{"title":"未来金枪鱼上岸量是否达到目标?使用季节性 ARIMA 模型预测马来西亚金枪鱼上岸量","authors":"Aslina Nasir, Yeny Nadira Kamaruzzaman","doi":"10.1108/ijse-03-2023-0233","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>This study was conducted to forecast the monthly number of tuna landings between 2023 and 2030 and determine whether the estimated number meets the government’s target.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The ARIMA and seasonal ARIMA (SARIMA) models were employed for time series forecasting of tuna landings from the Malaysian Department of Fisheries. The best ARIMA (p, d, q) and SARIMA(p, d, q) (P, D, Q)<sup>12</sup> model for forecasting were determined based on model identification, estimation and diagnostics.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>SARIMA(1, 0, 1) (1, 1, 0)<sup>12</sup> was found to be the best model for forecasting tuna landings in Malaysia. The result showed that the fluctuation of monthly tuna landings between 2023 and 2030, however, did not achieve the target.</p><!--/ Abstract__block -->\n<h3>Research limitations/implications</h3>\n<p>This study provides preliminary ideas and insight into whether the government’s target for fish landing stocks can be met. Impactful results may guide the government in the future as it plans to improve the insufficient supply of tuna.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>The outcome of this study could raise awareness among the government and industry about how to improve efficient strategies. It is to ensure the future tuna landing meets the targets, including increasing private investment, improving human capital in catch and processing, and strengthening the system and technology development in the tuna industry.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This paper is important to predict the trend of monthly tuna landing stock in the next eight years, from 2023 to 2030, and whether it can achieve the government’s target of 150,000 metric tonnes.</p><!--/ Abstract__block -->","PeriodicalId":47714,"journal":{"name":"INTERNATIONAL JOURNAL OF SOCIAL ECONOMICS","volume":"9 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Does future tuna landing stock meet the target? Forecasting tuna landing in Malaysia using seasonal ARIMA model\",\"authors\":\"Aslina Nasir, Yeny Nadira Kamaruzzaman\",\"doi\":\"10.1108/ijse-03-2023-0233\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3>Purpose</h3>\\n<p>This study was conducted to forecast the monthly number of tuna landings between 2023 and 2030 and determine whether the estimated number meets the government’s target.</p><!--/ Abstract__block -->\\n<h3>Design/methodology/approach</h3>\\n<p>The ARIMA and seasonal ARIMA (SARIMA) models were employed for time series forecasting of tuna landings from the Malaysian Department of Fisheries. The best ARIMA (p, d, q) and SARIMA(p, d, q) (P, D, Q)<sup>12</sup> model for forecasting were determined based on model identification, estimation and diagnostics.</p><!--/ Abstract__block -->\\n<h3>Findings</h3>\\n<p>SARIMA(1, 0, 1) (1, 1, 0)<sup>12</sup> was found to be the best model for forecasting tuna landings in Malaysia. The result showed that the fluctuation of monthly tuna landings between 2023 and 2030, however, did not achieve the target.</p><!--/ Abstract__block -->\\n<h3>Research limitations/implications</h3>\\n<p>This study provides preliminary ideas and insight into whether the government’s target for fish landing stocks can be met. Impactful results may guide the government in the future as it plans to improve the insufficient supply of tuna.</p><!--/ Abstract__block -->\\n<h3>Practical implications</h3>\\n<p>The outcome of this study could raise awareness among the government and industry about how to improve efficient strategies. 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Does future tuna landing stock meet the target? Forecasting tuna landing in Malaysia using seasonal ARIMA model
Purpose
This study was conducted to forecast the monthly number of tuna landings between 2023 and 2030 and determine whether the estimated number meets the government’s target.
Design/methodology/approach
The ARIMA and seasonal ARIMA (SARIMA) models were employed for time series forecasting of tuna landings from the Malaysian Department of Fisheries. The best ARIMA (p, d, q) and SARIMA(p, d, q) (P, D, Q)12 model for forecasting were determined based on model identification, estimation and diagnostics.
Findings
SARIMA(1, 0, 1) (1, 1, 0)12 was found to be the best model for forecasting tuna landings in Malaysia. The result showed that the fluctuation of monthly tuna landings between 2023 and 2030, however, did not achieve the target.
Research limitations/implications
This study provides preliminary ideas and insight into whether the government’s target for fish landing stocks can be met. Impactful results may guide the government in the future as it plans to improve the insufficient supply of tuna.
Practical implications
The outcome of this study could raise awareness among the government and industry about how to improve efficient strategies. It is to ensure the future tuna landing meets the targets, including increasing private investment, improving human capital in catch and processing, and strengthening the system and technology development in the tuna industry.
Originality/value
This paper is important to predict the trend of monthly tuna landing stock in the next eight years, from 2023 to 2030, and whether it can achieve the government’s target of 150,000 metric tonnes.
期刊介绍:
The International Journal of Social Economics publishes original and peer-reviewed theoretical and empirical research in the field of social economics. Its focus is on the examination and analysis of the interaction between economic activity, individuals and communities. Social economics focuses on the relationship between social action and economies, and examines how social and ethical norms influence the behaviour of economic agents. It is inescapably normative and focuses on needs, rather than wants or preferences, and considers the wellbeing of individuals in communities: it accepts the possibility of a common good rather than conceiving of communities as merely aggregates of individual preferences and the problems of economics as coordinating those preferences. Therefore, contributions are invited which analyse and discuss well-being, welfare, the nature of the good society, governance and social policy, social and economic justice, social and individual economic motivation, and the associated normative and ethical implications of these as they express themselves in, for example, issues concerning the environment, labour and work, education, the role of families and women, inequality and poverty, health and human development.