Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
Large Language Models (LLMs) present remarkable opportunities for researchers and professionals to improve the effectiveness of software agents acting on companies' behalf. A particularly promising application is using LLMs to negotiate deals with potential customers. This paper proposes integrating negotiation models with LLM capabilities to generate textual offers in machine-human negotiations. It builds on an assumption that LLMs demonstrate emotional intelligence in their interactions with humans, positively influencing negotiation outcomes and human perceptions. The work introduces a prototype agent application based on a phone plan sales scenario. An experiment with human participants tested the performance of the LLM-powered negotiation agent against a version without LLM. The results indicate that the LLM-enhanced software agent reached agreements with better prices.
Recommended Citation
Vahidov, Rustam and Carbonneau, Real, "Customer – Software Agent Negotiations Using Large Language Model: An Experimental Study" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 2.
https://aisel.aisnet.org/hicss-58/in/consumer_facing_technologies/2
Customer – Software Agent Negotiations Using Large Language Model: An Experimental Study
Hilton Waikoloa Village, Hawaii
Large Language Models (LLMs) present remarkable opportunities for researchers and professionals to improve the effectiveness of software agents acting on companies' behalf. A particularly promising application is using LLMs to negotiate deals with potential customers. This paper proposes integrating negotiation models with LLM capabilities to generate textual offers in machine-human negotiations. It builds on an assumption that LLMs demonstrate emotional intelligence in their interactions with humans, positively influencing negotiation outcomes and human perceptions. The work introduces a prototype agent application based on a phone plan sales scenario. An experiment with human participants tested the performance of the LLM-powered negotiation agent against a version without LLM. The results indicate that the LLM-enhanced software agent reached agreements with better prices.
https://aisel.aisnet.org/hicss-58/in/consumer_facing_technologies/2