Project selection in a biotechnology startup using combinatorial acceptability analysis




Decision analysis, acceptability analysis, group decision-making, shared mental models, consensus-building


Combinatorial Multi-Criteria Acceptability Analysis (CMAA) is a new algorithmic framework that enables the use of standard (i.e., single-user) multicriteria decision-making methods by groups. In this paper, we present the first application of CMAA to a real-life decision. Our objectives were to study the performance of the method in a real-life setting and to test two hypotheses concerning the application of the method. Three founders of a biotechnology startup had to choose a product development project. We describe the decision problem and the consensus path taken by the founders, and we illustrate some of the analytical possibilities offered by the method. Of the 25 evaluation conflicts contained in the initial input, only eight needed to be resolved in order to achieve a hard consensus. A simulation experiment showed that the expected value for this size problem is 7.6 resolution steps. The method generates a very large state space, so complete enumeration can become prohibitively expensive. A computational experiment confirmed our assumption that 10,000 random samples are sufficient if Monte Carlo simulation is used instead. A third simulation experiment provided support for the hypothesis that consensus-building with the non-compensatory decision model used is more efficient than with a more typical compensatory model. We conclude that the CMAA method is well-suited for multi-criteria group decisions; it provides a wealth of analytical detail, and its entropy-based heuristic can guide the group to consensus in a small number of steps.


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Bairagi, B. (2022). A fuzzy interval based multi-criteria homogeneous group decision making technique: An application to airports ranking problem. Decision Making: Appli-cations in Management and Engineering, 6(2), 1–15.

Boix-Cots, D., Pardo-Bosch, F., & Alvarez, P. P. (2023). A systematic review on multi-criteria group decision-making methods based on weights: Analysis and classification scheme. Information Fusion, 96(2), 16–36.

Bortolini, R. F., Cortimiglia, M. N., de Moura Ferreira Danilevicz, A., & Ghezzi, A. (2021). Lean Startup: a comprehensive historical review. Management Decision, 59(8), 1765–1783.

Cai, Y., Jin, F., Liu, J., Zhou, L., & Tao, Z. (2023). A survey of collaborative decision-making: Bibliometrics, preliminaries, methodologies, applications and future direc-tions. Engineering Applications of Artificial Intelligence, 122, 106064.

Chao, X., Kou, G., Peng, Y., & Viedma, E. H. (2021). Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in fi-nancial inclusion. European Journal of Operational Research, 288(1), 271–293.

DeSanctis, G., & Gallupe, R. B. (1987). A foundation for the study of group decision support systems. Management Science, 33(5), 589–609.

Dong, Y., Zhang, H., & Herrera-Viedma, E. (2016). Integrating experts’ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decision Support Systems, 84, 1–15.

Dreu, C. K. W. De, & West, M. A. (2001). Minority dissent and team innovation: The im-portance of participation in decision making. Journal of Applied Psychology, 86(6), 1191.

Goers, J., & Horton, G. (2023). Combinatorial Multi-Criteria Acceptability Analysis: A Decision Analysis and Consensus-Building Approach for Cooperative Groups. Europe-an Journal of Operational Research, 308(1), 243–254.

Guo, W., Gong, Z., Zhang, W.-G., & Xu, Y. (2023). Minimum cost consensus modeling under dynamic feedback regulation mechanism considering consensus principle and tolerance level. European Journal of Operational Research, 306(3), 1279–1295.

Herrera-Viedma, E., Cabrerizo, F. J., Kacprzyk, J., & Pedrycz, W. (2014). A Review of Soft Consensus Models in a Fuzzy Environment. Information Fusion, 17, 4–13.

Horton, G., & Goers, J. (2021). ABX-LEX: An Argument-Driven Approach for the Digital Facilitation of Efficient Group Decisions. International Journal of Information Tech-nology & Decision Making, 20(01), 137–164.

Janković, A., & Popović, M. (2019). Methods for assigning weights to decision makers in group AHP decision-making. Decision Making: Applications in Management and En-gineering, 2(1), 147–165.

