Making personalized recommendations to customers in a service-oriented economy: a quantitative model based on reputation and risk attitude

Authors:
Dickson K. W. Chiu;Ho-fung Leung;Ka-man Lam
Affiliations:
Dickson Computer Systems, Hong Kong, China;The Chinese University of Hong Kong, Hong Kong, China;The Chinese University of Hong Kong, Hong Kong, China
Venue:
ICEC '05 Proceedings of the 7th international conference on Electronic commerce
Year:
2005

Citing 11
Cited 1

Socially conscious decision-making

AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
A fuzzy model of reputation in multi-agent systems

Proceedings of the fifth international conference on Autonomous agents
Social trust: a cognitive approach

Trust and deception in virtual societies
Notions of reputation in multi-agents systems: a review

Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Rational Coordination in Multi-Agent Environments

Autonomous Agents and Multi-Agent Systems
Rational Communication in Multi-Agent Environments

Autonomous Agents and Multi-Agent Systems
A Computational Model of Trust and Reputation for E-businesses

HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 7 - Volume 7
Principles of Trust for MAS: Cognitive Anatomy, Social Importance, and Quantification

ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Coalition formation through motivation and trust

AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Detecting deception in reputation management

AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Trust in information sources as a source for trust: a fuzzy approach

AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems

On the making of service recommendations: An action theory based on utility, reputation, and risk attitude

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In the current service-oriented economy, professional workforce and service personnel have to make not only reasonable but also personalized recommendations in response to individual customer's query. This affects not only the likelihood that the customer takes the recommendations as a short-term benefit but also the service providers' reputation in a long run. However, as different customers have different risk attitudes, they have different trade-off between the service providers' reputation and the recommendations' utilities. Therefore, the classical decision model considering only the utility and success rate is inadequate. We reconsider the problem of making recommendations from multiple perspectives, including reputation and risk attitude. We explain how this model can facilitate service providers to make effective decisions at strategic, tactical, and operations level regarding service recommendations.