Abstract:
Food product labels play a crucial role in conveying information from food producers to consumers. As consumers recognize the significance of label information, the need to access complete informationbecomesparamountsothattheycanmakethebestchoicesbasedontheirdifferenthealthgoals.
Health considerations vary from person to person; some have restrictions from doctors due to health conditions, some individuals are sensitive to allergenic foods, others prioritize maintaining a stable weight, and some are already overweight, aiming to decrease their weight, while others are slim and wish to increase their weight. Additionally, diverse beliefs and cultural practices influence dietary choices.
Due to this wide range of considerations, information on labels should be sufficient for all individuals, enabling them to make informed decisions when purchasing or consuming food.
This research project aims to address challenges related to the availability, completeness, and findability of information on food product labels. These challenges arise from the limitations of package size, which cannot accommodate all necessary information, and findability issues resulting from attempting to include too much information on small package sizes, leading to information overload. The research seeks to find innovative solutions to improve food product labels and enhance consumers’ ability to access complete information for their individual health considerations.
Recognizing the global nature of the issue, data was collected from people located in different locations worldwide to ensure diverse perspectives. Emphasizing user needs, a Human-Centered Design approach was utilized, highlighting challenges arising when information is missing. Integrating this global perspective and Human-Centered Design approach, the research aims to contribute to addressing challenges in food labeling and fostering a universally applicable solution that aligns with consumers’ diverse needs.
This work contributes to advancing the application of Augmented Reality (AR) technology in food retail environments. The research advances our understanding of how AR technology can be developed to enhance the availability of information on labels, fostering informed consumer choices.
In this report, I utilized the language model GPT-3.5 (OpenAI, 2023) to generate ideas and arguments, as well as for grammar and spelling corrections. I did not use GPT-3.5 to compose entire paragraphs or chapters. Instead, I employed it solely for generating suggestions that I subsequently evaluated and incorporated into my work.
