GEOGRAPHICAL RESEARCH ›› 2014, Vol. 33 ›› Issue (7): 1207-1216.doi: 10.11821/dlyj201407002

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Group decision-making on well-order renovation of urban villages:A case study of Guangzhou

TAO Haiyan1,2, ZHOU Shuli1, ZHUO Li1,2   

  1. 1. Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China;
    2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, Guangzhou 510275, China
  • Received:2013-08-26 Revised:2014-03-06 Online:2014-07-10 Published:2014-07-10

Abstract: Public participation has become one of the city planning processes with legal procedures, so studying well-order renovation of urban villages based on public participant is of great value theoretically and practically for exploring the implement mechanism of rebuilding in China. However an individual decision-maker who is lack of information because of his/her self-interest, knowledge, experience and other restrictions, usually only perceives local space environment, and evaluates partial alternatives according to his preference, i.e., only can be given partial evaluation list. In order to research spatial group decision making based on incomplete information, Kemeny local optimization, which is proposed by Cynthia Dwork et al., is introduced. Steps of aggregation and optimization are as follows: firstly, find all elements in partial lists; then use a simple power-iteration algorithm to obtain a reasonable approximation to the stationary distribution of Markov chain, and the Markov chain ordering is the aggregated initial ordering; last, in order to improve consensus ranking, initial list has been locally Kemeny optimized. The normalized Kendall tau distance was used to evaluate the level of agreement from all the decision makers regarding all the possible alternatives in a given situation. With the example of 52 urban villages in Guangzhou, three different types of decision makers among villagers according to their main source of income and one type of environmentalists are introduced respectively, who are evaluating and ranking the urgency of urban villages rebuilding from their individual preference and perspective. Furthermore, a group decision making solution is obtained by using Kemeny local optimization algorithm. The method is realized by Python. The normalized Kendall tau distance of group solution to four individual solutions is 0.2873, which indicates that the result of group decision-making with all the individuals' decision making has a good consistency. The research demonstrates that the method is useful in making the most consistent group decision while comprehensively considering advices from different interest group, providing a quantitate method for public participation in democratic decision making and scientific decision support to public policy formulation.

Key words: public participant, group decision-making, Kemeny rule, local optimization, urban village, Guangzhou