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1 – 2 of 2Aslina Nasir and Yeny Nadira Kamaruzzaman
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.
Abstract
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.
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Ahmad Farhan Alshira’h, Malek Hamed Alshirah and Abdalwali Lutfi
This study aims to determine the impact of forensic accounting, probability of detections, tax penalties, government spending, tax justice and tax ethics on value-added tax (VAT…
Abstract
Purpose
This study aims to determine the impact of forensic accounting, probability of detections, tax penalties, government spending, tax justice and tax ethics on value-added tax (VAT) evasion.
Design/methodology/approach
The study uses partial least squares-structural equation modeling to examine the connection between tax sanction, probability of detection, tax ethics, tax justice, forensic accounting and government spending on VAT evasion based on 248 responses collected from the retail industry in Jordan.
Findings
The findings also demonstrate that there is a negative correlation between tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting, government spending and VAT evasion efficiency.
Practical implications
The results, considering forensic accounting and government expenditure considerations, may emphasize the importance of the tax sanction, probability of detection, tax ethics, adoption of tax justice in the public sector and tax authority. Additionally, the findings are important for regulators and decision-makers in announcing new laws and strategies for VAT evasion.
Social implications
It turns out that the tax authority and public sector can definitely improve their capacity to protect public funds and limit VAT evasion practices within SMEs by adopting increased tax sanctions, probability of detection, tax ethics, tax justice, forensic accounting and government spending.
Originality/value
Numerous studies have been conducted at the individual level in the context of income tax on the link between tax punishment, probability of detection, tax ethics, tax justice, forensic accounting and tax evasion. This study expands on the scant evidence of this connection to the retail business in the context of VAT avoidance. Additionally, it advances prior studies by integrating fresh elements, such as forensic accounting and government expenditure, that have never been considered in connection to VAT evasion in the retail sector.
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