Skip to main content
SpringerLink
Log in
Book cover

International Business and Emerging Economy Firms pp 163–194Cite as

Palgrave Macmillan

An Acceptance Model for the Adoption of Smart Glasses Technology by Healthcare Professionals

  • Chapter
  • First Online:

Abstract

In recent years, there has been an increase in the interest from different industries in the adoption of smart wearable devices in the light of their inevitable ubiquity. One type of these devices is the Augmented Reality Smart Glasses (ARSGs), which can have great effect in different areas through providing timely information to users. One of the industries that can significantly reap the benefits of this technology is health care. However, as healthcare is a very multidimensional industry, there is a need for a multifaceted look into the adoption and acceptance of smart glasses by health professionals. This study tends to examine the acceptance of smart glasses by healthcare professionals based on Technology Acceptance Model (TAM) as there is an imperative for empirical studies on user perceptions, attitudes, and intentions. For this purpose, five external factors are extracted from the literature and field study, being integration with information systems, external effects, hands-free feature, technological compatibility, and documentation. The model is examined by using PLS-SEM methodology. This study found documentation to have the strongest impact on intention due to the substitution of paperwork by mobile devices and facilitation of continuous documentation.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Albrecht, U.-V., Folta-Schoofs, K., Behrends, M., & von Jan, U. (2013). Effects of mobile augmented reality learning compared to textbook learning on medical students: Randomized controlled pilot study. Journal of Medical Internet Research, 15(8), e182. https://doi.org/10.2196/jmir.2497.

    Article  Google Scholar 

  • Albrecht, U. V., Von Jan, U., Kuebler, J., Zoeller, C., Lacher, M., Muensterer, O. J., et al. (2014). Google glass for documentation of medical findings: Evaluation in forensic medicine. Journal of Medical Internet Research, 16(2). https://doi.org/10.2196/jmir.3225.

  • Aldaz, G., Shluzas, L. A., Pickham, D., Eris, O., & Sadler, J. (2015). Hands-free image capture, data tagging and transfer using Google Glass: A pilot study for improved wound care management. PLoS ONE, 10(4), 1–21. https://doi.org/10.1371/journal.pone.0121179.

    Article  Google Scholar 

  • Amft, O., Wahl, F., Ishimaru, S., & Kunze, K. (2015). Making regular eyeglasses smart. IEEE Pervasive Computing, 14(3), 32–43. https://doi.org/10.1109/MPRV.2015.60.

    Article  Google Scholar 

  • Armstrong, D. G., Rankin, T. M., Giovinco, N. A., Mills, J. L., & Matsuoka, Y. (2014). A heads-up display for diabetic limb salvage surgery: A view through the Google looking glass. Journal of Diabetes Science and Technology, 8(5), 951–956. https://doi.org/10.1177/1932296814535561.

    Article  Google Scholar 

  • Başoğlu, N., Göken, M., Dabic, M., et al. (2018). Exploring adoption of augmented reality smart glasses: Applications in the medical industry. Frontiers of Engineering Management , 5(2), 167–181.

    Google Scholar 

  • Başoğlu, N., Ok, E. A., & Daim, T. U. (2017). What will it take to adopt smart glasses: A consumer choice based review? Technology in Society, 50, 50–56. https://doi.org/10.1016/j.techsoc.2017.04.005.

    Article  Google Scholar 

  • Bhattacherjee, A., & Hikmet, N. (2007). Physicians’ resistance toward healthcare information technology: A theoretical model and empirical test. European Journal of Information Systems, 16(6), 725–737. https://doi.org/10.1057/palgrave.ejis.3000717.

    Article  Google Scholar 

  • Borchers, C. (2014). Beth Israel to use Google Glass throughout emergency room. The Boston Globe.

    Google Scholar 

  • Brusie, T., Fijal, T., Keller, A., Lauff, C., Barker, K., Schwinck, J., et al. (2015). Usability evaluation of two smart glass systems. 2015 Systems and Information Engineering Design Symposium, 0(c), 336–341. https://doi.org/10.1109/SIEDS.2015.7117000.

  • Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS Quarterly, 33(4), 689–707.

    Article  Google Scholar 

  • Chau, P. Y. K., & Hu, P. J. (2002). Examining a model of information technology acceptance by individual professionals: An exploratory study. Journal of Management Information Systems, 18(4), 191–230. https://doi.org/10.2307/40398548.

    Article  Google Scholar 

  • Cheng, S.-T., Hsu, C.-W., & Li, J.-P. (2013). Combined hand gesture—Speech model for human action recognition. Sensors, 13, 17098–17129. https://doi.org/10.3390/s131217098.

