Group decision-making models for venture capitalists: the PROMETHEE with hesitant fuzzy linguistic information
Abstract
Venture capitalists (VCs) have long been preoccupied by the issue of selecting a promising start-up firm, whereas, ranking the available start-up firms is an effective way to solve this issue. In this paper, the PROMETHEE is chosen to be the fundamental ranking method. Also, the hesitant fuzzy linguistic term set is a suitable tool to simulate VCs’ evaluation information. Additionally, as the deepening of social division of labor and specialization of individuals, group decision making is famous for improving decision-making quality. Moreover, in the decision-making process, VCs exhibit behavioral characteristics which is depicted well by prospect theory that VCs are risk averse for gains and risk seeking for losses and rely on the transformed probability to make their decisions rather than unidimensional probability. Thus, a group prospect PROMETHEE with hesitant fuzzy linguistic information is constructed for VCs to make a better decision. Then, the proposed method is applied to rank start-up firms and the comparative analyses are made as well. It confirms that the group prospect PROMETHEE is better in describing the common behavioral characteristics of VCs and in enhancing the quality of evaluation.
First published online 12 July 2019
Keyword : group decision making, PROMETHEE, prospect theory, hesitant fuzzy linguistic information, venture capital
How to Cite
Tian, X., Xu, Z., & Gu, J. (2019). Group decision-making models for venture capitalists: the PROMETHEE with hesitant fuzzy linguistic information. Technological and Economic Development of Economy, 25(5), 743-773. https://doi.org/10.3846/tede.2019.8741
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Afful-Dadzie, E., Nabareseh, S., Oplatková, Z. K., & Klimek, P. (2016). Using fuzzy PROMETHEE to select countries for developmental aid. In Y. Bi, S. Kapoor, & R. Bhatia (Eds.), Intelligent systems and applications. Series studies in computational intelligence (Vol. 650, pp. 109-132). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-33386-1_6
Afful-Dadzie, E., Oplatková, Z. K., & Nabareseh, S. (2015). Selecting start-up businesses in a public venture capital financing using fuzzy PROMETHEE. Procedia Computer Science, 60(1), 63-72. https://doi.org/10.1016/j.procs.2015.08.105
Amaral, T. M., & Costa, A. P. C. (2014). Improving decision-making and management of hospital resources: An application of the PROMETHEE II method in an Emergency Department. Operations Research for Health Care, 3(1), 1-6. https://doi.org/10.1016/j.orhc.2013.10.002
Aouni, B., Colapinto, C., & Torre, D. L. (2014). A fuzzy goal programming model for venture capital investment decision making. Information Systems and Operational Research, 52(3), 138-146. https://doi.org/10.3138/infor.52.3.138
Avikal, S., Mishra, P. K., & Jain, R. (2014). A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems. International Journal of Production Research, 52(5), 13061317. https://doi.org/10.1080/00207543.2013.831999
Babic, Z., & Plazibat, N. (1998). Ranking of enterprises based on multicriterial analysis. International Journal of Production Economics, 56-57(1-3), 29-35. https://doi.org/10.1016/S0925-5273(97)00133-3
Brans, J. P. (1982). L’ingénièrie de la décision; Elaboration d’instruments d’aide à la décision. La méthode PROMETHEE. In R. Nadeau & M. Landry (Eds.), L’aide à la décision: nature, instruments et perspectives d’avenir (pp. 183-214). Québec, Canada: Presses de l’Université Laval.
