آگاهی، تعیین کننده ها و ارزش مدیریت ریسک اعتبار: شواهد تجربی از صنعت بانکداری و بیمه / Awareness, Determinants and Value of Reputation Risk Management: Empirical Evidence from the Banking and Insurance Industry

آگاهی، تعیین کننده ها و ارزش مدیریت ریسک اعتبار: شواهد تجربی از صنعت بانکداری و بیمه Awareness, Determinants and Value of Reputation Risk Management: Empirical Evidence from the Banking and Insurance Industry

  • نوع فایل : کتاب
  • زبان : انگلیسی
  • ناشر : Elsevier
  • چاپ و سال / کشور: 2018

توضیحات

رشته های مرتبط مدیریت، اقتصاد
گرایش های مرتبط بانکداری، بیمه، مدیریت مالی، اقتصاد مالی
مجله بانکداری و امور مالی – Journal of Banking and Finance
دانشگاه Friedrich-Alexander University Erlangen-Nürnberg (FAU) – Germany
شناسه دیجیتال – doi https://doi.org/10.1016/j.jbankfin.2018.04.004
منتشر شده در نشریه الزویر
کلمات کلیدی انگلیسی Reputation risk management; Reputation risk; Corporate reputation; Text mining

Description

1. Introduction The management of reputation risk is challenging, as it is generally considered to be a risk of risks (see, e.g., Scott and Walsham, 2005; Regan, 2008; Gatzert and Schmit, 2016), thus having various sources.1 At the same time, several drivers and developments make the management of reputation risk even more important, especially the prominence of social media, where news circulates faster and faster, allowing stakeholders to spread information in an unfiltered manner and to dynamically interact with each other (see Aula, 2010), thus giving rise to reputation risks (see Scott and Walsham, 2005).2 The necessity of building capabilities for managing reputation risks is especially pronounced in the banking and insurance industry, whose business model is based on trust (see, e.g., Fiordelisi et al., 2014; Csiszar and Heidrich, 2006). This is also reflected in the Allianz Risk Barometer, where the loss of reputation or brand value is among the top ten business risks, and even among the top five risks in the subsample of financial services firms. 3 In a study by Deloitte (2014), reputation risks even take the first place among strategic risks. Against this background, the aim of this paper is to conduct the first empirical study regarding the awareness, determinants and value of reputation risk management based on a sample of European and US banks and insurers, which to the best of our knowledge has not previously been done. Much research exists on corporate reputation, especially concerning its definition and measurement (for a review, see, e.g., Barnett et al., 2006; Clardy, 2012; Lange et al., 2011; Walker, 2010) as well as the impact of reputation on financial performance (see de la Fuente Sabate and de Quevedo Puente, 2003; Gatzert, 2015, for reviews). In comparison, the scientific literature on reputation risk is relatively scarce. Empirical studies concerning reputation risk mostly focus on market reactions following operational loss events and find that they (by far) exceed the original loss in most cases, thus indicating severe financial reputational losses (see, e.g., Biell and Muller, 2013; Cummins et al., 2006; Fiordelisi et al., 2014; Gillet et al., 2010; Sturm, 2013). Fiordelisi et al. (2013) further investigate which factors determine reputation risk for banks. Another strand of the literature deals with approaches to managing reputation risk. Several papers focus on reputation repair after a crisis event, including communication strategies (see, e.g., Chakravarthy et al., 2014; Coombs, 2007; Hosseinali-Mirza et al., 2015; Rhee and Valdez, 2009), but there is less research dealing with proactive reputation risk management approaches (see, e.g., Eccles et al., 2007; Scandizzo, 2011; Scott and Walsham, 2002). Gatzert and Schmit (2016) and Regan (2008) address the topic of embedding reputation risk in a holistic enterprise risk management (ERM) framework, while Gatzert et al. (2016) investigate stand-alone insurance solutions for reputation risk as one risk management measure. In addition, Mukherjee et al. (2014) analyze disclosures of 20 European banks on reputation risk and calculate the frequencies of related words.
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