12,244 research outputs found
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Economia colaborativa
A importância de se proceder à análise dos principais desafios jurÃdicos que a economia colaborativa coloca – pelas implicações que as mudanças de paradigma dos modelos de negócios e dos sujeitos envolvidos suscitam − é indiscutÃvel, correspondendo à necessidade de se fomentar a segurança jurÃdica destas práticas, potenciadoras de crescimento económico e bem-estar social.
O Centro de Investigação em Justiça e Governação (JusGov) constituiu uma equipa multidisciplinar que, além de juristas, integra investigadores de outras áreas, como a economia e a gestão, dos vários grupos do JusGov – embora com especial participação dos investigadores que integram o grupo E-TEC (Estado, Empresa e Tecnologia) – e de outras prestigiadas instituições nacionais e internacionais, para desenvolver um projeto neste domÃnio, com o objetivo de identificar os problemas jurÃdicos que a economia colaborativa suscita e avaliar se já existem soluções para aqueles, refletindo igualmente sobre a conveniência de serem introduzidas alterações ou se será mesmo necessário criar nova regulamentação.
O resultado desta investigação é apresentado nesta obra, com o que se pretende fomentar a continuação do debate sobre este tema.Esta obra é financiada por fundos nacionais através da FCT — Fundação para a Ciência e a Tecnologia, I.P., no âmbito do Financiamento UID/05749/202
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?
The use of pretrained embeddings has become widespread in modern e-commerce
machine learning (ML) systems. In practice, however, we have encountered
several key issues when using pretrained embedding in a real-world production
system, many of which cannot be fully explained by current knowledge.
Unfortunately, we find that there is a lack of a thorough understanding of how
pre-trained embeddings work, especially their intrinsic properties and
interactions with downstream tasks. Consequently, it becomes challenging to
make interactive and scalable decisions regarding the use of pre-trained
embeddings in practice.
Our investigation leads to two significant discoveries about using pretrained
embeddings in e-commerce applications. Firstly, we find that the design of the
pretraining and downstream models, particularly how they encode and decode
information via embedding vectors, can have a profound impact. Secondly, we
establish a principled perspective of pre-trained embeddings via the lens of
kernel analysis, which can be used to evaluate their predictability,
interactively and scalably. These findings help to address the practical
challenges we faced and offer valuable guidance for successful adoption of
pretrained embeddings in real-world production. Our conclusions are backed by
solid theoretical reasoning, benchmark experiments, as well as online testings
Marketing Through Microcultures on Social Media: An Examination of BookTok and Independent Bookstores
This thesis explores the role of microcultures in social media marketing, by focusing on the BookTok microculture and its significant role in the marketing strategies of independent bookstores. The research includes an examination of microcultures and their impact on businesses, the effectiveness of the key social media marketing tactics used on TikTok, what BookTok is, how independent bookstores engage with BookTok, and an interview with an independent bookstore on their uses of BookTok
Fair Assortment Planning
Many online platforms, ranging from online retail stores to social media
platforms, employ algorithms to optimize their offered assortment of items
(e.g., products and contents). These algorithms tend to prioritize the
platforms' short-term goals by solely featuring items with the highest
popularity or revenue. However, this practice can then lead to undesirable
outcomes for the rest of the items, making them leave the platform, and in turn
hurting the platform's long-term goals. Motivated by that, we introduce and
study a fair assortment planning problem, which requires any two items with
similar quality/merits to be offered similar outcomes. We show that the problem
can be formulated as a linear program (LP), called (FAIR), that optimizes over
the distribution of all feasible assortments. To find a near-optimal solution
to (FAIR), we propose a framework based on the Ellipsoid method, which requires
a polynomial-time separation oracle to the dual of the LP. We show that finding
an optimal separation oracle to the dual problem is an NP-complete problem, and
hence we propose a series of approximate separation oracles, which then result
in a -approx. algorithm and a PTAS for the original Problem (FAIR). The
approximate separation oracles are designed by (i) showing the separation
oracle to the dual of the LP is equivalent to solving an infinite series of
parameterized knapsack problems, and (ii) taking advantage of the structure of
the parameterized knapsack problems. Finally, we conduct a case study using the
MovieLens dataset, which demonstrates the efficacy of our algorithms and
further sheds light on the price of fairness.Comment: 86 pages, 7 figure
Discreetly Exploiting Inter-session Information for Session-based Recommendation
Limited intra-session information is the performance bottleneck of the early
GNN based SBR models. Therefore, some GNN based SBR models have evolved to
introduce additional inter-session information to facilitate the next-item
prediction. However, we found that the introduction of inter-session
information may bring interference to these models. The possible reasons are
twofold. First, inter-session dependencies are not differentiated at the
factor-level. Second, measuring inter-session weight by similarity is not
enough. In this paper, we propose DEISI to solve the problems. For the first
