TY - JOUR
T1 - Towards an effective negotiation modeling
T2 - Investigating transboundary disputes with cases of lower possibilities
AU - Chang, Victor
AU - Liu, Ben S.C.
AU - Sudharshan, D.
AU - Xu, Qianwen Ariel
N1 - Funding Information:
This research is partly supported by VC Research (VCR 0000019).
Publisher Copyright:
© 2020
PY - 2021/4
Y1 - 2021/4
N2 - Existing literature in group-decision making proposed various rules of aggregating individuals’ opinions to group outcomes.With anonymity maintained, this paper can model round-robin assessments by a group with individuals updating their assessments every round in a Bayesian manner as per Bordley (1983, 1986, 2009). Utilizing the properties of the finite Markov Chain process, the analysis shows (a) the conditions for a group consensus to converge, (b) the maximum number of rounds before such convergence occurs, and (c) the consensus assessment. The resulting dynamic model is tested to show that it also captures the results of several empirical studies. We apply them to the negotiationfor the transboundary dispute and our simulations demonstrate the convergence of three different cases of lower possibilities, which support transboundary cases and resolutions. We also develop algorithms based on Fuzzy Delphi (Murray et al. 1985, Ishikawa et al. 1993) and Grey Delphi Methods (Ma et al., 2011) to predict the probability and likely outcomes of the transboundary dispute between China and India, which is one of the cases with low probability. Upon 1,000 simulations under volatile international relations, the development of theconvergence demonstrates the integrated Delphi Method is more suitable for predicting volatile situations.
AB - Existing literature in group-decision making proposed various rules of aggregating individuals’ opinions to group outcomes.With anonymity maintained, this paper can model round-robin assessments by a group with individuals updating their assessments every round in a Bayesian manner as per Bordley (1983, 1986, 2009). Utilizing the properties of the finite Markov Chain process, the analysis shows (a) the conditions for a group consensus to converge, (b) the maximum number of rounds before such convergence occurs, and (c) the consensus assessment. The resulting dynamic model is tested to show that it also captures the results of several empirical studies. We apply them to the negotiationfor the transboundary dispute and our simulations demonstrate the convergence of three different cases of lower possibilities, which support transboundary cases and resolutions. We also develop algorithms based on Fuzzy Delphi (Murray et al. 1985, Ishikawa et al. 1993) and Grey Delphi Methods (Ma et al., 2011) to predict the probability and likely outcomes of the transboundary dispute between China and India, which is one of the cases with low probability. Upon 1,000 simulations under volatile international relations, the development of theconvergence demonstrates the integrated Delphi Method is more suitable for predicting volatile situations.
KW - Bayesian updating
KW - Dynamic assessment model
KW - Finite Markov chain process
KW - Fuzzy Delphi and Grey Delphi methods
KW - Group decision making
KW - Negotiation with lower possibilities
KW - Transboundary disputes
UR - http://www.scopus.com/inward/record.url?scp=85099512980&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2020.120491
DO - 10.1016/j.techfore.2020.120491
M3 - Article
AN - SCOPUS:85099512980
SN - 0040-1625
VL - 165
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 120491
ER -