Electricity Supply Interruptions: Sectoral Interdependencies and the Cost of Energy Not Served for the Scottish Economy

The power sector has a central role in modern economies and other interdependent infrastructures rely heavily upon secure electricity supplies. Due to interdependencies, major electricity supply interruptions result in cascading effects in other sectors of the economy. This paper investigates the economic effects of large power supply disruptions taking such interdependencies into account. We apply a dynamic inoperability input–output model (DIIM) to 101 sectors (including households) of the Scottish economy in 2009 in order to explore direct, indirect, and induced effects of electricity supply interruptions. We then estimate the societal cost of energy not supplied (SCENS) due to interruption, in the presence of interdependency among the sectors. The results show that the most economically affected industries, following an outage, can be different from the most inoperable ones. The results also indicate that SCENS varies with duration of a power cut, ranging from around £4300/MWh for a one-minute outage to around £8100/MWh for a three hour (and higher) interruption. The economic impact of estimates can be used to design policies for contingencies such as roll-out priorities as well as preventive investments in the sector

A fuzzy dynamic inoperability input-output model for strategic risk management in global production networks

Strategic decision making in Global Production Networks (GPNs) is quite challenging, especially due to the unavailability of precise quantitative knowledge, variety of relevant risk factors that need to be considered and the interdependencies that can exist between multiple partners across the globe. In this paper, a risk evaluation method for GPNs based on a novel Fuzzy Dynamic Inoperability Input Output Model (Fuzzy DIIM) is proposed. A fuzzy multi-criteria approach is developed to determine interdependencies between nodes in a GPN using experts’ knowledge. An efficient and accurate method based on fuzzy interval calculus in the Fuzzy DIIM is proposed. The risk evaluation method takes into account various risk scenarios relevant to the GPN and likelihoods of their occurrences. A case of beverage production from food industry is used to showcase the application of the proposed risk evaluation method. It is demonstrated how it can be used for GPN strategic decision making. The impact of risk on inoperability of alternative GPN configurations considering different risk scenarios is analysed

A resilience analysis of the contraction of the accommodation and food service sector on the Scottish food industry

Funding Information: This paper derives from work under Topics B4 (Food supply and security) and B5 (Food and Drink Improvement), which are part of the Scottish Government—Rural and Environment Science and Analytical Services Division (RESAS) as part of their Strategic Research Programme 2022-27. This article is part of the Research Topic: Reorganization and Resilience of Food Supply Chains According to Current International Crisis ScenarioPeer reviewedPublisher PD

Three Essays on Understanding Social and Economic Responses to Crisis and Disaster Events

The dissertation comprises three chapters that analyze the social and economic responses to crises and disasters. In the first chapter, I have investigated whether media affects the US official foreign aid channel or crisis related aid. I have examined natural disaster citations in four mainstream US newspapers to analyze whether they influence the Official Development Assistance (ODA) or the short-term crisis related aid need of a recipient following a natural disaster. I created three new media variables to measure the strength of media effect on US ODA, humanitarian aid, and food aid. The empirical analyses indicate that media citation only affects crisis related food and humanitarian assistance. In the subsequent chapters I focus on the impacts of coastal hazards on affected communities. Every year hurricanes of different intensities make landfall in the US. The devastation and havoc of those hurricanes often have long-lasting effects on people\u27s livelihood, infrastructure, and homes. The deadliest hurricane ever recorded in Puerto Rico, Hurricane Maria, made landfall in 2017. In the second chapter, I investigated how the devastation of Hurricane Maria affected the housing prices in Puerto Rico. I gathered home sales data in Puerto Rico after Hurricane Maria from Zillow, a leading multiple listing service (MLS) platform for real estate transactions in the US. I combined the traditional hedonic price model with Regression Discontinuity Design (RDD) to measure Hurricane Maria\u27s causal (treatment) effect on housing prices in Puerto Rico. In 2017, another hurricane (Hurricane Harvey) wreaked havoc in Texas. Floodwaters inundated homes in Texas and disrupted utility services. Hurricane Harvey resulted in significant economic and social consequences by disrupting public utility services such as power supply, telecommunication , and transportation. The interruption in one sector impacted the operation in other interdependent sectors. In the third chapter, I use household survey data that was collected following the event of Hurricane Harvey to analyze the performance of critical infrastructure systems and the impacts of utility disruptions in Houston, Texas. I incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses in multiple linked sectors. This chapter also assessed the top ten inoperable (stalled) sectors in the affected area

Different approaches to model economic dimension of community resilience

Earthquakes and extreme events in general cause direct and indirect economic effects on every major economic sector of a given community. These effects have grown in the last years due to the increasing interdependency of the infrastructures and make the community more vulnerable to natural and human-induced disruptive events. Therefore, there is need for metrics and models which are able to describe economic resilience, defined as the ability of a community affected by a disaster to resist at the shock and bounce back to the economy in normal operating conditions. Several attempts have been made in the past to achieve a better measurement and representation of the economic resilience and to find suitable metrics to help decision planning. The most popular methodologies are based on Computable General Equilibrium models (CGE) and Inoperability Input-Output models (IIM). In this study, we analyze these methods, showing advantages and limitations. Finally, a new method is proposed to evaluate economic resilience which is based on equilibrium growth models and compared with other approaches

Infastructure Interdependencies Modeling and Analysis - A Review and Synthesis

The events of 9/11 and the occurrence of major natural disasters in recent years has resulted in increased awareness and renewed desire to protect critical infrastructure that are the pillars to maintaining what has become normal life in our economy. The problem has been compounded because the increased connectedness between the various sectors of the economy has resulted in interdependencies that allow for problems and issues with one infrastructure to affect other infrastructures. This area is now being investigated extensively after the Department of Homeland Security (DHS) prioritized this issue. There is now a vast extant of literature in the area of infrastructure interdependencies and the modeling of it. This paper presents a synthesis and survey of the literature in the area of infrastructure interdependency modeling methods and proposes a framework for classification of these studies. The framework classifies infrastructure interdependency modeling and analysis methods into four quadrants in terms of system complexities and risks. The directions of future research are also discussed in this paper