The impact of smart aquaculture environmental characteristics and system quality on acceptance intentions through value recognition of the fisheries industry in the era of AI

So-Jeong Jang (), Yuan-Yuan Liu (), Jing Liu () and Ha-Kyun Kim ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 2, 1348-1358

Abstract: The global fisheries industry plays a critical role in providing essential nutrients and animal protein to humanity. However, the industry is undergoing a rapid paradigm shift due to technological advancements and demographic changes, particularly the aging population in fishing villages. This study aims to analyze how smart aquaculture environmental characteristics and system quality in the AI era influence the acceptance intention of these technologies through the recognition of the value of the fishery industry. This study employs an empirical approach to assess the impact of smart aquaculture on the fisheries sector. The research utilizes Smart PLS 4.0 for statistical analysis, drawing data from individuals engaged in or interested in the fishery industry. The study focuses on evaluating the relationship between smart aquaculture environmental characteristics, system quality, value perception of the fisheries industry, and acceptance intention of AI-driven technologies. The results indicate that the higher the impact of smart aquaculture environmental characteristics and system quality on the value perception of the fisheries industry, the stronger the acceptance intention of AI-driven technologies. This confirms that enhancing technological infrastructure and system efficiency significantly contributes to the greater adoption of smart aquaculture solutions. The study highlights the transformative role of AI-based automation and ICT convergence technology in the fisheries industry. As smart aquaculture continues to evolve, its adoption is influenced by how stakeholders perceive its value. The findings emphasize that technological advancements must be accompanied by efforts to enhance users’ trust and understanding of AI-driven systems. The study provides valuable insights for policymakers, stakeholders, and industry professionals. By leveraging system quality and social influence factors, stakeholders can enhance the adoption of smart aquaculture technologies. Addressing challenges such as an aging workforce and improving fishery production efficiency through AI-driven smart systems will contribute to the long-term sustainability and competitiveness of the fisheries industry.

Keywords: Acceptance intention opportunity capture; Process improvement; Smart aquaculture environmental characteristics; Smart aquaculture system quality; Value recognition of fisheries. (search for similar items in EconPapers)
Date: 2025
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