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    A decision-making approach for open innovation model selection in the Turkish automotive industry
    (Inderscience Publishers, 2023) Demir, Ayşe; Peker, İskender; Gök Kısa, Ayşe Cansu
    Abstract: The concept of open innovation (OI) has become crucial in the sustainable competitiveness of industries. The selection and application of appropriate OI models for businesses also compose an important research question. This study aims to decide the most suitable OI model in the Turkish automotive industry through a three-step multi-criteria decision-making (MCDM) model. Firstly, the criteria that may affect the evaluation of the OI models are stated and weighted by analytic hierarchy process (AHP). Afterward, VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is used to rank the OI models that can be implemented in the automotive industry. In the last phase, the impacts of differentiation in criteria weights are tested with one-dimensional sensitivity analysis. According to the results, the coupled open innovation model is ranked as the best alternative and the differentiation in criterion weights does not affect this ranking. This study is the first attempt that attains the most suitable OI model in the automotive industry by a hybrid MCDM approach.