decision-Making and Performance},
  volume = {88}
}

@article{brodbeckDisseminationCriticalUnshared2002,
  abstract = {Previous research in group decision making has found that in situations of a hidden profile (i.e. the best choice alternative is hidden from individual members as they consider their pre-discussion information), unshared information is disproportionately neglected and sub-optimal group choices are highly likely. In an experimental study, three-person groups decided which of three candidates to select for a professorial appointment. We hypothesised that minority dissent in pre-discussion preferences improves the consideration of unshared information in groups and increases the discovery rate of hidden profiles. As predicted, consideration of unshared information increased with minority dissent. The expectation of an improvement of group decision quality was partially supported. In diversity groups (i.e. each member prefers a different alternative) consideration of unshared information and group decision quality was significantly higher than in simple minority groups. Results are discussed in the light of theories of minority influence. The benefits of using the hidden profile paradigm with minority and diversity groups for theory development in the area of group decision making are highlighted. Copyright \textcopyright{} 2002 John Wiley \& Sons, Ltd.},
  author = {Brodbeck, Felix C. and Kerschreiter, Rudolf and Mojzisch, Andreas and Frey, Dieter and Schulz-Hardt, Stefan},
  date = {2002},
  doi = {10.1002/ejsp.74},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\DTVUVFD5\\ejsp.html},
  issn = {1099-0992},
  journaltitle = {European Journal of Social Psychology},
  langid = {english},
  number = {1},
  pages = {35-56},
  shorttitle = {The Dissemination of Critical, Unshared Information in Decision-Making Groups},
  title = {The Dissemination of Critical, Unshared Information in Decision-Making Groups: The Effects of Pre-Discussion Dissent},
  volume = {32}
}

@article{burkeHybridRecommenderSystems2002,
  abstract = {Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine. They have become fundamental applications in electronic commerce and information access, providing suggestions that effectively prune large information spaces so that users are directed toward those items that best meet their needs and preferences. A variety of techniques have been proposed for performing recommendation, including content-based, collaborative, knowledge-based and other techniques. To improve performance, these methods have sometimes been combined in hybrid recommenders. This paper surveys the landscape of actual and possible hybrid recommenders, and introduces a novel hybrid, EntreeC, a system that combines knowledge-based recommendation and collaborative \textcent{}ltering to recommend restaurants. Further, we show that semantic ratings obtained from the knowledge-based part of the system enhance the effectiveness of collaborative \textcent{}ltering.},
  author = {Burke, Robin},
  date = {2002},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\7DKPN9IX\\Burke - Hybrid Recommender Systems Survey and Experiments.pdf},
  journaltitle = {User modeling and user-adapted interaction},
  langid = {english},
  number = {4},
  pages = {331-370},
  title = {Hybrid {{Recommender Systems}}: {{Survey}} and {{Experiments}}},
  volume = {12}
}

@article{carboneIndividualVsGroup2019,
  abstract = {This paper focuses on the comparison of individual and group decision making, in a stochastic inter-temporal problem in two decision environments, namely risk and ambiguity. Using a consumption/saving laboratory experiment, we investigate behaviour in four treatments: (1) individual choice under risk; (2) group choice under risk; (3) individual choice under ambiguity and (4) group choice under ambiguity. Comparing decisions within and between decision environments, we find an anti-symmetric pattern. While individuals are choosing on average closer to the theoretical optimal predictions, compared to groups in the risk treatments, groups tend to deviate less under ambiguity. Within decision environments, individuals deviate more when they choose under ambiguity, while groups are better planners under ambiguity rather than under risk. Our results extend the often observed pattern of individuals (groups) behaving more optimally under risk (ambiguity), to its dynamic dimension.},
  author = {Carbone, Enrica and Georgalos, Konstantinos and Infante, Gerardo},
  date = {2019-07},
  doi = {10.1007/s11238-019-09694-8},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\QMM4YRBJ\\Carbone et al. - 2019 - Individual vs. group decision-making an experimen.pdf},
  issn = {0040-5833, 1573-7187},
  journaltitle = {Theory and Decision},
  langid = {english},
  number = {1},
  pages = {87-122},
  shortjournal = {Theory Decis},
  shorttitle = {Individual vs. Group Decision-Making},
  title = {Individual vs. Group Decision-Making: An Experiment on Dynamic Choice under Risk and Ambiguity},
  volume = {87}
}

@online{CASSoftwareAG,
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\2JDND869\\cas-software-ag.html},
  title = {{{CAS Software AG}}},
  type = {Company Website},
  url = {https://www.cas.de/en/company/cas-software-ag.html},
  urldate = {2019-11-13}
}

@article{charnessGroupsMakeBetter2012,
  author = {Charness, Gary and Sutter, Matthias},
  date = {2012-08},
  doi = {10.1257/jep.26.3.157},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\43PXHXSK\\Charness und Sutter - 2012 - Groups Make Better Self-Interested Decisions.pdf},
  issn = {0895-3309},
  journaltitle = {Journal of Economic Perspectives},
  keywords = {group-decisions},
  langid = {english},
  number = {3},
  pages = {157-176},
  shortjournal = {Journal of Economic Perspectives},
  title = {Groups {{Make Better Self}}-{{Interested Decisions}}},
  volume = {26}
}

@article{charnessSilenceGoldenTeam2019,
  abstract = {We conduct experiments comparing the performance of individuals and teams of four subjects in solving two rather different tasks. The first involves nonograms (numerical logic puzzle). Here the solution requires a series of incremental steps. The second task uses CRT-type questions, which require a single, specific insight. Contrary to the existing literature, team performance in both tasks is statistically indistinguishable from that of individuals when there is no cost to sending a message. If a tiny message cost is imposed, team performance improves and becomes statistically better than that of individuals, although still worse than previous research on teams would have suggested. Message costs reduce the quantity of messages but increase the quality, specifically the mix of good and bad suggestions. The improved quality of communication with message costs allows teams to outperform individuals.},
  author = {Charness, Gary and Cooper, David J. and Grossman, Zachary},
  date = {2019-10-19},
  doi = {10.1007/s10683-019-09627-w},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\L24AG7GK\\Charness et al. - 2019 - Silence is golden team problem solving and commun.pdf},
  issn = {1386-4157, 1573-6938},
  journaltitle = {Experimental Economics},
  langid = {english},
  shortjournal = {Exp Econ},
  shorttitle = {Silence Is Golden},
  title = {Silence Is Golden: Team Problem Solving and Communication Costs}
}

@inproceedings{chenEmpatheticonsDesigningEmotion2014,
  abstract = {Group recommender systems help users to find items of interest collaboratively. Support for such collaboration has been mainly provided by tools that visualize membership awareness, preference awareness and decision awareness. However, these mechanisms do not address group dynamic issues: how member may affect each other. In this paper, we investigate the roles of emotion awareness tools and how they may enable positive group dynamics. We first describe the design process behind a set of dynamic emoticons, which we call empatheticons. We then show that they allow users to represent, annotate, and visualize group members' emotions in GroupFun, a group music recommender. An in-depth user study (N = 18) with GroupFun demonstrates that users' emotion annotation for recommended songs can be influenced by other group members. Most importantly, empatheticons enhance users' perceptions of the connectedness (immediacy) and familiarity (intimacy) with each other and the positive group dynamics.},
  author = {Chen, Yu and Ma, Xiaojuan and Cerezo, Alfredo and Pu, Pearl},
  booktitle = {Proceedings of the {{XV International Conference}} on {{Human Computer Interaction}} - {{Interacci\'on}} '14},
  date = {2014},
  doi = {10.1145/2662253.2662269},
  eventtitle = {The {{XV International Conference}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\5U62TD2Q\\Chen et al. - 2014 - Empatheticons Designing Emotion Awareness Tools f.pdf},
  isbn = {978-1-4503-2880-7},
  langid = {english},
  location = {{Puerto de la Cruz, Tenerife, Spain}},
  pages = {1-8},
  publisher = {{ACM Press}},
  shorttitle = {Empatheticons},
  title = {Empatheticons: {{Designing Emotion Awareness Tools}} for {{Group Recommenders}}}
}

@inproceedings{chenInterfaceInteractionDesign2011,
  abstract = {Group and social recommender systems aim to recommend items of interest to a group or a community of people. The user issues in such systems cannot be addressed by examining the satisfaction of their members as individuals. Rather, group satisfaction should be studied as a result of the interaction and interface methods that support group dynamics and interaction. In this paper, we survey the state-of-the-art in user experience design of group and social recommender systems. We further apply the techniques used in the current recommender systems to GroupFun, a music social group recommender system. After presenting the interface and interaction characteristics of GroupFun, we further analyze the design space and propose areas for future research in pursuit of an affective recommender.},
  author = {Chen, Yu},
  booktitle = {Proceedings of the Fifth {{ACM}} Conference on {{Recommender}} Systems - {{RecSys}} '11},
  date = {2011},
  doi = {10.1145/2043932.2044007},
  eventtitle = {The Fifth {{ACM}} Conference},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\BXIV2L5C\\Chen - 2011 - Interface and interaction design for group and soc.pdf},
  isbn = {978-1-4503-0683-6},
  langid = {english},
  location = {{Chicago, Illinois, USA}},
  pages = {363},
  publisher = {{ACM Press}},
  title = {Interface and Interaction Design for Group and Social Recommender Systems}
}

