Mapping Vulnerability through ABC Analysis & Building Hierarchy Matrix

Posted: 18 Dec 2012

Date Written: December 17, 2012

Abstract

Assessing vulnerability is often very difficult for the government and donor organizations. The type, time and points of action to be taken are often planned in arbitrary manner during the emergency or during economic downturn and extended assistance uniformly to all affected population. The each affected person may require different type & extent of help. Scientific analysis may help to classify vulnerability to know extent of risk exposure into high (A), medium (B), and low (C). Vulnerability assessment is critical to decide the time, type & extent of help; this paper gives a new approach of mapping vulnerability with indicators of risk and classifying risk exposure for ABC analysis. Based on building hierarchy matrix, we propose new conceptual model as a solution. Several researchers have examined components of risk and level of risk centers, and attempted to define risk. The Society of Risk Analysis gave up defining risk after the expert committee failed to have universal definition of risk. Rather than defining ‘risk’, this paper intends to identify essential elements of risk that remains prevalent in vulnerable people and communities. The final objective is to build a conceptual model to prevent and overcome hazards to vulnerable people using ABC analysis of vulnerability. We first classify and quantify the risk factors in order to measure vulnerability level and then establish center of risk.

Relevant literature: In order to be effective and dynamically efficient, the intervention must specifically address the type of risk and its environment, Holzmann & Jorgensen (1999) emphasize expanded role of risk management by promoting risk taking capacity in poor. Vlaev et al (2009) in their research found sub-optimal risk management and mismatches between consumers understanding of risk, attitudes to risk, and financial decisions. Holzmann, Sherburne-Benz & Tesliuc (2003) attempted to understand the type of shock that damages most and estimated vulnerability with cross-sectional data. Hoogeveen et al (2004) uses analytical approaches to risk and vulnerability analysis, social risk management of vulnerable groups and finds that policy should not neglect vulnerable population living in invulnerable region. Social Risk Management framework highlights the importance of ex-ante strategies, constraints and processes.

Motivation of this study remains in the fact that current literature does not provide any model based either on systematic classified grading of level of vulnerability or systematic establishing hierarchy of responsibility center. We argue that vulnerability, the exposure to risk exists at different unit level e.g. individual, family, community, local government, state and national government. Chambers (1989) put his empirical findings on a conceptual level and argued that vulnerability has an external and internal side. People are exposed to specific natural, physical, economic and social risk. People possess different capacities to deal with their exposure by means of various strategies of action, therefore if focus limited to the stresses associated with a particular vulnerability analysis will be insufficient for understanding the impact on and responses of the affected system or its components (Kaperson et al 2003). The government may more effectively help people in mitigating the hazards, if actions are based on scientific method to ascertain vulnerable population, unit of vulnerability and root cause of vulnerability internal capacities of unit of vulnerability to cope with hazards, and, integrated action plan among different stakeholders.

The questions to be examined: 1. To identify the elements of various types of risks 2. To objectively classify vulnerability as low, medium and high 3. To establish benchmark standards & different cutoffs to classify vulnerability 4. To identify the center of responsibility 5. To understand internal linkages among various responsibility centers Unique contribution to the literature:

The research paper objectively classifies vulnerability into three classes A, B & C; the external support intervention will be accordingly high, medium and low respectively. For each root of vulnerability, we earmark logical & rationale indicator. The new conceptual model will define level of vulnerability and center of responsibility, so as to take suitable measures to mitigate risks during emergency, pre & post emergency.

Research methodology to be employed: The research is based on secondary data. As stated in the premise described at the outset, our research is in four parts. The first part identifies essential elements of the major risk and classifying risk factors into human, economic, social, technical and political. The second part deals with quantifying above matrix (type of risk factor for a given unit) to classify vulnerability level into A, B & C. To determine cut-off for vulnerability, for each item, we have considered logically available authentic data as the base, e.g. for poverty (per capita income), pregnant woman (mortality rate), house (type of construction, seismic zone) etc. We are establishing center of risk on the basis of vulnerability of an individual, family, community, local, province & national government. After studying internal capabilities of each unit, we develop action plan through integrated model.

Conclusion & beneficiary: External agencies can play very important role using this model on continuous basis to help mitigating risk of vulnerable population. Resources of external agencies will be optimally used for mitigating the risk & impact of hazards, because most deserving population will get the most & vice versa internal unique capabilities of each unit will be used in risk mitigating process, and different stakeholders’ activities are integrated to create synergy.

Suggested Citation

Sapovadia, Vrajlal K., Mapping Vulnerability through ABC Analysis & Building Hierarchy Matrix (December 17, 2012). Available at SSRN: https://ssrn.com/abstract=2190243

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