Multi-angle view on preference elicitation for negotiation support systems

Pommeranz, Alina; Broekens, Joost; Visser, Wietske; Brinkman, Willem‐Paul; Wiggers, Pascal; Jonker, Catholijn M.

doi:10.1145/1609170.1609173

Cited by 6 publications

(4 citation statements)

References 14 publications

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“…Preference ordering We used the information collected in tasks 1A, 2A, 3C and 3D (tasks based on holiday properties) as input for the lexicographic ordering to compute orderings of all 27 holidays [for details see (Pommeranz et al 2008)]. Besides an objective comparison, we asked participants to judge which list better reflected their preferences; the one they specified themselves in task 1B or the list generated with the lexicographic ordering method from the input from task 1A.…”

Section: Designmentioning

confidence: 99%

“…This suggests that different input method combined with lexicographic ordering can result in "true" preference orderings. For more details on the analysis, please see (Pommeranz et al 2008). As we cannot guarantee that the user-specified list (ranking of 27 holidays) is ideal, given that the task was tedious and little appreciated by the users, it is hard to say how close each generated list came to an ideal list of a person's preferences.…”

Section: Preference Orderingmentioning

confidence: 99%

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Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process

Pommeranz

Broekens

Wiggers

et al. 2012

User Model User-Adap Inter

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Two problems may arise when an intelligent (recommender) system elicits users' preferences. First, there may be a mismatch between the quantitative preference representations in most preference models and the users' mental preference models. Giving exact numbers, e.g., such as "I like 30 days of vacation 2.5 times better than 28 days" is difficult for people. Second, the elicitation process can greatly influence the acquired model (e.g., people may prefer different options based on whether a choice is represented as a loss or gain). We explored these issues in three studies. In the first experiment we presented users with different preference elicitation methods and found that cognitively less demanding methods were perceived low in effort and high in liking. However, for methods enabling users to be more expressive, the perceived effort was not an indicator of how much the methods were liked. We thus hypothesized that users are willing to spend more effort if the feedback mechanism enables them to be more expressive. We examined this hypothesis in two follow-up studies. In the second experiment, we explored the trade-off between giving detailed preference feedback and effort. We found that familiarity with and opinion about an item are important factors mediating this trade-off. Additionally, affective feedback was preferred over a finer grained one-dimensional rating scale for giving additional detail. In the third study, we explored the influence of the interface on the elicitation process in a participatory set-up. People considered it helpful to be able to explore the link between their interests, preferences and the desirability of outcomes. We also confirmed that people do not want to spend additional effort in cases where it seemed unnecessary. Based on the findings, we propose four design guidelines to foster interface design of preference elicitation from a user view.

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Section: Designmentioning

confidence: 99%

Section: Preference Orderingmentioning

confidence: 99%

Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process

Pommeranz

Broekens

Wiggers

et al. 2012

User Model User-Adap Inter

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence, a DSS should not be structured or designed in a way that its user gets confused or is over-whelmed (Schoop, Jertila, & List, 2003), since an artificially constructed source of information overload may influence negotiation effectiveness and efficiency negatively (Vahidov et al, 2013), which is the opposite of what a DSS is intended for (Singh & Ginzberg, 1996). Thus, it is argued that the usefulness and potentially beneficial impacts of a DSS depend on its functionalities (Jain & Solomon, 2000) as well as the abilities of its users to handle these and cope with these (Kersten & Lo, 2003;Pommeranz, Brinkman, Wiggers, Broekens, & Jonker, 2009). This argument rests upon the assumptions of the Technology Acceptance Model (TAM) that the "perceived usefulness and perceived ease of use" (Davis, 1989, p. 333) of a system is, at least partly, responsible for the benefits it can provide to its users.…”

Section: Potential Impacts Of Decision Support On Emotional Expressionsmentioning

confidence: 99%

“…In sum, the available literature generally indicates that DSSs impact the behaviors of the supported negotiators, but also that this interconnection warrants more attention of research. Since negotiations, naturally, are interactions of social nature, we can also expect an influence of decision support on socio-emotional behaviors (Pommeranz et al, 2009). Consequently, we argue that the design of and research on DSSs should incorporate its impacts on emotional behaviors to a larger extent.…”

Section: Potential Impacts Of Decision Support On Emotional Expressionsmentioning

confidence: 99%

A DSS User is a Happy Negotiator

Hippmann

2014

International Journal of Decision Support System Technology

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The present work states that the analysis and design of decision support systems should consider their impacts on the emotional behaviors of negotiators. This paper provides a brief literature review with respect to this issue, and an outline of a research framework, which explains how to assess and analyze the dynamics of emotional behaviors in text-based negotiations. Subsequently, it provides some results, which show that a decision support system does not mitigate but intensifies emotional behaviors, toward the end of successful as well as failed text-based online negotiations. It is concluded that the research and design of decision support systems should focus more on the impact such systems have on the emotional behaviors of the supported negotiators.

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AffectButton: A method for reliable and valid affective self-report

Broekens

Brinkman

2013

International Journal of Human-Computer Studies

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105

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In this article we report on a new digital interactive self-report method for the measurement of human affect. The AffectButton (Broekens & Brinkman, 2009) is a button that enables users to provide affective feedback in terms of values on the well-known three affective dimensions of Pleasure (Valence), Arousal and Dominance. The AffectButton is an interface component that functions and looks like a medium-sized button. The button presents one dynamically changing iconic facial expression that changes based on the coordinates of the user's pointer in the button. To give affective feedback the user selects the most appropriate expression by clicking the button, effectively enabling 1-click affective self-report on 3 affective dimensions. Here we analyze 5 previously published studies, and 3 novel large-scale studies (n=325, n=202, n=128). Our results show the reliability, validity, and usability of the button for acquiring three types of affective feedback in various domains. The tested domains are holiday preferences, real-time music annotation, emotion words, and textual situation descriptions (ANET). The types of affective feedback tested are preferences, affect attribution to the previously mentioned stimuli, and self-reported mood. All of the subjects tested were Dutch and aged between 15 and 56 years. We end this article with a discussion of the limitations of the AffectButton and of its relevance to areas including recommender systems, preference elicitation, social computing, online surveys, coaching and tutoring, experimental psychology and psychometrics, content annotation, and game consoles.

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Multi-angle view on preference elicitation for negotiation support systems

Cited by 6 publications

References 14 publications

Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process

Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process

A DSS User is a Happy Negotiator

AffectButton: A method for reliable and valid affective self-report

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