Human Negotiation Research Articles

Exploring the Function of Expressions in Negotiation: The DyNego-WOZ Corpus

For affective computing to have an impact outside the laboratory, facial expressions must be studied in rich naturalistic situations. We argue negotiations are one such situation as they are ubiquitous in daily life, often evoke strong emotions, and perceived emotion shapes decisions and outcomes. Negotiations are a growing focus in AI research and applications, including agents that negotiate directly with people and attempt to use affective information. We introduce the DyNego-WOZ Corpus, which includes dyadic negotiation between participants and wizard-controlled virtual humans. We demonstrate the value of this corpus to the affective computing community by examining participants' facial expressions in response to a virtual human negotiation partner. We show that people's facial expressions typically co-occur with the end of their partner's speech (suggesting they reflect a reaction to the content of this speech), that these reactions do not correspond to prototypical <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">emotional</i> expressions, and that these reactions can help predict the expresser's subsequent action. We highlight challenges in working with such naturalistic data, including difficulties of expression recognition during speech, and the extreme variability of expressions, both across participants and within a negotiation. Our findings reinforce arguments that facial expressions convey more than emotional state but serve important communicative functions.

How to Recognize Arguments? A Study of Human Negotiations

Different kinds of negotiations and presented arguments are considered in this paper. Discussions in the Parliament of Estonia as well as negotiation in telemarketing calls, travel, and everyday conversations are studied. In the Parliament, negotiation involves many participants while the other conversations take place between two participants. In the analyzed texts, argument components (premises and claims), argument structures (basic, linked, etc.), and relations (support, attack, and rebuttal) are annotated manually. For annotating dialogue acts (DAs), a customized typology and custom-made software is used. This preliminary study aims to find cues for recognizing arguments in Estonian texts automatically. It turns out that some DAs and language features contribute to the recognition of arguments and inter-argument relations.

Conflict Resolution

TRULY effective and successful human negotiation and the resolution of conflict (also where South Africa is concerned) can only be developed by a process preceding actual negotiation. Destructive tendencies resulting from perceptions or expectations deeply rooted in different cultural backgrounds, can only be overcome through the conscious effort to create a basic, mutually acceptable communication sub-culture in which trust plays a central role. Rather than approaching any given negotiation situation with a fixed, preconceived action model already in mind, communication scholars will have to begin their work much earlier. Individual, social, and cultural components which exist prior to interpersonal communication situations will have to be identified and studied. This approach requires the initial acceptance of complexity, and the ability to allow specific conditions to assist them in discovering and developing situationally appropriate techniques.

Modeling and prediction of human negotiation behavior in human-computer negotiation

• This study proposes a segmented linear regression Strategy (SLR) model, which can predict the opponent's future offer patterns. • Segmented linear regression method can model complex concession behavior dynamically. • A theoretical framework is built upon the hope-based and game-based negotiation theories. • The model is validated empirically through computer-to-computer and human-to-computer negotiation experiments based on a prototype system. With increasing e-commerce activities, the human–computer negotiation mechanism for online transactions emerges. This study proposes a segmented linear regression strategy (SLR) model, which can predict the opponent's future offer patterns and dynamically adjust the model parameters according to the opponent's behavior. We use the hope-based (behavior-oriented) and game-based (technical-oriented) negotiation theories as the theory ground to explicate the logic of the agent's negotiation strategy. Upon which we propose a theoretical model of bilateral negotiation as the framework for designing the SLR model. We then propose the testable hypotheses to evaluate the utility of the proposed model against the benchmark results. We build a prototype system and empirically test the hypotheses using computer-to-computer (CtC) and human-to-computer (HtC) negotiation experiments. The empirical results show that the proposed system outperforms the benchmark system in both CtC and HtC negotiations regarding deal price and utility. The proposed model provides an automated negotiation solution for online platforms that can improve the efficiency and effectiveness of their negotiation capability.

The Promise and Peril of Automated Negotiators

Innovations in artificial intelligence are enabling a new class of applications that can negotiate with people through chat or spoken language. Developed in close collaboration with behavioral science research, these algorithms can detect, mimic, and leverage human psychology, enabling them to undertake such functions as the detection of common mistakes made by novice negotiators. These algorithms can simulate the cognitive processes that shape human negotiations and make use of these models to influence negotiated outcomes. This article reviews some of the scientific advances enabling this technology and discusses how it is being used to advance negotiation research, teaching, and practice.

