Over the past decades, technological advancements have made everyday objects smart, and naturally, these developments have reached the packaging industry too. Packaging equipped with sensors and chips can provide new experiences to its customers and one of the technologies that has shown its potential to contribute to this is Near Field Communication (NFC). Previous implementations of NFC in product packaging were limited to higher-end products. However, production costs of the chips have dropped substantially and has led to more adaptations. With more and more products using the technology, more consumers will get exposed to NFC- enabled packaging. Generation Z is one of those consumer groups. Thus, this study aimed to explore how NFC technology embedded in product packaging can influence the user experience for Generation Z and their relationships with brands. To achieve this goal, a qualitative approach was implemented, and 5 semi-structured interviews were conducted to get an understanding of the members of the generation’s view on NFC-enabled packaging. Emerging themes included added value, brand image, ease of use, right product, and environmental concerns. The findings from this study revealed the potential of NFC-embedded packaging and highlights the benefits it can provide to Generation Z but also several pain points and considerations.

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Karton ist ein aus nachwachsenden Rohstoffen hergestelltes Halbzeug, biologisch abbaubar und mit sehr guter Wiederverwertbarkeit. Damit stellt Karton eine zukunftsträchtige Grundlage für die Herstellung von Verpackungen für die Lebensmittel- und Konsumgüterproduktion dar. Schon heute werden in vielen Verpackungslösungen Kunststoffe durch naturfaserbasierte Halbzeuge ersetzt, um von den genannten Vorteilen zu profitieren. Um die Verbreitung dieses Naturstoffes weiter zu unterstützen, werden intelligente und effektive Herstellungsverfahren benötigt, die eine Massenfertigung von Packmitteln in hoher Qualität ermöglichen. [... aus der Einleitung]

This thesis deals with three selected current trends related to consumer behavior -- onslaught of retro products and retro marketing generally, changes in behavior related to electronic marketplace, and stricter demands for flawlessly designed products and services. Each trend is described and attention is given to driving forces of these trends, the ways they can affect consumers' lives and how they can be observed. The knowledge of the trends is then applied to determine how different groups of Czech consumers can be affected by those trends, thus giving businesses hints on how to incorporate the trends in the approach to their customers and monetize on them.

Decision making for fast-moving consumer goods involves a choice between numerous similar alternatives. Under such demanding circumstances, a decision is made for one product. The decision is dependent on the interaction between the environment and the mind of the consumer, both of which are filled with information that can influence the outcome. The aim of this dissertation is to explore how the mind and the environment guides attention towards considered and chosen products in consumer decision making at the point-of-purchase. Consumers are equipped with several effort reduction strategies to simplify complex decision making. The selection of strategies can be conscious or automatic and driven by information in the environment or the mind of the decision maker. The selected decision strategy reduces the set of options to one alternative in an iterative process of comparisons that are fast and rely on perceptual cues to quickly exclude irrelevant products. This thesis uses eye-tracking to explore this rapid processing that lacks conscious access or control. The purpose is to explore how product packaging and placement (as in-store factors), and recognition, preferences, and choice task (as out-of-store factors) influence the decision-making process through visual attention. The results of the 10 experiments in the five papers that comprise this thesis shed new light on the role of visual attention in the interaction between the environment and the mind, and its influence on the consumer. It is said that consumers choose with their eyes, which means that unseen is unsold. The results of this thesis show that it is just as important to be comprehended as it is to be seen. In split-second decision making, the ability to recognize and comprehend a product can significantly impact preferences. Comprehension stretches beyond perception as consumers infer value from memory structures that influence attention. Hence, the eye truly sees what the mind is prepared to comprehend.

Uppmärksamhet på miljön och att uppnå ett mer hållbart sätt att leva har ökat bland allmänheten och företag under flera år. Denna artikel har som ändamål att undersöka hur ett företag kan förmedla sina värderingar om hållbarhet inte bara genom ord och texter utan också genom grafisk design och visuell kommunikation. Artikeln djupdyker i grafiska profiler och identiteter och undersöker hur man med hjälp av dem kan visuellt uttrycka ett företags fokus på och värderingar kring hållbara tillverkning, förpackning samt hållbarhet för företaget och dess anställda. Artikeln bidrar med forskning som kan hjälpa designers att kommunicera specifika värderingar, i denna kontext hållbarhet, genom grafik samt visuella element, och dessutom hur man potentiellt kan förhålla sig till ämnen som “greenwashing”. Resultaten baseras på relevant litteratur i området, information samlad ifrån metoder som fokusgruppdiskussion och internetenkät, samt en visuell gestaltning i form av en grafisk profil för ett mock-up företag. / Awareness of the environment and achieving a more sustainable way of life has increased among the general public and companies for several years. The purpose of this article is to investigate how a company might convey its values ​​of sustainability not only through words and texts but also through graphic design and visual communication. The article delves into graphic profiles and brand identities and examines how they can be used to visually express a company's focus on, and values ​​around sustainable manufacturing, packaging, and sustainability for the company and its employees. The article contributes research that could help designers, in the context of sustainability, deliver specific messages and values through graphics and visual elements, as well as how one can potentially approach topics such as "greenwashing". The results are based on relevant literature in the area, information gathered from methods such as focus groups and surveys, as well as a practical design in the form of a graphic profile for a mock-up company.

