It Consumerization: Byod-Program Acceptance and its Impact on Employer Attractiveness

Many firms are considering ‘bring-your-own-device’ (BYOD) programs, under which their employees are allowed to bring their own devices to work and use them for both private and business purposes. This study examines what factors determine an employee's intention to participate in a corporate BYOD program and how such programs affect employer attractiveness. We approach our study of acceptance of corporate BYOD programs from the perspective of technology acceptance research. For this purpose, we propose a modified and extended UTAUT model. The model was tested by surveying students in their final term (n = 444). We show that performance expectancies have the strongest positive effect on intention, while perceived threats negatively impact intention. Finally, behavioural intention was positively associated with employer attractiveness, which leads to clear indications for companies considering establishing corporate BYOD programs. BYOD seems to play an increasingly important role in attracting and retaining future talent.

[1]  R. J. Repique.  Digital Natives, Digital Immigrants , 2013, Journal of the American Psychiatric Nurses Association.

[2]  Blake Ives,et al.  IT Consumerization: When Gadgets Turn Into Enterprise IT Tools , 2012, MIS Q. Executive.

[3]  Michael H. Breitner,et al.  Investigating the Influence of Security, Privacy, and Legal Concerns on Employees' Intention to Use BYOD Mobile Devices , 2013, AMCIS.

[4]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .

[5]  Marius Preda,et al.  Mobile Cloud Convergence in GaaS: A Business Model Proposition , 2012, 2012 45th Hawaii International Conference on System Sciences.

[6]  Jens Böcker,et al.  ICT-Innovationen erfolgreich nutzen , 2012 .

[7]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[8]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[9]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[10]  D. Straub,et al.  Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly , 2012 .

[11]  Heiko Gewald,et al.  BYOD - The Next Big Thing in Recruiting? Examining the Determinants of BYOD Service Adoption Behavior from the Perspective of Future Employees , 2013, AMCIS.

[12]  Wynne W. Chin.  How to Write Up and Report PLS Analyses , 2010 .

[13]  Jason Bennett Thatcher,et al.  What Cell Phones Mean in Young People's Daily Lives and Social Interactions , 2011 .

[14]  Walter Brenner,et al.  European Conference on Information Systems ( ECIS ) 5-15-2012 EXPLORING THE SHADOWS : IT GOVERNANCE APPROACHES TO USER-DRIVEN INNOVATION , 2012 .

[15]  Sven Laumer,et al.  Who influences whom? Analyzing workplace referents' social influence on IT adoption and non-adoption , 2009, J. Inf. Technol..

[16]  Matti Rossi,et al.  An empirical investigation of mobile ticketing service adoption in public transportation , 2006, Personal and Ubiquitous Computing.

[17]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[18]  Richard Baskerville,et al.  Individual information systems as a research arena , 2011, Eur. J. Inf. Syst..

[19]  M. Prensky.  Digital Natives, Digital Immigrants Part 1 , 2001 .

[20]  Jan-Bernd Lohmöller,et al.  Latent Variable Path Modeling with Partial Least Squares , 1989 .

[21]  Björn Niehaves,et al.  AIS Electronic , 2017 .

[22]  M. Salo,et al.  Identifiability at the boundary for first-order terms , 2006 .

[23]  Chun-Der Chen,et al.  Predicting electronic toll collection service adoption: An integration of the technology acceptance model and the theory of planned behavior , 2007 .

[24]  Wynne W. Chin.  The partial least squares approach for structural equation modeling. , 1998 .

[25]  Roman Beck,et al.  Switch to Your Own to Work with the Known: An Empirical Study on Consumerization of IT , 2013, AMCIS.

[26]  Shashikant Rai,et al.  BRING YOUR OWN DEVICE (BYOD): SECURITY RISKS AND MITIGATING STRATEGIES , 2013 .

[27]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

[28]  Jeffrey A. Ingalsbe,et al.  Threat Modeling the Cloud Computing, Mobile Device Toting, Consumerized Enterprise - an overview of considerations , 2011, AMCIS.

[29]  Mark A. Harris,et al.  The Need for BYOD Mobile Device Security Awareness and Training , 2013, AMCIS.

[30]  Detmar W. Straub,et al.  A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example , 2005, Commun. Assoc. Inf. Syst..

[31]  Bill Holtsnider,et al.  IT Manager's Handbook: Getting your New Job Done , 2010 .

[32]  Detmar W. Straub,et al.  An Update and Extension to SEM Guidelines for Admnistrative and Social Science Research , 2011 .

[33]  Straub,et al.  Editor's Comments: An Update and Extension to SEM Guidelines for Administrative and Social Science Research , 2011 .

[34]  Jan Marco Leimeister,et al.  Consumerization - IT Innovations from the Consumer Market as a Challenge for Corporate IT , 2012, Bus. Inf. Syst. Eng..

[35]  Michael Amberg,et al.  The Compass Acceptance Model for the analysis and evaluation of mobile services , 2004, Int. J. Mob. Commun..

[36]  Seymour Geisser,et al.  The Predictive Sample Reuse Method with Applications , 1975 .

[37]  Jon Friedman,et al.  Protecting data on mobile devices: A taxonomy of security threats to mobile computing and review of applicable defenses , 2008, Inf. Knowl. Syst. Manag..

[38]  Ronald T. Cenfetelli.  Inhibitors and Enablers as Dual Factor Concepts in Technology Usage , 2004, J. Assoc. Inf. Syst..

[39]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[40]  Daniel Beimborn,et al.  Enterprise App Stores for Mobile Applications - Development of a Benefits Framework , 2013, AMCIS.

[41]  Shin-Yuan Hung,et al.  User acceptance of WAP services: test of competing theories , 2005, Comput. Stand. Interfaces.

[42]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[43]  Deborah Compeau,et al.  Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study , 1999, MIS Q..

[44]  M. Lindell,et al.  Accounting for common method variance in cross-sectional research designs. , 2001, The Journal of applied psychology.

[45]  Björn Niehaves,et al.  The Effect of Private IT Use on Work Performance - Towards an IT Consumerization Theory , 2013, Wirtschaftsinformatik.

[46]  K. D. Joshi,et al.  The Pathway to Enterprise Mobile Readiness: Analysis of Perceptions, Pressures, Preparedness, and Progression , 2012, AMCIS.

[47]  Nikhilesh Dholakia,et al.  Social behavior and brand devotion among iPhone innovators , 2010, Int. J. Inf. Manag..

[48]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[49]  R. Schuler,et al.  Global talent management: Literature review, integrative framework, and suggestions for further research , 2010 .

[50]  M. Featherman,et al.  EXTENDING THE TECHNOLOGY ACCEPTANCE MODEL BY INCLUSION OF PERCEIVED RISK , 2001 .

[51]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[52]  Phil Wood.  Confirmatory Factor Analysis for Applied Research , 2008 .

[53]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[54]  D. F. Blankertz,et al.  Risk taking and information handling in consumer behavior , 1969 .

[55]  M. Stone.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[56]  E. Straub.  Understanding Technology Adoption: Theory and Future Directions for Informal Learning , 2009 .

[57]  Anol Bhattacherjee,et al.  Physicians' resistance toward healthcare information technology: a theoretical model and empirical test , 2007, Eur. J. Inf. Syst..

[58]  Karol Jakubowicz.  The Genie Is Out of the Bottle , 2018 .