USING THE BINARY MATRICES FOR MODELING THE COMPLEX RELATIONSHIPS AMONG ENABLERS OF COMBATING THE DAMAGES BY FLOODS

Abstract

The aim of study is modeling the complex relationships among enablers of combating the damages by floods. The study’s overall design entails of a literature-review, data-collection, and analysis. Population under study is all stakeholders of phenomenon of floods in Pakistan. Sampling design is non-probability based focus group (i.e. panel of experts). Data gathering is done from experts on a matrix type questionnaire. The data is aggregated through mode using some functions of MS excel.  Results of the literature review reveal that there are total twenty enablers of combating the damages by floods.  Results of ISM modeling show that the enablers improved drainage system, afforestation, strict construction regulations, adherence to flood early warning system, elevate furnaces, water heaters, and electric panels, install check valve in sewer traps, seal walls in basements, keep an adequate supply of food, candles and drinking water, listen to designated radio/TV emergency alert systems, secure outdoor hazardous equipment, move valuable items to upper floors, seek high ground, beware of flash flood areas, be ready to evacuate, use a stick to test depth while leaving homes, do not drive over a flooded road, stay away from flood water, avoid downed/fallen power lines, and do not drink tap water until advised by health officials occupy Level I whereas only one factor i.e. beware of weekend and collapsed roads fall at Level II of ISM structural model. Results of Scale-centric MICMAC analysis show that the independent, dependent and autonomous quadrant are empty. All the enablers are classified in linkage quadrant. Results of Data-centric MICMAC analysis show that autonomous quadrant is empty. Enabler ‘install a check valve in sewer traps’ is classified in independent quadrant. Enabler ‘beware of weekend and collapsed roads’, is classified in dependent quadrant. All other enablers are classified in linkage quadrant. The findings of the study are highly useful for all the stakeholders. It is an original valuable study because it is based on real-time experimental first-hand data collected by authors who have hands on jobs of data collection for decades. It also uses unique and different methodologies to collect data, modeling, and analysis.