Brans, J. P., & Mareschal, B. (1992). Promethee V: MCDM problems with segmentation constraints. Information Systems and Operational Research, 30(2), 85-96. https://doi.org/10.1080/03155986.1992.11732186
Brans, J. P., & Mareschal, B. (1995). The PROMETHEE VI procedure: How to differentiate hard from soft multicriteria problems. Journal of Decision Systems, 4(3), 213-223. https://doi.org/10.1080/12460125.1995.10511652
Brans, J. P., & Vincke, P. H. (1985). A preference ranking organization method. Management Science, 31(6), 647-656. https://doi.org/10.1287/mnsc.31.6.647
Brans, J. P., Vincke, P. H., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. European Journal of Operational Research, 24(2), 228-238. https://doi.org/10.1016/0377-2217(86)90044-5
Bouri, A., Martel, J. M., & Chabchoub, H. (2002). A multi‐criterion approach for selecting attractive portfolio. Journal of Multi-Criteria Decision Analysis, 11(4‐5), 269-277. https://doi.org/10.1002/mcda.334
Gannon, R., Hogan, K. M., & Olson, G. T. (2015). A multicriteria decision model for venture capital firms’ evaluation of new technology business firms. In Applications of Management Science (pp. 27-50). Emerald Group Publishing Limited.
Chen, C. T., Hung, W. Z., & Cheng, H. L. (2011a). Applying linguistic PROMETHEE method in investment portfolio decision-making. International Journal of Electronic Business Management, 9(2), 139-148.
Chen, C. T., Pai, P. F., & Hung, W. Z. (2010). An integrated methodology using linguistic PROMETHEE and maximum deviation method for third-party logistics supplier selection. International Journal of Computational Intelligence Systems, 3(4), 438-451. https://doi.org/10.1080/18756891.2010.9727712
Chen, T. Y. (2014). A PROMETHEE-based outranking method for multiple criteria decision analysis with interval type-2 fuzzy sets. Soft Computing, 18(5), 923-940. https://doi.org/10.1007/s00500-013-1109-4
Chen, T. Y. (2015). IVIF-PROMETHEE outranking methods for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets. Fuzzy Optimization and Decision Making, 14(2), 173-198. https://doi.org/10.1007/s10700-014-9195-z
Chen, Y. H., Wang, T. C., & Wu, C. Y. (2011b). Strategic decisions using the fuzzy PROMETHEE for IS outsourcing. Expert Systems with Applications, 38(10), 13216-13222. https://doi.org/10.1016/j.eswa.2011.04.137
Colapinto, C., & Torre, D. L. (2015). Multiple criteria decision making and goal programming for optimal venture capital investments and portfolio management (pp. 9-30). Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-21158-9_2
Delgado, M., Verdegay, J. L., & Vila, M. A. (1993). On aggregation operations of linguistic labels. International Journal of Intelligent Systems, 8(3), 351-370. https://doi.org/10.1002/int.4550080303
Goumas, M., & Lygerou, V. (2000). An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects. European Journal of Operational Research, 123(3), 606-613. https://doi.org/10.1016/S0377-2217(99)00093-4
Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. https://doi.org/10.1016/j.omega.2016.10.004
Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2018). A fuzzy logic based promethee method for material selection problems. Beni-Suef University Journal of Basic and Applied Sciences, 7(1), 68-79. https://doi.org/10.1016/j.bjbas.2017.07.002
Halouani, N., Chabchoub, H., & Martel, J. M. (2009). PROMETHEE-MD-2T method for project selection. European Journal of Operational Research, 195(3), 841-849. https://doi.org/10.1016/j.ejor.2007.11.016
Herrera, F., & Martínez, L. (2000). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, 8(6), 746-752. https://doi.org/10.1109/91.890332
Jiménez, M. (2005). PROMETHEE: An extension through fuzzy mathematical programming. Journal of the Operational Research Society, 56(1), 119-122. https://doi.org/10.1057/palgrave.jors.2601828
Kabir, G., & Sumi, R. S. (2014). Power substation location selection using fuzzy analytic hierarchy process and PROMETHEE: A case study from Bangladesh. Energy, 72(2), 717-730. https://doi.org/10.1016/j.energy.2014.05.098
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185
Kahraman, C., Onar, S. C., & Oztaysi, B. (2015). Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 8(4), 637-666. https://doi.org/10.1080/18756891.2015.1046325
Kilic, H. S., Zaim, S., & Delen, D. (2015). Selecting “The Best” ERP system for SMEs using a combination of ANP and PROMETHEE methods. Expert Systems with Applications, 42(5), 2343-2352. https://doi.org/10.1016/j.eswa.2014.10.034
Krishankumar, R., Ravichandran, K. S., & Saeid, A. B. (2017). A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences. Applied Soft Computing, 60, 564-576. https://doi.org/10.1016/j.asoc.2017.07.028
Lee, M. C., & Chang, T. (2010). Linguistic variables and PROMETHEE method as tools in evaluation of quality of portal website service. International Journal of Research and Reviews in Computer Science, 1(3), 20-28.
