A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA
M. Tavana, H. Mina, F.J. Santos-Arteaga, Journal of Business Research 154 (2023).
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Journal Article
| Published
| English
Author
Tavana, MadjidLibreCat;
Mina, Hassan;
Santos-Arteaga, Francisco J.
Keywords
Publishing Year
Journal Title
Journal of Business Research
Volume
154
Article Number
113272
ISSN
LibreCat-ID
Cite this
Tavana M, Mina H, Santos-Arteaga FJ. A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA. Journal of Business Research. 2023;154. doi:10.1016/j.jbusres.2022.08.036
Tavana, M., Mina, H., & Santos-Arteaga, F. J. (2023). A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA. Journal of Business Research, 154, Article 113272. https://doi.org/10.1016/j.jbusres.2022.08.036
@article{Tavana_Mina_Santos-Arteaga_2023, title={A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA}, volume={154}, DOI={10.1016/j.jbusres.2022.08.036}, number={113272}, journal={Journal of Business Research}, publisher={Elsevier BV}, author={Tavana, Madjid and Mina, Hassan and Santos-Arteaga, Francisco J.}, year={2023} }
Tavana, Madjid, Hassan Mina, and Francisco J. Santos-Arteaga. “A General Best-Worst Method Considering Interdependency with Application to Innovation and Technology Assessment at NASA.” Journal of Business Research 154 (2023). https://doi.org/10.1016/j.jbusres.2022.08.036.
M. Tavana, H. Mina, and F. J. Santos-Arteaga, “A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA,” Journal of Business Research, vol. 154, Art. no. 113272, 2023, doi: 10.1016/j.jbusres.2022.08.036.
Tavana, Madjid, et al. “A General Best-Worst Method Considering Interdependency with Application to Innovation and Technology Assessment at NASA.” Journal of Business Research, vol. 154, 113272, Elsevier BV, 2023, doi:10.1016/j.jbusres.2022.08.036.
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