@inproceedings{choudharyMulticriteriaGroupRecommender2020,
  abstract = {Current researches have demonstrated that the significance of Multi-Criteria Decision-Making (MCDM) methods in Group Recommender Systems (GRSs) has yet to be thoroughly discovered. Thus, we have proposed a Multi-criteria GRS (MCGRS) to provide recommendations for group of users based on multi-criteria optimization. The idea behind our approach is that, each member in a group have different opinions about each criterion and he/she would try to make the best use of multi-criteria to fulfill his/her own preference in decision-making process. Therefore, we have employed Analytical Hierarchy Process (AHP) to learn the priority of each criterion to maximize the utility for each criterion. Then, MCGRS generate the most appropriate recommendation for the group. Experiments are performed on Yahoo! Movies dataset and the results of comparative analysis of proposed MCGRS with baseline GRSs techniques clearly demonstrate the supremacy of our proposed model.},
  author = {Choudhary, Nirmal and Bharadwaj, K. K.},
  booktitle = {Smart {{Systems}} and {{IoT}}: {{Innovations}} in {{Computing}}},
  date = {2020},
  doi = {10.1007/978-981-13-8406-6_8},
  editor = {Somani, Arun K. and Shekhawat, Rajveer Singh and Mundra, Ankit and Srivastava, Sumit and Verma, Vivek Kumar},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\EFVTG9VE\\Choudhary_Bharadwaj_2020_Multi-criteria Group Recommender System Based on Analytical Hierarchy Process.pdf;C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\GCKZA5ZN\\2018_MA_Rubinshteyn_Hybrider Recommender für die Produktkonfiguration.pdf},
  isbn = {9789811384066},
  keywords = {Analytical hierarchy process,Decision-making,Multi-criteria group recommender systems,Recommendation mechanism},
  langid = {english},
  location = {{Singapore}},
  pages = {75-84},
  publisher = {{Springer}},
  series = {Smart {{Innovation}}, {{Systems}} and {{Technologies}}},
  title = {Multi-Criteria {{Group Recommender System Based}} on {{Analytical Hierarchy Process}}}
}

@incollection{choudharyMulticriteriaGroupRecommender2020a,
  abstract = {Current researches have demonstrated that the significance of MultiCriteria Decision-Making (MCDM) methods in Group Recommender Systems (GRSs) has yet to be thoroughly discovered. Thus, we have proposed a Multi-criteria GRS (MCGRS) to provide recommendations for group of users based on multicriteria optimization. The idea behind our approach is that, each member in a group have different opinions about each criterion and he/she would try to make the best use of multi-criteria to fulfill his/her own preference in decision-making process. Therefore, we have employed Analytical Hierarchy Process (AHP) to learn the priority of each criterion to maximize the utility for each criterion. Then, MCGRS generate the most appropriate recommendation for the group. Experiments are performed on Yahoo! Movies dataset and the results of comparative analysis of proposed MCGRS with baseline GRSs techniques clearly demonstrate the supremacy of our proposed model.},
  author = {Choudhary, Nirmal and Bharadwaj, K. K.},
  booktitle = {Smart {{Systems}} and {{IoT}}: {{Innovations}} in {{Computing}}},
  date = {2020},
  doi = {10.1007/978-981-13-8406-6_8},
  editor = {Somani, Arun K. and Shekhawat, Rajveer Singh and Mundra, Ankit and Srivastava, Sumit and Verma, Vivek Kumar},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\NN5RCJY2\\Choudhary und Bharadwaj - 2020 - Multi-criteria Group Recommender System Based on A.pdf},
  isbn = {9789811384059 9789811384066},
  langid = {english},
  location = {{Singapore}},
  pages = {75-84},
  publisher = {{Springer Singapore}},
  title = {Multi-Criteria {{Group Recommender System Based}} on {{Analytical Hierarchy Process}}},
  volume = {141}
}

@inproceedings{cosley2003seeing,
  author = {Cosley, Dan and Lam, Shyong K and Albert, Istvan and Konstan, Joseph A and Riedl, John},
  booktitle = {Proceedings of the {{SIGCHI}} Conference on {{Human}} Factors in Computing Systems},
  date = {2003},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\X5WCB36N\\Cosley et al_2003_Is seeing believing.pdf},
  organization = {{ACM}},
  pages = {585-592},
  title = {Is Seeing Believing?: How Recommender System Interfaces Affect Users' Opinions}
}

@article{crottGroupDecisionChoice1991,
  author = {Crott, Helmut W and Szilvas, Klaus and Zuber, Johannes A},
  date = {1991-06},
  doi = {10.1016/0749-5978(91)90040-Z},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\CXGJWE27\\Crott et al. - 1991 - Group decision, choice shift, and polarization in .pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  number = {1},
  pages = {22-41},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  shorttitle = {Group Decision, Choice Shift, and Polarization in Consulting, Political, and Local Political Scenarios},
  title = {Group Decision, Choice Shift, and Polarization in Consulting, Political, and Local Political Scenarios: {{An}} Experimental Investigation and Theoretical Analysis},
  volume = {49}
}

@inproceedings{delgadoSimpleObjectivesWork2019,
  author = {Delgado, Joaquin and Lind, Samuel and Radecke, Carl and Konijeti, Satish},
  booktitle = {Proceedings of the {{Workshop}} on {{Recommendation}} in {{Multi}}-Stakeholder {{Environments}}},
  date = {2019-09-20},
  eventtitle = {{{RMSE}} 2019},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\6CPFZC8M\\Delgado et al_2019_Simple Objectives Work Better.pdf},
  location = {{Copenhagen, Denmark}},
  title = {Simple {{Objectives Work Better}}}
}

@article{delicResearchMethodsGroup2016,
  abstract = {In this article we argue that the research on group recommender systems must look more carefully at group dynamics in decision making in order to produce technologies that will be truly beneficial for users. Hence, we illustrate a user study method aimed at observing and measuring the evolution of user preferences and actions in a tourism decision making task: finding a destination to visit. We discuss the benefits and caveats of such an observational study method and we present the implications that the derived data and findings may have on the design of interactive group recommender systems.},
  author = {Delic, Amra and Neidhardt, Julia and Nguyen, Thuy Ngoc},
  date = {2016},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\IXW2MLZP\\Delic et al. - Research Methods for Group Recommender Systems.pdf},
  keywords = {group recommender,methods},
  langid = {english},
  pages = {8},
  title = {Research {{Methods}} for {{Group Recommender Systems}}}
}

@article{elahiSurveyActiveLearning2016,
  abstract = {In collaborative filtering recommender systems user's preferences are expressed as ratings for items, and each additional rating extends the knowledge of the system and affects the system's recommendation accuracy. In general, the more ratings are elicited from the users, the more effective the recommendations are. However, the usefulness of each rating may vary significantly, i.e., different ratings may bring a different amount and type of information about the user's tastes. Hence, specific techniques, which are defined as ``active learning strategies'', can be used to selectively choose the items to be presented to the user for rating. In fact, an active learning strategy identifies and adopts criteria for obtaining data that better reflects users' preferences and enables to generate better recommendations.},
  author = {Elahi, Mehdi and Ricci, Francesco and Rubens, Neil},
  date = {2016-05},
  doi = {10.1016/j.cosrev.2016.05.002},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\4IR8QEFN\\Elahi et al. - 2016 - A survey of active learning in collaborative filte.pdf},
  issn = {15740137},
  journaltitle = {Computer Science Review},
  langid = {english},
  note = {ZSCC: 0000118},
  pages = {29-50},
  shortjournal = {Computer Science Review},
  title = {A Survey of Active Learning in Collaborative Filtering Recommender Systems},
  volume = {20}
}

@article{esserAliveWell251998,
  abstract = {This article provides a summary of empirical research on groupthink theory. Groupthink research, including analyses of historical cases of poor group decision making and laboratory tests of groupthink, is reviewed. Results from these two research areas are briefly compared. Theoretical and methodological issues for future groupthink research are identified and discussed. I conclude that groupthink research has had and continues to have considerable heuristic value. A small, but growing, body of empirical literature has been generated. In addition, groupthink research has stimulated a number of theoretical ideas, most of which have yet to be tested.},
  author = {Esser, James K},
  date = {1998-02-01},
  doi = {10.1006/obhd.1998.2758},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\KMR4CLGA\\Esser_1998_Alive and Well after 25 Years.pdf;C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\NSYG2B7Z\\S0749597898927583.html},
  issn = {0749-5978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  keywords = {group-decisions,groupthink},
  langid = {english},
  number = {2},
  pages = {116-141},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  shorttitle = {Alive and {{Well}} after 25 {{Years}}},
  title = {Alive and {{Well}} after 25 {{Years}}: {{A Review}} of {{Groupthink Research}}},
  volume = {73}
}