Lerche, N., & Geldermann, J. (2015). Integration of prospect theory into PROMETHEE-a case study concerning sustainable bioenergy concepts. International Journal of Multicriteria Decision Making, 5(4), 309-333. https://doi.org/10.1504/IJMCDM.2015.074085
Li, W. X., & Li, B. Y. (2010). An extension of the Promethee II method based on generalized fuzzy numbers. Expert Systems with Applications, 37(7), 5314-5319. https://doi.org/10.1016/j.eswa.2010.01.004
Liao, B. Q., Wang, L. D., & Liu, X. D. (2016). Possibility-based outranking comparison for PROMETHEE II with uncertain linguistic fuzzy variables. In International conference on oriental thinking and fuzzy logic. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-30874-6_8
Liao, H. C., & Xu, Z. S. (2014). Multi-criteria decision making with intuitionistic fuzzy PROMETHEE. Journal of Intelligent and Fuzzy Systems Applications in Engineering and Technology, 27(4), 17031717.
Liao, H. C., Xu, Z. S, & Zeng, X. J. (2014). Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making. Information Sciences, 271, 125142. https://doi.org/10.1016/j.ins.2014.02.125
Liao, H. C., Xu, Z. S., & Zeng, X. J. (2015). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 13431355. https://doi.org/10.1109/TFUZZ.2014.2360556
Macharis, C., Brans, J. P., & Mareschal, B. (1998). The GDSS PROMETHEE procedure: A PROMETHEE-GAIA based procedure for group decision support. Journal of Decision Systems, 7, 283-307.
Mahmoudi, A., Sadi-Nezhad, S., Makui, A., & Vakili, M. R. (2016). An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem. Kybernetes, 45(8), 1213-1231. https://doi.org/10.1108/K-10-2015-0271
Mateo, J. R. S. C. (2012). Fuzzy PROMETHEE. In Multi criteria analysis in the renewable energy industry. London: Springer. https://doi.org/10.1007/978-1-4471-2346-0_11
Mattos, F., & Garcia, P. (2011). Applications of behavioral finance to entrepreneurs and venture capitalists: Decision making under risk and uncertainty in futures and options markets. In Advances in entrepreneurial finance (pp. 191-205). New York: Springer.
Peko, I., Gjeldum, N., & Bilić, B. (2018). Application of AHP, fuzzy AHP and PROMETHEE method in solving additive manufacturing process selection problem. Tehnički Vjesnik-Technical Gazette Scientific Professional Journal of Technical Faculties of the Josip Juraj Strossmayer University of Osijek, 25(2), 710-719.
