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Evaluating the Effectiveness of Large Language Models in Human Computer Online Negotiation

Title:

Evaluating the Effectiveness of Large Language Models in Human Computer Online Negotiation

Verma, Jai Priya (2025) Evaluating the Effectiveness of Large Language Models in Human Computer Online Negotiation. Masters thesis, Concordia University, John Molson School of Business.

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Abstract

ABSTRACT

Evaluating the Effectiveness of Large Language Models in Human Computer Online Negotiation

Jai Priya Verma

Large Language Models (LLMs) are changing how automated systems engage with people during decision-making processes as they become increasingly integrated into online human
computer discussions. By analyzing their capacity to understand human intent, produce strong arguments, adjust to changing tactics, and produce positive results, this study assesses how
effective LLMs are in negotiating situations. Strategic rigidity, contextual misinterpretation, and ethical issues about bias and justice are some of the challenges that LLMs face despite their
strengths in language fluency, contextual reasoning, and data-driven decision-making. This study compares LLM-driven and human-driven negotiations to identify important aspects that
affect negotiating effectiveness, examine the shortcomings of existing models, and point up areas for improvement in LLM-driven bargaining systems. The research advances the field of
artificial intelligence's involvement in human-computer cooperation, negotiation automation, and the creation of more capable and flexible negotiation agents.
In various disciplines, LLMs have proven to be remarkably adept at producing intelligible writing, comprehending human intent, and supporting complicated problem-solving. Ongoing study is necessary to address objective issues like tempting offers, monetary factors, generating offers, and subjective aspects like satisfaction, fairness, and intent to return. Examining LLMs can improve their effectiveness, flexibility, and equity, increasing their
dependability for contract analysis, automated negotiations, and real-time decision assistance. In order to ensure that LLM based negotiation agent systems continue to be reliable and
efficient, my research is also essential for enhancing model transparency and resilience against hostile challenges. Understanding LLMs' advantages and disadvantages will help determine how responsibly they may be used in various situations, spurring advancements in AI-assisted communication and negotiation tools.

Keywords: Large Language Models, Online Negotiation, Human-Computer Negotiation, Software Studies, Artificial Intelligence

Divisions:Concordia University > John Molson School of Business > Management
Item Type:Thesis (Masters)
Authors:Verma, Jai Priya
Institution:Concordia University, John Molson School of Business
Degree Name:M. Sc.
Program:Business Analytics and Technology Management
Date:11 April 2025
Thesis Supervisor(s):Vahidov, Rustam
ID Code:995434
Deposited By: Jai Priya Verma
Deposited On:17 Jun 2025 17:44
Last Modified:17 Jun 2025 17:44
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