@article{falknerRecommendationTechnologiesConfigurable2011,
  abstract = {State of the art recommender systems support users in the selection of items from a predefined assortment (e.g., movies, books, and songs). In contrast to an explicit definition of each individual item, configurable products such as computers, financial service portfolios, and cars are represented in the form of a configuration knowledge base that describes the properties of allowed instances. Although the knowledge representation used is different compared to non-configurable products, the decision support requirements remain the same: users have to be supported in finding a solution that fits their wishes and needs. In this paper we show how recommendation technologies can be applied for supporting the configuration of products. In addition to existing approaches we discuss relevant issues for future research.},
  author = {Falkner, Andreas and Felfernig, Alexander and Haag, Albert},
  date = {2011-10-31},
  doi = {10.1609/aimag.v32i3.2369},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\4QVSX5DQ\\Falkner et al. - 2011 - Recommendation Technologies for Configurable Produ.pdf},
  issn = {0738-4602, 0738-4602},
  journaltitle = {AI Magazine},
  langid = {english},
  number = {3},
  pages = {99},
  shortjournal = {AIMag},
  title = {Recommendation {{Technologies}} for {{Configurable Products}}},
  volume = {32}
}

@incollection{felfernigBiasesGroupDecisions2018,
  abstract = {Decision biases can be interpreted as tendencies to think and act in specific ways that result in a systematic deviation of potentially rational and high-quality decisions. In this chapter, we provide an overview of example decision biases and show possibilities to counteract these. The overview includes (1) biases that exist in both single user and group decision making (decoy effects, serial position effects, framing, and anchoring) and (2) biases that especially occur in the context of group decision making (GroupThink, polarization, and emotional contagion).},
  author = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  booktitle = {Group {{Recommender Systems}} : {{An Introduction}}},
  date = {2018},
  doi = {10.1007/978-3-319-75067-5_8},
  editor = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\NPY64XZ8\\Felfernig et al_2018_Biases in Group Decisions.pdf},
  isbn = {978-3-319-75067-5},
  langid = {english},
  location = {{Cham}},
  pages = {145-155},
  publisher = {{Springer International Publishing}},
  series = {{{SpringerBriefs}} in {{Electrical}} and {{Computer Engineering}}},
  title = {Biases in {{Group Decisions}}}
}

@inproceedings{felfernigConstraintbasedRecommenderSystems2008,
  abstract = {Recommender systems support users in identifying products and services in e-commerce and other information-rich environments. Recommendation problems have a long history as a successful AI application area, with substantial interest beginning in the mid1990s, and increasing with the subsequent rise of e-commerce. Recommender systems research long focused on recommending only simple products such as movies or books; constraint-based recommendation now receives increasing attention due to the capability of recommending complex products and services. In this paper, we first introduce a taxonomy of recommendation knowledge sources and algorithmic approaches. We then go on to discuss the most prevalent techniques of constraint-based recommendation and outline open research issues.},
  author = {Felfernig, A and Burke, R},
  booktitle = {Proceedings of the 10th International Conference on {{Electronic}} Commerce},
  date = {2008},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\BBYQH8IW\\Felfernig und Burke - Constraint-based Recommender Systems Technologies.pdf},
  langid = {english},
  pages = {3},
  title = {Constraint-Based {{Recommender Systems}}: {{Technologies}} and {{Research Issues}}}
}

@incollection{felfernigDecisionTasksBasic2018,
  abstract = {Recommender systems are decision support systems helping users to identify one or more items (solutions) that fit their wishes and needs. The most frequent application of recommender systems nowadays is to propose items to individual users. However, there are many scenarios where a group of users should receive a recommendation. For example, think of a group decision regarding the next holiday destination or a group decision regarding a restaurant to visit for a joint dinner. The goal of this book is to provide an introduction to group recommender systems, i.e., recommender systems that determine recommendations for groups. In this chapter, we provide an introduction to basic types of recommendation algorithms for individual users and characterize related decision tasks. This introduction serves as a basis for the introduction of group recommendation algorithms in Chap. 2.},
  author = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  booktitle = {Group {{Recommender Systems}} : {{An Introduction}}},
  date = {2018},
  doi = {10.1007/978-3-319-75067-5_1},
  editor = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\745225S2\\Felfernig et al_2018_Decision Tasks and Basic Algorithms.pdf},
  isbn = {978-3-319-75067-5},
  langid = {english},
  location = {{Cham}},
  pages = {3-26},
  publisher = {{Springer International Publishing}},
  series = {{{SpringerBriefs}} in {{Electrical}} and {{Computer Engineering}}},
  title = {Decision {{Tasks}} and {{Basic Algorithms}}}
}

@inproceedings{felfernigGroupDecisionSupport2011,
  abstract = {Requirements engineering is one of the most critical phases in software development. Requirements verbalize decision alternatives that are negotiated by stakeholders. In this paper we present the results of an empirical analysis of the effects of applying group recommendation technologies to requirements negotiation. This analysis has been conducted within the scope of software development projects at our university where development teams were supported with group recommendation technologies when deciding which requirements should be implemented. A major result of the study is that group recommendation technologies can improve the perceived usability (in certain cases) and the perceived quality of decision support. Furthermore, it is not recommended to disclose preferences of individual group members at the beginning of a decision process \textendash{} this could lead to an insufficient exchange of decision-relevant information.},
  author = {Felfernig, Alexander and Zehentner, Christoph and Ninaus, Gerald and Grabner, Harald and Maalej, Walid and Pagano, Dennis and Weninger, Leopold and Reinfrank, Florian},
  date = {2011},
  eventtitle = {International {{Conference}} on {{User Modeling}}, {{Adaptation}}, and {{Personalization}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\H3ESBD4X\\Felfernig et al. - 2011 - Group Decision Support for Requirements Negotiatio.pdf},
  langid = {english},
  pages = {105-116},
  title = {Group {{Decision Support}} for {{Requirements Negotiation}}}
}

@book{felfernigGroupRecommenderSystems2018,
  abstract = {This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The authors summarize different technologies and applications of group recommender systems. They include an in-depth discussion of state-of-the-art algorithms, an overview of industrial applications, an inclusion of the aspects of decision biases in groups, and corresponding de-biasing approaches. The book includes a discussion of basic group recommendation methods, aspects of human decision making in groups, and related applications. A discussion of open research issues is included to inspire new related research. The book serves as a reference for researchers and practitioners working on group recommendation related topics.},
  author = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  date = {2018},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\HC6C7C89\\Felfernig et al. - 2018 - Group recommender systems an introduction.pdf},
  isbn = {978-3-319-75067-5},
  langid = {english},
  shorttitle = {Group Recommender Systems},
  title = {Group Recommender Systems: An Introduction}
}

@book{felfernigGroupRecommenderSystems2018a,
  abstract = {This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The authors summarize different technologies and applications of group recommender systems. They include an in-depth discussion of state-of-the-art algorithms, an overview of industrial applications, an inclusion of the aspects of decision biases in groups, and corresponding de-biasing approaches. The book includes a discussion of basic group recommendation methods, aspects of human decision making in groups, and related applications. A discussion of open research issues is included to inspire new related research. The book serves as a reference for researchers and practitioners working on group recommendation related topics.},
  author = {Felfernig, Alexander and Boratto, Ludovico and Stettinger, Martin and Tkal{\v c}i{\v c}, Marko},
  date = {2018},
  isbn = {978-3-319-75067-5},
  langid = {english},
  note = {OCLC: 1103789993},
  title = {Group {{Recommender Systems An Introduction}}}
}

@collection{felfernigKnowledgebasedConfigurationResearch2014,
  date = {2014},
  editor = {Felfernig, Alexander and Hotz, Lothar and Bagley, Claire and Tiihonen, Juha},
  isbn = {978-0-12-415817-7},
  langid = {english},
  location = {{Amsterdam}},
  note = {OCLC: 915548311},
  publisher = {{Elsevier/MK, Morgan Kaufmann}},
  shorttitle = {Knowledge-Based Configuration},
  title = {Knowledge-Based Configuration: From Research to Business Cases}
}

@inproceedings{felfernigOpenConfiguration2014,
  abstract = {Configuration technologies are typically applied in closed settings where one (or a small group of) knowledge engineer(s) is in charge of knowledge base development and maintenance. In such settings it is also assumed that only single users configure the corresponding products and services. Nowadays, a couple of scenarios exist that require more openness: it should be possible to cooperatively develop knowledge bases and to jointly configure products and services, even by adding new features or constraints in a flexible fashion. We denote this integration of groups of users into configuration-related tasks as open configuration. In this paper we introduce features of open configuration environments and potential approaches to implement these features.},
  author = {Felfernig, Alexander and Stettinger, Martin and Ninaus, Gerald and Jeran, Michael and Reiterer, Stefan and Falkner, Andreas and Leitner, Gerhard and Tiihonen, Juha},
  date = {2014},
  eventtitle = {Configuration {{Workshop}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\KA3YWQCN\\Felfernig et al. - 2014 - Towards Open Conﬁguration.pdf},
  langid = {english},
  pages = {89-94},
  title = {Towards {{Open Configuration}}}
}

@article{felfernigOpenConfiguration2014a,
  author = {Felfernig, Alexander and Stettinger, Martin and Ninaus, Gerald and Jeran, Michael and Reiterer, Stefan and Falkner, Andreas and Leitner, Gerhard and Tiihonen, Juha},
  date = {2014},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\NAFRZ496\\towards-open-configuration.html},
  langid = {english},
  title = {Towards {{Open Configuration}}},
  url = {https://researchportal.helsinki.fi/en/publications/towards-open-configuration},
  urldate = {2019-10-15}
}

