A Computational Social Science Approach To Examine The Duality Between Productivity And Cybersecurity Policy Compliance Within Organizations

Keywords

Cybersecurity compliance; Decision making; Habituation; Productivity modeling; Workforce modeling

Abstract

Organizational employees often face conflicting responsibilities intheir daily tasks. On one hand, employees must be productive members of theirorganization; on the other, they must perform their tasks while conforming tocybersecurity policies thereby causing a reduction in their performance rates.Such compliance can also lead to increases in stress, which might already be relatively high given the workload placed on the employees.In addition to this dichotomy, organizations vary significantly in the amount ofemphasis placed on their productivity and cybersecurity goals. Employees usethis and other information when making determinations about whether to followcybersecurity policies for a given task. And while some of these determinationsare based in rational cost-vs-benefits analyses, many are born out of habituation.Despite the importance of understanding individual-level decision making in regard to performance-both in productivity and compliance-little research hasexamined how such micro-level actions aggregate to macro-level phenomenawithin organizations. Given this opportunity, we explore how varying workload,productivity and compliance emphases (i.e., culture), and the degree by whichcompliance decreases productivity (i.e., friction) for a given task affects a simulated organization's employees' stress levels. Moreover, we investigate howthese factors (including rationality vs habituation, morality) combine to formemergent noncompliance patterns at the organizational level.

Publication Date

1-1-2018

Publication Title

2018 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction and Behavior Representation in Modeling and Simulation, BRiMS 2018

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

85084095356 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85084095356

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