Privacy and biometrics: An empirical examination of employee concerns

Darrell Carpenter (), Alexander McLeod, Chelsea Hicks and Michele Maasberg
Additional contact information
Darrell Carpenter: Longwood University
Alexander McLeod: Texas State University
Chelsea Hicks: The University of Texas at San Antonio
Michele Maasberg: The University of Texas at San Antonio

Information Systems Frontiers, 2018, vol. 20, issue 1, No 6, 110 pages

Abstract: Abstract Advances in authentication technology have led to a proliferation of biometric-based systems in the workplace. Although biometric technologies offer organizations a cost-effective method of increasing security, employees are often hesitant to permit use. The collection and storage of employee biometric data raises concerns about proper use of these intensely personal identifiers. This work draws from organizational privacy practices, electronic monitoring, procedural fairness, self-construal, and technology adoption theories. We investigate the effects of independent and interdependent self-construal on three newly developed dimensions of employee privacy concern related to organizational use of biometric technology. These dimensions include perceived accountability, perceived vulnerability, and perceived distrust toward the organization. We test the predictive power of our model using data from an organization deploying a new biometric system designed to track employee work assignments under the auspices of improving personnel safety. Results indicate that self-construal plays a significant role in the formulation of privacy concerns and both perceived accountability concerns and perceived vulnerability concerns are significant predictors of attitude toward using biometric technology in the workplace.

Keywords: Privacy concerns; Biometric technology; Self-construal; Perceived privacy control; Electronic employee monitoring; Partial Least Squares (PLS) (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10796-016-9667-5

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