**7. Conclusions and discussion**

In sum, the model shows three conditions for the generation of imaginative and creative technological innovation: 1. the importance of cross-domain knowledge is stressed, not just because an innovative solution, by its definition, cannot be found in the original domain of the product but also because the nature of technological innovation, more often than not, involves combinations or incorporation of new functions from other domains. For example, a smartphone is a combination of an original mobile phone and internet functions. 2. conceptual combination is viewed as a primitive heuristic for information searching and interpretation. The human ability to imagine and create is rooted in the brain's capability to randomly combine information stored in memory and make sense of these novel conceptual combinations. It highlights the importance of not only memory search and retrieval but also cognitive mechanisms to make sense of the meanings implied by the remote associations of the concepts. Many heuristics and methods for innovative ideas such as Triz [48], SCAMPER [49], and morphological analysis [50] are just more elaborate and structured methods of conceptual combination. 3. Pattern recognition is a cognitive task not very well explained before in terms of how an original idea can be recognized and selected as a plausible solution to the problem. Here, it is proposed that the ability to recognize and select the outcome from conceptual combinations is a joint function of the goal, the interpretation efforts, and the value

(bias) held by the individual and the team members. Recognition of a solution in its primitive form is shaped by the goal one is searching for in the creative process. Without it, one can be totally blind to the opportunity [51]. However, the acceptance and adoption of technological innovation are also determined by the group's value about what the most desirable outcome is and how much risk (the investment) the group would take for its success in the making and selling of the product. Cultural and social factors may also come into play at the verification stage of every phase of CDIO [25, 42, 52].

The plausibility of the model awaits empirical verification. It cannot be tested directly. However, its theoretical and practical implications can be tested by logical analyses, experiments, field studies, or case studies. Because technological innovation is an application of scientific knowledge to the development of artifacts for human use, the importance of scientific knowledge and user experience for innovation in every phase of CDIO is beyond doubt. The nature of technological innovation itself is a combination of different technological products employed to produce a function that has higher utility than the previous one. Conceptual combination is the most primitive form of creative thinking. Empirical studies that examined the effects of conceptual combination in technological innovation were reported in the earlier sections of this paper. Studies can also be done to examine the effects of diversity of a team's knowledge and its team members' imaginative abilities on product innovation. For example, in Wang, Lu and Li's study [53], data were drawn from 49 dyads who were the finalists out of 120 teams of a collegiate saw-design competition. Their task was to conceive and design an unusual use of the saw. The ideas behind the sketches of their design were presented and scored by 3 professors and 2 design professionals according to three criteria: inventiveness (60%), clarity of conceptualization and presentation (20%), and creative strategy for competition and marketing (20%). Results showed that participants' imagination score measured by a conceptual combination test, efficiency, effectiveness of communication between the dyad, and heterogeneity of the team composition all contributed positively to design performance. The interaction between the imagination score and the heterogeneity of the team suggested that the dyads with higher imagination scores produced more creative designs when their collaborators were from a more different domain. In addition, a behavioral measure of imagination was constructed based on conceptual combination theory with acceptable reliability and validity [7]. The test scores were found to be able to predict design students' design performance more than the originality measure of divergent thinking ability. Methods of training to enhance engineering imagination based on conceptual combination theory have also been designed and can be incorporated into engineering education [32].

One practical implication that deserves special attention for technological education and the industry is that chance plays a role in creative processes, but it does not come without cost. The magic of incubation and illumination suggests that, given sufficient motivation and prerequisite conditions, human minds may continue to freely search and combine ideas even subconsciously. In an industry, the absorptive ability of a firm, most likely an effect spilled over from its leaders, affects the innovativeness of the firm [54]. In engineering education, efforts should not be limited to only acquiring the CDIO knowledge necessary for technological innovation but also include recognition and cultivation of the important environmental conditions for innovative ideas to be brooded upon, pop out, and be recognized and selected.

Conceptual combination is a simple heuristic for generating imaginative ideas. It is made possible by the way human neurons may randomly combine with other neurons and generate new links between existing nodes. This automatic bottom-up process is accompanied by a top-down interpretation process that makes sense of the possible
