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      Trend prediction and influencing factors of the production comparative advantage of China’s main apple-producing provinces

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          Abstract

          Introduction

          The apple industry is an essential industry to assist in rural revitalization. However, in recent years, the urbanization, industrialization, globalization and climate change have brought various challenges to the apple industry in China’s main apple-producing provinces. Given this, effectively identifying, enhancing on apple production comparative advantage (APCA) is imperative to safeguard the long-term sustainable development of China’s apple industry. This study aims to explore the evolutionary trends and influencing factors of APCA, and to provide quantitative support for the formulation of scientific and effective apple production policies.

          Methods

          In this paper, the APCA of China’s eight main apple-producing provinces from 2013 to 2022 was measured by using a aggregate comparative advantage index. The spatio-temporal dynamic evolution characteristics of APCA were revealed by adopted Arc GIS and kernel density estimation method. Second, the transfer probabilities of different types of APCA were predicted by empolyed traditional and spatial Markov chains. Finally, the driving mechanism of APCA is explored with the panel quantile model.

          Results

          1) The average value of APCA of the main producing provinces increased from 1.330 in 2013 to 1.419 in 2022. 2) The probabilities of provinces with low, primary and middle level of advantage jumping to the next level are 31.58%, 16.67% and 11.76%, respectively. When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.

          Conclusions

          1) Temporally, APCA shows a trend of slow growth, ups and downs. Spatially, APCA shows a distribution pattern of “west high, east low”. 2) APCA mainly shifted sequentially between neighbouring ranks. Besides, the change of APCA had significant spatial spillover effect, and highly advantage provinces featured more prominent proactive spillovers. 3) There is significant heterogeneity among the influencing factors.

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          Most cited references28

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          Trade Liberalisation and "Revealed" Comparative Advantage

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            How does technological innovation mitigate CO2 emissions in OECD countries? Heterogeneous analysis using panel quantile regression

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              • Record: found
              • Abstract: not found
              • Article: not found

              Examining the coordination between urbanization and eco-environment using coupling and spatial analyses: A case study in China

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                Author and article information

                Contributors
                Role: ConceptualizationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                18 October 2024
                2024
                : 19
                : 10
                : e0311912
                Affiliations
                [001] School of Economics and Management, Shandong Agricultural University, Taian, Shandong, China
                University of Southampton, MALAYSIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-8652-1696
                Article
                PONE-D-24-34178
                10.1371/journal.pone.0311912
                11488726
                39423223
                6c619f43-b7d0-4332-b162-9d484a4bdd02
                © 2024 Ning et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 August 2024
                : 26 September 2024
                Page count
                Figures: 6, Tables: 4, Pages: 18
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100012456, National Social Science Fund of China;
                Award ID: 23FJY170
                Award Recipient :
                This work was supported by National Social Science Fund of China [number 23FJY170]. The recipient of this funding is Zhang Fuhong. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Fruits
                Apples
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Fruits
                Physical Sciences
                Mathematics
                Probability Theory
                Markov Models
                People and Places
                Geographical Locations
                Asia
                China
                People and Places
                Population Groupings
                Professions
                Agricultural Workers
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Fruit Crops
                Biology and Life Sciences
                Agriculture
                Agronomy
                Horticulture
                Planting
                Biology and Life Sciences
                Agriculture
                Agricultural Methods
                Agricultural Irrigation
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information file.

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                Uncategorized

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