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.
Similar content being viewed by others
References
Agrawal, N., & Maheswaran, D. (2005). The effects of self-construal and commitment on persuasion. Journal of Consumer Research, 31(4), 841–849.
Aiello, J. R., & Kolb, K. J. (1995). Electronic performance monitoring and social context: impact on productivity and stress. Journal of Applied Psychology, 80(3), 339.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Ajzen, I. (2001). Nature and operation of attitudes. Annual Review of Psychology, 52(1), 27–58.
Ajzen, I. (2002). Constructing A TpB questionnaire: Conceptual and methodological considerations.
Ajzen, I., & Fishbein, M. (1972). Attitudes and normative beliefs as factors influencing behavioral intentions. Journal of Personality and Social Psychology, 21(1), 1.
Alder, S. (2001). Employee reactions to electronic performance monitoring. Journal of High Technology Management Research, 12, 323–342.
Alder, S., & Ambrose, M. (2005). Toward understanding fairness judgements associated with computer performance monitoring: an integration of the feedback, justice, and monitoring research. Human Resource Management Review, 15, 43–67.
Alge, B. J. (2001). Effects of computer surveillance on perceptions of privacy and procedural justice. Journal of Applied Psychology, 86(4), 797–804.
Alhussain, T., & Drew, S. (2012). Employees’ perceptions of biometric technology adoption in e-government: An exploratory study in the kingdom of Saudi Arabia. In E-adoption and technologies for empowering developing countries: Global advances (p. 129). Hershey: Information Science Reference.
Ambrose, M., Alder, S., & Noel, T. (1998). Electronic performance monitoring: A consideration of rights. In M. Schminke (Ed.), Managerial ethics: Moral management of people and processes. Mahwah: Lawrence Erlbaum Associates.
Anandarajan, M., D’ovidio, R., & Jenkins, A. (2013). Safeguarding consumers against identity-related fraud: examining data breach notification legislation through the lens of routine activities theory. International Data Privacy Law, 3(1), 51.
Ball, K., Daniel, E. M., & Stride, C. (2012). Dimensions of employee privacy: An empirical study. Information Technology & People, 25(4), 376–394.
Barbanell, J. (2015). Needing a new approach to address employee data breaches in the american workplace. Journal of Law and Cyber Warfare, 4(3).
Beeler, J. D., & Hunton, J. E. (1997). The influence of compensation method and disclosure level on information search strategy and escalation of commitment. Journal of Behavioral Decision Making, 10(2), 77–91.
Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: A review of information privacy research in information systems. MIS Quarterly, 35(4), 1017–1042.
Benitez, P. (2015). Record data breaches in 2014 teach important lessons. Retrieved From Http://Blog.Gemalto.Com/Blog/2015/01/27/Record-Data-Breaches-In-2014-Teach-Important-Lessons/
Bollen, K., & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation model perspective. Psychological Bulletin, 110, 305–314.
Bond, R., & Smith, P. B. (1996). Culture and conformity: A meta-analysis of studies using Asch’s (1952b, 1956) line judgment task. Psychological Bulletin, 119(1), 111.
Bonett, D. G., & Wright, T. A. (2015). Cronbach’s alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3–15.
Brandimarte, L., Acquisti, A., & Loewenstein, G. (2010). Misplaced Confidences: Privacy and the Control Paradox. Paper Presented at the Ninth Workshop on the Economics of Information Security (Weis 2010), Harvard University.
Brockner, J., De Cremer, D., Van Den Bos, K., & Chen, Y.-R. (2005). The influence of interdependent self-construal on procedural fairness effects. Organizational Behavior and Human Decision Processes, 96(2), 155–167.
Bulgurcu, B., Cavusoglu, H., & Benbasat, I. (2010a). Information security policy compliance: an empirical study of rationality-based beliefs and information security awareness. MIS Quarterly, 34(3), 523–548.
Bulgurcu, B., Cavusoglu, H., & Benbasat, I. (2010b). Understanding Emergence and Outcomes of Information Privacy Concerns: A Case of Facebook. Paper Presented at the ICIS.
Carpenter, D. (2011). The impact of user privacy concerns and ethnic cultural values on attitudes toward the use of biometric technology. Proquest.