    Article  Google Scholar 

  • Chin, W. W. (2000). Partial least squares for IS researchers: An overview and presentation of recent advances using the PLS approach. In International Conference on Information Systems (pp. 741–742).

    Google Scholar 

  • Chin, W. W. (2010). How to write up and report PLS analyses. In E. V. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbooks of computational statistics series (pp. 655–690). Cham: Springer.

    Google Scholar 

  • Czuszynski, K., Ruminski, J., Kocejko, T., & Wtorek, J. (2015, November). Septic safe interactions with smart glasses in health care. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015, pp. 1604–1607). Milan, Italy. https://doi.org/10.1109/EMBC.2015.7318681.

  • Daim, T. U., Basoglu, N., & Topacan, U. (2013). Adoption of health information technologies: The case of a wireless monitor for diabetes and obesity patients. Technology Analysis & Strategic Management, 25(8), 923–938. https://doi.org/10.1080/09537325.2013.823150.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Information Technology MIS Quarterly, 13(3), 319–340.

    Google Scholar 

  • Davis, F., & Bagozzi, R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  • Davis, C. R., & Rosenfield, L. K. (2015). Looking at plastic surgery through Google evidence and the first plastic surgical procedures. Plastic and Reconstructive Surgery, 135(3), 918–928. https://doi.org/10.1097/PRS.0000000000001056.

    Article  Google Scholar 

  • Ducey, A. J., & Coovert, M. D. (2016). Predicting tablet computer use: An extended technology acceptance model for physicians. Health Policy and Technology, 5(3), 268–284. https://doi.org/10.1016/j.hlpt.2016.03.010.

    Article  Google Scholar 

  • Feng, S., Caire, R., Cortazar, B., Turan, M., & Wong, A. (2014). Immunochromatographic diagnostic test analysis using Google Glass. ACS Nano, 8(3), 3069–3079.

    Article  Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluation structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  • Friedman, E. (2016). Top features of smart glasses: Hands-free documentation. Retrieved September 12, 2017, from https://brainxchange.io/4-features-smart-glasses-hands-free-documentation/.

  • Göken, M., Başoğlu, N. A., & Dabic, M. (2016). Exploring adoption of smart glasses: Application in medical industry. PICMET. Hawaii.

    Google Scholar 

  • Gregg, H. (2014a). 5 hospitals using, piloting Google Glass.

    Google Scholar 

  • Gregg, H. (2014b). Why hospitals are hesitant to use Google Glass. Health IT & CIO Review, 1–7.

    Google Scholar 

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202.

    Article  Google Scholar 

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: The better approach to structural equation modeling? Long Range Planning, 45(5–6), 312–319. https://doi.org/10.1016/j.lrp.2012.09.011.

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001.

    Article  Google Scholar 

  • Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The Use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340. https://doi.org/10.1016/j.lrp.2012.09.008.

  • Hein, D. W. E., & Rauschnabel, P. A. (2016). Augmented reality smart glasses and knowledge management: A conceptual framework for enterprise social networks. In Enterprise social networks (pp. 83–109). Wiesbaden: Springer Gabler.

    Google Scholar 

  • Hofmann, B., Haustein, D., & Landeweerd, L. (2017). Smart-glasses: Exposing and elucidating the ethical issues. Science and Engineering Ethics, 23(3), 701–721. https://doi.org/10.1007/s11948-016-9792-z.

    Article  Google Scholar 

  • Holden, R. J., & Karsh, B.-T. (2010). The technology acceptance model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172. https://doi.org/10.1016/j.jbi.2009.07.002.

    Article  Google Scholar 

  • Hong, J. (2013). Considering privacy issues in the context of Google glass. Communications of the ACM, 56(11), 10–11.

    Google Scholar 

  • Hsiao, J., & Chen, R. (2016). Critical factors influencing physicians’ intention to use computerized clinical practice guidelines: An integrative model of activity theory and the technology acceptance model. BMC Medical Informatics and Decision Making, 16(3), 1–15. https://doi.org/10.1186/s12911-016-0241-3.

    Article  Google Scholar 

  • Hung, S., Tsai, J. C., & Chuang, C. (2014). Investigating primary health care nurses â€TM intention to use information technology: An empirical study in Taiwan. Decision Support Systems, 57, 331–342.

    Article  Google Scholar 

  • Kalantari, M., & Rauschnabel, P. A. (2018). Exploring the early adopters of augmented reality smart glasses: The case of Microsoft HoloLens. In T. Jung & M. C. T. Dieck (Eds.), Augmented reality and virtual reality (pp. 1–17). https://doi.org/10.1007/978-3-319-64027-3.

