Quantitative Forecasting and Development Pathways of the Linkages between the Shellfish Industry and Fishermen's Income in Liaoning Province: An Empirical Analysis Based on the GM(1,1) Model
DOI:
https://doi.org/10.5281/zenodo.20605779Keywords:
Shellfish industry, Fishermen's income, Grey prediction, GM(1,1) model, Liaoning Province, Fishery economy, Industrial structureAbstract
This study takes Liaoning Province, a core fishery region in Northeast China, as a case study to quantify the contribution and long-term impact mechanisms of the shellfish aquaculture industry on regional fishermen's household business income. Addressing the typical characteristics of limited data samples and incomplete system information, the research employs the GM(1,1) prediction model from grey system theory to independently model and forecast shellfish production and fishermen's household business income for the period 2010-2033. The empirical results indicate: using the original, non-translated data, the Liaoning shellfish production prediction model passed the ratio test, with a development coefficient (a) of -0.01885, forecasting a sustained and steady expansion of the industry scale, with production projected to reach approximately 3.19 million tons by 2033. The fishermen's household business income series, due to initial high volatility, required the application of a translation constant C=265,410 to establish a viable GM(1,1) model, which yielded a development coefficient (a) of -0.02986, also predicting a long-term growth trend for income. Model accuracy evaluation showed that the shellfish production forecast had a mean relative error of 4.839%, a posterior variance ratio C of 0.502, and a small error probability P of 0.786, achieving an accuracy grade between "qualified" and "good". Although the income prediction model had a higher mean relative error (20.125%), its posterior variance ratio C was 0.272, and the small error probability P was 1, indicating a robust trend in the forecasted sequence. Integrating a literature review on Liaoning's fishery industrial structure—where the primary sector dominates but the secondary and tertiary sectors' shares are gradually increasing—and fishermen's income composition—where household business income is the core pillar—this study further elucidates the transmission mechanisms through which the shellfish industry influences fishermen's income via multiple pathways, including direct sales, value-added processing, and linkages with recreational fisheries. Finally, based on the forecast results and the current industrial landscape, the study proposes countermeasures and suggestions, such as promoting intensive and ecological shellfish aquaculture, deepening aquatic product processing, fostering industrial integration, and strengthening scientific, technological, and policy support. These recommendations aim to provide a theoretical basis and decision-making reference for the sustainable and inclusive development of the marine fishery economy in Liaoning Province and similar regions in China.
Downloads
References
Zhang Y Z , Xue C , Chen W G .A comparative study on the measurement of sustainable development of marine fisheries in China[J].Ocean & coastal management, 2024, 247(Jan.):106911.1-106911.9.DOI:10.1016/j.ocecoaman.2023.106911.
Kong F , Cui W .Spatial-temporal evolution and drivers of ecological sustainability of coastal fisheries in China[J].Ocean & Coastal Management, 2024, 258(000).DOI:10.1016/j.ocecoaman.2024.107403.
Chang Y C , Zhang X , Khan M I .The impact of the COVID-19 on China's fisheries sector and its countermeasures[J].Ocean & Coastal Management, 2022, 216:105975-.DOI:10.1016/j.ocecoaman.2021.105975.
Rahman M S , Toiba H , Huang W C .The Impact of Climate Change Adaptation Strategies on Income and Food Security: Empirical Evidence from Small-Scale Fishers in Indonesia[J].Sustainability, 2021, 13(14):7905.DOI:10.3390/su13147905.
Wang P , Mendes I .Assessment of Changes in Environmental Factors Affecting Aquaculture Production and Fisherfolk Incomes in China between 2010 and 2020[J].Fishes (MDPI AG), 2022, 7(4).DOI:10.3390/fishes7040192.
Wang Y , Yang Y , Hu X .The evolution and effectiveness of China's marine carbon sink fishery policies[J].Ocean & coastal management, 2024(Dec.):259.DOI:10.1016/j.ocecoaman.2024.107470.
Xu J , Han L , Yin W .Research on the ecologicalization efficiency of mariculture industry in China and its influencing factors[J].Marine policy, 2022(Mar.):137.DOI:10.1016/j.marpol.2021.104935.
Wang B , Han L , Zhang H .Analysis on the structure effect of marine fishery total factor productivity under high-quality development in China[J].PLOS ONE, 2021, 16.DOI:10.1371/journal.pone.0259853.
Su M , Cheng K , Kong H .Spatial and Temporal Differentiation of the Coordination and Interaction among the Three Fishery Industries in China from the Value Chain Perspective[J].Fishes, 2023, 8(5):21.DOI:10.3390/fishes8050232.
Riantini M , Mardiharini M ,Saptana,et al.Livelihood vulnerability household fishermen household due to climate change in Lampung Province, Indonesia[J].PLOS ONE, 2024, 19(12).DOI:10.1371/journal.pone.0315051.
Wang G , Feng Y .Assessment and prediction of net carbon emission from fishery in Liaoning Province based on eco-economic system simulation[J].Journal of cleaner production, 2023, 419(Sep.20):138080.1-138080.10.DOI:10.1016/j.jclepro.2023.138080.
