Consumer demand based recombinant search for idea generation

Extant studies of recombinant innovation focus on technology-driven recombinant search. Meanwhile, the methodological investigation of how to generate new combinations with potentially high values, especially based on consumer demands, is still very less common. This article is among the first efforts to cope with consumer demand based recombinant search to generate technology opportunities or ideas with potentially high values. Since function is the most important concept in determining an invention’s basic characteristics, which greatly relate to and influence consumer demands, we first propose a conceptual recombinant search framework, where functions serve as the role of a bridge between technologies and demands. We then propose a four-phase solution to implement the proposed conceptual framework. Empirically, the proposed methodology is finally applied to the rehabilitation robot industry, which is characterized by a huge market size with fierce competition, immature development as well as the importance of considering consumer demands. The results show that: 1) greater familiarity does not necessarily induce more higher consumer satisfaction; 2) there is an inverted U-shaped relationship between the level of recombination and the overall consumer satisfaction; and 3) our model outperforms three baseline models in terms of quantity rate and quality rate for the ideas generated.