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Despite the technological advances in artificial intelligence (AI) and the keen interest of this technology for the public sector, the use of AI in the public sector and its added value are not systematically documented. This paper studies the usefulness of AI in the public sector. This scientific research consists of two parts. The first part includes a detailed literature study on AI in general and AI in the public sector. The second part contains a systematic literature review (SLR) about the usefulness of AI in the public sector. This review used the PRISMA protocol, which is a standard for SLR. The process of this research has led to a sample of 70 articles. These articles were further summarised and analysed. After performing the systematic literature review, it was possible to make a classification of added values in the public sector, which could answer the main research questions on: “what is the usefulness of AI in the public sector?”. The results show that AI solutions can be useful to perform specific tasks in the public sector, but these solutions are difficult to reuse for other public tasks and not easy to integrate into other environments. Also, public staff must be highly skilled in the domain of computer science to develop, maintain and use AI tools.

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Individuals often rely on heuristics that provide mental strategies to speed up the cognitive process and come up with efficient judgment when making decisions. Recently, consumers are trending towards more health-conscious eating. Using that consideration, a specific relation – the perceived health-perceived weight heuristic – is scrutinised in this paper to explore if the correlation between healthiness and weight perception exists. The purpose of this paper is to determine whether the perceived healthiness of a product exerts an influence on the perceived weight of that product. A laboratory study with ninety participants was designed to investigate the question, hence to find statistical significance of the perceived health-perceived weight heuristic. The findings failed to support the hypothesis, suggesting that there is no significant effect of healthiness on weight perception. Concerning prior studies, no research has yet been carried out on this specific topic. Given that a series of heuristics (e.g., healthy-expensive, weight-importance) has been activated by previous researchers’ demonstrations, heuristics would correspondingly convince individuals to believe in the perceived health-perceived weight heuristic. Yet, the results of this study do not hold with the antecedents as the relationship between healthiness and weight perception is not significant.

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The purpose of this study was to determine whether letter case in a brand name had an influence on consumers. More specifically, on their purchase intention, brand attitude and brand personality. In recent years, some companies switched from an uppercase wordmark design to a lowercase wordmark design. Concerning the topic of letter case in wordmark design for brand names, there is very little research. The findings of these studies all suggest that letter case has an effect on consumer perceptions. This study made use of an experimental design in which the letter case condition was manipulated. The findings of our research suggest that there is no significant effect of letter case on brand personality, brand attitude and purchase intention, neither is there a mediating role of brand personality on purchase intention and/or brand attitude. Thus, our findings contrast the findings of previous studies.

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This paper investigates the set of events that have taken place since the Rana Plaza collapse in 2013, where 1129 garment workers died, to ensure safe working conditions in garment factories. It depicts a current overview of the garment industry, six years later, by focusing on the perspective and actions of the industry’s most important stakeholders: garment factory workers, factory managers, retailers, Bangladesh's government officials, intergovernmental organizations, non-governmental organizations and consumers. This is done with semi-structured face-to-face and email interviews, and the use of reports published by relevant organizations such as the International Labour Organization. The findings show that even though famous western brands such as Primark, H&M and Zara care deeply about making profits, they also care about their reputation and their product’s quality. Since the Rana Plaza collapse, garment factories have gained leverage on their clients and allowed them to bargain higher prices in exchange of higher product quality and better working conditions inside their factories. However, garment factories have many clients, and each brand imposes its own safety standards and code of conduct, making it impossible to comply with all of them. The Higg Index goal is to harmonise every environmental and social standard in the garment industry allowing the industry to move away from fast-fashion. Brands such as Patagonia and Arket have understood that consumers are concerned about the climate crisis and factory worker’s rights and have turned it into their strength. Today, they are leading the way in the transition to sustainable fashion and are showing to the rest of the industry that profits go together with planet and people. However, in the end, the real player that can bring change to the industry is Bangladesh’s government. As Bangladesh is set to go from a least developed country to a developing country in 2023, better governance will be needed to ensure garment factories remediation, and therefore safer working conditions in the second largest apparel exporter in the world.

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User stories are system requirements written in natural language from the point of view of the user. These artefacts can only lead to the construction of a software system when sets of them express complementary features that should be implemented. The present paper determines which factors improve the ability of modelers to understand the requirements problem through a visual representation (called the Rationale Tree) built out of a user story set. It continues previous work on the feasibility of generating such a representation out of a user story set by comparing the Rationale Tree with the (industry-adopted) User Story Mapping approaches. This was achieved by performing a two-group quantitative comparative study. The factors identified were clarity, ease of understanding, ease of use, consistency, completeness, accuracy, correctness, complexity, maintainability and adaptability. Three evaluation methods were used. The three criteria method and the golden standard for the Rationale Tree and a genuine evaluation method developed for the User Story Map. User Story Mapping scored better in the criteria of clarity, ease of understanding and ease of use. The Rationale Tree model scored better in consistency, completeness, accuracy, complexity, maintainability and adaptability. We finally point to some potential improvements that can be done onto the Rationale Tree.