@inproceedings{felfernigPersuasiveRecommendationSerial2007,
  abstract = {Recommender technologies are crucial for the effective support of customers in online sales situations. The state-of-the-art research in recommender systems is not aware of existing theories in the areas of cognitive and decision psychology and thus lacks of deeper understanding of online buying situations. In this paper we present results from user studies related to serial position effects in human memory in the context of knowledge-based recommender applications. We discuss serial position effects on the recall of product descriptions as well as on the probability of product selection. Serial position effects such as primacy and recency are major building blocks of persuasive, next generation knowledge-based recommender systems.},
  author = {Felfernig, A. and Friedrich, G. and Gula, B. and Hitz, M. and Kruggel, T. and Leitner, G. and Melcher, R. and Riepan, D. and Strauss, S. and Teppan, E. and Vitouch, O.},
  booktitle = {Persuasive {{Technology}}},
  date = {2007},
  doi = {10.1007/978-3-540-77006-0_34},
  editor = {de Kort, Yvonne and IJsselsteijn, Wijnand and Midden, Cees and Eggen, Berry and Fogg, B. J.},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\T38JCWRX\\Felfernig et al_2007_Persuasive Recommendation.pdf},
  isbn = {978-3-540-77006-0},
  keywords = {human memory,interactive selling,knowledge-based recommendation,persuasive technologies,recommender systems},
  langid = {english},
  location = {{Berlin, Heidelberg}},
  options = {useprefix=true},
  pages = {283-294},
  publisher = {{Springer}},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  shorttitle = {Persuasive {{Recommendation}}},
  title = {Persuasive {{Recommendation}}: {{Serial Position Effects}} in {{Knowledge}}-{{Based Recommender Systems}}}
}

@inproceedings{felfernigPersuasiveRecommendationSerial2007a,
  abstract = {Recommender technologies are crucial for the effective support of customers in online sales situations. The state-of-the-art research in recommender systems is not aware of existing theories in the areas of cognitive and decision psychology and thus lacks of deeper understanding of online buying situations. In this paper we present results from user studies related to serial position effects in human memory in the context of knowledge-based recommender applications. We discuss serial position effects on the recall of product descriptions as well as on the probability of product selection. Serial position effects such as primacy and recency are major building blocks of persuasive, next generation knowledge-based recommender systems.},
  author = {Felfernig, A. and Friedrich, G. and Gula, B. and Hitz, M. and Kruggel, T. and Leitner, G. and Melcher, R. and Riepan, D. and Strauss, S. and Teppan, E. and Vitouch, O.},
  booktitle = {Persuasive {{Technology}}},
  date = {2007},
  doi = {10.1007/978-3-540-77006-0_34},
  editor = {de Kort, Yvonne and IJsselsteijn, Wijnand and Midden, Cees and Eggen, Berry and Fogg, B. J.},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\FK4JBI59\\Felfernig et al_2007_Persuasive Recommendation.pdf},
  isbn = {978-3-540-77006-0},
  keywords = {human memory,interactive selling,knowledge-based recommendation,persuasive technologies,recommender systems},
  langid = {english},
  location = {{Berlin, Heidelberg}},
  options = {useprefix=true},
  pages = {283-294},
  publisher = {{Springer}},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  shorttitle = {Persuasive {{Recommendation}}},
  title = {Persuasive {{Recommendation}}: {{Serial Position Effects}} in {{Knowledge}}-{{Based Recommender Systems}}}
}

@inproceedings{felfernigProceedings20thInternational,
  author = {Felfernig, Alexander and Tiihonen, Juha and Hotz, Lothar and Stettinger, Martin},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\FW39YC58\\Felfernig et al. - University of Hamburg Hamburger Informatik Technol.pdf},
  langid = {english},
  pages = {132},
  title = {Proceedings of the 20th {{International Configuration Workshop}}}
}

@inproceedings{felferningGroupBasedConfiguration2016,
  author = {Felferning, Alexander and Atas, M\"usl\"um and Tran, Thi Ngoc Trang and Stettinger, Martin},
  date = {2016},
  eventtitle = {International {{Workshop}} on {{Configuration}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\YF83I4TQ\\Felferning et al. - 2016 - Towards Group-Based Configuration.pdf},
  isbn = {979-10-91526-04-3},
  langid = {english},
  location = {{Albi}},
  pages = {69-72},
  publisher = {{\'Ecole des Mines d'Albi-Carmaux}},
  shorttitle = {18th {{International}} Configuration Workshop},
  title = {Towards {{Group}}-{{Based Configuration}}}
}

@article{glogerScrumPradigmenwechselIm2010,
  author = {Gloger, Boris},
  date = {2010-04},
  doi = {10.1007/s00287-010-0426-6},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\JQ3EDHKS\\Gloger - 2010 - Scrum Der Pradigmenwechsel im Projekt- und Produk.pdf},
  issn = {0170-6012, 1432-122X},
  journaltitle = {Informatik-Spektrum},
  langid = {german},
  number = {2},
  pages = {195-200},
  shortjournal = {Informatik Spektrum},
  shorttitle = {Scrum},
  title = {Scrum: Der Pradigmenwechsel im Projekt- und Produktmanagement \textendash{} Eine Einf\"uhrung},
  volume = {33}
}

@article{hernandezdelolmoEvaluationRecommenderSystems2008,
  abstract = {It is difficult to deny that comparison between recommender systems requires a common way for evaluating them. Nevertheless, at present, they have been evaluated in many, often incompatible, ways. We affirm this problem is mainly due to the lack of a common framework for recommender systems, a framework general enough so that we may include the whole range of recommender systems to date, but specific enough so that we can obtain solid results. In this paper, we propose such a framework, attempting to extract the essential features of recommender systems. In this framework, the most essential feature is the objective of the recommender system. What is more, in this paper, recommender systems are viewed as applications with the following essential objective. Recommender systems must: (i) choose which (of the items) should be shown to the user, (ii) decide when and how the recommendations must be shown. Next, we will show that a new metric emerges naturally from this framework. Finally, we will conclude by comparing the properties of this new metric with the traditional ones. Among other things, we will show that we may evaluate the whole range of recommender systems with this single metric.},
  author = {Hern\'andez del Olmo, F\'elix and Gaudioso, Elena},
  date = {2008-10},
  doi = {10.1016/j.eswa.2007.07.047},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\B5DFYUDA\\Hernández del Olmo und Gaudioso - 2008 - Evaluation of recommender systems A new approach.pdf},
  issn = {09574174},
  journaltitle = {Expert Systems with Applications},
  langid = {english},
  number = {3},
  pages = {790-804},
  shortjournal = {Expert Systems with Applications},
  shorttitle = {Evaluation of Recommender Systems},
  title = {Evaluation of Recommender Systems: {{A}} New Approach},
  volume = {35}
}

@article{herrera-viedmaConsensusSupportSystem2005,
  abstract = {The group decision-making framework with linguistic preference relations is studied. In this context, we assume that there exist several experts who may have different background and knowledge to solve a particular problem and, therefore, different linguistic term sets (multigranular linguistic information) could be used to express their opinions. The aim of this paper is to present a model of consensus support system to assist the experts in all phases of the consensus reaching process of group decision-making problems with multigranular linguistic preference relations. This consensus support system model is based on i) a multigranular linguistic methodology, ii) two consensus criteria, consensus degrees and proximity measures, and iii) a guidance advice system. The multigranular linguistic methodology permits the unification of the different linguistic domains to facilitate the calculus of consensus degrees and proximity measures on the basis of experts' opinions. The consensus degrees assess the agreement amongst all the experts' opinions, while the proximity measures are used to find out how far the individual opinions are from the group opinion. The guidance advice system integrated in the consensus support system model acts as a feedback mechanism, and it is based on a set of advice rules to help the experts change their opinions and to find out which direction that change should follow in order to obtain the highest degree of consensus possible. There are two main advantages provided by this model of consensus support system. Firstly, its ability to cope with group decision-making problems with multigranular linguistic preference relations, and, secondly, the figure of the moderator, traditionally presents in the consensus reaching process, is replaced by the guidance advice system, and in such a way, the whole group decision-making process is automated.},
  author = {Herrera-Viedma, E. and Martinez, L. and Mata, F. and Chiclana, F.},
  date = {2005-10},
  doi = {10.1109/TFUZZ.2005.856561},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\9RI7MLEU\\Herrera-Viedma et al. - 2005 - A Consensus Support System Model for Group Decisio.pdf},
  issn = {1063-6706},
  journaltitle = {IEEE Transactions on Fuzzy Systems},
  langid = {english},
  number = {5},
  pages = {644-658},
  shortjournal = {IEEE Trans. Fuzzy Syst.},
  title = {A {{Consensus Support System Model}} for {{Group Decision}}-{{Making Problems With Multigranular Linguistic Preference Relations}}},
  volume = {13}
}

@article{hevnerDesignScienceInformation2004,
  author = {Hevner, Alan and March, Salvatore T. and Park, Jinsoo and Ram, Sudha},
  date = {2004},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\WJHPP9MZ\\Hevner et al. - 2004 - Design Science in Information Systems Research.pdf},
  journaltitle = {MIS Quaterly},
  langid = {english},
  number = {1},
  pages = {75-105},
  title = {Design {{Science}} in {{Information Systems Research}}},
  volume = {28}
}