Chau, P. Y. K. (1996). An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems, 13(2), 185–204.
Chen, R., & Sharma, S. K. (2013). Self-disclosure at social networking sites: An exploration through relational capitals. Information Systems Frontiers, 15(2), 269–278.
Chen, J. V., Yen, D. C., Pornpriphet, W., & Widjaja, A. E. (2015). E-commerce web site loyalty: A cross cultural comparison. Information Systems Frontiers, 17(6), 1283–1299.
Chin, W. W. (1998). Issues and opinion on structural equation modeling. Management Information Systems Quarterly, 22(1), 7–16.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217.
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.
Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral), Massachusetts Institute of Technology, Boston.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80.
Dinnel, D. L., Kleinknecht, R. A., & Tanaka-Matsumi, J. (2002). A cross-cultural comparison of social phobia symptoms. Journal of Psychopathology and Behavioral Assessment, 24(2), 75–84.
Dwyer, C. (2007). Digital Relationships in the “Myspace” Generation: Results from a Qualitative Study. Paper Presented at the Proceedings of the 40th Annual Hawaii International Conference on System Sciences.
Dwyer, C., Hiltz, S., & Passerini, K. (2007). Trust and Privacy Concern Within Social Networking Sites: A Comparison of Facebook and Myspace. Paper Presented at the Proceedings of the Thirteenth Americas Conference on Information Systems, Keystone, Colorado.
Eddy, E. R., Stone, D. L., & Stone-Romero, E. F. (1999). The effects of information management policies on reactions to human resource information systems: An integration of privacy and procedural justice perspectives. Personnel Psychology, 52, 335–358.
Elgarah, W., & Falaleeva, N. (2005). Adoption of Biometric Technology: Information Privacy in TAM. AMCIS 2005 Proceedings, 222.
Fishbien, M., & Azjen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addison-Wesley.
Friedman, B. A., & Reed, L. J. (2007). Workplace privacy: Employee relations and legal implications of monitoring employee e-mail use. Employee Responsibilities and Rights Journal, 19(2), 75–83.
Fusilier, M. R., & Hoyer, W. D. (1980). Variables affecting perceptions of invasion of privacy in a personnel selection situation. Journal of Applied Psychology, 65(5), 623.
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16, 91–109.
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 7.
Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and tam in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.
Grant, R. A., Higgins, C. A., & Irving, R. H. (1988). Computerized performance monitors: Are they costing you customers? MIT Sloan Management Review, 29(3), 39.
Greenaway, K. E., & Chan, Y. E. (2005). Theoretical explanations for firms’ information privacy behaviors. Journal of the Association for Information Systems, 6(6), 171–198.
Gudykunst, W. B., Matsumoto, Y., Ting‐Toomey, S., Nishida, T., Kim, K., & Heyman, S. (1996). The influence of cultural individualism-collectivism, self construals, and individual values on communication styles across cultures. Human Communication Research, 22(4), 510–543.
Haenlein, M., & Kaplan, A. (2004). A beginner’s guide to partial least squares analysis. Understanding Statistics, 3(4), 283–297.
Hann, I., Hui, K. L., Lee, T., & Png, I. (2002). Online information privacy: Measuring the cost-benefit trade-off. Paper presented at the twenty-third international conference on information systems, Barcelona.
Hann, I., Hui, K., Lee, S.-Y. T., & Png, I. (2007). Overcoming online information privacy concerns: An information-processing approach. Journal of Management Information Systems, 24(2), 13–42.
Hoffman, D., Novak, T., & Peralta, M. (1999). Information privacy in the marketspace: Implications for the commercial uses of anonymity on the web. The Information Society, 15(2), 129–139.
Hofstede, G. (1984). Culture’s consequences: International differences in work-related values (Vol. 5). Newbury Park: Sage.
Hofstede, G. (2001). Culture’ consequences: Comparing values, behaviors, institutions, and organizations across nations (2nd ed.). Thousand Oaks: Sage Publications.
Hovorka-Mead, A. D., Ross, W. H., Jr., Whipple, T., & Brenchin, M. B. (2002). Watching the detectives: Seasonal student employee reactions to electronic monitoring with and without advance notification. Personnel Psychology, 55(2), 329.
