Purpose
The purpose of this paper is to investigate the influence of halal concern as well as emotional and epistemic values on consumer behaviour in the choice and purchase of halal-certified food supplies.
Design/methodology/approach
This study used a quantitative methodology of convenience sampling to collect survey data from 1,550 Muslim respondents in Malaysia. It also employed multiple regressions by covariance-based structural equation modelling in the data analysis as well as in the validation of the proposed model.
Findings
The empirical results showed that the importance of halal certification had the highest impact on consumer choice behaviour, particularly in the purchase of halal-certified food supplies. Also, epistemic and emotional values were both statistically significant in terms of their influence on the consumer decision-making process.
Research limitations/implications
The results emphasize the importance of enhancing the hedonic (halal concern and emotional value) aspect as a way for the halal food industries to obtain an added value advantage for their products and services.
Originality/value
This paper is the first to employ an empirical approach to consider the halal sentiment as a determinant of consumer purchasing behaviour in the context of halal-certified food supplies.
Missing data is a common problem in hydrological studies; therefore, data reconstruction is critical, especially when it is crucial to employ all available resources, even incomplete records. Furthermore, missing data could have an impact on statistical analysis results, and the amount of variability in the data would not be fittingly anticipated. As a result, this study compared the performance of three imputation methods in predicting recurrence in streamflow datasets: robust random regression imputation (RRRI), k-nearest neighbours (k-NN), and classification and regression tree (CART). Furthermore, entire historical daily streamflow data from 2012 to 2014 (as training dataset) were utilised to assess and validate the effectiveness of the imputation methods in addressing missing streamflow data. Following that, all three methods coupled with multiple linear regression (MLR), were used to restore streamflow rates in Malaysia's Langat River Basin from 1978 to 2016. The estimation techniques effectiveness was evaluated using metrics inclusive of the Nash-Sutcliffe efficiency coefficient (CE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE). The results confirmed that RRRI coupled with MLR (RRRI-MLR) had the lowest RMSE and MAPE values, outperforming all other techniques tested for filling missing data in daily streamflow datasets. This indicates that the RRRI-MLR is the best method for dealing with missing data in streamflow datasets. Doi: 10.28991/cej-2021-03091747 Full Text: PDF
Background: COVID-19 outbreak is being studied throughout the world. Adding more analysis to date strengthening the information about the illness. Here, we analysis the data of Malaysian Ministry of Health from February 15, 2020 until January 10, 2021 was analysed using linear regression model statistical analysis with aim to forecast the trend.
Materials and Methods: This study reviewed the data by Malaysia Ministry of Health from February 15, 2020, until January 10, 2021. Linear regression model statistical analysis was used for predictive modelling. The forecasting of the linear trend of the Covid-19 outbreak prediction is purposed to estimate the number of confirm cases according to the number of recoveries patients.
Results: Malaysia is currently anticipating another lockdown restriction as new confirmed case of COVID-19 hit new record high. The cumulative confirmed Covid-19 cases in MCO predicted a sharp increase. At the first of March, 2021, the predicted cumulative confirmed Covid-19 cases are 319,477 cases.
Conclusions: Covid-19 cases projected to 315766 by end of February 2021 with 3000- 4000 daily cases predicted. Initiative and proactive measurement by Malaysian government hopefully can reduce the number of cases and flatten the infection curve.
Bangladesh Journal of Medical Science Vol.20(3) 2021 p.504-510
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