The Effects of Experience on Deception in Human-Agent Negotiation

Negotiation is the complex social process by which multiple parties come to mutual agreement over a series of issues. As such, it has proven to be a key challenge problem for designing adequately social AIs that can effectively navigate this space. Artificial AI agents that are capable of negotiating must be capable of realizing policies and strategies that govern offer acceptances, offer generation, preference elicitation, and more. But the next generation of agents must also adapt to reflect their users’ experiences.&#x0D; The best human negotiators tend to have honed their craft through hours of practice and experience. But, not all negotiators agree on which strategic tactics to use, and endorsement of deceptive tactics in particular is a controversial topic for many negotiators. We examine the ways in which deceptive tactics are used and endorsed in non-repeated human negotiation and show that prior experience plays a key role in governing what tactics are seen as acceptable or useful in negotiation. Previous work has indicated that people that negotiate through artificial agent representatives may be more inclined to fairness than those people that negotiate directly. We present a series of three user studies that challenge this initial assumption and expand on this picture by examining the role of past experience.&#x0D; This work constructs a new scale for measuring endorsement of manipulative negotiation tactics and introduces its use to artificial intelligence research. It continues by presenting the results of a series of three studies that examine how negotiating experience can change what negotiation tactics and strategies human endorse. Study #1 looks at human endorsement of deceptive techniques based on prior negotiating experience as well as representative effects. Study #2 further characterizes the negativity of prior experience in relation to endorsement of deceptive techniques. Finally, in Study #3, we show that the lessons learned from the empirical observations in Study #1 and #2 can in fact be induced—by designing agents that provide a specific type of negative experience, human endorsement of deception can be predictably manipulated.

Trouble on the shop floor

Supplementary materials The case is supported with a teaching note, discussion questions and suggested responses to those as well as verbatim transcripts from interviews conducted with managers and others for purposes of a research project after the strike had ended. Teaching Notes are available for educators only. Learning outcomes The learning outcomes are as follows: students will be able to critique the approach to collective bargaining of both the company and the union in the case and suggest alternative approaches; identify the steps the company could take to both deal with the aftermath of the strike and develop preventive measures for the future; and advise the company on a series of questions it needs advice on. Case overview/synopsis A violent strike erupted after failed wage negotiations. It laid bare deep divisions between African and non-African employees and between permanent employees and those appointed as temporary employees only. It also revealed the mindsets of people on both sides of the conflict, as well as several errors made by management in the manner in which they viewed the role of the union and failed to build strong relations with employees on the shop floor. Complexity academic level The case is suitable for students at honours or masters level in conflict studies, dispute resolution, employment relations, human resource management and negotiation. Subject code CSS 6: Human resource management.

Adaptive Negotiation Model for Human-Machine Interaction on Decision Level

Our work is a contribution to automation design for human-machine cooperation with explicit emancipated cooperative decision making. We propose an adaptive negotiation framework as a model for human-machine interaction on decision level. This expands modeling of human-machine cooperation, starting at the stabilization and trajectory level with approaches such as shared control, towards higher levels of interaction as guidance and navigation. In essence, the framework extends the well-known basic negotiation model of multi-agent systems by an explicit adaptation of the agent’s negotiation behavior. The adaptation is based on an opponent model using a Bayesian learning approach. An exemplary implementation for the application of human-automation interaction in autonomous driving is introduced. First results prove the high flexibility of the framework to model human negotiation behavior.

The State – a necessity or an enemy?

This paper seeks to show the State in its historical and analytical approaches. In view of history, we find two principal solutions. In this text they are called metaphysical and contractual. The metaphysical solution is characteristic of the pre-modern era with its Aristotelian claim that we carry the social principle in our human nature; the principle is the spawning ground for the State. Now, the contractual, i.e. the modern, approach defines the State as a result of human negotiation. Historically speaking, there have been many proposals along the spectrum from an overgrown institution to its, much atrophied, form. The author proposes a modest approach to our understanding of the State: it is needed from the well-being of social community. The condition, however, of this well-being is that the State be limited, allowing much space for its society to grow and form indispensable interrelations.

Using Automated Agents to Teach Negotiation

Negotiation is an integral part of our daily lives regardless of occupation. Although ubiquitous to our experience, we are never taught to negotiate. This lack of training presents many consequences from unfair salary negotiation to geopolitical ramification. The ability to resolve conflicts and negotiate is becoming more critical due to the rise of automated systems which look to replace various repetitive task jobs. In hopes of improving human negotiation skills, my work seeks to develop automated negotiation agents capable of providing personalized feedback. In this paper, I provide an overview of my past , current, and future work.

