The Polarizing Effect of Arousal on Negotiation

In this research, we examined the impact of physiological arousal on negotiation outcomes. Conventional wisdom and the prescriptive literature suggest that arousal should be minimized given its negative effect on negotiations, whereas prior research on misattribution of arousal suggests that arousal might polarize outcomes, either negatively or positively. In two experiments, we manipulated arousal and measured its effect on subjective and objective negotiation outcomes. Our results support the polarization effect. When participants had negative prior attitudes toward negotiation, arousal had a detrimental effect on outcomes, whereas when participants had positive prior attitudes toward negotiation, arousal had a beneficial effect on outcomes. These effects occurred because of the construal of arousal as negative or positive affect, respectively. Our findings have important implications not only for negotiation, but also for research on misattribution of arousal, which previously has focused on the target of evaluation, in contrast to the current research, which focused on the critical role of the perceiver

Predicting video-conferencing conversation outcomes based on modeling facial expression synchronization

Effective video-conferencing conversations are heavily influenced by each speaker's facial expression. In this study, we propose a novel probabilistic model to represent interactional synchrony of conversation partners' facial expressions in video-conferencing communication. In particular, we use a hidden Markov model (HMM) to capture temporal properties of each speaker's facial expression sequence. Based on the assumption of mutual influence between conversation partners, we couple their HMMs as two interacting processes. Furthermore, we summarize the multiple coupled HMMs with a stochastic process prior to discover a set of facial synchronization templates shared among the multiple conversation pairs. We validate the model, by utilizing the exhibition of these facial synchronization templates to predict the outcomes of video-conferencing conversations. The dataset includes 75 video-conferencing conversations from 150 Amazon Mechanical Turkers in the context of a new recruit negotiation. The results show that our proposed model achieves higher accuracy in predicting negotiation winners than support vector machine and canonical HMMs. Further analysis indicates that some synchronized nonverbal templates contribute more in predicting the negotiation outcomes

Understanding social interpersonal interaction via synchronization templates of facial events

Automatic facial expression analysis in inter-personal communication is challenging. Not only because conversation partners' facial expressions mutually influence each other, but also because no correct interpretation of facial expressions is possible without taking social context into account. In this paper, we propose a probabilistic framework to model interactional synchronization between conversation partners based on their facial expressions. Interactional synchronization manifests temporal dynamics of conversation partners' mutual influence. In particular, the model allows us to discover a set of common and unique facial synchronization templates directly from natural interpersonal interaction without recourse to any predefined labeling schemes. The facial synchronization templates represent periodical facial event coordinations shared by multiple conversation pairs in a specific social context. We test our model on two different dyadic conversations of negotiation and job-interview. Based on the discovered facial event coordination, we are able to predict their conversation outcomes with higher accuracy than HMMs and GMMs

What do People Value when they Negotiate? Mapping the Domain of Subjective Value in Negotiation

Four studies provide support for the development and validation of a framework for understanding the range of social psychological outcomes valued subjectively as consequences of negotiations. Study 1 inductively elicited and coded elements of subjective value among students, community members, and negotiation practitioners, revealing 20 categories that negotiation theorists in Study 2 sorted to reveal four underlying dimensions: Feelings about Instrumental Outcomes, the Self, Process, and Relationship. Study 3 proposed a new Subjective Value Inventory (SVI) questionnaire and confirmed its 4-factor structure, and Study 4 presents convergent, discriminant, and predictive validity data for this SVI. Results suggest the SVI is a promising tool to systematize and encourage research on the subjective outcomes of negotiation