IDEAS home Printed from https://ideas.repec.org/a/cmj/seapas/y2015i9p155-165.html
   My bibliography  Save this article

Drivers And Barriers For Video Technologies Adoption - An Exploratory Analysis On Students

Author

Listed:
  • Rodica IANOLE

    (Faculty of Business and Administration, University of Bucharest)

  • Camelia COJOCARU

    (Faculty of Business and Administration, University of Bucharest)

  • Cătălin NEDELCEA

    (Faculty of Psychology and Educational Sciences, University of Bucharest)

Abstract

The paper aims to elicit and discuss upon the main factors influencing the process of adopting video technologies by employing a mix of qualitative and quantitative methods. In the first stage, a focus group research was implemented on four samples of subjects with different levels of resistance to the use of technology, generating a set of barriers and facilitators, classified by their nature and level of interdependence. The second part of the investigation consisted in the application of a supervised questionnaire, following an adapted version of the mental representation methodology of Svenson and Nilsson (1986), for economics (marketing specialization) and psychology students. The preliminary results are pointing out to a couple of significant differences in perceiving the influence of the analyzed factors, suggesting the need for a customized policy of minimizing resistance to innovation.

Suggested Citation

  • Rodica IANOLE & Camelia COJOCARU & Cătălin NEDELCEA, 2015. "Drivers And Barriers For Video Technologies Adoption - An Exploratory Analysis On Students," SEA - Practical Application of Science, Romanian Foundation for Business Intelligence, Editorial Department, issue 9, pages 155-165, December.
  • Handle: RePEc:cmj:seapas:y:2015:i:9:p:155-165
    as

    Download full text from publisher

    File URL: http://seaopenresearch.eu/Journals/articles/SPAS_9_22.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Svenson, Ola & Nilsson, Goran, 1986. "Mental economics: Subjective representations of factors related to expected inflation," Journal of Economic Psychology, Elsevier, vol. 7(3), pages 327-349, September.
    2. Kleijnen, Mirella & Lee, Nick & Wetzels, Martin, 2009. "An exploration of consumer resistance to innovation and its antecedents," Journal of Economic Psychology, Elsevier, vol. 30(3), pages 344-357, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hans-Jürgen Engelbrecht, 2015. "A General Model of the Innovation - Subjective Well-Being Nexus," Economic Complexity and Evolution, in: Andreas Pyka & John Foster (ed.), The Evolution of Economic and Innovation Systems, edition 127, pages 69-90, Springer.
    2. Michelsen, Carl Christian & Madlener, Reinhard, 2016. "Switching from fossil fuel to renewables in residential heating systems: An empirical study of homeowners' decisions in Germany," Energy Policy, Elsevier, vol. 89(C), pages 95-105.
    3. Yi, Jisu & Lee, Youseok & Suh, Jungmin & Kim, Sang-Hoon, 2022. "Psychological determinants of non-attendees’ resistance toward performing arts," Journal of Business Research, Elsevier, vol. 149(C), pages 690-699.
    4. Hajiheydari, Nastaran & Delgosha, Mohammad Soltani & Olya, Hossein, 2021. "Scepticism and resistance to IoMT in healthcare: Application of behavioural reasoning theory with configurational perspective," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    5. Lena Dräger & Ulrich Fritsche, 2013. "Don't Worry, Be Right! Survey Wording Effects on In flation Perceptions and Expectations," Macroeconomics and Finance Series 201308, University of Hamburg, Department of Socioeconomics.
    6. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    7. Chamaret, Cécile & Steyer, Véronique & Mayer, Julie C., 2020. "“Hands off my meter!” when municipalities resist smart meters: Linking arguments and degrees of resistance," Energy Policy, Elsevier, vol. 144(C).
    8. Nel, Jacques & Boshoff, Christo, 2021. "“I just don't like digital-only banks, and you should not use them either†: Traditional-bank customers' opposition to using digital-only banks," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    9. Godart, Frédéric & Pistilli, Luca, 2024. "The multifaceted concept of disruption: A typology," Journal of Business Research, Elsevier, vol. 170(C).
    10. Petschnig, Martin & Heidenreich, Sven & Spieth, Patrick, 2014. "Innovative alternatives take action – Investigating determinants of alternative fuel vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 68-83.
    11. Komulainen, Ruey & Nätti, Satu, 2023. "Barriers to blockchain adoption: Empirical observations from securities services value network," Journal of Business Research, Elsevier, vol. 159(C).
    12. Faten Baklouti & Fayçal Boukamcha, 2024. "Consumer resistance to internet banking services: implications for the innovation resistance theory," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(2), pages 364-376, June.
    13. Shahbaz, Muhammad & Gao, Changyuan & Zhai, LiLi & Shahzad, Fakhar & Khan, Imran, 2021. "Environmental air pollution management system: Predicting user adoption behavior of big data analytics," Technology in Society, Elsevier, vol. 64(C).
    14. Han-Shen Chen & Bi-Kun Tsai & Chi-Ming Hsieh, 2018. "The Effects of Perceived Barriers on Innovation Resistance of Hydrogen-Electric Motorcycles," Sustainability, MDPI, vol. 10(6), pages 1-15, June.
    15. Friedman, Nicola & Ormiston, Jarrod, 2022. "Blockchain as a sustainability-oriented innovation?: Opportunities for and resistance to Blockchain technology as a driver of sustainability in global food supply chains," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    16. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    17. Malodia, Suresh & Kaur, Puneet & Ractham, Peter & Sakashita, Mototaka & Dhir, Amandeep, 2022. "Why do people avoid and postpone the use of voice assistants for transactional purposes? A perspective from decision avoidance theory," Journal of Business Research, Elsevier, vol. 146(C), pages 605-618.
    18. Barbarossa, Camilla & De Pelsmacker, Patrick & Moons, Ingrid, 2017. "Personal Values, Green Self-identity and Electric Car Adoption," Ecological Economics, Elsevier, vol. 140(C), pages 190-200.
    19. Querci, Ilaria & Monsurrò, Luigi & Peverini, Paolo, 2024. "When anthropomorphism backfires: Anticipation of negative social roles as a source of resistance to smart object adoption," Technovation, Elsevier, vol. 132(C).
    20. Hong, Areum & Nam, Changi & Kim, Seongcheol, 2020. "What will be the possible barriers to consumers’ adoption of smart home services?," Telecommunications Policy, Elsevier, vol. 44(2).

    More about this item

    Keywords

    Adoption rate; Video technologies; Resistance to innovation; Mental representations;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cmj:seapas:y:2015:i:9:p:155-165. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Serghie Dan (email available below). General contact details of provider: https://seaopenresearch.eu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.