Defrosting the freezer and other acts of quiet resistance: Affective practice theory, everyday activism and affective dilemmas

ABSTRACTThis article illustrates the mode of thinking about affect that practice theory offers qualitative research in psychology. A focus on affective practice draws attention to the entanglement of embodied states with meaning making, to the role of routine and habit, and to the formation of new and creative affective-discursive patterns. Crucially, affective practice highlights human activity and negotiation, intertwining the subjective and the social organisation of affect. To exemplify these points, we draw on a research project on affect and national commemoration in Aotearoa New Zealand, specifically on research on participant engagements with Anzac Day. We elaborate three case studies investigating some of the alternative affective practices developed by those engaged in “quiet resistance” to hegemonic emotion. We discuss the core features of affective practice these case studies illuminate. Overall, the assumed national unity and normative national identity work of Anzac Day commemoration become fragmented, complicated, and troubled. We argue an affective practices approach is a particularly useful route into everyday negotiations of power that might otherwise be rendered mysterious.

The effects of interplay between negotiation tactics and task complexity in software agent to human negotiations

Modern networked business environment enables design of flexible and effective mechanisms of exchange between economic parties. Online negotiations allow geographically and temporally separated participants to engage in exchange of offers in search for acceptable agreements. The digital medium enables development of software agents, which can assist with negotiation tasks while saving time and human effort. The current paper investigates the prospects of utilizing software agents in negotiations with the human counterparts. It presents the findings from experiment where human subjects acted as buyers negotiating with software agent sellers over a mobile phone plan. An electronic negotiation system incorporating software agents was used in the experiment. The agents employed various concession-making schedules while engaging in negotiation tasks involving one of two complexity levels. Negotiation task complexity was manipulated using different number of issues involved in the negotiations. Subjects were recruited among university students. Negotiations between the subjects and agents took place during a two-day period in an asynchronous mode through the web. The findings suggest that interaction between negotiation task complexity and negotiation tactic has significant effects on negotiation outcomes and subjective assessments by the human participants. In particular, task complexity had a higher impact on the agreement rate when agents employed a competitive tactic vs. when they used a conceding one.

Neurodharma Self-Help: Personalized Science Communication as Brain Management.

Over the past ten to fifteenyears, medical interventions, therapeutic approaches and scientific studies involving mindfulness meditation have gained traction in areas such as clinical psychology, psychotherapy, and neuroscience. Simultaneously, mindfulness has had a very strong public appeal. This article examines some of the ways in which the medical and scientific meaning of mindfulness is communicated in public and to the public. In particular, it shows how experts in the field of mindfulness neuroscience seek to communicate to the public at large the imperative of brain fitness for the promotion of health, wellbeing and happiness. The study identifies claims being made in popular outlets that, by and large, bypass traditional mass media, such as self-help books, websites and online videos. By treating this material as a form of personalized science communication, this article contributes to the body of literature that understands science communication as a continuum and the boundary between science and popularized science as the outcome of human negotiations. The study finds that processes of personalization help to build bridges between scientific findings and their supposed application,that they infuse science with subjective meaning, and turn expert communication with the public into a moral vocation.

Subjective Perceptions in Wartime Negotiation

The prevalence of negotiation in social interaction has motivated researchers to develop virtual agents that can understand, facilitate, teach and even carry out negotiations. While much of this research has analyzed how to maximize the objective outcome, there is a growing body of work demonstrating that subjective perceptions of the outcome also play a critical role in human negotiation behavior. People derive subjective value from not only the outcome, but also from the process by which they achieve that outcome, from their relationship with their negotiation partner, etc. The affective responses evoked by these subjective valuations can be very different from what would be evoked by the objective outcome alone. We investigate such subjective valuations within human-agent negotiation in four variations of a wartime negotiation scenario taken from the political science literature. We observe that the objective outcomes of these negotiations are not strongly related to the human negotiators' subjective perceptions, as measured by the Subjective Value Index. We examine the game dynamics and agent behaviors to identify features that induce different subjective values in the participants, even when separated from the effect of the objective outcomes. We thus are able to identify characteristics of the interaction between negotiation and battlefield processes that most impact people's subjective valuations.

