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Corporate Information Security Investment Decisions: A Qualitative Data Analysis Approach

Corporate Information Security Investment Decisions: A Qualitative Data Analysis Approach

Daniel Schatz, Rabih Bashroush
Copyright: © 2018 |Volume: 14 |Issue: 2 |Pages: 20
ISSN: 1548-1115|EISSN: 1548-1123|EISBN13: 9781522542698|DOI: 10.4018/IJEIS.2018040101
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MLA

Schatz, Daniel, and Rabih Bashroush. "Corporate Information Security Investment Decisions: A Qualitative Data Analysis Approach." IJEIS vol.14, no.2 2018: pp.1-20. http://doi.org/10.4018/IJEIS.2018040101

APA

Schatz, D. & Bashroush, R. (2018). Corporate Information Security Investment Decisions: A Qualitative Data Analysis Approach. International Journal of Enterprise Information Systems (IJEIS), 14(2), 1-20. http://doi.org/10.4018/IJEIS.2018040101

Chicago

Schatz, Daniel, and Rabih Bashroush. "Corporate Information Security Investment Decisions: A Qualitative Data Analysis Approach," International Journal of Enterprise Information Systems (IJEIS) 14, no.2: 1-20. http://doi.org/10.4018/IJEIS.2018040101

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Abstract

This article describes how with information security steadily moving up on board room agendas, security programs are found to be under increasing scrutiny by practitioners. This level of attention by senior business leaders is new to many security professionals as their field has been of limited interest to non-executive directors so far. Currently, they have to regularly report on efficiency and value of their security capabilities whilst being measured against business priorities. Based on the Grounded Theory approach, the authors analysed the data gathered in a series of interviews with senior professionals in order to identify key factors in the context of information security investment decisions. The authors present detailed findings in context of a simplified framework that security practitioners can utilise for critical review or improvements of investment decisions in their own environments. Extensive details for each category as extracted through a qualitative data analysis are provided along with a category network analysis that highlights strong relationships within the framework.

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