Generation of new service concepts: A morphology analysis and genetic algorithm approach

The concept generation is the first and most important stage in the process of new service development (NSD). Morphology analysis (MA), which is aimed at modeling a complex problem, provides strong possibility of revealing unexpected new service concepts (NSCs), but the weakness lies in screening and selecting satisfactory ones. The NSCs derived through MA may be too much for further investigation. In response, this study proposes a systematic approach to generation of NSCs based on MA and genetic algorithm (GA). The proposed approach is comprised of two stages, NSC derivation and NSC screening. During the first stage, MA is conducted to derive service concepts by exploring all possible combinations of a morphology matrix. The second stage deals with screening concepts that have been derived at the first stage. GA is employed here not merely as an optimization engine, but also as a search tool with screening criteria. The practical utility and benefits are that the possible and reasonable NSCs can be identified at the very first time in the process of NSD. In addition, it may lessen the pressures, such as time constraints, of concept generation. The final result, a set of 10–20 satisfactory NSCs, is expected to aid decision making on generation of NSCs. A case on game service is presented to illustrate the proposed approach in detail.