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Title: Consumer's adoption of virtual reality technologies for marine conservation: motivational and technology acceptance perspectives
Authors: Yuen, Kum Fai
Chua, Jessana
Li, Kevin X.
Wang, Xueqin
Keywords: Engineering::Civil engineering
Issue Date: 2022
Source: Yuen, K. F., Chua, J., Li, K. X. & Wang, X. (2022). Consumer's adoption of virtual reality technologies for marine conservation: motivational and technology acceptance perspectives. Technological Forecasting and Social Change, 182, 121891-.
Journal: Technological Forecasting and Social Change
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.
ISSN: 0040-1625
DOI: 10.1016/j.techfore.2022.121891
Rights: © 2022 Elsevier Inc. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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