PhD Thesis of Management Sample
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(2000) separates uncertainty and risk according to both factors<br />
Abstract<br />
The existence <strong>of</strong> uncertainty, complexity and ambiguity in the<br />
business environment promotes the need to establish a dependable<br />
risk governance. The use <strong>of</strong> Enterprise Risk <strong>Management</strong> (ERM) has<br />
also been considered as an effective method to attain good risk<br />
governance in order to deal with both upside and downside <strong>of</strong><br />
uncertainty and risk. ERM treats all <strong>of</strong> the risks holistically in order to<br />
achieve organization aims in volatile, normal and crisis situations. This<br />
<strong>PhD</strong> thesis will discuss issues related to the ERM implementation and<br />
how it has been adapted and implemented in the insurance market <strong>of</strong><br />
both India and UK. Mixed methods for research have also been<br />
employed coming from a qualitative stand point in order to explore<br />
research issues, consisting two surveys in both countries, with more<br />
than 50 interviews, as well as two case studies in the country’s<br />
insurance markets. The study revealed that an ambiguity is present<br />
when it comes to understanding all definitions <strong>of</strong> ERM, as well as the<br />
risks involved across both <strong>of</strong> the countries.<br />
Background <strong>of</strong> the Study<br />
In the current environment <strong>of</strong> business, corporations faced<br />
ambiguity, volatility, and uncertainty. Understanding uncertainty<br />
and risk has posed a number <strong>of</strong> challenges, and a clear<br />
distinction between uncertainty and risk is not clear. Ramir<br />
as measurability and immeasurability. It also highlights the<br />
impact <strong>of</strong> individual characteristic involved in the situation in<br />
terms <strong>of</strong> probability determination. Bernel (1998) also<br />
connected the importance <strong>of</strong> conditions to uncertainty where<br />
both measurement and rationality are vital to the process <strong>of</strong><br />
decision making.