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Evolutional Attitude Based on Option Prioritization for Conflict Analysis of Urban Transport Planning in Pakistan

Journal of Systems Science and Systems Engineering. 2019. Vol. 28. P. 356–381.
Ali S., Haiyan X., Xu P., Ahmed W.

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.

Research target: Economics and Management Social and Economic Geography (including Urban and Transportation Studies) Political Science, International Relations, and Public Administration
Language: English
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Keywords: conflict managementurban planningdecision makingheritage protectioninfrastructure management,evolutional attitudesevolutional GMCR
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