Modeling purchase intention towards edible bird's nest products among Malaysians
Interests in the nutraceutical or food supplement are growing around Asia in response to health and beauty concerns. Nutraceutical supplements seem to dominate the Malaysian market as the awareness of health conscious arise. The consumptions of these nutraceutical products are to cover insufficient...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Faculty of Food Science and Technology, Universiti Putra Malaysia
2018
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Online Access: | http://psasir.upm.edu.my/id/eprint/77404/1/6%20-%20IFRJ18298.R1%20edited_1.pdf http://psasir.upm.edu.my/id/eprint/77404/ http://www.ifrj.upm.edu.my/25%20(08)%202018%20supplementary%202/6%20-%20IFRJ18298.R1%20edited_1.pdf |
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Summary: | Interests in the nutraceutical or food supplement are growing around Asia in response to health and beauty concerns. Nutraceutical supplements seem to dominate the Malaysian market as the awareness of health conscious arise. The consumptions of these nutraceutical products are to cover insufficient nutrient in their diet intakes. Edible bird nest (EBN) is made from saliva produced by the male’s swiftlet and been consumed as a health supplement due to their high nutritional value. Despite an ever-growing number of EBN products and options available in the market, there are still fewer purchasers among Malaysian consumers as compared to other countries. This study aims to determine factors that influence consumers’ intention in purchasing EBN products. The number of complete response from the survey were 1310 samples. The questionnaire includes nine variables that are determined from the theory of planned behavior and marketing mix. Exploratory factor analysis with promax rotation is conducted to remove items with factor loading less than 0.5 and confirmatory factor analysis is constructed to measure the fitness of the model so that it can be used in predictive models. The three popular classification algorithms from predictive models which are decision tree, logistic regression, and artificial neural network will be used to analyze the dataset and determined the best model building. These comparisons are highly evaluated based on the prediction performance and it does not conclude that one method will be superior to other predictive methods. Results showed logistic regression outer perform other classifiers to develop the purchase intention model. There are five variables identified which consist of age, gender, price, accessibility and halal authorize. This study provides an input of consumers’ concern and interest that can be used as a strategic tool and give special attention to those elements to promote the EBN products. |
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