A conjoint analysis to identify the attributes of a device to characteristics recognition in customized food products
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Abstract The possibility of combining food ingredients at each meal makes it difficult to recognize the characteristics of personalized foods. The use of devices with the Internet of Things (IoT) technologies is an alternative for customers to access customized food information. Five main attributes present in the composition of such devices, aiming ingredients recognition in customized meals, were considered in this study: (A) portability, (B) precision, (C) diet customization, (D) food quality control and (E) price. This study aims to identify the combination of such value generating attributes in a device of food characteristics recognition in customized foods. A fractional factorial design 25-1 was used to display the device characteristics, in the form of scenarios, following the joint analysis method based on choice. For data collection, a survey was carried out with a sample of 303 respondents. Gender moderation and food restriction variables were also analyzed. The results present greater significance for the attributes of measurement accuracy and quality analysis. As contributions, this study presents information for investments targeting in research for the manufacturing of a technological device aiming the recognition of characteristics of a mass-modified food product.