A conjoint analysis to consumer choice in Brazil: Defining device attributes for recognizing customized foods characteristics. (July 2018)

• Record Type: Journal Article
• Authors: Calegari, L.P.; Barbosa, J.; Marodin, G.A.; Fettermann, D.C.
• Is Part Of: Food research international. Volume 109(2018)
• Page Start: 1
• Page End: 13
• Publication Date: 2018-07
• Subjects: South America -- Customer -- Conjoint analysis -- Food technologies -- Customized product -- Nutritional label; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2018.03.080
• Languages: English
• ISSNs: 0963-9969

Abstract

Abstract: the availability of information about food products may be an essential factor in the consumer's value perception in their purchasing decision. As the food product becomes personalized, the customization of this information becomes complex due to the possible combinations of product components. The use of smart technology in devices is one way to provide customers with customized food information. In the following research five attributes were identified in the composition of these devices: (A) portability; (B) precision; (C) diet customization; (D) food quality analysis; and (E) price. This study aims to identify the appropriate combination of possible functionalities or attributes that must be present in a device in order to detect the food composition of customized foods and their relation to market characteristics. One experiment used fractional factorial project to present the attributes in the form of scenarios following the Choice-Based Conjoint Analysis (CBCA) method. The data collection was done using survey methodology, through online questionnaire, with some 303 Brazilian respondents. So, the Logistic Regression was applied to data analysis. The moderating variables—gender, age, gluten restriction, lactose restriction and other restrictions—were also added to verify potential interactions with the primary attributes. From the results obtained, it was possible to observe higher significance for the primary attributes of diet personalization and quality food analyzes function. Our study contributes to the literature by enhancing the understanding about what the attributes should be in a technological device that has the purpose of recognizing food characteristics and is capable of generating information about customized food products. Furthermore, this device can enabler the production of mass customized food with the nutritional labels for each possible combination. Graphical abstract: Highlights: Smart technology is one way to provide customers with customized food information. Factorial design was used with scenarios following the Choice-Based Conjoint Analysis. To direct investments in devices that has propose of recognizing food characteristics.