Decoding the strike at Bajaj Auto's Chakan plant: a negotiator's framework

Subject area Negotiation, Human Resource Management. Study level/applicability Graduate and post graduate level course in Human Resource Management, Industrial Relations, and Negotiation. Case overview The present case unfolds sequence of events in the wake of collective bargaining between the union and the management of Bajaj Auto for settling the issue of wage revision. Since no agreement could be reached between both the parties, the workers' union called for a strike. This was the first case of strike in the plant in its 16 years of existence. Bajaj Auto is India's second-largest motorcycle manufacturer in the country, having its manufacturing plants at Chakan (Pune, Maharashtra), Pantnagar (Uttrakhand), Waluj in Aurangabad, Maharashtra. The Chakan plant, set up in 1999, has an installed capacity of over 3,000 units a day. The present case relates to workers' strike at its Chakan Plant which lasted for more than 50 days. The case is analysed from the negotiation point of view. Expected learning outcomes To understand basic principles/rules of negotiation; to explain the framework that can be used to assess the relative strength of power of the parties involved in negotiation; and to understand various power moves used by parties involved in negotiation. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

A Socio-Legal Perspective to Human Rights Negotiations

This essay discusses human rights negotiations within the setting of plural legal orders from a socio-legal perspective. Human rights is approached here as a socially constructed concept, resulting from continuous and circular practices of negotiations. The ways actors invoked human rights to formulate claims against agricultural modernisation in Merauke, Indonesia are analysed as a case study.

Dilemmas in sustainability

Purpose – The purpose of this paper is to contextualize the potential contribution that experiential learning and a learner-centred pedagogical approach may have when aiming to embed sustainability-focused and corporate social responsibility issues in businesses throughout the core curriculum targetted at international cohorts of undergraduate management students. Design/methodology/approach – A new conceptual framework for experiential learning that draws on both scholarly and experimental learning. Using learner-centred learning, the approach aims to engage each student to act both as a learner and a mentor, thus empowering them into enhancing their own and the overall class’ learning experience. Findings – Applying the diversity of students’ individual cultural mindsets to analyse and critically evaluate some of the current most pressing organizational and national/international dilemmas in sustainability. The preliminary outcomes seem to indicate that this approach enriches the students’ learning experience and motivates them to become reflective practitioners and sustainability-focused leaders in their future organizational roles. Research limitations/implications – A framework for an empirical mapping of this important area of teaching and learning (T &amp; L) aimed at a highly international body of undergraduate management students. This is currently under-represented in academic writing and practice, as most of the comparable situations so far mainly address post-graduate cases and do not reflect on the international diversity of the student body. Practical implications – This research reflects on the importance of embedding diverse views on the same issues based on different cultural and socio-economic perspectives, and therefore it brings value to the students’ experience in view of enhancing their global and international human relations awareness and negotiation skills in view of more meaningful sustainability-focused plans and actions. Social implications – Students become aware of differences in needs, resources, cultural perceptions, business standards, practices and policies in place in different countries, and they will be committed to embedding sustainability issues in their future life as business practitioners and will be able to ensure the most appropriate business responses to a planet and humanity under pressure. Originality/value – A rather innovative T &amp; L approach to embed sustainability issues in undergraduate management students training in a highly international context. This is currently under-represented in academic writing and practice, in spite of the numerous programmes that nowadays bring students from all over the world to study together at higher education/university undergraduate level.

Edward Wheatley Stumbling Blocks before the Blind: Medieval Constructions of a DisabilityStumbling Blocks before the Blind: Medieval Constructions of a Disability. Edward Wheatley. Ann Arbor: University of Michigan Press, 2010. Pp. xiii+284.

<i>Edward Wheatley</i> Stumbling Blocks before the Blind: Medieval Constructions of a Disability<i>Stumbling Blocks before the Blind: Medieval Constructions of a Disability</i>. Edward Wheatley. Ann Arbor: University of Michigan Press, 2010. Pp. xiii+284.

An Automated Bilateral Negotiation about Price and Quantity in E-Commerce

Automated negotiation about price and quantity is increasingly common in e-commerce. This paper presents an automated bilateral negotiation conducted by labor-saving and emotion-free autonomous agents. An automated negotiation may alleviate the difficulties inherent in human negotiations. To avoid a deadlock in which both agents are unwilling to concede may arise in the traditional alternating-offer pattern, a mediator agent is introduced. After outlining the negotiation workflow, we aim to analyze the correlation of price and quantity in a bilateral negotiation in different situations; then propose the negotiation methods how negotiate price and quantity for different situations. We hope the research can offer the guide for applying the proposed method to the e-commerce.

Reasoning about Goal Revelation in Human Negotiation

This article studies how people reveal private information in strategic settings in which participants need to negotiate over resources but are uncertain about each other's objectives. The study compares two negotiation protocols that differ in whether they allow participants to disclose their objectives in a repeated negotiation setting of incomplete information. Results show that most people agree to reveal their goals when asked, and this leads participants to more beneficial agreements. Machine learning was used to model the likelihood that people reveal their goals in negotiation, and this model was used to make goal request decisions in the game. In simulation, use of this model is shown to outperform people making the same type of decisions. These results demonstrate the benefit of this approach towards designing agents to negotiate with people under incomplete information.