Towards a Multi-User Experience Data-Driven Design Framework for Sustainable Smart Take-Away Food Packaging

Abstract Smart packaging transcends traditional packaging’s basic functions by meeting emerging consumer expectations for quality and sustainability. COVID-19 has notably increased take-away orders, spotlighting the need for sustainable food packaging. By incorporating smart features, packaging usability is enhanced, and the likelihood of disposal due to obsolescence is reduced. Moreover, smart packaging acceptance relies on consumer values. To address these evolving needs, designers are encouraged to embrace a user-centered design (UCD) approach to develop sustainable smart take-away packaging. However, a review of literature reveals a gap in design support systems that could assist designers in this endeavor. Interviews with packaging designers outlined framework requirements, leading to the creation of SUSTAIN-MULTI-UCD. This framework advocates for a multi-UCD approach tailored for sustainable smart take-away packaging development. The innovative use of big data analytics in this context enables gathering diverse user data to help enhance user experience. The SUSTAIN-MULTI-UCD contribution lies in applying big data analytics to the data-driven UCD of sustainable smart take-away packaging, offering insights that could be beneficial across various food packaging applications. Furthermore, innovations in the framework’s data-driven approaches, such as the application of topic modelling and text classification, identifies user requirements, and furthermore guides the designer on how to meet these needs.

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Publication Details

Published
2024-08-25
DOI
https://doi.org/10.1115/detc2024-143104
Citations
1
Primary Topic
Consumer Packaging Perceptions and Trends
Type
article
Field-Weighted Citation Impact
0.44
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article

Towards a Multi-User Experience Data-Driven Design Framework for Sustainable Smart Take-Away Food Packaging

Philip Farrugia, Tamasine Camilleri, Paul Refalo, Marvin K. Bugeja
1 citations
Consumer Packaging Perceptions and Trends
0.44
article

Towards a Multi-User Experience Data-Driven Design Framework for Sustainable Smart Take-Away Food Packaging

Philip Farrugia, Tamasine Camilleri, Paul Refalo, Marvin K. Bugeja
article en
1 citations

Abstract

Abstract Smart packaging transcends traditional packaging’s basic functions by meeting emerging consumer expectations for quality and sustainability. COVID-19 has notably increased take-away orders, spotlighting the need for sustainable food packaging. By incorporating smart features, packaging usability is enhanced, and the likelihood of disposal due to obsolescence is reduced. Moreover, smart packaging acceptance relies on consumer values. To address these evolving needs, designers are encouraged to embrace a user-centered design (UCD) approach to develop sustainable smart take-away packaging. However, a review of literature reveals a gap in design support systems that could assist designers in this endeavor. Interviews with packaging designers outlined framework requirements, leading to the creation of SUSTAIN-MULTI-UCD. This framework advocates for a multi-UCD approach tailored for sustainable smart take-away packaging development. The innovative use of big data analytics in this context enables gathering diverse user data to help enhance user experience. The SUSTAIN-MULTI-UCD contribution lies in applying big data analytics to the data-driven UCD of sustainable smart take-away packaging, offering insights that could be beneficial across various food packaging applications. Furthermore, innovations in the framework’s data-driven approaches, such as the application of topic modelling and text classification, identifies user requirements, and furthermore guides the designer on how to meet these needs.

University of Malta (MT)
Responsible consumption and production
Openalex Percentile: Top 26%
Consumer Packaging Perceptions and Trends
0.44
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Towards a Multi-User Experience Data-Driven Design Framework for Sustainable Smart Take-Away Food Packaging — Philip Farrugia, Tamasine Camilleri, et al. · (2024) | TGRS Research Map | TGRS