Optimal Planning of University Technology Transfer Measures With FDANP-F-FlowSort and an Extended Multiobjective PROMETHEE V

Abstract

This work offers an integrated methodological framework for decision support in planning the implementation of measures that address the barriers of university technology transfer. The planning problem consists of two parts: (1) identifying the high priority measures, and (2) optimally implementing these measures over a specified planning horizon subject to resource constraints. Treated as a multiple criteria sorting problem under uncertainty, the high priority measures are determined via fuzzy DEMATEL and ANP for evaluating the barriers, and the fuzzy FlowSort for classifying the priority of the various measures. Then, an extended multi-objective extension of the PROMETHEE V is offered to determine the degree of implementation of the high priority measures over multiple periods. Demonstrated in an actual case study with 29 identified measures under 24 previously known barriers, findings reveal six high priority measures, which include designing a sustained partnership, engaging in joint research ventures, establishing partnerships from international financial institutions, streamlining objectives to full support of the technology readiness levels, establishing a holistic system approach towards technology readiness levels, and establishing agreements to have access to the industry laboratory facilities. The implementation plan, represented as a set of Pareto optimal solutions, is obtained through the AUGMECON algorithm for the 𝜀-constrained multiobjective linear programming formulation of the extended PROMETHEE V. A layer of sensitivity analysis was performed to test the robustness of the results to changes in the parameters. Finally, policy insights are provided to key decision-makers for advancing UTT.

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