  • Karahanna, E., Agarwal, R., & Angst, C. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30(4), 781–804. https://doi.org/10.2307/25148754.

    Article  Google Scholar 

  • Kassirer, J. P. (2000). Patients, physicians, and the Internet. Health Affairs, 19(6), 115.

    Article  Google Scholar 

  • Kim, K. J., & Dong-Hee, S. (2015). An acceptance model for smart watches implications for the adoption of future wearable technology. Internet Research, 25(4), 527–541. https://doi.org/10.1108/MBE-09-2016-0047.

    Article  Google Scholar 

  • Kolodzey, L., Grantcharov, P. D., Rivas, H., Schijven, M. P., & Grantcharov, T. P. (2017). Wearable technology in the operating room: A systematic review. BMJ Innovations, 3, 55–63. https://doi.org/10.1136/bmjinnov-2016-000133.

    Article  Google Scholar 

  • Kuo, K. M., Liu, C. F., & Ma, C. C. (2013). An investigation of the effect of nurses’ technology readiness on the acceptance of mobile electronic medical record systems. BMC Medical Informatics and Decision Making, 13(8), 1–14. https://doi.org/10.1186/1472-6947-13-88.

    Article  Google Scholar 

  • Kwong, K., & Wong, K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, Technical Note.

    Google Scholar 

  • Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3), 461–491. https://doi.org/10.2307/25148692.

    Article  Google Scholar 

  • Lazuras, L., & Dokou, A. (2016). Mental health professionals’ acceptance of online counseling. Technology in Society, 44, 10–14. https://doi.org/10.1016/j.techsoc.2015.11.002.

    Article  Google Scholar 

  • Lee, F., Teich, J. M., Spurr, C. D., & Bates, D. W. (1996). Implementation of physician order entry: User satisfaction and self- reported usage patterns. Journal of the American Medical Informatics Association, 3(November), 42–55. https://doi.org/10.1136/jamia.1996.96342648.

    Article  Google Scholar 

  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4.

    Article  Google Scholar 

  • Lukowicz, P., Kirstein, T., & Tröster, G. (2004). Wearable systems for health care applications. Methods of Information in Medicine, 43(3), 232–238. https://doi.org/10.1267/METH04030232.

    Article  Google Scholar 

  • May, C., Gask, L., Atkinson, T., Ellis, N., Mair, F., & Esmail, A. (2001). Resisting and promoting new technologies in clinical practice: The case of telepsychiatry. Social Science and Medicine, 52(12), 1889–1901. https://doi.org/10.1016/S0277-9536(00)00305-1.

    Article  Google Scholar 

  • Mechanic, D. (2003). Physician discomfort challenges and opportunity. Journal of the American Medical Association, 290(7), 941–946. https://doi.org/10.1001/jama.290.7.941.

    Article  Google Scholar 

  • Meyers, S. (2003). ‘Concierge’ medicine. Who really pays for gold standard access to doctors? Trustee: The Journal for Hospital Governing Boards, 56(1), 12–14.

    Google Scholar 

  • Mitrasinovic, S., Camacho, E., Trivedi, N., Logan, J., Campbell, C., Zilinyi, R., et al. (2015). Clinical and surgical applications of smart glasses. Technology and Health Care, 23(4), 381–401. https://doi.org/10.3233/THC-150910.

  • Monroy, G. L., Shemonski, N. D., Shelton, R. L., Nolan, R. M., & Boppart, S. A. (2014). Implementation and evaluation of Google Glass for visualizing real-time image and patient data in the primary care office. Proceedings of SPIE, 8935, 893514–893519. https://doi.org/10.1117/12.2040221.

    Article  Google Scholar 

  • Moon, S., & Seo, J. (2015). Integration of smart glass technology for information exchange at construction sites. In Proceedings of the International Symposium on Automation and Robotics in Construction (pp. 1–2).

    Google Scholar 

  • Moshtaghi, O., Kelley, K. S., Armstrong, W. B., Ghavami, Y., Gu, J., & Djalilian, H. R. (2015). Using Google Glass to solve communication and surgical education challenges in the operating room. The Laryngoscope, 125(10), 2295–2297. https://doi.org/10.1002/lary.25249.

    Article  Google Scholar 

  • Muensterer, O. J., Lacher, M., Zoeller, C., & Bronstein, M. (2014). Google Glass in pediatric surgery: An exploratory study. International Journal of Surgery, 12(4), 281–289.

    Article  Google Scholar 

  • Ni, T., & Baudisch, P. (2009). Disappearing mobile devices. In Proceedings of UIST 2009 (pp. 101–110). https://doi.org/10.1145/1622176.1622197.