@article{hevnerRolesDigitalInnovation2019,
  author = {Hevner, Alan and vom Brocke, Jan and Maedche, Alexander},
  date = {2019-02},
  doi = {10.1007/s12599-018-0571-z},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\6AE5NV89\\Hevner et al. - 2019 - Roles of Digital Innovation in Design Science Rese.pdf},
  issn = {2363-7005, 1867-0202},
  journaltitle = {Business \& Information Systems Engineering},
  langid = {english},
  number = {1},
  options = {useprefix=true},
  pages = {3-8},
  shortjournal = {Bus Inf Syst Eng},
  title = {Roles of {{Digital Innovation}} in {{Design Science Research}}},
  volume = {61}
}

@article{hoangthuanConstructionDesignScience2019,
  abstract = {Posing research questions is a fundamental step to guide and direct knowledge development in research. In design science research (DSR), research questions are important to define the scope and the modes of inquiry, characterize the artifacts, and communicate the contributions. Despite the importance of research questions, there are few guidelines on how to construct suitable DSR research questions. We fill this gap by exploring ways of constructing DSR research questions and analyzing the research questions in a sample of 104 DSR publications. The results show that about two thirds of the analyzed DSR publications actually use research questions to link their problem statements to research approaches and that most of the questions are aimed at problem-solving. Based on our analysis, we derive a typology of DSR question formulation to provide guidelines and patterns that help researchers formulate research questions during their DSR projects' duration.},
  author = {Hoang Thuan, Nguyen and Drechsler, Andreas and Antunes, Pedro},
  date = {2019},
  doi = {10.17705/1CAIS.04420},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\B7J5BEGT\\Hoang Thuan et al. - 2019 - Construction of Design Science Research Questions.pdf},
  issn = {15293181},
  journaltitle = {Communications of the Association for Information Systems},
  langid = {english},
  pages = {332-363},
  shortjournal = {CAIS},
  title = {Construction of {{Design Science Research Questions}}}
}

@article{hollingsheadRankOrderEffectGroup1996,
  author = {Hollingshead, Andrea B.},
  date = {1996-12},
  doi = {10.1006/obhd.1996.0098},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\GPRG7D8G\\Hollingshead - 1996 - The Rank-Order Effect in Group Decision Making.pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  number = {3},
  pages = {181-193},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  title = {The {{Rank}}-{{Order Effect}} in {{Group Decision Making}}},
  volume = {68}
}

@incollection{jamesonRecommendationGroups2007,
  abstract = {Recommender systems have traditionally recommended items to individual users, but there has recently been a proliferation of recommenders that address their recommendations to groups of users. The shift of focus from an individual to a group makes more of a difference than one might at first expect. This chapter discusses the most important new issues that arise, organizing them in terms of four subtasks that can or must be dealt with by a group recommender: 1. acquiring information about the user's preferences; 2. generating recommendations; 3. explaining recommendations; and 4. helping users to settle on a final decision. For each issue, we discuss how it has been dealt with in existing group recommender systems and what open questions call for further research.},
  author = {Jameson, Anthony and Smyth, Barry},
  booktitle = {The {{Adaptive Web}}: {{Methods}} and {{Strategies}} of {{Web Personalization}}},
  date = {2007},
  doi = {10.1007/978-3-540-72079-9_20},
  editor = {Brusilovsky, Peter and Kobsa, Alfred and Nejdl, Wolfgang},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\Q9DL2M5M\\Jameson_Smyth_2007_Recommendation to Groups.pdf},
  isbn = {978-3-540-72079-9},
  keywords = {Animated Character,Explicit Preference,Group Recommender,Individual Group Member,Recommender System},
  langid = {english},
  location = {{Berlin, Heidelberg}},
  pages = {596-627},
  publisher = {{Springer}},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  title = {Recommendation to {{Groups}}}
}

@book{janis1982groupthink,
  author = {Janis, Irving Lester and Janis, Irving Lester},
  date = {1982},
  publisher = {{Houghton Mifflin Boston}},
  title = {Groupthink: {{Psychological}} Studies of Policy Decisions and Fiascoes},
  volume = {349}
}

@incollection{janisGroupthink1991,
  author = {Janis, Irving},
  booktitle = {A {{First Look}} at {{Communication Theory}}},
  date = {1991},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\3JN8DV3U\\griffin-groupthink-challenger.pdf},
  pages = {235-246},
  title = {Groupthink}
}

@article{kerrBiasJudgmentComparing1996,
  author = {Kerr, Norbert L and MacCoun, Robert J and Kramer, Geoffrey P},
  date = {1996},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\HQGR93PH\\Kerr et al_1996_Bias in judgment.pdf},
  journaltitle = {Psychological review},
  keywords = {bias,group-decisions},
  number = {4},
  pages = {687},
  publisher = {{American Psychological Association}},
  title = {Bias in Judgment: {{Comparing}} Individuals and Groups.},
  volume = {103}
}

@inproceedings{knijnenburgEachHisOwn2011,
  author = {Knijnenburg, Bart P. and Reijmer, Niels J.M. and Willemsen, Martijn C.},
  booktitle = {Proceedings of the Fifth {{ACM}} Conference on {{Recommender}} Systems - {{RecSys}} '11},
  date = {2011},
  doi = {10.1145/2043932.2043960},
  eventtitle = {The Fifth {{ACM}} Conference},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\9MQQP8WF\\Knijnenburg et al_2011_Each to his own.pdf},
  isbn = {978-1-4503-0683-6},
  langid = {english},
  location = {{Chicago, Illinois, USA}},
  pages = {141-148},
  publisher = {{ACM Press}},
  shorttitle = {Each to His Own},
  title = {Each to His Own: How Different Users Call for Different Interaction Methods in Recommender Systems}
}

@article{loucaJointOptimizationProfit2019,
  author = {Louca, Raphael and Bhattacharya, Moumita and Hu, Diane and Hong, Liangjie},
  date = {2019},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\AMRZSDHT\\Louca et al. - 2019 - Joint Optimization of Profit and Relevance for Rec.pdf},
  langid = {english},
  note = {ZSCC: 0000001},
  pages = {4},
  title = {Joint {{Optimization}} of {{Profit}} and {{Relevance}} for {{Recommendation Systems}} in {{E}}-Commerce}
}

@article{malthouseMultistakeholderRecommenderSystems2019,
  abstract = {Retailing and social media platforms recommend two types of items to their users: sponsored items that generate ad revenue and nonsponsored ones that do not. The platform selects sponsored items to maximize ad revenue, often through some form of programmatic auction, and non-sponsored items to maximize user utility with a recommender system (RS). We develop a multiobjective binary integer programming model to allocate sponsored recommendations considering a dual objective of maximizing ad revenue and user utility. We propose an algorithm to solve it in a computationally efficient way. Our method can be applied as a form of post processing to an existing RS, making it widely applicable. We apply the model to data from an online grocery retailer and show that user utility for the recommended items can be improved while reducing ad revenue by a small amount. This multiobjective approach, which unifies programmatic advertising and RS, opens a new frontier for advertising and RS research and we therefore provide an extended discussion of future research topics.},
  author = {Malthouse, Edward C and Vakeel, Khadija Ali and Hessary, Yasaman Kamyab and Burke, Robin and Fuduri\'c, Morana},
  date = {2019},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\ZCMF3A2J\\Malthouse et al. - 2019 - A Multistakeholder Recommender Systems Algorithm f.pdf},
  langid = {english},
  note = {ZSCC: 0000001},
  pages = {8},
  title = {A {{Multistakeholder Recommender Systems Algorithm}} for {{Allocating Sponsored Recommendations}}}
}

@article{mendoncaCollaborativeProductConfiguration2008,
  abstract = {In the Software Product Line approach, product configuration is a key activity in which stakeholders choose features for a product. This activity is critical in the sense that careless feature selections might lead to undesirable products. Even though product configuration is seen as a team activity in which divergent interests and views are merged into a single consistent product specification, current configuration technology is essentially single-userbased. This configuration approach can be error-prone and time-consuming as it usually requires numerous interactions between the product manager and the stakeholders to resolve decision conflicts. To tackle this problem we have proposed an approach called ``Collaborative Product Configuration'' (CPC). In this paper, we extend the CPC approach by providing efficient dependency analysis algorithms to support the validation of workflow-based descriptions called CPC plans. In addition, we add to previous work by providing a formal description of the approach's concepts, an augmented illustrated example, and a discussion covering several prototype tools now available.},
  author = {Mendon{\c c}a, Marc\'ilio and Cowan, Donald and Malyk, William and Oliveira, Toacy},
  date = {2008-01},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\RWRMVBZ2\\Mendonça et al. - 2008 - Collaborative Product Configuration.pdf},
  journaltitle = {Journal of Software},
  langid = {english},
  number = {2},
  pages = {69-82},
  shortjournal = {JSW},
  title = {Collaborative {{Product Configuration}}},
  volume = {3}
}

