Modeling consumer purchase intentions for plant factory products using logistic regression
A plant factory is a closed-growing system that allows farmers to control growing conditions and ensure safer vegetables without pesticides. However, to maximise the success of the plant factory, it is critical to discover the aspects regarded as relevant by consumers when purchasing vegetables and...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
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| Online Access: | http://journalarticle.ukm.my/25778/ http://journalarticle.ukm.my/25778/1/207-216%20-.pdf |
| _version_ | 1848816446903156736 |
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| author | Aimi Athirah Ahmad, Nik Rahimah Nik Omar, Nadiah Sa’at, Nur Hidayah Md Noh, Nurul Syahida Abu Bakar, |
| author_facet | Aimi Athirah Ahmad, Nik Rahimah Nik Omar, Nadiah Sa’at, Nur Hidayah Md Noh, Nurul Syahida Abu Bakar, |
| author_sort | Aimi Athirah Ahmad, |
| building | UKM Institutional Repository |
| collection | Online Access |
| description | A plant factory is a closed-growing system that allows farmers to control growing conditions and ensure safer vegetables without pesticides. However, to maximise the success of the plant factory, it is critical to discover the aspects regarded as relevant by consumers when purchasing vegetables and fruits. This study uses the logistic regression model to explore the market potential of curly kale and strawberries cultivated in plant factories by determining the factors influencing the consumer intention to purchase plant factory products. Data were collected through a structured face-to-face survey in two phases in 2022 (curly kale) and 2023 (strawberry). A total of n = 558 in phase one and n = 438 in phase two were randomly selected in urban areas across Malaysia. The result of this study explains that socio-demographic factors such as household income, plant factory consumers, lifestyle diets and consumer concerns about pesticide-free positively influence the consumer intention to purchase plant factory curly kale. Meanwhile, the logistic regression model also revealed that socio-demographic factors such as age and household size, selected attributes (taste and colour) and consumer knowledge of plant factories significantly influenced consumer intention to purchase plant factory strawberries. This study has practical consequences, particularly for individuals or businesses interested in introducing the notion of a plant factory in Malaysia. These models' significant factors can be employed to establish the value proposed to the client as well as the marketing strategy for plant factory producers. |
| first_indexed | 2025-11-15T01:06:01Z |
| format | Article |
| id | oai:generic.eprints.org:25778 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:06:01Z |
| publishDate | 2025 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org:257782025-08-15T03:46:46Z http://journalarticle.ukm.my/25778/ Modeling consumer purchase intentions for plant factory products using logistic regression Aimi Athirah Ahmad, Nik Rahimah Nik Omar, Nadiah Sa’at, Nur Hidayah Md Noh, Nurul Syahida Abu Bakar, A plant factory is a closed-growing system that allows farmers to control growing conditions and ensure safer vegetables without pesticides. However, to maximise the success of the plant factory, it is critical to discover the aspects regarded as relevant by consumers when purchasing vegetables and fruits. This study uses the logistic regression model to explore the market potential of curly kale and strawberries cultivated in plant factories by determining the factors influencing the consumer intention to purchase plant factory products. Data were collected through a structured face-to-face survey in two phases in 2022 (curly kale) and 2023 (strawberry). A total of n = 558 in phase one and n = 438 in phase two were randomly selected in urban areas across Malaysia. The result of this study explains that socio-demographic factors such as household income, plant factory consumers, lifestyle diets and consumer concerns about pesticide-free positively influence the consumer intention to purchase plant factory curly kale. Meanwhile, the logistic regression model also revealed that socio-demographic factors such as age and household size, selected attributes (taste and colour) and consumer knowledge of plant factories significantly influenced consumer intention to purchase plant factory strawberries. This study has practical consequences, particularly for individuals or businesses interested in introducing the notion of a plant factory in Malaysia. These models' significant factors can be employed to establish the value proposed to the client as well as the marketing strategy for plant factory producers. Penerbit Universiti Kebangsaan Malaysia 2025-03 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/25778/1/207-216%20-.pdf Aimi Athirah Ahmad, and Nik Rahimah Nik Omar, and Nadiah Sa’at, and Nur Hidayah Md Noh, and Nurul Syahida Abu Bakar, (2025) Modeling consumer purchase intentions for plant factory products using logistic regression. Journal of Quality Measurement and Analysis, 21 (1). pp. 207-216. ISSN 2600-8602 https://www.ukm.my/jqma/ |
| spellingShingle | Aimi Athirah Ahmad, Nik Rahimah Nik Omar, Nadiah Sa’at, Nur Hidayah Md Noh, Nurul Syahida Abu Bakar, Modeling consumer purchase intentions for plant factory products using logistic regression |
| title | Modeling consumer purchase intentions for plant factory products using logistic regression |
| title_full | Modeling consumer purchase intentions for plant factory products using logistic regression |
| title_fullStr | Modeling consumer purchase intentions for plant factory products using logistic regression |
| title_full_unstemmed | Modeling consumer purchase intentions for plant factory products using logistic regression |
| title_short | Modeling consumer purchase intentions for plant factory products using logistic regression |
| title_sort | modeling consumer purchase intentions for plant factory products using logistic regression |
| url | http://journalarticle.ukm.my/25778/ http://journalarticle.ukm.my/25778/ http://journalarticle.ukm.my/25778/1/207-216%20-.pdf |