IDEAS home Printed from https://ideas.repec.org/p/zbw/itsb21/238024.html
   My bibliography  Save this paper

Perception of innovation in Spain

Author

Listed:
  • Gijón, Covadonga
  • Albarrán Lozano, Irene
  • Molina, José Manuel

Abstract

The present paper analyses the perception of innovation of individuals in Spain and the factors associated with it. Data from 2015 and 2018 about individuals from the Spanish surveys are used. The data include several measures of innovation perception, gender, age, educational level, and other socioeconomic and technical variables. The aim of this paper is to determine the perception of innovation, in its different aspects, of Spanish people. To this end, several ordered logit models have been developed to determine how much the socio-demographic characteristics and other aspects of innovation affect the perception of innovation. Results indicate that people have a better perception of innovation if they are training in innovation or have good Information and Communication Technology skills. Among the main results, there is evidence of a gender gap in the perception of innovation, as well as differences according to digital skills.

Suggested Citation

  • Gijón, Covadonga & Albarrán Lozano, Irene & Molina, José Manuel, 2021. "Perception of innovation in Spain," 23rd ITS Biennial Conference, Online Conference / Gothenburg 2021. Digital societies and industrial transformations: Policies, markets, and technologies in a post-Covid world 238024, International Telecommunications Society (ITS).
    • Handle: RePEc:zbw:itsb21:238024
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/238024/1/Gijon-Lozano-Molina.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Antioco & Mirella Kleijnen, 2010. "Consumer adoption of technological innovations : Effects of psychological and functional barriers in a lack of content versus a presence of content situation," Post-Print hal-02312561, HAL.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. 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).
    4. M. Antioco & M. Kleijnen, 2010. "Consumer adoption of technological innovations Effects of psychological and functional barriers in a lack of content versus a presence of content situation," Post-Print hal-00387308, HAL.
    5. Seth, Himanshu & Talwar, Shalini & Bhatia, Anuj & Saxena, Akanksha & Dhir, Amandeep, 2020. "Consumer resistance and inertia of retail investors: Development of the resistance adoption inertia continuance (RAIC) framework," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    6. Grimm, Veronika & Kretschmer, Sandra & Mehl, Simon, 2020. "Green innovations: The organizational setup of pilot projects and its influence on consumer perceptions," Energy Policy, Elsevier, vol. 142(C).
    7. Fonseca, Tiago & de Faria, Pedro & Lima, Francisco, 2019. "Human capital and innovation: the importance of the optimal organizational task structure," Research Policy, Elsevier, vol. 48(3), pages 616-627.
    8. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    9. Egfjord, Kathrine Friis-Holm & Sund, Kristian J., 2020. "Do you see what I see? How differing perceptions of the environment can hinder radical business model innovation," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    10. Heidenreich, Sven & Kraemer, Tobias, 2015. "Passive innovation resistance: The curse of innovation? Investigating consequences for innovative consumer behavior," Journal of Economic Psychology, Elsevier, vol. 51(C), pages 134-151.
    11. Röth, Tobias & Spieth, Patrick, 2019. "The influence of resistance to change on evaluating an innovation project's innovativeness and risk: A sensemaking perspective," Journal of Business Research, Elsevier, vol. 101(C), pages 83-92.
    12. Karolin Frankenberger & Tobias Weiblen & Michaela Csik & Oliver Gassmann, 2013. "The 4I-framework of business model innovation: a structured view on process phases and challenges," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 18(3/4), pages 249-273.
    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. Huang, Dan & Jin, Xin & Coghlan, Alexandra, 2021. "Advances in consumer innovation resistance research: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    2. 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).
    3. Talwar, Shalini & Talwar, Manish & Kaur, Puneet & Dhir, Amandeep, 2020. "Consumers’ resistance to digital innovations: A systematic review and framework development," Australasian marketing journal, Elsevier, vol. 28(4), pages 286-299.
    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. Laukkanen, Tommi, 2016. "Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking," Journal of Business Research, Elsevier, vol. 69(7), pages 2432-2439.
    6. Lalicic, Lidija & Weismayer, Christian, 2021. "Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents," Journal of Business Research, Elsevier, vol. 129(C), pages 891-901.
    7. Delgosha, Mohammad Soltani & Hajiheydari, Nastaran, 2020. "On-demand service platforms pro/anti adoption cognition: Examining the context-specific reasons," Journal of Business Research, Elsevier, vol. 121(C), pages 180-194.
    8. Chakraborty, Debarun & Singu, Hari Babu & Patre, Smruti, 2022. "Fitness Apps's purchase behaviour: Amalgamation of Stimulus-Organism-Behaviour-Consequence framework (S–O–B–C) and the innovation resistance theory (IRT)," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    9. Talwar, Manish & Talwar, Shalini & Kaur, Puneet & Tripathy, Naliniprava & Dhir, Amandeep, 2021. "Has financial attitude impacted the trading activity of retail investors during the COVID-19 pandemic?," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    10. Attié, Elodie & Meyer-Waarden, Lars, 2022. "The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy ca," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    11. Kamoonpuri, Sana Zehra & Sengar, Anita, 2023. "Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    12. 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).
    13. Dongming Wu & Liukai Yu & Qianqian Zhang & Yangyang Jiao & Yuhe Wu, 2021. "Materialism, Ecological Consciousness and Purchasing Intention of Electric Vehicles: An Empirical Analysis among Chinese Consumers," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    14. Pal, Debajyoti & Zhang, Xiangmin & Siyal, Saeed, 2021. "Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach," Technology in Society, Elsevier, vol. 66(C).
    15. Muhammad Ilyas & Arif ud din & Muhammad Haleem & Irshad Ahmad, 2023. "Digital entrepreneurial acceptance: an examination of technology acceptance model and do-it-yourself behavior," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-19, December.
    16. Mahmud, Hasan & Islam, A.K.M. Najmul & Mitra, Ranjan Kumar, 2023. "What drives managers towards algorithm aversion and how to overcome it? Mitigating the impact of innovation resistance through technology readiness," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    17. Jennifer S. Labrecque & Wendy Wood & David T. Neal & Nick Harrington, 2017. "Habit slips: when consumers unintentionally resist new products," Journal of the Academy of Marketing Science, Springer, vol. 45(1), pages 119-133, January.
    18. Arun T. M. & Puneet Kaur & Stefano Bresciani & Amandeep Dhir, 2021. "What drives the adoption and consumption of green hotel products and services? A systematic literature review of past achievement and future promises," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2637-2655, July.
    19. Kuo Cheng Chung & Silvia Wan-Ju Liang, 2020. "Understanding Factors Affecting Innovation Resistance of Mobile Payments in Taiwan: An Integrative Perspective," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    20. Mendoza, Mario A. & Rodriguez Alfonso, Mauricio & Lhuillery, Stephane, 2021. "A battle of drones: Utilizing legitimacy strategies for the transfer and diffusion of dual-use technologies," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

    More about this item

    Keywords

    perception; innovation; survey data; ordered logit;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:itsb21:238024. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: http://www.itsworld.org/ .

    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.