244 research outputs found
An Investigation of Teenagers’ Advertising Literacy in the Context of the Brand-Rich Environment of Social Media
Teenagers are avid consumers of social media and consequently, constitute attractive target audiences for marketers. On social media, advertising can be integrated into content such as YouTube videos and Instagram posts which means the boundary between commercial content (the advertisement) and non-commercial content (e.g., the video in which the ad appears) becomes increasingly blurred. Therefore, in this context, the consumer must be able to navigate a minefield of overt and covert advertising that is disseminated by a range of sources, including brands and social media influencers. A resulting concern for academics, parents and policy makers alike relates to young people’s understanding, evaluation and critical responses to such advertising practices, i.e., their advertising literacy. In order to command a basic level of advertising literacy, consumers need to be able to recognise the source of an advertisement, identify the commercial and persuasive intent, and subsequently enact a critical response. However, this can become challenging in the context of newer advertising practices on social media platforms where advertising content can be seamlessly woven into editorial content that is interactive, entertaining, and engaging. It follows that if a young consumer cannot properly identify and respond to an advertising episode, then the act of targeting them is unethical.
This thesis reports on a qualitative study of 29 teenagers aged 15–17 years. The aim was to investigate teenagers’ dispositional and situational advertising literacy in the context of the overt and covert advertising formats which prevail on social media platforms. The study sought to investigate their general knowledge, attitudes and judgements regarding advertising which develops over time (dispositional AL), but also their ability to retrieve and apply this knowledge during exposure to specific advertising episodes (situational AL). The findings indicate that whilst the participants had a highly developed associative network about SM advertising (i.e., their dispositional AL), their ability to retrieve and apply it (i.e., their situational AL) was dependent on the nature and origin of advertising. Specifically, the marketer’s ability to craft messaging which delights the consumer; emerges from a meaningful source; or provides opportunities for social learning can impede critical response
The New Regulatory Imperative for Insurance
This Article addresses emerging gaps in consumer protection. Insurers, like companies in other industries, are revolutionizing their practices with artificial intelligence and big data. Insurers are finding new ways to price risks and policies, tailor coverage, offer advice to purchasers, identify fraud, and sequence the payment of claims. These changes have subverted consumer protections built into current regulatory regimes, and regulators are struggling to adapt. This is not a niche problem. Insurance is a vital part of the U.S. economy: it rakes in over 1.2 trillion dollars in premiums a year; employs more than 2.7 million people; and undergirds transactions as simple as home purchases and as complex as corporate mergers and acquisitions, the multi-trillion-dollar tort system, and a vast system of private risk management and loss avoidance advice. Despite playing these critical roles, the insurance market is surprisingly inefficient. Deep information asymmetries make it difficult for consumers to evaluate the quality of policies and carriers, for insurers to price risks properly, and make it possible for both sides to act opportunistically. Further, behavioral barriers hamper purchasers, who often buy too little or the wrong insurance. And, in some markets, private insurers might not be willing to supply enough insurance because the underlying risks cannot be adequately spread. Insurance regulation is a necessary part of solving these complex market failures. Most of the previous legal scholarship about algorithmic justice has been in the context of information platforms, criminal justice, and employment discrimination. This Article connects to those discussions and expands them in the specific context of insurance. It does so by providing a taxonomy of the changes in the insurance industry, the potential danger to consumers as a result of those changes, the reasons for regulation, and the ways that regulators must adapt to protect individual consumers and the insurance market
Managing the Paradox of Growth in Brand Communities Through Social Media
The commercial benefits of online brand communities are an important focus for marketers seeking deeper engagement with increasingly elusive consumers. Managing participation in these socially bound brand conversations challenges practitioners to balance authenticity towards the community against corporate goals. This is important as social media proliferation affords communities the capacity to reach a scale well beyond their offline equivalents and to operate independently of brands. While research has identified the important elements of engagement in brand communities, less is known about how strategies required to maximise relationships in these circumstances must change with growth. Using a case study approach, we examine how a rapidly growing firm and its community have managed the challenges of a maturing relationship. We find that, in time, the community becomes self-sustaining, and a new set of marketing management strategies is required to move engagement to the next level