Rodríguez, R. M., Martínez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109-119. https://doi.org/10.1109/TFUZZ.2011.2170076
Rodríguez, R. M., Martínez, L., & Herrera, F. (2013). A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets. Information Sciences, 241(12), 28-42. https://doi.org/10.1016/j.ins.2013.04.006
Rodríguez, R. M., Álvaro, L., & Martínez, L. (2016). An overview on fuzzy modelling of complex linguistic preferences in decision making. International Journal of Computational Intelligence Systems, 9, 81-94. https://doi.org/10.1080/18756891.2016.1180821
Samanlioglu, F., & Ayağ, Z. (2017). A fuzzy AHP-PROMETHEE II approach for evaluation of solar power plant location alternatives in Turkey. Journal of Intelligent and Fuzzy Systems, 33(2), 859-871. https://doi.org/10.3233/JIFS-162122
Samanlioglu, F., & Ayağ, Z. (2016). Fuzzy ANP-based PROMETHEE II approach for evaluation of machine tool alternatives. Journal of Intelligent and Fuzzy Systems, 30(4), 2223-2235. https://doi.org/10.3233/IFS-151991
Shih, H. S., Chang, Y. T., & Cheng, C. P. (2016). A generalized PROMETHEE III with risk preferences on losses and gains. International Journal of Information and Management Sciences, 27, 117-127.
Singh, A., Gupta, A., & Mehra, A. (2016). Energy planning problems with interval-valued 2-tuple linguistic information. Operational Research, 1-28.
Treville, S. D., Petty, J. S., & Wager, S. (2014). Economies of extremes: Lessons from venture-capital decision making. Journal of Operations Management, 32(6), 387-398. https://doi.org/10.1016/j.jom.2014.07.002
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323. a target="_blank" href= "https://doi.org/10.1007/BF00122574"> https://doi.org/10.1007/BF00122574
Wang, L., Labella, Á., Rodríguez, R. M., Wang, Y. M., & Martínez, L. (2017). Managing non-homogeneous information and experts’ psychological behavior in group emergency decision making. Symmetry, 9(10), 234. https://doi.org/10.3390/sym9100234
Wang, L., Wang, Y. M., & Martínez, L. (2018). A group decision method based on prospect theory for emergency situations. Information Sciences, 418-419, 119-135. https://doi.org/10.1016/j.ins.2017.07.037
Wang, L., Wang, Y. M., Rodríguez, R. M., & Martínez, L. (2017). A hesitant fuzzy linguistic model for emergency decision making based on fuzzy TODIM method. In IEEE International Conference on Fuzzy Systems (pp. 1-6). Naples, Italy: IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015550
Wei, C., Rodríguez, R. M., & Martínez, L. (2018). Uncertainty measures of extended hesitant fuzzy linguistic term sets. IEEE Transactions on Fuzzy Systems, 26(3), 1763-1768. https://doi.org/10.1109/TFUZZ.2017.2724023
Wei, C. P., Ren, Z. L., & Rodríguez, R. M. (2015). A hesitant fuzzy linguistic TODIM Method based on a score function. International Journal of Computational Intelligence Systems, 8(4), 701-712. https://doi.org/10.1080/18756891.2015.1046329
Widyanto, H. A., & Dalimunthe, Z. (2015). Evaluation criteria of venture capital firms investing on Indonesians’ SME. New York: Social Science Electronic Publishing.
Wiratno, S. E., Latiffianti, E., & Wirawan, K. K. (2015). Selection of business funding proposals using analytic network process: A case study at a venture capital company. Procedia Manufacturing, 4, 237-243. https://doi.org/10.1016/j.promfg.2015.11.037
Xu, Z. S. (2005). Deviation measures of linguistic preference relations in group decision making. Omega, 33(3), 249-254. https://doi.org/10.1016/j.omega.2004.04.008
Yilmaz, B., & Dağdeviren, M. (2011). A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming. Expert Systems with Applications, 38(9), 11641-11650. https://doi.org/10.1016/j.eswa.2011.03.043
Zadeh, L. A. (1975a). The concept of a linguistic variable and its applications to approximate reasoningI. Information Sciences, 8, 199-249. https://doi.org/10.1016/0020-0255(75)90036-5
Zadeh, L. A. (1975b). The concept of a linguistic variable and its applications to approximate reasoningII. Information Sciences, 8, 301-357. https://doi.org/10.1016/0020-0255(75)90046-8
Zadeh, L. A. (1975c). The concept of a linguistic variable and its applications to approximate reasoningIII. Information Sciences, 9, 43-80. https://doi.org/10.1016/0020-0255(75)90017-1
Zhang, X. B. (2012). Venture capital investment selection decision-making base on fuzzy theory. Physics Procedia, 25(22), 1369-1375. https://doi.org/10.1016/j.phpro.2012.03.248
Zhao, L. K. (2009). The study of complex multi-stage dynamic decision making in venture capital project based on piecewise function. In International Conference on Management Science and Engineering (pp. 107-111). Beijing, China.