Hui, K., Teo, H., & Lee, S.-Y. T. (2007). The value of privacy assurance: An exploratory field experiment. MIS Quarterly, 31(1), 19–33.
Jain, A. K., & Kumar, A. (2010). Biometrics of next generation: An overview. Second Generation Biometrics, 12(1), 2–3.
Jain, A. K., Ross, A., & Pankanti, S. (2006). Biometrics: A tool for information security. IEEE Transactions on Information Forensics and Security, 1(2), 125–143.
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an internet store. Information Technology and Management, 1, 45–71.
Jennings, M. M. (2006). Why do smart businesspeople do ethically dumb things? Corporate Finance Review, 11(3), 38.
Jones, L., Anton, A., & Earp, J. (2007). Toward Understanding User Perceptions of Authentication Technologies. Paper Presented at the Proceedings of the 2007 ACM Workshop on Privacy in Electronic Society, Alexandria, VA.
Josang, A., Ismail, R., & Boyd, C. (2007). A survey of trust and reputation systems for online service provision. Decision Support Systems, 43, 618–644.
Kaplowitz, M., Hadlock, T., & Levine, R. (2004). A comparison of web and mail survey response rates. Public Opinion Quarterly, 68(1), 94–101.
Kofman, J., & Potter, N. (2011). Rupert murdoch’s news of the world accused of more phone hacks. Retrieved from Http://Abcnews.Go.Com/Technology/News-World-Phone-Hacking-Scotland-Yard-Investigates-Links/Story?Id=14007604.
Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3), 461–491.
Lee, M., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91.
Lee, J., Lee, J.-N., & Tan, B. C. (2015). Antecedents of cognitive trust and affective distrust and their mediating roles in building customer loyalty. Information Systems Frontiers, 17(1), 159–175.
Liu, C., & Arnett, K. P. (2000). Exploring the factors associated with web site success in the context of electronic commerce. Information & Management, 38(1), 23–33.
Liu, C., Marchewka, J., & Ku, C. (2004). American and Taiwanese perceptions concerning privacy, trust, and behavioral intentions in electronic commerce. Journal of Global Information Management, 12(1), 18–40.
Liu, C., Marchewka, J., Lu, J., & Yu, C. S. (2005). Beyond concern—a privacy-trust-behavioral intention model of electronic commerce. Information & Management, 42, 289–304.
Malhotra, N., Kim, S., & Agarwal, J. (2004). Internet users’ information privacy concerns IUIPC: The contruct, the scale, and a causal model. Information Systems Research, 15(4), 336–355.
Mandel, N. (2003). Shifting selves and decision making: The effects of self-construal priming on consumer risk-taking. Journal of Consumer Research, 30(1), 30–40.
Marakas, G., Johnson, R., & Clay, P. F. (2007). The evolving nature of the computer self-efficacy construct: An empirical investigation of measurement construction, validity, reliability and stability over time. Journal of the Association for Information Systems, 8(1), 15.
Marcoulides, G. A., & Saunders, C. (2006). PLS: A silver bullet? MIS Quarterly, 30(2), 3–9.
Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224.
Mcknight, D., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359.
Milberg, S. J., Smith, H. J., & Burke, S. J. (2000). Information privacy: Corporate management and national regulation. Organization Science, 11(1), 35–57.
Nov, O., & Wattal, S. (2009). Social computing privacy concerns: antecedents and effects. Proceedings of the SIGCHI conference on human factors in computing systems, ACM, 333–336.
Oyserman, D., Coon, H. M., & Kemmelmeier, M. (2002a). Rethinking individualism and collectivism: Evaluation of theoretical assumptions and meta-analyses. Psychological Bulletin, 128(1), 3.
Oyserman, D., Coon, H. M., & Kemmelmeier, M. (2002b). Rethinking inividualism and collectivism: Evaluation of theoretical assumptions and meta-analyses. Psychological Bulletin, 128(1), 3–72.
Oz, E., Glass, R., & Behling, R. (1999). Electronic workplace monitoring: What employees think. Omega, 27(2), 167–177.
Pato, J. N., Millett, L. I., & Whither Biometrics Committee. (2010). Biometric recognition: Challenges and opportunities. Washington DC: National Academies Press.
