IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v182y2022ics0040162522004140.html
   My bibliography  Save this article

Consumer's adoption of virtual reality technologies for marine conservation: Motivational and technology acceptance perspectives

Author

Listed:
  • Yuen, Kum Fai
  • Chua, Jessana
  • Li, Kevin X.
  • Wang, Xueqin

Abstract

As the marine ecosystem deteriorates over time, more efforts are made to raise public awareness. Virtual reality technology in marine ecotourism (VRTME) enhances the travel experiences of those affected by the COVID-19 pandemic. This study adopts Maslow's hierarchy of motivational needs and the technology acceptance model to investigate the factors influencing consumers' behavioural intention (BI) towards VRTME and examines their interrelationships. An online survey was conducted with 451 people, and the results were analysed using structural equation modelling. The findings show how motivational constructs, namely, environmental knowledge, biospheric values, risk perception of marine pollution, social susceptibility, and green self-image, as mediated by perceived usefulness (PU), affect the adoption of VRTME. Perceived ease of use (PEOU) further impacted PU. The total effect analysis indicated that PU had the strongest influence, followed by PEOU, social susceptibility, biospheric values, environmental knowledge, green self-image, and risk perception of marine pollution. To substantiate the constructs motivating BI, this study combined two disparate research paradigms centred on the environmental needs and technological characteristics of VRTME. Overall, this study contributes to the existing literature on consumers' adoption of VRTME by introducing new perspectives and recommending policies to raise public awareness and support ongoing conservation efforts.

Suggested Citation

  • Yuen, Kum Fai & Chua, Jessana & Li, Kevin X. & Wang, Xueqin, 2022. "Consumer's adoption of virtual reality technologies for marine conservation: Motivational and technology acceptance perspectives," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    • Handle: RePEc:eee:tefoso:v:182:y:2022:i:c:s0040162522004140
    DOI: 10.1016/j.techfore.2022.121891
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162522004140
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2022.121891?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Sabrina Stöckli & Doris Hofer, 2020. "Susceptibility to social influence predicts behavior on Facebook," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    3. Yuen, Kum Fai & Wang, Xueqin & Ma, Fei & Wong, Yiik Diew, 2019. "The determinants of customers’ intention to use smart lockers for last-mile deliveries," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 316-326.
    4. Ponzoa, José M. & Gómez, Andrés & Villaverde, Silvia & Díaz, Vicente, 2021. "Technologically empowered? perception and acceptance of AR glasses and 3D printers in new generations of consumers," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    5. Nikhil Menon & Yu Zhang & Abdul Rawoof Pinjari & Fred Mannering, 2020. "A statistical analysis of consumer perceptions towards automated vehicles and their intended adoption," Transportation Planning and Technology, Taylor & Francis Journals, vol. 43(3), pages 253-278, April.
    6. Yuen, Kum Fai & Bin Saidi, Muhammad Syukri & Bai, Xiwen & Wang, Xueqin, 2021. "Cruise transport service usage post COVID-19: The health belief model application," Transport Policy, Elsevier, vol. 111(C), pages 185-196.
    7. Wang, Xueqin & Wong, Yiik Diew & Liu, Feng & Yuen, Kum Fai, 2021. "A push–pull–mooring view on technology-dependent shopping under social distancing: When technology needs meet health concerns," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    8. FIORILLO, Damiano & SENATORE, Luigi, 2016. "Self Image and Environmental Attitude and Behavior," CELPE Discussion Papers 140, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    9. Alan T. Sorensen, 2006. "Social learning and health plan choice," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 929-945, December.
    10. Cui, Lixin & Wang, Yonggui & Chen, Weiming & Wen, Wen & Han, Myat Su, 2021. "Predicting determinants of consumers' purchase motivation for electric vehicles: An application of Maslow's hierarchy of needs model," Energy Policy, Elsevier, vol. 151(C).
    11. Alan T. Sorensen, 2006. "Social learning and health plan choice," RAND Journal of Economics, The RAND Corporation, vol. 37(4), pages 929-945, December.
    12. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    13. Xianwei Liu & Yang Zou & Jianping Wu, 2018. "Factors Influencing Public-Sphere Pro-Environmental Behavior among Mongolian College Students: A Test of Value–Belief–Norm Theory," Sustainability, MDPI, vol. 10(5), pages 1-19, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hoang, Sinh Duc & Dey, Sandeep Kumar & Tučková, Zuzana & Pham, Tien Phat, 2023. "Harnessing the power of virtual reality: Enhancing telepresence and inspiring sustainable travel intentions in the tourism industry," Technology in Society, Elsevier, vol. 75(C).
    2. Yuen, Kum Fai & Koh, Le Yi & Tan, Luan Yi Hazel & Wang, Xueqin, 2023. "The determinants of virtual reality adoption for marine conservation," Technology in Society, Elsevier, vol. 72(C).
    3. Saif, Mashaal A.M. & Hussin, Nazimah & Husin, Maizaitulaidawati Md & Muneer, Amgad & Alwadain, Ayed, 2024. "Beyond conventions: Unravelling perceived value's role in shaping digital-only banks' adoption," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    4. Badghish, Saeed & Shaik, Aqueeb Sohail & Sahore, Nidhi & Srivastava, Shalini & Masood, Ayesha, 2024. "Can transactional use of AI-controlled voice assistants for service delivery pickup pace in the near future? A social learning theory (SLT) perspective," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    5. Wang, Xueqin & Wong, Yiik Diew & Liu, Feng & Yuen, Kum Fai, 2023. "Consumers' paradoxical motives of co-creation: From self-service technology to crowd-sourcing platform," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    6. Allal-Chérif, Oihab & Puertas, Rosa & Carracedo, Patricia, 2024. "Intelligent influencer marketing: how AI-powered virtual influencers outperform human influencers," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    7. Andreea-Ionela Puiu & Rodica Ianole-Călin & Elena Druică, 2023. "Exploring the Consumer Acceptance of Nano Clothing Using a PLS-SEM Analysis," Stats, MDPI, vol. 6(4), pages 1-19, October.
    8. Yohan Wismantoro & Vincent Didiek Wiet Aryanto & Imang Dapit Pamungkas & Nanda Adhi Purusa & Amron & Amalia Nur Chasanah & Usman, 2022. "Virtual Reality Destination Experiences Model: A Moderating Variable between Wisesa Sustainable Tourism Behavior and Tourists’ Intention to Visit," Sustainability, MDPI, vol. 15(1), pages 1-13, December.
    9. Fang, Xiaohan & Zhang, Ying & Yang, Jiajia & Zhan, Guohua, 2024. "An evaluation of marine economy sustainable development and the ramifications of digital technologies in China coastal regions," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 554-570.