Zhou, J. S. (2012). Research on appraisal model of venture capital investing project based on high-tech outcome transformation with uncertain linguistic information. Advances in Information Sciences and Service Sciences, 4(1), 224-229. https://doi.org/10.4156/aiss.vol4.issue1.29
Afful-Dadzie, E., Oplatková, Z. K., & Nabareseh, S. (2015). Selecting start-up businesses in a public venture capital financing using fuzzy PROMETHEE. Procedia Computer Science, 60(1), 63-72. https://doi.org/10.1016/j.procs.2015.08.105
Amaral, T. M., & Costa, A. P. C. (2014). Improving decision-making and management of hospital resources: An application of the PROMETHEE II method in an Emergency Department. Operations Research for Health Care, 3(1), 1-6. https://doi.org/10.1016/j.orhc.2013.10.002
Aouni, B., Colapinto, C., & Torre, D. L. (2014). A fuzzy goal programming model for venture capital investment decision making. Information Systems and Operational Research, 52(3), 138-146. https://doi.org/10.3138/infor.52.3.138
Avikal, S., Mishra, P. K., & Jain, R. (2014). A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems. International Journal of Production Research, 52(5), 13061317. https://doi.org/10.1080/00207543.2013.831999
Babic, Z., & Plazibat, N. (1998). Ranking of enterprises based on multicriterial analysis. International Journal of Production Economics, 56-57(1-3), 29-35. https://doi.org/10.1016/S0925-5273(97)00133-3
Brans, J. P. (1982). L’ingénièrie de la décision; Elaboration d’instruments d’aide à la décision. La méthode PROMETHEE. In R. Nadeau & M. Landry (Eds.), L’aide à la décision: nature, instruments et perspectives d’avenir (pp. 183-214). Québec, Canada: Presses de l’Université Laval.
Brans, J. P., & Mareschal, B. (1992). Promethee V: MCDM problems with segmentation constraints. Information Systems and Operational Research, 30(2), 85-96. https://doi.org/10.1080/03155986.1992.11732186
Brans, J. P., & Mareschal, B. (1995). The PROMETHEE VI procedure: How to differentiate hard from soft multicriteria problems. Journal of Decision Systems, 4(3), 213-223. https://doi.org/10.1080/12460125.1995.10511652
Brans, J. P., & Vincke, P. H. (1985). A preference ranking organization method. Management Science, 31(6), 647-656. https://doi.org/10.1287/mnsc.31.6.647
Brans, J. P., Vincke, P. H., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. European Journal of Operational Research, 24(2), 228-238. https://doi.org/10.1016/0377-2217(86)90044-5
Bouri, A., Martel, J. M., & Chabchoub, H. (2002). A multi‐criterion approach for selecting attractive portfolio. Journal of Multi-Criteria Decision Analysis, 11(4‐5), 269-277. https://doi.org/10.1002/mcda.334
Gannon, R., Hogan, K. M., & Olson, G. T. (2015). A multicriteria decision model for venture capital firms’ evaluation of new technology business firms. In Applications of Management Science (pp. 27-50). Emerald Group Publishing Limited.
Chen, C. T., Hung, W. Z., & Cheng, H. L. (2011a). Applying linguistic PROMETHEE method in investment portfolio decision-making. International Journal of Electronic Business Management, 9(2), 139-148.
