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Dynamic inoperability input-output modeling for economic losses estimation in industries during flooding

Qazi Muhammad Yaseen, Rehman Akhtar, Muhammad Kaleem Ullah Khalil and Qazi Muhammad Usman Jan

Socio-Economic Planning Sciences, 2020, vol. 72, issue C

Abstract: Among all natural disasters, flood stands as a recurrently happening disaster. It holds the aptitude to disrupt the organizations and to cause absenteeism of the workforce in industries. As the workforce is directly involve in the functioning of industries, work force absenteeism can cause reduced production and inoperability which outcomes in financial losses of industrial sectors. This research objects to estimate inoperability of industries due to distraction of workers by incorporating Dynamic Inoperability Input-Output Model (DIIM). Economic losses are determined from inoperability. Industrial area which is selected for the research includes local industries in Peshawar, Khyber-Pakhtunkhwa, Pakistan. Various industries are chosen and are ordered according to inoperability and economic losses. Industries having highest financial damages are: (i) Agriculture; (ii) Sugar mills; and (iii) Marble industry. These three industries hold liable for 40.6% of the overall financial losses of fifteen industries. Industries suffering from highest inoperability include (i) Sugar mills; (ii) Agriculture and (iii) Marble industry. A risk analysis frame work has also been developed to help industrial sectors to recover after a disaster. Besides, data of three different floods has also been taken for the above mentioned critical sectors to plot probability distributions for predicting economic losses of most frequent floods. Furthermore, this research methodology has been applied to flooding but it can be applied to any other disaster, everywhere.

Keywords: Natural disasters; Workers absenteeism; Disruption estimation; Dynamic modeling; Triangular distribution (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:72:y:2020:i:c:s0038012119302265

DOI: 10.1016/j.seps.2020.100876

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