Kacprzyk, J., & Fedrizzi, M. (1988). A ‘soft’ measure of consensus in the setting of par-tial (fuzzy) preferences. European Journal of Operational Research, 34(3), 316–325.

Kline, D. A. (2005). Intuitive team decision making. In H. Montgomery, R. Lipshitz, & B. Brehmer (Eds.), How professionals make decisions (pp. 171–182). Lawrence Erlbaum Associates.

Koksalmis, E., & Kabak, Ö. (2019). Deriving decision makers’ weights in group deci-sion making: An overview of objective methods. Information Fusion, 49, 146–160.

Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making. Operations Research, 49(3), 444–454.

Li, Y., Chen, X., Dong, Y., & Herrera, F. (2020). Linguistic group decision making: Axio-matic distance and minimum cost consensus. Information Sciences, 541, 242–258.

Lu, L., Yuan, Y. C., & McLeod, P. L. (2012). Twenty-Five Years of Hidden Profiles in Group Decision Making: A Meta-Analysis. Personality and Social Psychology Review, 16(1), 54–75.

Moogk, R. (2012). Minimum Viable Product and the Importance of Experimentation in Technology Startups. Technology Innovation Management Review, 2(3), 23–26.

Moral, M. J. Del, Chiclana, F., Tapia, J. M., & Herrera-Viedma, E. (2018). A comparative study on consensus measures in group decision making. International Journal of Intel-ligent Systems, 33(8), 1624–1638.

Nijstad, B. A., Berger-Selman, F., & Dreu, C. K. W. De. (2014). Innovation in top man-agement teams: Minority dissent, transformational leadership, and radical innovations. European Journal of Work and Organizational Psychology, 23(2), 310–322.

Ries, E. (2011). The lean startup: How today’s entrepreneurs use continuous innova-tion to create radically successful businesses. Crown Business.

Schulz-Hardt, S., Brodbeck, F. C., Mojzisch, A., Kerschreiter, R., & Frey, D. (2006). Group decision making in hidden profile situations: dissent as a facilitator for decision quali-ty. Journal of Personality and Social Psychology, 91(6), 1080.

Schulz-Hardt, S., & Mojzisch, A. (2012). How to achieve synergy in group decision mak-ing: Lessons to be learned from the hidden profile paradigm. European Review of Social Psychology, 23(1), 305–343.

Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Tech-nical Journal, 27(4), 623–666.

Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision mak-ing: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48(6), 1467–1478.

Tapia, J. M., Chiclana, F., del Moral, M. J., & Herrera–Viedma, E. (2023). Measuring Con-sensus in Group Decision-Making Problems Through an Inequality Measure. Interna-tional Conference on Computers Communications and Control, 313–319.

Tech, R. P. G. (2018). Introduction: High-Tech Startup Financing. In Financing High-Tech Startups: Using Productive Signaling to Efficiently Overcome the Liability of Complexity (pp. 1–28). Springer International Publishing.

De Vreede, T. De, Reiter-Palmon, R., & Vreede, G.-J. De. (2013). The Effect of Shared Mental Models on Consensus. Proceedings of the Annual Hawaii International Confer-ence on System Sciences, 263–272.

Xu, Z. (2009). An automatic approach to reaching consensus in multiple attribute group decision making. Computers & Industrial Engineering, 56(4), 1369–1374.

Yahaya, S.-Y., & Abu-Bakar, N. (2007). New product development management issues and decision-making approaches. Management Decision, 45(7), 1123–1142.

Yue, C. (2017). Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations. Applied Soft Computing, 60, 737–749.

Zhang, H., Dong, Y., Chiclana, F., & Yu, S. (2019). Consensus efficiency in group decision making: A comprehensive comparative study and its optimal design. European Journal of Operational Research, 275(2), 580–598.



How to Cite

Goers, J., & Horton, G. (2023). Project selection in a biotechnology startup using combinatorial acceptability analysis. Decision Making: Applications in Management and Engineering, 6(2), 828–852.