problem, DEISI differentiates the types of inter-session dependencies at the
factor-level with the help of DRL technology. For the second problem, DEISI
introduces stability as a new metric for weighting inter-session dependencies
together with the similarity. Moreover, CL is used to improve the robustness of
the model. Extensive experiments on three datasets show the superior
performance of the DEISI model compared with the state-of-the-art models
The Professional Identity of Doctors who Provide Abortions: A Sociological Investigation
Abortion is a medicalised problem in England and Wales, where the law places doctors at the centre of legal provision and puts doctors in control of who has an abortion. However, the sex-selection abortion scandal of 2012 presented a very real threat to 'abortion doctors', when the medical profession's values and practices were questioned in the media, society and by Members of Parliament. Doctors found themselves at the centre of a series of claims that stated doctors were acting both illegally and unethically, driven by profit rather than patient needs. Yet, the perspectives of those doctors who provide abortions has been under-researched; this thesis aims to fill that gap by examining the beliefs and values of this group of doctors. Early chapters highlight the ambiguous position of the abortion provider in Britain, where doctors are seen as a collective group of professionals motivated by medical dominance and medical autonomy. They outline how this position is then questioned and contested, with doctors being presented as unethical. By studying abortion at the macro-, meso- and micro-levels, this thesis seeks to better understand the values of the 'abortion doctor', and how these levels shape the work and experiences of abortion providers in England and Wales. This thesis thus addresses the question: 'What do abortion doctors' accounts of their professional work suggest about the contemporary dynamics of the medicalisation of abortion in Britain?'. It investigates the research question using a qualitative methodological approach: face-to-face and telephone interviews were conducted with 47 doctors who provide abortions in England and Wales. The findings from this empirical study show how doctors' values are linked to how they view the 'normalisation of abortion'. At the macro-level doctors, openly resisted the medicalisation of abortion through the position ascribed to them by the legal framework, yet at the meso-level doctors construct an identity where normalising abortion is based on further medicalising services. Finally, at the micro-level, the ambiguous position of the abortion provider is further identified in terms of being both a proud provider and a stigmatised individual. This thesis shows that while the existing medicalisation literature has some utility, it has limited explanatory power when investigating the problem of abortion. The thesis thus provides some innovative insights into the relevance and value of medicalisation through a comprehensive study on doctors' values, beliefs and practices
The developing maternal-infant relationship: a qualitative longitudinal study
Aim
The study aimed to explore maternal perceptions and the use of knowledge relating to their infant’s mental health over time using qualitative longitudinal research.
Background
There has been a growing interest in infant mental health over recent years. Much of this interest is directed through the lens of infant determinism, through knowledge regarding neurological development resulting in biological determinism. Research and policy in this field are directed toward individual parenting behaviours, usually focused on the mother. Despite this, there is little attention given to maternal perspectives of infant mental health, indicating that a more innovative approach to methodology is required.
Methods
This study took a qualitative longitudinal approach, and interviews were undertaken with seven mothers from the third trimester of pregnancy and then throughout the first year of the infant’s life. Interviews were conducted at 34 weeks of pregnancy, and then when the infant was 6 and 12 weeks, 6, 9, and 12 months, alongside the collection of researcher field notes—a total of 41 interviews. Data were analysed by creating case profiles, memos, and summaries, and then cross-comparison of the emerging narratives. A psycho-socially informed approach was taken to the analysis of data.
Findings
Three interrelated themes emerged from the data: evolving maternal identity, growing a person, and creating a safe space. The theme of evolving maternal identity dominated the other themes of growing a person and creating a safe space in a way that met perceived socio-cultural requirements for mothering and childcare practices. Participants’ personal stories give voice to their perceptions of the developing maternal-infant relationship in the context of their socio-cultural setting, relationships with others, and experiences over time.
Conclusions
This study adds new knowledge by giving mothers a voice to express how the maternal-infant relationship develops over time. The findings demonstrate how the developing maternal-infant relationship grows in response to their mutual needs as the mother works to create and sustain identities for herself and the infant that will fit within their socio-cultural context and individual situations. Additionally, the findings illustrate the importance of temporal considerations, social networks, and intergenerational relationships to this evolving process. Recommendations for practice, policy, and education are made that reflect the unique relationship between mother and infant and the need to conceptualise this using an ecological approach
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