Abstract
Innovation involves matching needs and solutions to form need–solution pairs (NSPs). This study investigates how organizations systemically identify and develop NSPs when searching for novel applications of existing technologies through technology-market linking—a critical yet underexplored process in strategy and innovation research. Using a multiple case study design, we analyze four innovation projects drawing on 306 expert interviews , 89 innovation proposals, and longitudinal data from diaries and retrospective interviews with 18 search agents. Our findings show that searchers engage in recurring learning practices to acquire knowledge about unmet needs, potential solutions, and how they co-evolve. These practices structure the integration of different types of knowledge over time, giving rise to four distinct search patterns that guide the direction and evolution of innovation efforts. With this study, we advance research on problem solving in innovation by unpacking how NSPs can be deliberately discovered and developed through exploratory search, rather than emerging solely from spontaneous or serendipitous encounters. We expand the literature on organizational search and learning by empirically documenting the micro-level learning processes and behaviors enabling the dynamic coupling of need and solution spaces. Finally, we contribute to the open innovation perspective by demonstrating how external knowledge critically shapes emerging technology–market combinations.
