Open innovation has gradually gained greater importance over time as commitment to a culture of constant innovation has become increasingly indispensable for organizations' long-term survival. This trend has made understanding the factors that affect innovation capacity and success imperative. Given the wide range of determinants already identified, researchers seeking to analyze these factors face difficult, extremely complex challenges in terms of determining their effects on small and medium-sized enterprises (SMEs). The existing literature mentions limitations arising from how criteria have been selected for evaluation systems and how these determinants' relative weights have been defined. This article develops an analysis system that combines cognitive mapping—based on the jointly understanding, reflecting, and negotiating strategy making approach—and the best-worst method. The two main aims are to identify the most significant criteria for evaluations of SME propensity to engage in open innovation and to calculate these factors' relative weights. This article focuses on promoting realistic, comprehensive analyses that foster clearer and more conscious decision making based on a holistic view of open innovation assessment.

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Best worst method (BWM),Cognitive mapping,Decision-making support,Multiple criteria decision analysis (MCDA),Journey making,Open innovation,Small and medium-sized enterprise (SME)

• Economics and Business - Social Sciences