Evolutional Attitude Based on Option Prioritization for Conflict Analysis of Urban Transport Planning in Pakistan
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This paper constructs a dynamic conflict model that considers Decision Makers’ (DMs) evolutional attitude using the option prioritization. The proposed evolutional attitude approach is based on the framework of the Graph Model for Conflict Resolution (GMCR). Compared with the existing state-based preference, the option prioritization is a more convenient and efficient approach to analyze larger models with consideration of the evolutional attitude, which exists broadly in the evolutional conflicts in real-life. This study reveals how the evolutional attitude of a DM succeeds in the overall evolution of conflict. The analysis unfolds that DMs change their attitude(s) consequent upon the changes in DMs and options available to them as conflict evolves from one level to the next. The changes in attitude of DMs during dynamic conflict situation have substantial effects on the equilibrium outcomes of a conflict. The proposed evaluation attitude-based approach is employed to analyze the conflict between the Punjab Government (G) and Heritage Campaigner and the Public (P) in Pakistan that appeared due to the inappropriate design, planning, and construction of an urban transport system project in Lahore, Pakistan. The present study demonstrates the modeling procedure of a two-level evolutional attitude-based conflict analysis. The results of the stability analysis reveal that improper (negative) attitude may result in undesirable and unexpected consequences, such as project temporalities and delays. This research provides a foundation for future research in urban project planning that employs strategic ways to avoid disputes caused by DMs’ attitudes.
KeywordsUrban planning infrastructure management heritage protection decision making evolutional attitudes conflict management evolutional GMCR
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The authors appreciate financial support from the National Natural Science Foundation of China (71471087, 71071076, and 61673209). We would like to thank Prof. Ginger Y. Ke, Faculty of Business Administration, Memorial University of Newfoundland St. John’s, NL, Canada, who provided great help for improving the English language of this research. Moreover, we extend our cordial thanks to the Editor and the anonymous referees for valuable suggestions and constructive comments which have helped significantly to enhance the quality of this paper.
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