Modeling Consumer Purchase Intentions for Plant Factory Products Using Logistic Regression

Abstract

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.