Wang P , Mendes I .Assessment of Changes in Environmental Factors Affecting Aquaculture Production and Fisherfolk Incomes in China between 2010 and 2020[J].Fishes (MDPI AG), 2022, 7(4).DOI:10.3390/fishes7040192.
Li T , Nie J , Qiu G ,et al.Time Series Forecasting via an Elastic Optimal Adaptive GM(1,1) Model[J].Electronics (2079-9292), 2025, 14(10).DOI:10.3390/electronics14102071.
Wang B , Li H , Sun P ,et al.The effects and paths of regional industrial structure transformation on the fluctuation and quality of the marine fisheries economy in China[J]. 2023.DOI:10.3389/fmars.2022.944630. .
Wahyudi F .Analysis of the Potential of Fishermen's Communities in Increasing Income In Payangan, Sumberejo Village, Ambulu District, Jember Regency[J].PROCEEDING INTERNATIONAL CONFERENCE ON ECONOMICS, BUSINESS AND INFORMATION TECHNOLOGY (ICEBIT), 2023, 4:693-711.DOI:10.31967/prmandala.v4i0.811.
Li T , Nie J , Qiu G ,et al.Time Series Forecasting via an Elastic Optimal Adaptive GM(1,1) Model[J].Electronics (2079-9292), 2025, 14(10).DOI:10.3390/electronics14102071.
ningsih a r , indah p n , fitriana n h i .analisis nilai tambah dan optimasi keuntungan produksi olahan kerang kampak (studi kasus pada umkm bunda surabaya)[j].agroteksos, 2024, 34(2):249.doi:10.29303/agroteksos.v34i2.1108.
Maghfira R , Maulina I , Grandiosa R ,et al.Analysis of Factors Affecting Fishermen's Income in Darmaraja District, Sumedang Regency, Indonesia[J].Asian Journal of Fisheries and Aquatic Research, 2023, 25(3):156-165.DOI:10.9734/ajfar/2023/v25i3675.
Rajabhat S .Factor Effecting the Sustainable Income Generation of the Value Added Products of Local Fishery in Ranong Province, Thailand[J].International journal of health sciences, 2022.DOI:10.53730/ijhs.v6ns2.5193.
Wang B , Han L , Zhang H .The Impact of Regional Industrial Structure Upgrading on the Economic Growth of Marine Fisheries in China—The Perspective of Industrial Structure Advancement and Rationalization[J].Frontiers in Marine Science, 2021, 8(8):693804.DOI:10.3389/fmars.2021.693804.
Lao T , Chen X , Zhu J .The Optimized Multivariate Grey Prediction Model Based on Dynamic Background Value and Its Application[J].Complexity, 2021, 2021.DOI:10.1155/2021/6663773.
Wang B , Han L , Zhang H .The Impact of Regional Industrial Structure Upgrading on the Economic Growth of Marine Fisheries in China—The Perspective of Industrial Structure Advancement and Rationalization[J].Frontiers in Marine Science, 2021, 8(8):693804.DOI:10.3389/fmars.2021.693804.
Batr E ,Aydn, Theodorou J A ,et al.Mytilus galloprovincialis's role in Integrated Multi-Trophic Aquaculture (IMTA): A comprehensive review[J].Journal of the World Aquaculture Society, 2025, 56(2).DOI:10.1111/jwas.70013.
D'Orbcastel E R , Lutier M , Le Floc'H E ,et al.Marine ecological aquaculture: a successful Mediterranean integrated multi-trophic aquaculture case study of a fish, oyster and algae assemblage[J].Aquaculture International, 2022, 30(6):3143-3157.DOI:10.1007/s10499-022-00953-0.
Teh L S L , Teh L C L , Sumaila U R ,et al.Poverty line income and fisheries subsidies in developing country fishing communities[J].npj Ocean Sustainability, 2023.DOI:10.21203/rs.3.rs-2731208/v1.
Xu J , Han L , Yin W .Research on the ecologicalization efficiency of mariculture industry in China and its influencing factors[J].Marine policy, 2022(Mar.):137.DOI:10.1016/j.marpol.2021.104935.
Wang Y , Yang Y , Hu X .The evolution and effectiveness of China's marine carbon sink fishery policies[J].Ocean & coastal management, 2024(Dec.):259.DOI:10.1016/j.ocecoaman.2024.107470.
Wang P , Mendes I .Assessment of Changes in Environmental Factors Affecting Aquaculture Production and Fisherfolk Incomes in China between 2010 and 2020[J].Fishes (MDPI AG), 2022, 7(4).DOI:10.3390/fishes7040192.
Li B , Liu Z .Measurement and Evolution of High-quality Development Level of Marine Fishery in China[J].Chinese Geographical Science, 2022.DOI:10.1007/s11769-022-1263-7.
Zhang Y Z , Xue C , Chen W G .A comparative study on the measurement of sustainable development of marine fisheries in China[J].Ocean & coastal management, 2024, 247(Jan.):106911.1-106911.9.DOI:10.1016/j.ocecoaman.2023.106911.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Zhu shenghu, Chen tian, Liu jiawen, Gong mali, Zhang kaixing (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