  • Oremus, W. (2015). Google Glass: The future’s not very bright. Charlotte Observer.

    Google Scholar 

  • Overhage, J. M., Perkins, S., Tierney, W. M., & McDonald, C. J. (2001). Controlled trial of direct physician order entry. Journal of the American Medical Informatics Association, 8(4), 361–371. https://doi.org/10.1136/jamia.2001.0080361.

    Article  Google Scholar 

  • Procurement Guide for Hospital Information Management Systems. (2010). Ankara: TC Ministry of Health Administrative and Financial Affairs Department.

    Google Scholar 

  • Quint, F., & Loch, F. (2015). Using smart glasses to document maintenance processes. Mensch und Computer 2015–Workshopband.

    Google Scholar 

  • Ratanawongsa, N., Barton, J. L., Lyles, C. R., Wu, M., Yelin, E. H., Matinez, D., et al. (2015). Association between clinician computer use and communication with patients in safety-net clinics. JAMA, 176(1), 125–127. https://doi.org/10.1001/jamainternmed.2015.6102.4.

    Article  Google Scholar 

  • Rauschnabel, P. A., Brem, A., & Ivens, B. S. (2015). Who will buy smart glasses? Empirical results of two pre-market-entry studies on the role of personality in individual awareness and intended adoption of Google Glass wearables. Computers in Human Behavior, 49, 635–647. https://doi.org/10.1016/j.chb.2015.03.003.

    Article  Google Scholar 

  • Richardson, L., Keefe, K., Huber, C., Racevskis, L., Reynolds, G., Thourot, S., et al. (2014). Assessing the value of the Central Everglades Planning Project (CEPP) in Everglades restoration: An ecosystem service approach. Ecological Economics, 107, 366–377. https://doi.org/10.1016/j.ecolecon.2014.09.011.

    Article  Google Scholar 

  • Ro, Y. K., Brem, A., & Rauschnabel, P. A. (2018). Augmented reality smart glasses: Definition, concepts and impact on firm value creation (pp. 169–181). Cham: Springer. https://doi.org/10.1007/978-3-319-64027-3_12.

  • Rodríguez, H. B. M., Salem, S. J., & Gomez, I. T. J. (2017). Feasibility and safety of augmented reality—Assisted urological surgery using smartglass. World Journal of Urology, 35, 967–972. https://doi.org/10.1007/s00345-016-1956-6.

    Article  Google Scholar 

  • Rogers, E. M., & Everett, M. (1983). Diffusion of innovation (3rd ed.). New York: The Free Press. https://doi.org/82-70998.

  • Rowe, M., Bozalek, V., & Frantz, J. (2013). Using Google Drive to facilitate a blended approach to authentic learning. British Journal of Educational Technology, 44(4), 594–606. https://doi.org/10.1111/bjet.12063.

    Article  Google Scholar 

  • Rubin, R. (2017). With Enterprise Edition, Google Glass finds its ROI calling. ZDNet.

    Google Scholar 

  • Ruminski, J., Bujnowski, A., Andrushevich, A., Biallas, M., & Kistler, R. (2016). The data exchange between smart glasses and healthcare information systems using the HL7 FHIR standard. In 2016 9th International Conference on Human System Interactions (HSI) (pp. 525–531).

    Google Scholar 

  • Sanchez, G. (2013). PLS path modeling with R. R package notes. https://doi.org/citeulike-article-id:13341888.

  • Shaoa, P., Ding, H., Wang, J., Liu, P., Ling, Q., Chen, J., et al. (2014). Designing a wearable navigation system for image-guided cancer resection surgery. Annals of Biomedical Engineering, 42(11), 2228–2237. https://doi.org/10.1007/s10439-014-1062-0.Designing.

  • Shaygan, A., Ozdemir-Gungor, D., Kutgun, H., & Daneshi, A. (2017). Adoption criteria evaluation of activity tracking Wristbands for university students. PICMET.

    Google Scholar 

  • Sijie, X., Sujie, Z., Yisheng, J., Binyao, J., Xiaohua, T., Xuesheng, Z., et al. (2017). iBlink: Smart glasses for facial paralysis patients. In MobiSys ’17 Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (pp. 359–370). New York, USA. https://doi.org/10.1145/3081333.3081343.

  • TOBB. (2017). Turkey healthcare landscape. Retrieved from https://www.tobb.org.tr/saglik/20171229-tss-genel-bakis-en.pdf.

  • Township, D., & District, L. (2017). The staffs’ adoption intention of knowledge management system in green hospital—The theory of technology acceptance model applied. Internation Journal of Organizational Innovation, 9(3), 27–36.