@article{mendoncaDecisionmakingCoordinationEfficient2010,
  abstract = {Software Product Lines is a contemporary approach to software development that exploits the similarities and differences within a family of systems in a particular domain of interest in order to provide a common infrastructure for deriving members of this family in a timely fashion, with high-quality standards, and at lower costs.},
  author = {Mendonca, Marcilio and Cowan, Donald},
  date = {2010-05},
  doi = {10.1016/j.scico.2009.12.004},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\PKMHKVGL\\Mendonca und Cowan - 2010 - Decision-making coordination and efficient reasoni.pdf},
  issn = {01676423},
  journaltitle = {Science of Computer Programming},
  langid = {english},
  number = {5},
  pages = {311-332},
  shortjournal = {Science of Computer Programming},
  title = {Decision-Making Coordination and Efficient Reasoning Techniques for Feature-Based Configuration},
  volume = {75}
}

@article{milchIndividualPreferenceConstruction2009,
  abstract = {Two choice tasks known to produce framing effects in individual decisions were used to test group sensitivity to framing, relative to that of individuals, and to examine the effect of prior, individual consideration of a decision on group choice. Written post-decision reasons and pre-decision group discussions were analyzed to investigate process explanations of choices made by preexisting, naturalistic groups. For a risky choice problem, a similar framing effect was observed for groups and individuals. For an intertemporal choice task where consumption was either delayed or accelerated, na\"ive groups (whose members had not preconsidered the decision) showed a framing effect, less discounting in the delay frame, opposite to that observed in individuals. Predecided groups showed a non-significant effect in the other, expected direction. In all cases, process measures better explained variability in choices across conditions than frame alone. Implications for group decision research and design considerations for committee decisions are addressed.},
  author = {Milch, Kerry F. and Weber, Elke U. and Appelt, Kirstin C. and Handgraaf, Michel J.J. and Krantz, David H.},
  date = {2009-03},
  doi = {10.1016/j.obhdp.2008.11.003},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\V444AHG9\\Milch et al. - 2009 - From individual preference construction to group d.pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  number = {2},
  pages = {242-255},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  shorttitle = {From Individual Preference Construction to Group Decisions},
  title = {From Individual Preference Construction to Group Decisions: {{Framing}} Effects and Group Processes},
  volume = {108}
}

@article{murphyPrimacyRecencyEffects2006,
  author = {Murphy, Jamie and Hofacker, Charles and Mizerski, Richard},
  date = {2006-01},
  doi = {10.1111/j.1083-6101.2006.00025.x},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\29P4CLMW\\Murphy et al. - 2006 - Primacy and Recency Effects on Clicking Behavior.pdf},
  issn = {1083-6101, 1083-6101},
  journaltitle = {Journal of Computer-Mediated Communication},
  langid = {english},
  number = {2},
  pages = {522-535},
  shortjournal = {J Comp Mediated Comm},
  title = {Primacy and {{Recency Effects}} on {{Clicking Behavior}}},
  volume = {11}
}

@inproceedings{ninausINTELLIREQIntelligentTechniques2014,
  abstract = {Requirements Engineering is considered as one of the most critical phases of a software development project. Low-quality requirements are a major reason for the failure of a project. Consequently, techniques are needed that help to improve the support of stakeholders in the development of requirements models as well as in the process of deciding about the corresponding release plans. In this paper we introduce the INTELLIREQ Requirements Engineering environment. This environment is based on different recommendation approaches that support stakeholders in requirements-related activities such as definition, quality assurance, reuse, and release planning. We provide an overview of recommendation approaches integrated in INTELLIREQ and report results of empirical studies that show in which way recommenders can improve the quality of Requirements Engineering processes.},
  author = {Ninaus, Gerald and Felfernig, Alexander and Stettinger, Martin and Reiterer, Stefan and Leitner, Gerhard and Weninger, Leopold and Schanil, Walter},
  booktitle = {Prestigious {{Applications}} of {{Intelligent Systems}}},
  date = {2014},
  eventtitle = {European {{Conference}} on {{Artificial Intelligence}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\YKJ2AIB9\\Ninaus et al. - INTELLIREQ Intelligent Techniques for Software Re.pdf},
  langid = {english},
  location = {{Montpellier, France}},
  pages = {1161-1166},
  title = {{{INTELLIREQ}}: {{Intelligent Techniques}} for {{Software Requirements Engineering}}}
}

@incollection{ningComprehensiveSurveyNeighborhoodBased2015,
  abstract = {Among collaborative recommendation approaches, methods based on nearest-neighbors still enjoy a huge amount of popularity, due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations. This chapter presents a comprehensive survey of neighborhood-based methods for the item recommendation problem. In particular, the main benefits of such methods, as well as their principal characteristics, are described. Furthermore, this document addresses the essential decisions that are required while implementing a neighborhood-based recommender system, and gives practical information on how to make such decisions. Finally, the problems of sparsity and limited coverage, often observed in large commercial recommender systems, are discussed, and some solutions to overcome these problems are presented.},
  author = {Ning, Xia and Desrosiers, Christian and Karypis, George},
  booktitle = {Recommender {{Systems Handbook}}},
  date = {2015},
  doi = {10.1007/978-1-4899-7637-6_2},
  editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\D6HDEGBT\\Ning et al_2015_A Comprehensive Survey of Neighborhood-Based Recommendation Methods.pdf},
  isbn = {978-1-4899-7637-6},
  keywords = {Diffusion Kernel,Recommendation Approach,Recommender System,Side Information,Similarity Weight},
  langid = {english},
  location = {{Boston, MA}},
  pages = {37-76},
  publisher = {{Springer US}},
  title = {A {{Comprehensive Survey}} of {{Neighborhood}}-{{Based Recommendation Methods}}}
}

@inproceedings{offermannOutlineDesignScience2009,
  abstract = {Discussions about the body of knowledge of information systems, including the research domain, relevant perspectives and methods have been going on for a long time. Many researchers vote for a combination of research perspectives and their respective research methodologies; rigour and relevance as requirements in design science are generally accepted. What has been lacking is a formalisation of a detailed research process for design science that takes into account all requirements. We have developed such a research process, building on top of existing processes and findings from design research. The process combines qualitative and quantitative research and references well-known research methods. Publication possibilities and self-contained work packages are recommended. Case studies using the process are presented and discussed.},
  author = {Offermann, Philipp and Levina, Olga and Sch\"onherr, Marten and Bub, Udo},
  booktitle = {Proceedings of the 4th {{International Conference}} on {{Design Science Research}} in {{Information Systems}} and {{Technology}} - {{DESRIST}} '09},
  date = {2009},
  eventtitle = {The 4th {{International Conference}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\8BE6HMR6\\Offermann et al. - 2009 - Outline of a design science research process.pdf},
  isbn = {978-1-60558-408-9},
  langid = {english},
  location = {{Philadelphia, Pennsylvania}},
  pages = {1},
  publisher = {{ACM Press}},
  title = {Outline of a Design Science Research Process}
}

@article{peffersDesignScienceResearch2007,
  abstract = {The paper motivates, presents, demonstrates in use, and evaluates a methodology for conducting design science (DS) research in information systems (IS). DS is of importance in a discipline oriented to the creation of successful artifacts. Several researchers have pioneered DS research in IS, yet over the past 15 years, little DS research has been done within the discipline. The lack of a methodology to serve as a commonly accepted framework for DS research and of a template for its presentation may have contributed to its slow adoption. The design science research methodology (DSRM) presented here incorporates principles, practices, and procedures required to carry out such research and meets three objectives: it is consistent with prior literature, it provides a nominal process model for doing DS research, and it provides a mental model for presenting and evaluating DS research in IS. The DS process includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication. We demonstrate and evaluate the methodology by presenting four case studies in terms of the DSRM, including cases that present the design of a database to support health assessment methods, a software reuse measure, an Internet video telephony application, and an IS planning method. The designed methodology effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.},
  author = {Peffers, Ken and Tuunanen, Tuure and Rothenberger, Marcus A. and Chatterjee, Samir},
  date = {2007-12},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\7A9P9P9J\\Peffers et al. - 2007 - A Design Science Research Methodology for Informat.pdf},
  issn = {0742-1222, 1557-928X},
  journaltitle = {Journal of Management Information Systems},
  langid = {english},
  number = {3},
  pages = {45-77},
  shortjournal = {Journal of Management Information Systems},
  title = {A {{Design Science Research Methodology}} for {{Information Systems Research}}},
  volume = {24}
}

@article{peffersDesignScienceResearch2007a,
  author = {Peffers, Ken and Tuunanen, Tuure and Rothenberger, Marcus A. and Chatterjee, Samir},
  date = {2007-12},
  doi = {10.2753/MIS0742-1222240302},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\GCVWBMVC\\Peffers et al. - 2007 - A Design Science Research Methodology for Informat.pdf},
  issn = {0742-1222, 1557-928X},
  journaltitle = {Journal of Management Information Systems},
  langid = {english},
  number = {3},
  pages = {45-77},
  shortjournal = {Journal of Management Information Systems},
  title = {A {{Design Science Research Methodology}} for {{Information Systems Research}}},
  volume = {24}
}

