Abstract:     With the development of the digital economy, digital technology has broken the boundaries between different industries, and products and technologies have spread across different industries. In this process, companies will accidentally discover that products and technologies from different industries can be recombined, apply in new fields and discover new functions of products and technologies, and then open up new markets. This innovative method, which is different from launching new products and new technologies, is called exaptation. Exaptation is a very important innovative method for companies to improve existing products and technologies to expand the market, but existing research has paid little attention to this. 
    Combining the characteristics of the era of digital economy, this paper found that the ability of patent pools to integrate scattered patents, promote communication between companies in the pool, and create an environment for knowledge sharing is an important factor affecting exaptation. Moreover, digital technology is conducive to patent pools to obtain more innovative resources, and the connection with users is getting closer. Therefore, this research which has introduced two variables, big data capabilities and user innovation, is trying to reveal the mechanism of patent pools′ adaptation to exaptation. To this end, this paper is based on the IPO model and constructed a chain-type intermediary model in which the patent pool acts on exaptation through big data capabilities and user innovation. Since data such as patent pools, big data capabilities, user innovation and exaptation cannot be obtained from publicly available data, the research uses questionnaires to collect data. In order to ensure the persuasiveness and reference value of the research conclusions, the questionnaire is mainly distributed to product developers, market intelligence personnel, technical R&D personnel and other relevant personnel in high-tech enterprises with strong innovation activity and initiative. 
    Using SPSS and AMOS software to conduct hypothesis testing on the collected data using structural equation models and Bootstrap, this paper has obtained the following results which show that: (1) Patent pools have a positive impact on exaptation. Patent pools can be implemented by eliminating barriers to patent, reduce business transaction costs and promote technical exchanges between enterprises, create opportunities for the application of existing products and technologies in new areas, promote exaptation; (2) Big data capabilities play a part of the intermediary role in the positive impact of patent pools on exaptation, and companies rely on big data capabilities look for potential value in existing resources, explore new combinations of production factors, and capture unexpected discoveries; (3) User innovation plays a part of the intermediary role in the positive impact of patent pools on exaptation. Patent pools improve product quality and reduce prices expand the number of users, expand the use of existing products, and promote the discovery of new features of existing products; (4) Big data capabilities and user innovation play a chain-like intermediary role in the positive impact of patent pools on exaptation. The patent pool needs big data capabilities to integrate and analyze users′ opinions and views on existing products, explore new features of the product while meeting user needs, and promote the emergence of exaptation. Both play a role of linkage between the patent pool and exaptation. 
   Finally, this paper provides some theoretical reference and practical guidance for enterprises to transform their innovative thinking and explore the potential value of existing products and technologies.

Key words: exaptation, patent pool, big data capability, user innovation