Structured selection of partners in Open Innovation communities: an IF-TOPSIS based approach

Purpose – Open innovation (OI) literature suggests that firms can improve their innovation performance by learning from a large set of actors in the innovation process. However, the extant literature has overlooked the “who” question: which partners should be included in the different phases of the innovation funnel? How should they be selected? This paper aims to offer, while focusing in the early phases of the innovation process, a list of possible criteria for partner evaluation and suggests a structured methodology for their selection. Design/methodology/approach – An empirical test of both the criteria and the methodology is presented with reference to a company operating in the Advanced Underwater Systems sector. The authors propose a peer-based modification of intuitionistic fuzzy (IF) multi-criteria Group decision-making with TOPSIS method (peer IF-TOPSIS). IF-TOPSIS allows coping with subjectivity, imprecision and vagueness in group decision-making problem under multiple criteria. Findings – The paper proposes an innovative application of a peer-modified version of IF-TOPSIS to a challenging and complex decision problem – partner selection for OI – which is usually subjected to uncertainty and evaluation from multiple experts. Originality/value – This work contributes to the extant literature advancing the criteria that could be used in the selection process, avoiding focusing on single specific aspects of the collaboration phases or on specific types of partners (suppliers).