Analysis of Factors Affecting Consumer Payment Preferences for Organic Agricultural Products: Application of Structural Equation Modeling

Document Type : Research Article

Authors

• H. Aghasafari ¹
• A.R. Karbasi ¹
• H. Mohammadi ¹
• R. Calisti ²

¹ Ferdowsi University of Mashhad

² Italy

https://doi.org/10.22067/jead2.v33i4.76582

Abstract

Introduction: The environmental impacts of pesticides, genetically modified organisms and other chemicals used to increase agricultural production have raised consumers' concerns about the quality and safety of agricultural products. And now, with the increase of environmental awareness, it has criticized modern agricultural activities. These factors have encouraged consumers to consume organic agricultural products. Way of producing the organic products can increase the production costs and, finally, increase the total price of these products. So, consumers should pay more for these products than the inorganic ones. In spite of higher prices of these products, consumers are increasingly tending to consume organic products. So that, consumers tend to pay more for better and more organic and safe agricultural products. Several factors influence the consumer payment preferences for organic products. In this study, these factors are classified into four groups and their impacts on consumer preferences are examined.
Materials and Methods: This study has used the Structural Equation Modeling (SEM). Structural Equation Modeling (SEM) is a powerful collection of multivariate analysis techniques, which specifies the relationships between variables through the use of two main sets of models: Measurement model and Structural model. Measurement model tests the accuracy of proposed measurements by assessing relationships between latent variables and their respective indicators. The structural model drives the assessment of the hypothesized relationships between the latent variables, which allow testing the statistical hypotheses for the study. Additionally, SEM considers the modeling of interactions, nonlinearities, correlated independents, measurement error, correlated error terms, and multiple latent independents that each one is measured by multiple indicators. Unlike conventional analysis, SEM allows the inclusion of latent variables into the analysis and it is not limited to relationships among observed variables and constructs. It allows the study to measure any combination of relationships by examining a series of dependent relationships simultaneously while considering potential errors of measurement among all variables. SEM has several advantages over conventional analysis, including greater flexibility regarding assumptions (particularly allowing interpretation even in the face of multicollinearity). SEM allows the use of confirmatory factor analysis to reduce measurement error by testing multiple indicators per latent variable while offering superior model visualization through its graphical modeling interface. Structural Equation Modeling include six steps (data collection, model specification, identification, estimation, evaluation and modification). In the present study, the variables including marketing factors, awareness and knowledge, demographic characteristics and attitudes towards organic products are considered as latent variables that the relationship of these variables with the payment preferences is investigated. In order to collect required data, a researcher-made questionnaire and simple random sampling method has been used.
Results and Discussion: Results indicate that given the significance of factor loadings, the indicators (observed variables) such as packaging, brand, advertising, discounts and shopping incentives, familiarity with different types of products, way to get information, familiarity with organic agricultural product stores have the required accuracy to measure latent variables. Regarding the model fitting indexes and being model values in the acceptable range, we can say that the measurement and structural models fit well with the data. The results of structural model and hypothesis testing show that awareness and knowledge, demographic characteristics, attitude towards organic products have a significant effect (0.27, 0.59 and 0.21, respectively) on consumer payments preferences. In other words, increasing the awareness of consumer about organic products, increasing household size and income, the positive attitude of consumers towards the characteristics of organic products would increase consumer payments preferences. Also, marketing factors have a significant effect (0.68) on the attitude toward organic products. So that, marketing factors including packaging, brand, advertising and discounts and shopping incentives have a positive effect on the attitude toward organic products. Therefore, hypotheses 2 through 5 are supported.
Conclusion: The Findings indicate that increasing the awareness of consumer about organic agricultural products, increasing household size and income, the positive attitude of consumers towards the characteristics of organic agricultural products will increase consumer payments preferences. Therefore, it is suggested that the relevant authorities take serious action to inform about the properties and nutritional value of organic agricultural products, the differences in the labels of food products, and the existing stores supplying of organic products. Also, it is recommended that the numbers of organic supply stores are boosted, especially in areas where high-income people live.

Keywords

• Organic agricultural products
• Payment preferences
• Structural equation modeling

20.1001.1.20084722.1398.33.4.2.4

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