In search of a model explaining organic food purchase behavior - Mahmudur Rahman, Khandoker; Mohd Noor, Nor Azila (Emerald Group Publishing Limited, 2016)
Purpose – The purpose of this paper is to explore the domain relevance of a comprehensive yet almost overlooked theoretical framework for studying organic food purchase behavior in a global context.This conceptual paper argues that there exists an apparently powerful model in health behavior domain that may readily be brought into organic food purchase behavior research.The paper argues for domain relevance and proposes that Montano and Kasprzyk’s integrated behavior model may readily be used in organic food behavior studies with some relevant modification. Design/methodology/approach – The paper follows an exploratory approach and shows how variables used in the past may be aggregated to the model in question. The challenge is addressed by following both the inductive and the deductive reasoning. Deductive reasoning calls for investigating whether such behavior may be classified as health behavior.Inductive reasoning calls for proving relevance of all the variables in the aforesaid model to the organic food research context.Findings – The paper concludes that the Montano and Kasprzyk’s model is theoretically relevant to the organic food behavior domain.However, it is observed that the domain-specific ope rationalization is necessary for further empirical studies. Research limitations/implications – Since the model was rarely tested empirically in predicting organic food purchase intention, the variable-specific relevance may not warrant the relevance of the whole model with intertwined relationships at the same time.Practical implications – The paper may pave a way toward further empirical research and may also explain the apparent intention-behavior gap as often reported in literature.Originality/value – The paper may provide a useful direction in future organic food purchase behavior studies by showing the domain relevance of an apparently powerful model, along with addition of some newer variables that may enrich the existing model.