Chen, C. T., Pai, P. F., & Hung, W. Z. (2010). An integrated methodology using linguistic PROMETHEE and maximum deviation method for third-party logistics supplier selection. International Journal of Computational Intelligence Systems, 3(4), 438-451. https://doi.org/10.1080/18756891.2010.9727712
Chen, T. Y. (2014). A PROMETHEE-based outranking method for multiple criteria decision analysis with interval type-2 fuzzy sets. Soft Computing, 18(5), 923-940. https://doi.org/10.1007/s00500-013-1109-4
Chen, T. Y. (2015). IVIF-PROMETHEE outranking methods for multiple criteria decision analysis based on interval-valued intuitionistic fuzzy sets. Fuzzy Optimization and Decision Making, 14(2), 173-198. https://doi.org/10.1007/s10700-014-9195-z
Chen, Y. H., Wang, T. C., & Wu, C. Y. (2011b). Strategic decisions using the fuzzy PROMETHEE for IS outsourcing. Expert Systems with Applications, 38(10), 13216-13222. https://doi.org/10.1016/j.eswa.2011.04.137
Colapinto, C., & Torre, D. L. (2015). Multiple criteria decision making and goal programming for optimal venture capital investments and portfolio management (pp. 9-30). Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-21158-9_2
Delgado, M., Verdegay, J. L., & Vila, M. A. (1993). On aggregation operations of linguistic labels. International Journal of Intelligent Systems, 8(3), 351-370. https://doi.org/10.1002/int.4550080303
Goumas, M., & Lygerou, V. (2000). An extension of the PROMETHEE method for decision making in fuzzy environment: Ranking of alternative energy exploitation projects. European Journal of Operational Research, 123(3), 606-613. https://doi.org/10.1016/S0377-2217(99)00093-4
Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. https://doi.org/10.1016/j.omega.2016.10.004
Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2018). A fuzzy logic based promethee method for material selection problems. Beni-Suef University Journal of Basic and Applied Sciences, 7(1), 68-79. https://doi.org/10.1016/j.bjbas.2017.07.002
Halouani, N., Chabchoub, H., & Martel, J. M. (2009). PROMETHEE-MD-2T method for project selection. European Journal of Operational Research, 195(3), 841-849. https://doi.org/10.1016/j.ejor.2007.11.016
Herrera, F., & Martínez, L. (2000). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, 8(6), 746-752. https://doi.org/10.1109/91.890332
Jiménez, M. (2005). PROMETHEE: An extension through fuzzy mathematical programming. Journal of the Operational Research Society, 56(1), 119-122. https://doi.org/10.1057/palgrave.jors.2601828
Kabir, G., & Sumi, R. S. (2014). Power substation location selection using fuzzy analytic hierarchy process and PROMETHEE: A case study from Bangladesh. Energy, 72(2), 717-730. https://doi.org/10.1016/j.energy.2014.05.098
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185
Kahraman, C., Onar, S. C., & Oztaysi, B. (2015). Fuzzy multicriteria decision-making: A literature review. International Journal of Computational Intelligence Systems, 8(4), 637-666. https://doi.org/10.1080/18756891.2015.1046325
Kilic, H. S., Zaim, S., & Delen, D. (2015). Selecting “The Best” ERP system for SMEs using a combination of ANP and PROMETHEE methods. Expert Systems with Applications, 42(5), 2343-2352. https://doi.org/10.1016/j.eswa.2014.10.034
Krishankumar, R., Ravichandran, K. S., & Saeid, A. B. (2017). A new extension to PROMETHEE under intuitionistic fuzzy environment for solving supplier selection problem with linguistic preferences. Applied Soft Computing, 60, 564-576. https://doi.org/10.1016/j.asoc.2017.07.028
Lee, M. C., & Chang, T. (2010). Linguistic variables and PROMETHEE method as tools in evaluation of quality of portal website service. International Journal of Research and Reviews in Computer Science, 1(3), 20-28.
