A computing metaphor approach to customer experience based alliance partner recommendation

Abstract

Purpose – In the service economy era, service value is created from the evaluation of customer experience and it is important to study alliance partner selection for improving service provision. Nevertheless, most of the existing alliance partner selection approaches concentrate on the functional aspects. The purpose of this paper is to provide a novel approach that is customer-centric and emphasizes the emotional aspect of service value. Design/methodology/approach – This paper presents a metaphor-based alliance partner recommendation mechanism (MAPRM) that employs the computing metaphor approach to recommend alliance partners for companies in an innovative way. The main ideas of metaphors are the comparison made between two unlike things that actually have something in common so as to attain innovative thinking. Findings – This study uses the scenario of regional tourism innovation to demonstrate the attempted contributions of MAPRM. The simulation evaluation results show that MAPRM can utilize knowledge and resources from companies to achieve specific alliance goals of satisfying desired customer experiences represented by images that can be analyzed and created based on customers’ feedback and their interactions with companies. Originality/value – MAPRM aims to assist companies to find appropriate alliance partners which offer potential innovation opportunities for service value provision. It is capable of facilitating the alliance partner selection process and assessing customers’ needs at the same time.