    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. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    2. Yuen, Kum Fai & Chua, Jie Ying & Li, Xue & Wang, Xueqin, 2023. "The determinants of users’ intention to adopt telehealth: Health belief, perceived value and self-determination perspectives," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    3. Engström, Per & Forsell, Eskil, 2018. "Demand effects of consumers’ stated and revealed preferences," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 43-61.
    4. Muzhe Yang & Hsien-Ming Lien & Shin-Yi Chou, 2014. "Is There A Physician Peer Effect? Evidence From New Drug Prescriptions," Economic Inquiry, Western Economic Association International, vol. 52(1), pages 116-137, January.
    5. Manuela Angelucci & Silvia Prina & Heather Royer & Anya Samek, 2015. "When Incentives Backfire: Spillover Effects in Food Choice," NBER Working Papers 21481, National Bureau of Economic Research, Inc.
    6. Karen Ruckman & Nilesh Saraf & Vallabh Sambamurthy, 2015. "Market Positioning by IT Service Vendors Through Imitation," Information Systems Research, INFORMS, vol. 26(1), pages 100-126, March.
    7. Malani, Anup & Kinnan, Cynthia & Conti, Gabriella & Imai, Kosuke & Miller, Morgen & Swaminathan, Shailender & Voena, Alessandra & Woda, Bartek, 2024. "Evaluating and pricing health insurance in lower-income countries: A field experiment in India," CEPR Discussion Papers 19326, C.E.P.R. Discussion Papers.
    8. Branko Boskovic, David P.Byrne, Arvind Magesan, 2012. "Herding Among Bureaucrats," Department of Economics - Working Papers Series 1158, The University of Melbourne.
    9. Stanfors, Maria & Karlsson, Tobias & Andersson, Lars-Fredrik & Eriksson, Liselotte, 2022. "Membership in Mutual Health Insurance Societies: The Case of Swedish Manufacturing, circa 1900," Lund Papers in Economic History 238, Lund University, Department of Economic History.
    10. Ali, S. Nageeb, 2018. "Herding with costly information," Journal of Economic Theory, Elsevier, vol. 175(C), pages 713-729.
    11. Hang Xiong & Puqing Wang & Georgiy Bobashev, 2018. "Multiple peer effects in the diffusion of innovations on social networks: a simulation study," Journal of Innovation and Entrepreneurship, Springer, vol. 7(1), pages 1-18, December.
    12. Sridhar Narayanan & Harikesh S. Nair, 2011. "Estimating Causal Installed-Base Effects: A Bias-Correction Approach," Working Papers 11-22, NET Institute.
    13. John Beshears & James J. Choi & David Laibson & Brigitte C. Madrian & Katherine L. Milkman, 2015. "The Effect of Providing Peer Information on Retirement Savings Decisions," Journal of Finance, American Finance Association, vol. 70(3), pages 1161-1201, June.
    14. Ilan Lobel & Evan Sadler, 2016. "Preferences, Homophily, and Social Learning," Operations Research, INFORMS, vol. 64(3), pages 564-584, June.
    15. Anastasia Girshina & Thomas Y. Mathä & Michael Ziegelmeyer, 2019. "Peer effects in stock market participation: Evidence from immigration," BCL working papers 137, Central Bank of Luxembourg.
    16. Amedeo Piolatto, 2015. "Online booking and information: competition and welfare consequences of review aggregators," Working Papers 2015/11, Institut d'Economia de Barcelona (IEB).
    17. Bryan Bollinger & Kenneth Gillingham & Stefan Lamp & Tsvetan Tsvetanov, 2024. "Promotional Campaign Duration and Word of Mouth in Solar Panel Adoption," Marketing Science, INFORMS, vol. 43(5), pages 1132-1148, September.
    18. Mugerman, Yevgeny & Sade, Orly & Shayo, Moses, 2014. "Long term savings decisions: Financial reform, peer effects and ethnicity," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 235-253.
    19. Ryota Nakamura & Marc Suhrcke & Daniel John Zizzo, 2017. "A triple test for behavioral economics models and public health policy," Theory and Decision, Springer, vol. 83(4), pages 513-533, December.
    20. Malani, Anup & Holtzman, Phoebe & Imai, Kosuke & Kinnan, Cynthia & Miller, Morgen & Swaminathan, Shailender & Voena, Alessandra & Woda, Bartek & Conti, Gabriella, 2021. "Effect of Health Insurance in India: A Randomized Controlled Trial," IZA Discussion Papers 14913, Institute of Labor Economics (IZA).

    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:eee:tefoso:v:182:y:2022:i:c:s0040162522004140. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.