Lerche, N., & Geldermann, J. (2015). Integration of prospect theory into PROMETHEE-a case study concerning sustainable bioenergy concepts. International Journal of Multicriteria Decision Making, 5(4), 309-333. https://doi.org/10.1504/IJMCDM.2015.074085
Li, W. X., & Li, B. Y. (2010). An extension of the Promethee II method based on generalized fuzzy numbers. Expert Systems with Applications, 37(7), 5314-5319. https://doi.org/10.1016/j.eswa.2010.01.004
Liao, B. Q., Wang, L. D., & Liu, X. D. (2016). Possibility-based outranking comparison for PROMETHEE II with uncertain linguistic fuzzy variables. In International conference on oriental thinking and fuzzy logic. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-30874-6_8
Liao, H. C., & Xu, Z. S. (2014). Multi-criteria decision making with intuitionistic fuzzy PROMETHEE. Journal of Intelligent and Fuzzy Systems Applications in Engineering and Technology, 27(4), 17031717.
Liao, H. C., Xu, Z. S, & Zeng, X. J. (2014). Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making. Information Sciences, 271, 125142. https://doi.org/10.1016/j.ins.2014.02.125
Liao, H. C., Xu, Z. S., & Zeng, X. J. (2015). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 13431355. https://doi.org/10.1109/TFUZZ.2014.2360556
Macharis, C., Brans, J. P., & Mareschal, B. (1998). The GDSS PROMETHEE procedure: A PROMETHEE-GAIA based procedure for group decision support. Journal of Decision Systems, 7, 283-307.
Mahmoudi, A., Sadi-Nezhad, S., Makui, A., & Vakili, M. R. (2016). An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem. Kybernetes, 45(8), 1213-1231. https://doi.org/10.1108/K-10-2015-0271
Mateo, J. R. S. C. (2012). Fuzzy PROMETHEE. In Multi criteria analysis in the renewable energy industry. London: Springer. https://doi.org/10.1007/978-1-4471-2346-0_11
Mattos, F., & Garcia, P. (2011). Applications of behavioral finance to entrepreneurs and venture capitalists: Decision making under risk and uncertainty in futures and options markets. In Advances in entrepreneurial finance (pp. 191-205). New York: Springer.
Peko, I., Gjeldum, N., & Bilić, B. (2018). Application of AHP, fuzzy AHP and PROMETHEE method in solving additive manufacturing process selection problem. Tehnički Vjesnik-Technical Gazette Scientific Professional Journal of Technical Faculties of the Josip Juraj Strossmayer University of Osijek, 25(2), 710-719.
Rodríguez, R. M., Martínez, L., & Herrera, F. (2012). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109-119. https://doi.org/10.1109/TFUZZ.2011.2170076
Rodríguez, R. M., Martínez, L., & Herrera, F. (2013). A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets. Information Sciences, 241(12), 28-42. https://doi.org/10.1016/j.ins.2013.04.006
Rodríguez, R. M., Álvaro, L., & Martínez, L. (2016). An overview on fuzzy modelling of complex linguistic preferences in decision making. International Journal of Computational Intelligence Systems, 9, 81-94. https://doi.org/10.1080/18756891.2016.1180821
Samanlioglu, F., & Ayağ, Z. (2017). A fuzzy AHP-PROMETHEE II approach for evaluation of solar power plant location alternatives in Turkey. Journal of Intelligent and Fuzzy Systems, 33(2), 859-871. https://doi.org/10.3233/JIFS-162122
Samanlioglu, F., & Ayağ, Z. (2016). Fuzzy ANP-based PROMETHEE II approach for evaluation of machine tool alternatives. Journal of Intelligent and Fuzzy Systems, 30(4), 2223-2235. https://doi.org/10.3233/IFS-151991
Shih, H. S., Chang, Y. T., & Cheng, C. P. (2016). A generalized PROMETHEE III with risk preferences on losses and gains. International Journal of Information and Management Sciences, 27, 117-127.
