Coordinating negotiations in data-intensive collaborative working environments using an agent-based model-driven platform

This paper tackles the interoperability problems of enterprise information systems by presenting a distributive model-driven platform for parallel coordination of multiple negotiations in data-intensive collaborative working environments. The proposed model was validated and verified by an industrial application scenario within the European research project H2020 C2NET (Cloud Collaborative Manufacturing Networks). This real scenario developed data-intensive collaborative and cloud-enabled tools that allow the optimisation of the supply network of manufacturing SMEs, proposing a negotiation solution based on a model-driven interoperable decentralised architecture.info:eu-repo/semantics/acceptedVersio

Can a Negotiator Build a Tough Impression Without Chatting? —— Implicit Power and its Influence on Human-Computer Negotiation

In this paper, we studied the influence of implicit power in an e-commerce setting where humans negotiated with computer agents. Implicit power is defined as a kind of perceived power gained indirectly through offer exchange. In much of the past research, power was always considered to be expressed directly through chat or natural language communications during negotiation. We suggest that there is another mode of expressing power other than chat: implicitly influencing. Specifically, we designed an experiment where several aspects of implicit power were studied: anchoring, agent profile image, and experiment subjects’ personality. In our experiment, the subjects negotiated the purchase of a laptop with computer agents acting as sellers. The result suggested that implicit power indeed influenced the negotiation result

An intelligent system to ensure interoperability for the dairy farm business model

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Picking reliable partners, negotiating synchronously with all partners, and managing similar proposals are challenging tasks for any manager. This challenge is even harder when it concerns small and medium enterprises (SMEs) who need to deal with short budgets and evident size limitations, often leading them to avoid handling very large contracts. This size problem can only be mitigated by collaboration efforts between multiple SMEs, but then again this brings back the initially stated issues. To address these problems, this paper proposes a collaborative negotiation system that automates the outsourcing part by assisting the manager throughout a negotiation. The described system provides a comprehensive view of all negotiations, facilitates simultaneous bilateral negotiations, and provides support for ensuring interoperability among multiple partners negotiating on a task described by multiple attributes. In addition, it relies on an ontology to cope with the challenges of semantic interoperability, it automates the selection of reliable partners by using a lattice-based approach, and it manages similar proposals by allowing domain experts to define a satisfaction degree for each SME. To showcase this method, this research focused on small and medium-size dairy farms (DFs) and describes a negotiation scenario in which a few DFs are able to assess and generate proposals.publishersversionpublishe

A Novel Intelligence-based e-Procurement System to offer Maximum Fairness Index in Ongoing Auction Process

A perfect auction policy is one of the most strategic elements that contribute to success factor for any e-Procurement system. An auction policy can be only term as an effective if it really offer win-win situation to both the bidder as well as to the merchant. After reviewing existing studies on e-Procurement system, it is found that there isno effective research work focusing on this point and maximum research contribution has limited its scope to certain application or case studis. Hence, the proposed system introduces a novel e-Procurement system which is equipped by an itelligence-building process for performing predictive analysis of ongoing auction process. A mathematical modelling is implemented where all teh variables have been formed using practical implementation of auction system and followed by optimization process using regression-based approach. The study outcome shows that proposed system offers better response time and higher predictive accuracy in contrast to existing approaches