    Google Scholar 

  • Turan, A. H., & Palvia, P. C. (2014). Critical information technology issues in Turkish healthcare. Information & Management, 51(1), 57–68. https://doi.org/10.1016/J.IM.2013.09.007.

    Article  Google Scholar 

  • Vallurupalli, S., Paydak, H., Agarwal, S. K., Agrawal, M., & Assad-Kottner, C. (2013). Wearable technology to improve education and patient outcomes in a cardiology fellowship program—A feasibility study. Health and Technology, 3(4), 267–270. https://doi.org/10.1007/s12553-013-0065-4.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/WOS:000086130700002.

  • Venkatesh, V., & Zhang, X. (2014). Unified theory of acceptance and use of technology: U.S. vs. China. Journal of Global Information Technology Management, 13(1), 5–27. https://doi.org/10.1080/1097198X.2010.10856507.

  • Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: From foundations to recent developments and open issues for model assessment and improvement. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares (pp. 47–83). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-32827-8.

  • Wang, C.-H. (2015). A market-oriented approach to accomplish product positioning and product recommendation for smart phones and wearable devices. International Journal of Production Research, 53(8), 2542–2553. https://doi.org/10.1080/00207543.2014.991046.

    Article  Google Scholar 

  • Wu, J. H., Wang, S. C., & Lin, L. M. (2007). Mobile computing acceptance factors in the healthcare industry: A structural equation model. International Journal of Medical Informatics, 76(1), 66–77. https://doi.org/10.1016/j.ijmedinf.2006.06.006.

    Article  Google Scholar 

  • Yarbrough, A. K., & Smith, T. B. (2007). Technology acceptance among physicians: A new take on TAM. Medical Care Research and Review: MCRR, 64(6), 650–672. https://doi.org/10.1177/1077558707305942.

    Article  Google Scholar 

  • Yu, P., Li, H., & Gagnon, M.-P. (2009). Health IT acceptance factors in long-term care facilities: A cross-sectional survey. International Journal of Medical Informatics, 78(4), 219–229. https://doi.org/10.1016/j.ijmedinf.2008.07.006.

    Article  Google Scholar 

  • Zak, C., D’Aprix, T., & Billitier, A. (2002). Electronic data gathering for emergency medical services. United States.

    Google Scholar 

  • Zheng, X. S., Foucault, C., Silva, P. M. da, Dasari, S., Yang, T., & Goose, S. (2015). Eye-wearable technology for machine maintenance: Effects of display position and hands-free operation. Proceedings of the ACM CHI’15 Conference on Human Factors in Computing Systems, 1, 2125–2134. https://doi.org/10.1145/2702123.2702305.

Download references

Author information

Authors and Affiliations

  1. Izmir Katip Celebi University, Izmir, Turkey

    Dilek Özdemir-Güngör

  2. Istanbul Technical University, Istanbul, Turkey

    Müge Göken

  3. Izmir Institute of Technology, Izmir, Turkey

    Nuri Basoglu

  4. Portland State University, Portland, USA

    Amir Shaygan & Tugrul U. Daim

  5. Faculty of Economics and Business, University of Zagreb, Zagreb, Croatia

    Marina Dabić

  6. Nottingham Trent University, Nottingham, UK

    Marina Dabić

Authors
  1. Dilek Özdemir-Güngör
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Müge Göken
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nuri Basoglu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amir Shaygan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marina Dabić
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tugrul U. Daim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marina Dabić .

Editor information

Editors and Affiliations

  1. Faculty of Business Studies, University of Vaasa, Vaasa, Finland

    Jorma A. Larimo

  2. Aalborg Business School, Aalborg University, Aalborg, Denmark

    Marin A. Marinov

  3. Department of Business and Management, Aalborg University, Aalborg, Denmark

    Svetla T. Marinova

  4. School of Marketing and Communication, University of Vaasa, Vaasa, Finland

    Tiina Leposky

List of Appendix

List of Appendix

See Appendix 6.1

Appendix 6.1 Variables used in the model testing
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Özdemir-Güngör, D., Göken, M., Basoglu, N., Shaygan, A., Dabić, M., Daim, T.U. (2020). An Acceptance Model for the Adoption of Smart Glasses Technology by Healthcare Professionals. In: Larimo, J., Marinov, M., Marinova, S., Leposky, T. (eds) International Business and Emerging Economy Firms. Palgrave Studies of Internationalization in Emerging Markets. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-27285-2_6

Download citation

Publish with us

Policies and ethics

Search

Navigation