Singh, A., Gupta, A., & Mehra, A. (2016). Energy planning problems with interval-valued 2-tuple linguistic information. Operational Research, 1-28.
Treville, S. D., Petty, J. S., & Wager, S. (2014). Economies of extremes: Lessons from venture-capital decision making. Journal of Operations Management, 32(6), 387-398. https://doi.org/10.1016/j.jom.2014.07.002
Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323. a target="_blank" href= "https://doi.org/10.1007/BF00122574"> https://doi.org/10.1007/BF00122574
Wang, L., Labella, Á., Rodríguez, R. M., Wang, Y. M., & Martínez, L. (2017). Managing non-homogeneous information and experts’ psychological behavior in group emergency decision making. Symmetry, 9(10), 234. https://doi.org/10.3390/sym9100234
Wang, L., Wang, Y. M., & Martínez, L. (2018). A group decision method based on prospect theory for emergency situations. Information Sciences, 418-419, 119-135. https://doi.org/10.1016/j.ins.2017.07.037
Wang, L., Wang, Y. M., Rodríguez, R. M., & Martínez, L. (2017). A hesitant fuzzy linguistic model for emergency decision making based on fuzzy TODIM method. In IEEE International Conference on Fuzzy Systems (pp. 1-6). Naples, Italy: IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015550
Wei, C., Rodríguez, R. M., & Martínez, L. (2018). Uncertainty measures of extended hesitant fuzzy linguistic term sets. IEEE Transactions on Fuzzy Systems, 26(3), 1763-1768. https://doi.org/10.1109/TFUZZ.2017.2724023
Wei, C. P., Ren, Z. L., & Rodríguez, R. M. (2015). A hesitant fuzzy linguistic TODIM Method based on a score function. International Journal of Computational Intelligence Systems, 8(4), 701-712. https://doi.org/10.1080/18756891.2015.1046329
Widyanto, H. A., & Dalimunthe, Z. (2015). Evaluation criteria of venture capital firms investing on Indonesians’ SME. New York: Social Science Electronic Publishing.
Wiratno, S. E., Latiffianti, E., & Wirawan, K. K. (2015). Selection of business funding proposals using analytic network process: A case study at a venture capital company. Procedia Manufacturing, 4, 237-243. https://doi.org/10.1016/j.promfg.2015.11.037
Xu, Z. S. (2005). Deviation measures of linguistic preference relations in group decision making. Omega, 33(3), 249-254. https://doi.org/10.1016/j.omega.2004.04.008
Yilmaz, B., & Dağdeviren, M. (2011). A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming. Expert Systems with Applications, 38(9), 11641-11650. https://doi.org/10.1016/j.eswa.2011.03.043
Zadeh, L. A. (1975a). The concept of a linguistic variable and its applications to approximate reasoningI. Information Sciences, 8, 199-249. https://doi.org/10.1016/0020-0255(75)90036-5
Zadeh, L. A. (1975b). The concept of a linguistic variable and its applications to approximate reasoningII. Information Sciences, 8, 301-357. https://doi.org/10.1016/0020-0255(75)90046-8
Zadeh, L. A. (1975c). The concept of a linguistic variable and its applications to approximate reasoningIII. Information Sciences, 9, 43-80. https://doi.org/10.1016/0020-0255(75)90017-1
Zhang, X. B. (2012). Venture capital investment selection decision-making base on fuzzy theory. Physics Procedia, 25(22), 1369-1375. https://doi.org/10.1016/j.phpro.2012.03.248
Zhao, L. K. (2009). The study of complex multi-stage dynamic decision making in venture capital project based on piecewise function. In International Conference on Management Science and Engineering (pp. 107-111). Beijing, China.
Zhou, J. S. (2012). Research on appraisal model of venture capital investing project based on high-tech outcome transformation with uncertain linguistic information. Advances in Information Sciences and Service Sciences, 4(1), 224-229. https://doi.org/10.4156/aiss.vol4.issue1.29