Polyorat, K., Alden, D. L., & Alden, D. L. (2005). Self-construal and need-for-cognition effects on brand attitudes and purchase intentions in response to comparative advertising in Thailand and the United States. Journal of Advertising, 34(1), 37–48.
Prabhakar, S., Pankanti, S., & Jain, A. K. (2003). Biometric recognition: Security and privacy concerns. IEEE Security and Privacy, 1(2), 33–42.
Reay, I., Beatty, P., Dick, S., & Miller, J. (2013). Privacy policies and national culture on the internet. Information Systems Frontiers, 15(2), 279–292.
Ringle, C. M., Wende, S., & Will, S. (2005). Smartpls 2.0 (M3) Beta. Hamburg: Http://Www.Smartpls.De/.
Roca, J., García, J., & De La Vega, J. (2009). The importance of perceived trust, security and privacy in online trading systems. Information Management & Computer Security, 17(2), 96–113.
Salvagnini, P., Bazzani, L., Cristani, M., & Murino, V. (2013). Person re-identification with a ptz camera: an introductory study. 20th IEEE International Conference on Image Processing (ICIP), 2013.
Schumann, A., & Monari, E. (2014). A soft-biometrics dataset for person tracking and re-identification. 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2014.
Sharma, P., Chrisman, J. J., & Chua, J. H. (2003). Succession planning as planned behavior: Some empirical results. Family Business Review, 16(1), 1–15.
Sheehan, K. B. (1999). An investigation of gender differences in on-line privacy concerns and resultant behaviors. Journal of Interactive Marketing, 13(4), 24–38.
Singelis, T. M. (1994). The measurement of independent and interdependent self-construals. Personality and Social Psychology Bulletin, 20(5), 580–591.
Singelis, T. M., Triandis, H. C., Bhawuk, D. P. S., & Gelfand, M. J. (1995). Horizontal and vertical dimensions of individualism and collectivism: A theoretical and measurement refinement. Cross-Cultural Research, 29(3), 240–275.
Singelis, T. M., Bond, M. H., Sharkey, W. F., & Lai, C. S. Y. (1999). Unpackaging culture’s influence on self-esteem and embarrassability the role of self-construals. Journal of Cross-Cultural Psychology, 30(3), 315–341.
Smith, H., Milberg, S., & Burke, S. (1996). Information privacy: Measuring individual’s concerns about organizational practices. MIS Quarterly, 20(2), 167–196.
Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: An interdisciplinary review. MIS Quarterly, 35(4), 989–1016.
Soper, D. (2013). Post Hoc Statistical Power Analysis. Retrieved From Http://Www.Danielsoper.Com/Statcalc3/.
Spitzmüller, C., & Stanton, J. M. (2006). Examining employee compliance with organizational surveillance and monitoring. Journal of Occupational and Organizational Psychology, 79(2), 245–272.
Stanton, J. M., & Weiss, E. (2000). Electronic monitoring in their own words: An exploratory study of employees’ experiences with new types of surveillance. Computers in Human Behavior, 16(4), 423–440.
Stewart, K. A., & Segars, A. H. (2002). An empirical examination of the concern for information privacy instrument. Information Systems Research, 13(1), 36–49.
Stone, E. F., & Stone, D. L. (1990). Privacy in organizations: Theoretical issues, research findings, and protection mechanisms. Research in Personnel and Human Resources Management, 8, 349–411.
Stone, D. L., & Stone-Romero, E. F. (1998). A multiple stakeholder model of privacy in organizations. In M. Schminke (Ed.), Managerial ethics: Moral management of people and processes (pp. 35–59). Mahwah: Lawrence Erlbaum.
Stone-Romero, E. F., Gueutal, H. G., Gardner, D. G., & Mcclure, S. (1983). A field experiment comparing information-privacy values, beliefs, and attitudes across several types of organizations. Journal of Applied Psychology, 68(3), 459–468.
Sun, Y., & Upadhyaya, S. (2015). Secure and privacy preserving data processing support for active authentication. Information Systems Frontiers, 17(5), 1007–1015.
Swaminathan, V., Page, K. L., & Gürhan-Canli, Z. (2007). “My” brand or “our” brand: The effects of brand relationship dimensions and self-construal on brand evaluations. Journal of Consumer Research, 34(2), 248–259.
Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137–155.
Tolchinsky, P. D., Mccuddy, M. K., Adams, J., Ganster, D. C., Woodman, R. W., & Fromkin, H. L. (1981). Employee perceptions of invasion of privacy: A field simulation experiment. Journal of Applied Psychology, 66(3), 308.
Triandis, H. C. (1995). Individualism and collectivism. Boulder: Westview Press.
Triandis, H. C., & Gelfand, M. J. (1998). Converging measurement of horizontal and vertical individualism and collectivism. Journal of Personality and Social Psychology, 74(1), 118–128.
Urbaczewski, A., & Jessup, L. M. (2002). Does electronic monitoring of employee internet usage work? Communications of the ACM, 45(1), 80–83.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Wakunuma, K. J., & Stahl, B. C. (2014). tomorrow’s ethics and today’s response: an investigation into the ways information systems professionals perceive and address emerging ethical issues. Information Systems Frontiers, 16(3), 383–397.
Walczuch, R., & Lundgren, H. (2004). Psychological antecedents of institution-based consumer trust in e-retailing. Information & Management, 42(1), 159–177.
Westin, A. F. (2003). Social and political dimensions of privacy. Journal of Social Issues, 59(2), 431–453.
Woodward, J. D. (1997). Biometrics: Privacy’s foe or privacy’s friend? Proceedings of the IEEE, 85(9), 1480–1492.
Xu, H. (2007). The effects of self-construal and perceived control on privacy concerns. ICIS 2007 Proceedings, 125.
Xu, H., Dinev, T., Smith, J., & Hart, P. (2008). Examining the Formulation of Individual’s Privacy Concerns: Toward an Integrative View. Paper Presented at the Twenty Ninth International Conference on Information Systems, Paris.
Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information privacy concerns: Linking individual perceptions with institutional privacy assurances. Journal of the Association for Information Systems, 12(12), 798.
Zhou, T. (2015). Understanding user adoption of location-based services from a dual perspective of enablers and inhibitors. Information Systems Frontiers, 17(2), 413–422.
Zorkadis, V., & Donos, P. (2004). On biometrics-based authentication and identification from a privacy-protection perspective: Deriving privacy-enhancing requirements. Information Management & Computer Security, 12(1), 125–137.
Zweig, D., & Scott, K. (2007). When unfairness matters most: Supervisory violations of electronic monitoring practices. Human Resource Management Journal, 17(3), 227–247.
Zweig, D., & Webster, J. (2002). Where is the line between benign and invasive? An examination of psychological barriers to the acceptance of awareness monitoring systems. Journal of Organizational Behavior, 23(5), 605–633.
Acknowledgments
Portions of this research were supported by the National Institute of Standards and Technology Building and Fire Research Laboratory via Fire Research Grant #05-388, Award # 70NANB6H6124 for a project entitled “The Integration of Biometric Technologies with Fire Fighting Information Systems”. Support included funding for the pilot system implemented in the study and faculty support during the research effort.
Author information
Authors and Affiliations
Corresponding author
Appendix 1
Appendix 1
1.1 User opinions about biometric log-on systems: A research study
The Fire Department is continually exploring new methods of improving fire fighter safety. As part of those efforts the Department, in conjunction with UTSA researchers, will soon test a new system designed to ensure accurate personnel information is available to on-scene incident commanders. This new system will use biometric authentication to verify the identity of a fire fighter reporting for duty. A biometric authentication system is one that uses some feature of an individual, in this case finger pattern recognition, to discern one person from another.
Because biometric systems are not widely utilized by the general population, we would like your input about potential privacy concerns that are often mentioned in association with biometric systems. Please circle the number to the right of each statement that best describes the extent to which you, as an individual, agree or disagree with each statement. If you neither agree nor disagree with a statement please circle “4” as a neutral rating. There is no right or wrong answer. Your answers are confidential. Thank you for participating.
Rights and permissions
About this article
Cite this article
Carpenter, D., McLeod, A., Hicks, C. et al. Privacy and biometrics: An empirical examination of employee concerns. Inf Syst Front 20, 91–110 (2018). https://doi.org/10.1007/s10796-016-9667-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10796-016-9667-5