Dynamic inoperability input-output modeling for economic losses estimation in industries during flooding. (December 2020)

• Record Type: Journal Article
• Authors: Yaseen, Qazi Muhammad; Akhtar, Rehman; Khalil, Muhammad Kaleem Ullah; Usman Jan, Qazi Muhammad
• Is Part Of: Socio-economic planning sciences. Number 72(2020)
• Publication Date: 2020-12
• Subjects: Natural disasters -- Workers absenteeism -- Disruption estimation -- Dynamic modeling -- Triangular distribution; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2020.100876
• Languages: English
• ISSNs: 0038-0121

Abstract

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. Highlights: Natural disasters, like floods, cause inoperability in industries. Dynamic Inoperability Input-Output Model can be used to estimate disruptions in disasters like floods. Industries can be ranked on the basis of inoperability and economic losses to point out critical industries. Allocating budget to critical sectors, after flooding, reduces economic losses.