The Judge as a Negotiator: Claims Negotiating and Inequalities in China’s Judicial Mediation

I propose a three-way model of negotiation on judicial mediation: the judge as a negotiator. Primarily drawing on ethnographic observations of a civil judge in a basic-level court in hinterland China, I document Chinese judges’ tactics at the micro level. I find that the Chinese judge not only “expands” and “narrows” claims. In addition, included in her repertoire are “repression,” “conversion,” and “facilitation.” Following this, I explore the inequitable consequences of the judge’s apparent success in disposing cases. In negotiating the claims, the judge convinces or cajoles litigants who are economically vulnerable, inexperienced in the courtroom, legally bewildered, or timid in confronting the judges’ authority, into the settlement. But she often facilitates the claims of litigants who can mount credible political resistance. The interests of those who are vulnerable in one way or another, but not in a position to initiate political threats, are often dispensed. Inequalities are thus generated, reproduced, and reinforced. This three-way negotiation model provides a new perspective to study judicial mediation comparatively.

Negotiating Government-to-Government Food Importing Contracts: A Nash Bargaining Framework

Problem definition: Inspired by India’s challenges in importing pulses, we study the negotiation of government-to-government food importing contracts, with a focus on ad hoc and forward negotiations with multiple suppliers (henceforth referred to as multiple-sourcing negotiations). Academic/practical relevance: We are the first to comprehensively study ad hoc and forward multiple-sourcing negotiations for food importing. Such problems are widespread, especially in developing nations, and thus the research can be relevant to the wellbeing of large underprivileged populations. Methodology: We develop an analytical negotiation model in the Nash bargaining framework and adopt the Nash-in-Nash framework to analyze multiple-sourcing negotiations. Results: We find that while forward negotiations are not necessarily better than ad hoc negotiations for the buyer, it would be true with sufficiently many suppliers. When facing a supplier pool, we show that it may be optimal to mix forward and ad hoc suppliers. In general, fewer suppliers should be assigned as ad hoc as the pool size increases. We also find that adding a hybrid supplier (engaged in a forward negotiation with an ad hoc negotiation as the fallback option) may be better or worse than adding a forward supplier in the presence of other suppliers. Managerial implications: Our findings inform how a food importer should strategically utilize ad hoc and forward negotiations with its suppliers to improve the outcome. The work may help countries’ food importing policymaking and strategies and may improve the wellbeing of large underprivileged populations.

Schematic Structure and Stance in Students’ Writing in Business Communication: A Comparative Study of Native English Speaking and Iranian Students

This study reports on two knowledge elements of stance and schematic structure in order to help novice students increase the efficacy of their writing in business communication. With this regard, Santos’ (2002) Business Letters of Negotiation Model and Hyland’s (2005b) Stance Model of Interaction were drawn upon. Sixty business emails written by native English speaking (NS) and Iranian students of Business Management Departments in universities were analyzed. Two raters explored the corpus for their moves/steps frequencies and a concordance software was used in order to explore stance markers frequencies. To investigate whether Iranian and NS writers are statistically different from each other, the findings of frequencies were submitted to one-variable Chi-square test. The results showed that NS and Iranian writers are not different from each other in their content staging while they are providing information/answers or negotiating. Running counter to moves 2 and 23, move 3 turned out to have different results; there was a significant difference between NS and Iranian writers in their request of information/action/favors. Results presented no significant difference between NS and Iranian writers in their employment of hedges and attitude markers of stance with regard to one-variable Chi-square test results. For boosters, Chi-square test detected a significant difference between the groups only in move 2. There was a significant difference, however, between NS and Iranian writers in their use of self-mention markers in moves 3 and 23. The results of this paper have both theoretical and pedagogical significance.

Research on Integrated Learning of Industrial Clusters in Self-Created Districts

Under the premise of coordinated procurement bilateral and multi-issue negotiation, adaptive negotiation strategy has become an essential factor for multiagent conflict resolution. This paper studies an adaptive negotiation strategy based on selective integrated learning, which effectively improves negotiation. First, take the suppliers and purchasing companies in the cluster supply chain as the research objects and analyze the characteristics of multilateral negotiation of collaborative procurement. Secondly, the support vector machine algorithm performs adaptive learning for each evaluation data set to estimate the concession range. On this basis, remove the few submodels that perform poorly, recombine the calculation weights, and establish a multiagent clustered supply collaborative procurement negotiation model. The simulation experiment proves the feasibility of the adaptive negotiation strategy and the effectiveness of the adaptive coordination strategy based on selective ensemble learning proposed in this paper from the aspects of concession range prediction error rate, prediction accuracy rate, and negotiation utility.

The equal collective gains value in cooperative games

The property of equal collective gains means that each player should obtain the same benefit from the cooperation of the other players in the game. We show that this property jointly with efficiency characterize a new solution, called the equal collective gains value (ECG-value). We introduce a new class of games, the average productivity games, for which the ECG-value is an imputation. For a better understanding of the new value, we also provide four alternative characterizations of it, and a negotiation model that supports it in subgame perfect equilibrium.

An Application of Grice’s Cooperative Principle to the Analysis of a Written Business Negotiation Model

This article focuses on institutional discourse pragmatics, highlighting its salient features in a business to customer negotiation model, based on an authentic business correspondence (email), through a prism of H. Grice’s Theory of Cooperative Principle. The central thrust of this theory is the application of the maxims of Quantity, Quality, Relation and Manner to speech acts to secure identification of participants’ intentions and sentence meaning, excluding irrelevancies throughout the communication process. Any kind of interaction in our life is accompanied by diverse tangible and intangible components. The role, function and impact of these aggregate components on the natural flow of communication irrespective of the form (oral/written) are the concern of pragmatics.

ANEGMA: an automated negotiation model for e-markets

We present a novel negotiation model that allows an agent to learn how to negotiate during concurrent bilateral negotiations in unknown and dynamic e-markets. The agent uses an actor-critic architecture with model-free reinforcement learning to learn a strategy expressed as a deep neural network. We pre-train the strategy by supervision from synthetic market data, thereby decreasing the exploration time required for learning during negotiation. As a result, we can build automated agents for concurrent negotiations that can adapt to different e-market settings without the need to be pre-programmed. Our experimental evaluation shows that our deep reinforcement learning based agents outperform two existing well-known negotiation strategies in one-to-many concurrent bilateral negotiations for a range of e-market settings.