@article{qiuInfluenceGroupConfiguration2015,
  abstract = {Online discourse reading plays a very important role in collaborative discussions. However, not many studies have examined the influence of group configuration on online discourse note reading. The current study examined note reading workloads and participants' perceptions of the three group configurations (large whole class, small whole class, large with subgroups) in online graduate-level courses from one institute. In this mixed-methods study, we analyzed tracking logs from 25 graduate-level online courses (25 instructors and 341 students) and interviews from 10 instructors and 12 graduate students with diverse backgrounds. Findings suggest that all three configurations had their own advantages and disadvantages in fostering online discourse reading. However, our analysis suggests that the advantages of subgroup discussions in supporting note reading outweigh those of the Small and Large configurations. The overload effects in information reading due to large class sizes can be minimized by dividing students into small groups for discussion purposes. Group configuration into proper-size groups may reduce students' reading loads. Interviewees felt that the waving of small groups into large classes benefited their collaborative discussions. We conclude this paper with a list of pedagogical recommendations and new software features that may help group configuration and enhance learning in online courses. This study may have implications for both practitioners and researchers to seek optimal group configurations to achieve more fruitful online discussions through note reading.},
  author = {Qiu, Mingzhu and McDougall, Douglas},
  date = {2015-09},
  doi = {10.1016/j.compedu.2015.04.006},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\79AJNSBV\\Qiu und McDougall - 2015 - Influence of group configuration on online discour.pdf},
  issn = {03601315},
  journaltitle = {Computers \& Education},
  langid = {english},
  pages = {151-165},
  shortjournal = {Computers \& Education},
  title = {Influence of Group Configuration on Online Discourse Reading},
  volume = {87}
}

@thesis{raabKollaborativeProduktkonfigurationEchtzeit2019,
  author = {Raab, Fabian},
  date = {2019-09-30},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\PPAL2KE6\\Raab - 2019 - Kollaborative Produktkonfiguration in Echtzeit.pdf},
  institution = {{Hochschule Karlsruhe}},
  langid = {german},
  location = {{Karlsruhe}},
  pagetotal = {83},
  title = {Kollaborative Produktkonfiguration in Echtzeit},
  type = {Master's thesis}
}

@collection{ricciRecommenderSystemsHandbook2015,
  date = {2015},
  edition = {Second edition},
  editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\26HADE8N\\Ricci et al. - 2015 - Recommender systems handbook.pdf},
  isbn = {978-1-4899-7636-9 978-1-4899-7637-6},
  langid = {english},
  location = {{New York Heidelberg Dordrecht London}},
  note = {ZSCC: NoCitationData[s0] 
OCLC: 935904837},
  pagetotal = {1003},
  publisher = {{Springer}},
  title = {Recommender Systems Handbook}
}

@thesis{rubinshteynEntwicklungHybridenRecommender2018,
  author = {Rubinshteyn, Alexander},
  date = {2018-11-09},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\JXXN9BU8\\Rubinshteyn - Entwicklung eines hybriden Recommender Systems für.pdf},
  institution = {{Karlsruhe Institute of Technology}},
  langid = {german},
  location = {{Karlsruhe}},
  pagetotal = {98},
  title = {Entwicklung eines hybriden Recommender Systems f\"ur die Produktkonfiguration},
  type = {Master's thesis}
}

@article{sabinProductConfigurationFrameworksa1998,
  author = {Sabin, D. and Weigel, R.},
  date = {1998-07},
  doi = {10.1109/5254.708432},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\BG9A29JD\\Sabin und Weigel - 1998 - Product configuration frameworks-a survey.pdf},
  issn = {1094-7167},
  journaltitle = {IEEE Intelligent Systems},
  langid = {english},
  number = {4},
  pages = {42-49},
  shortjournal = {IEEE Intell. Syst.},
  title = {Product Configuration Frameworks-a Survey},
  volume = {13}
}

@inproceedings{samerGroupDecisionSupport2018,
  abstract = {Requests for proposal (RFP) trigger company-internal requirements management (RM) processes in order to assure that offers comply with a given set of customer requirements. As traditional RM approaches require a deep involvement of the requirements managers of a RM project especially when it comes to assigning suitable stakeholders to requirements, the quality of the decisions and the time effort for making correct decisions mainly depends on these experts. In this paper, we present a novel stakeholder assignment approach that reduces the overall involvement of these experts and also limits the uncertainty of overseeing suitable stakeholders at the same time. The assignment of responsible stakeholders is represented as a group decision task expressed in the form of a basic configuration problem. The outcome of such a task is a configuration which is represented in terms of an assignment of responsible stakeholders to corresponding requirements.},
  author = {Samer, R and Atas, M and Felfernig, A and Stettinger, M and Falkner, A and Schenner, G},
  date = {2018},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\7CZIDRDJ\\Samer et al. - Group Decision Support for Requirements Management.pdf},
  langid = {english},
  pages = {19-24},
  title = {Group {{Decision Support}} for {{Requirements Management Processes}}}
}

@article{schulz-hardtProductiveConflictGroup2002,
  abstract = {Decision-making groups in organizations are often expected to function as a ``think tank'' and to perform ``reality testing'' to detect the best alternative. A biased search for information supporting the group's favored alternative impairs a group's ability to fulfill these requirements. In a two-factorial experiment with 201 employees and managers from various economic and public organizations, genuine and contrived dissent were investigated as counterstrategies to biased information seeking. Genuine dissent was manipulated by forming three-person groups whose members either all favored the same alternative individually (homogeneous groups) or consisted of a minority and a majority faction with regard to their favored alternative (heterogeneous groups). Contrived dissent was varied by the use or nonuse of the ``devil's advocacy'' technique. The results demonstrate that heterogeneity was more effective in preventing a confirmatory information-seeking bias than devil's advocacy was. Confidence was identified as an important mediator. Implications for the design of interventions aimed at facilitating reality testing in group decision making are discussed. \'O 2002 Elsevier Science (USA). All rights reserved.},
  author = {Schulz-Hardt, Stefan and Jochims, Marc and Frey, Dieter},
  date = {2002},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\6C92UPS6\\Schulz-Hardt et al. - 2002 - Productive conﬂict in group decision making genui.pdf},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  pages = {24},
  title = {Productive Conflict in Group Decision Making: Genuine and Contrived Dissent as Strategies to Counteract Biased Information Seekingq}
}

@inproceedings{shafieeCostBenefitAnalysis2018,
  author = {Shafiee, Sara and Felfernig, Alexander and Hvam, Lars and Piroozfar, Poorang and Forza, Cipriano},
  booktitle = {Proceedings of the 20th {{Configuration Workshop}}},
  date = {2018},
  eventtitle = {{{ConfWS}}},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\3HAEAKPS\\Shafiee et al. - Cost Benefit Analysis in Product Configuration Sys.pdf},
  langid = {english},
  pages = {37-40},
  title = {Cost {{Benefit Analysis}} in {{Product Configuration Systems}}},
  volume = {2220}
}

@article{sniezekGroupsUncertaintyExamination1992,
  author = {Sniezek, Janet A},
  date = {1992-06},
  doi = {10.1016/0749-5978(92)90048-C},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\FB7B7PIK\\Sniezek - 1992 - Groups under uncertainty An examination of confid.pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  keywords = {confidence in decions,group-decisions},
  langid = {english},
  number = {1},
  pages = {124-155},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  shorttitle = {Groups under Uncertainty},
  title = {Groups under Uncertainty: {{An}} Examination of Confidence in Group Decision Making},
  volume = {52}
}

@inproceedings{stettingerCounteractingAnchoringEffects2015,
  abstract = {Similar to single user decisions, group decisions can be affected by decision biases. In this paper we analyze anchoring effects as a specific type of decision bias in the context of group decision scenarios. On the basis of the results of a user study in the domain of software requirements prioritization we discuss results regarding the optimal time when preference information of other users should be disclosed to the current user. Furthermore, we show that explanations can increase the satisfaction of group members with various aspects of a group decision process (e.g., satisfaction with the decision and decision support quality).},
  author = {Stettinger, Martin and Felfernig, Alexander and Leitner, Gerhard and Reiterer, Stefan},
  booktitle = {User {{Modeling}}, {{Adaptation}} and {{Personalization}}},
  date = {2015},
  doi = {10.1007/978-3-319-20267-9_10},
  editor = {Ricci, Francesco and Bontcheva, Kalina and Conlan, Owen and Lawless, S\'eamus},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\WEJED597\\Stettinger et al_2015_Counteracting Anchoring Effects in Group Decision Making.pdf},
  isbn = {978-3-319-20267-9},
  keywords = {Anchoring effects,Decision biases,Group decision making,Recommender systems},
  langid = {english},
  location = {{Cham}},
  pages = {118-130},
  publisher = {{Springer International Publishing}},
  series = {Lecture {{Notes}} in {{Computer Science}}},
  title = {Counteracting {{Anchoring Effects}} in {{Group Decision Making}}}
}

@misc{StudienUndPrufungsordnung2015,
  date = {2015-09-29},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\8TDXS8ES\\2015 - Studien- und Prüfungsordnung des Karlsruher Instit.pdf},
  title = {Studien- Und {{Pr\"ufungsordnung}} Des {{Karlsruher Instituts}} F\"ur {{Technologie}} ({{KIT}}) F\"ur Den {{Bachelorstudiengang Informatik}}},
  url = {https://www.informatik.kit.edu/downloads/info%20bsc%20spo%202015.pdf}
}