Manual proofreading of product packaging is a time-consuming and uncertain process that can pose significant challenges for companies, such as scalability issues, compliance risks and high costs. This thesis work introduces a novel solution by employing advanced computer vision and machine learning methods to automate the proofreading of multiple ingredients’ lists corresponding to multiple products simultaneously within a product package. By integrating Convolutional Neural Network (CNN) and Optical Character Recognition (OCR) techniques, this study examines the efficacy of automated proofreading in comparison to manual methods. The thesis involves analyzing product package artwork to identify ingredient lists utilizing the YOLOv5 object detection algorithm and the optical character recognition tool EasyOCR for ingredient extraction. Additionally, Python scripts are employed to extract ingredients from corresponding INCI PDF files (document that lists the standardized names of ingredients used in cosmetic products). A comprehensive comparison is then conducted to evaluate the accuracy and efficiency of automated proofreading. The comparison of the extracted ingredients from the product packages and their corresponding INCI PDF files yielded a match of 12.7%. Despite the suboptimal result, insights from the study highlights the limitations of current detection and recognition algorithms when applied to complex artwork. A few examples of the insights have been that the trained YOLOv5 model cuts through sentences in the ingredient list or that EasyOCR cannot extract ingredients from vertically aligned product package images. The findings underscore the need for advancements in detection algorithms and OCR tools to effectively handle objects like product packaging designs. The study also suggests that companies, such as H&M, consider updating their artwork and INCI PDF files to align with the capabilities of current AI-driven tools. By doing so, they can enhance the efficiency and overall effectiveness of automated proofreading processes, thereby reducing errors and improving accuracy. / Manuell korrekturläsning av produktförpackningar är en tidskrävande och osäker process som kan skapa betydande utmaningar för företag, såsom skalbarhetsproblem, efterlevnadsrisker och höga kostnader. Detta examensarbete presenterar en ny lösning genom att använda avancerade metoder inom datorseende och maskininlärning för att automatisera korrekturläsningen av flera ingredienslistor som motsvarar flera produkter samtidigt inom en produktförpackning. Genom att integrera Convolutional Neural Network (CNN) och Optical Character Recognition (OCR) utreder denna studie effektiviteten av automatiserad korrekturläsning i jämförelse med manuella metoder. Avhandlingen analyserar designen av produktförpackningar för att identifiera ingredienslistor med hjälp av objektdetekteringsalgoritmen YOLOv5 och det optiska teckenigenkänningsverktyget EasyOCR för extrahera enskilda ingredienser från listorna. Utöver detta används Python-skript för att extrahera ingredienser från motsvarande INCI-PDF filer (dokument med standardiserade namn på ingredienser som används i kosmetika produkter). En omfattande jämförelse genomförs sedan för att utvärdera noggrannheten och effektiviteten hos automatiserad korrekturläsning. Jämförelsen av de extraherade ingredienserna från produktförpackningarna och deras korresponderande INCI-PDF filer gav ett matchnings resultat på 12.7%. Trots de mindre optimala resultaten belyser studien de begränsningar som finns hos de nuvarande detekterings- och teckenigenkänningsalgoritmerna när de appliceras på komplexa verk av produktförpackningar. Ett fåtal exempel på insikterna är bland annat att den tränade YOLOv5 modellen skär igenom meningar i ingredienslistan eller att EasyOCR inte kan extrahera ingredienser från stående ingredienslistor på produktförpackningsbilder. Resultaten understryker behovet av framsteg inom detekteringsalgoritmer och OCR-verktyg för att effektivt kunna hantera komplexa objekt som produktförpackningar. Studien föreslår även att företag, såsom H&M, överväger att uppdatera sina design av produktförpackningar och INCI-PDF filer för att anpassa sig till kapaciteten hos aktuella AI-drivna verktyg. Genom att utföra detta kan de förbättra både effektiviteten och den övergripande kvaliteten hos de automatiserade korrekturläsningsprocesserna, vilket minskar fel och ökar noggrannheten.