@inproceedings{thumProductConfigurationWild2018,
  abstract = {Customization is omnipresent in our everyday live. There are web configurators to customize cars, trucks, bikes, computers, clothes, furniture, and food. At first glance, customization using configurators appears trivial; we simply select the configuration options that we want. However, in practice, options are usually dependent on each other. Reasons for dependencies are manifold and are typically specific for the particular domain. Dependencies can be simple, such as one option requiring or excluding another option, but also arbitrarily complex, involving numerous options. In this study, we aim to understand how today's web configurators support users in their decision making process. In particular, we are interested in understanding how configurators handle decisions that are in conflict with dependencies. To abstract from different visualizations, we classify the existing strategies of web configurators and discuss advantages and disadvantages of them. While we identified eight strategies, a single configurator typically uses several of those strategies.},
  author = {Th\"um, Thomas and Krieter, Sebastian and Schaefer, Ina},
  booktitle = {{{ConfWS}}},
  date = {2018},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\TR78W9RU\\Thüm et al. - Product Conﬁguration in the Wild Strategies for C.pdf},
  langid = {english},
  pages = {1-8},
  title = {Product {{Configuration}} in the {{Wild}}: {{Strategies}} for {{Conflicting Decisions}} in {{Web Configurators}}}
}

@article{tiihonenIntroductionPersonalizationMass2017,
  abstract = {Mass customization as a state-of-the-art production paradigm aims to produce individualized, highly variant products and services with nearly mass production costs. A major side-effect for companies providing complex products and services is that customers quite often get confused by the high variety and do not make a purchase. Personalization technologies can help to alleviate the challenges of mass customization. These technologies support customers in specifying products and services that fit their wishes and needs in a fashion where decision and interaction efforts with sales support systems are significantly reduced. We provide a short overview of related research and the articles that are part of this special issue on Personalization and Mass Customization.},
  author = {Tiihonen, Juha and Felfernig, Alexander},
  date = {2017-08},
  doi = {10.1007/s10844-017-0465-4},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\7LGAYLZB\\Tiihonen und Felfernig - 2017 - An introduction to personalization and mass custom.pdf},
  journaltitle = {Journal of Intelligent Information Systems},
  langid = {english},
  number = {1},
  pages = {1-7},
  title = {An Introduction to Personalization and Mass Customization},
  volume = {49}
}

@book{tsangFoundationsConstraintSatisfaction1993,
  author = {Tsang, Edward},
  date = {1993},
  isbn = {978-0-12-701610-8},
  langid = {english},
  location = {{London}},
  note = {OCLC: 636781070},
  pagetotal = {421},
  publisher = {{Academic Press}},
  series = {Computation in Cognitive Science},
  title = {Foundations of Constraint Satisfaction}
}

@thesis{ullmannEntwurfUndUmsetzung2017,
  author = {Ullmann, Nils Merlin},
  date = {2017-07-27},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\RT38GZN7\\Ullmann - Entwurf und Umsetzung einer Recommendation Engine .pdf},
  institution = {{Hochschule Flensburg}},
  langid = {english},
  location = {{Flensburg}},
  pagetotal = {77},
  title = {Entwurf Und {{Umsetzung}} Einer {{Recommendation Engine}} Zur {{Produktkonfiguration}} Mit Maschinellen {{Lernverfahren}} Bei Der {{CAS Software AG}}},
  type = {Bachelor's thesis}
}

@article{vanginkelKnowledgeDistributionInformation2009,
  abstract = {Research has shown that decision-making groups with distributed information perform better when group members know which member is knowledgeable about what. Thus far research has been unable to identify the process responsible for this effect. In the present study, we propose that group members' task representations mediate the effect of knowledge about the distribution of information on decision performance. Building on this proposition, we also propose that reflection about the task moderates the effect of knowledge about distributed information through its effect on task representations. These hypotheses were put to the test in an experimental study of decision-making groups (N = 125). As predicted, knowledge of distributed information interacted with reflection to affect decision quality. Findings confirmed the proposed mediating role of task representations and information elaboration.},
  author = {van Ginkel, Wendy P. and van Knippenberg, Daan},
  date = {2009-03},
  doi = {10.1016/j.obhdp.2008.10.003},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\Y4XVVAZ3\\van Ginkel und van Knippenberg - 2009 - Knowledge about the distribution of information an.pdf},
  issn = {07495978},
  journaltitle = {Organizational Behavior and Human Decision Processes},
  langid = {english},
  number = {2},
  options = {useprefix=true},
  pages = {218-229},
  shortjournal = {Organizational Behavior and Human Decision Processes},
  shorttitle = {Knowledge about the Distribution of Information and Group Decision Making},
  title = {Knowledge about the Distribution of Information and Group Decision Making: {{When}} and Why Does It Work?},
  volume = {108}
}

@inproceedings{velasquez-guevaraMultiSPLOTSupportingMultiuser2018,
  author = {Vel\'asquez-Guevara, Sebastian and Pedraza, Gilberto and Chavarriaga, Jaime},
  date = {2018},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\5TSAW84B\\ICAI - 2018 - Applied informatics First International Conferenc.pdf},
  isbn = {978-3-030-01535-0 978-3-030-01534-3},
  langid = {english},
  location = {{Cham}},
  pages = {364-378},
  publisher = {{Springer}},
  series = {Communications in Computer and Information Science},
  shorttitle = {Applied Informatics},
  title = {Multi-{{SPLOT}}: {{Supporting Multi}}-User {{Configurations}} with {{Constraint Programming}}},
  volume = {942}
}

@inproceedings{velasquez-guevaraMultiSPLOTSupportingMultiuser2018a,
  abstract = {Nowadays, companies have moved from offering a single product for all their clients, to offer different customized for each one. These companies provide Configuration Systems where a user can decide and discard which features she wants in her final product. However, although almost all of these systems support individual decisions, usually they do not offer an special support for decisions made by multiple users for the same product. This paper introduces Multi-SPLOT, a web-based Configuration System that supports simultaneous decisions from multiple users. This system uses off-the-shelf solvers to determine if these decisions are not conflicting among them, and to propose solutions when the decisions of an user conflict with decisions of the others. This paper shows the design of the solution and details of its implementation using Angular, Firebase and the optimization library in Google App Script.},
  author = {Vel\'asquez-Guevara, Sebastian and Pedraza, Gilberto and Chavarriaga, Jaime},
  booktitle = {Applied {{Informatics}}},
  date = {2018},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\G8E3GLZR\\Velásquez-Guevara et al. - 2018 - Multi-SPLOT Supporting Multi-user Configurations .pdf},
  isbn = {978-3-030-01535-0},
  keywords = {Configuration systems,Feature models,Multi-user configuration},
  langid = {english},
  pages = {364-378},
  publisher = {{Springer International Publishing}},
  series = {Communications in {{Computer}} and {{Information Science}}},
  shorttitle = {Multi-{{SPLOT}}},
  title = {Multi-{{SPLOT}}: {{Supporting Multi}}-User {{Configurations}} with {{Constraint Programming}}}
}

@inproceedings{wangEffectDefaultOptions2018,
  abstract = {Abstract. 1 Product configurators have been accepted as an important enabling toolkit to bridge customer needs and company offerings. In the configuration process, customers choose from a set of predefined attributes and their options. The combination of choices forms the desired product configuration. It is observed that some online configurators provide default options for each attribute. Although previous studies show that the default option significantly affects customers' choices during the product configuration process, it is not clear how other factors mediate this impact. In this paper, we investigate how product types, number of choices, customers' degree of expertise, the importance of the attributes and the configuring sequence affect consumers' decisions in the configuration process when default options are presented. Based on a series of empirical experiments, we find that customers' degree of expertise, the rating of the attribute importance, and the number of attribute choices have a significant effect on customers' choices for utilitarian products. For hedonic products, the importance of the attributes and the configuring sequence are significant factors.},
  author = {Wang, Yue and Mo, Daniel Yiu-Wing},
  booktitle = {{{ConfWS}}},
  date = {2018-09},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\NCWNAUII\\Wang und Mo - The Effect of Default Options on Consumer Decision.pdf},
  langid = {english},
  pages = {31-36},
  title = {The {{Effect}} of {{Default Options}} on {{Consumer Decisions}} in the {{Product Configuration Process}}}
}

@thesis{wetzelPersonalisierterUndLernender2017,
  author = {Wetzel, Gilles},
  date = {2017-10-30},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\GRXXLIXS\\Wetzel - Personalisierter und lernender Empfehlungsdienst f.pdf},
  institution = {{Hochschule Karlsruhe \textendash{} Technik und Wirtschaft}},
  langid = {german},
  location = {{Karlsruhe}},
  pagetotal = {90},
  title = {Personalisierter und lernender Empfehlungsdienst f\"ur komplexe Produktkonfigurationen},
  type = {Master's thesis}
}

@article{winterInterviewMitAlan2009,
  author = {Winter, Robert},
  date = {2009-02},
  doi = {10.1007/s11576-008-0109-y},
  file = {C\:\\Users\\Hannes.Kuchelmeister\\Zotero\\storage\\FZ8VR2JX\\Winter - 2009 - Interview mit Alan R. Hevner zum Thema „Design Sci.pdf},
  issn = {0937-6429, 1861-8936},
  journaltitle = {WIRTSCHAFTSINFORMATIK},
  langid = {german},
  number = {1},
  pages = {148-151},
  shortjournal = {Wirtsch. Inform.},
  title = {Interview mit Alan R. Hevner zum Thema ,,Design Science``},
  volume = {51}
}