Managing the Paradox of Growth in Brand Communities Through Social Media
The commercial benefits of online brand communities are an important focus for marketers seeking deeper engagement with increasingly elusive consumers. Managing participation in these socially bound brand conversations challenges practitioners to balance authenticity towards the community against corporate goals. This is important as social media proliferation affords communities the capacity to reach a scale well beyond their offline equivalents and to operate independently of brands. While research has identified the important elements of engagement in brand communities, less is known about how strategies required to maximise relationships in these circumstances must change with growth. Using a case study approach, we examine how a rapidly growing firm and its community have managed the challenges of a maturing relationship. We find that, in time, the community becomes self-sustaining, and a new set of marketing management strategies is required to move engagement to the next level
Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications
The last decade has seen a revolution in the theory and application of
machine learning and pattern recognition. Through these advancements, variable
ranking has emerged as an active and growing research area and it is now
beginning to be applied to many new problems. The rationale behind this fact is
that many pattern recognition problems are by nature ranking problems. The main
objective of a ranking algorithm is to sort objects according to some criteria,
so that, the most relevant items will appear early in the produced result list.
Ranking methods can be analyzed from two different methodological perspectives:
ranking to learn and learning to rank. The former aims at studying methods and
techniques to sort objects for improving the accuracy of a machine learning
model. Enhancing a model performance can be challenging at times. For example,
in pattern classification tasks, different data representations can complicate
and hide the different explanatory factors of variation behind the data. In
particular, hand-crafted features contain many cues that are either redundant
or irrelevant, which turn out to reduce the overall accuracy of the classifier.
In such a case feature selection is used, that, by producing ranked lists of
features, helps to filter out the unwanted information. Moreover, in real-time
systems (e.g., visual trackers) ranking approaches are used as optimization
procedures which improve the robustness of the system that deals with the high
variability of the image streams that change over time. The other way around,
learning to rank is necessary in the construction of ranking models for
information retrieval, biometric authentication, re-identification, and
recommender systems. In this context, the ranking model's purpose is to sort
objects according to their degrees of relevance, importance, or preference as
defined in the specific application.Comment: European PhD Thesis. arXiv admin note: text overlap with
arXiv:1601.06615, arXiv:1505.06821, arXiv:1704.02665 by other author
Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications
The last decade has seen a revolution in the theory and application of
machine learning and pattern recognition. Through these advancements, variable
ranking has emerged as an active and growing research area and it is now
beginning to be applied to many new problems. The rationale behind this fact is
that many pattern recognition problems are by nature ranking problems. The main
objective of a ranking algorithm is to sort objects according to some criteria,
so that, the most relevant items will appear early in the produced result list.
Ranking methods can be analyzed from two different methodological perspectives:
ranking to learn and learning to rank. The former aims at studying methods and
techniques to sort objects for improving the accuracy of a machine learning
model. Enhancing a model performance can be challenging at times. For example,
in pattern classification tasks, different data representations can complicate
and hide the different explanatory factors of variation behind the data. In
particular, hand-crafted features contain many cues that are either redundant
or irrelevant, which turn out to reduce the overall accuracy of the classifier.
In such a case feature selection is used, that, by producing ranked lists of
features, helps to filter out the unwanted information. Moreover, in real-time
systems (e.g., visual trackers) ranking approaches are used as optimization
procedures which improve the robustness of the system that deals with the high
variability of the image streams that change over time. The other way around,
learning to rank is necessary in the construction of ranking models for
information retrieval, biometric authentication, re-identification, and
recommender systems. In this context, the ranking model's purpose is to sort
objects according to their degrees of relevance, importance, or preference as
defined in the specific application.Comment: European PhD Thesis. arXiv admin note: text overlap with
arXiv:1601.06615, arXiv:1505.06821, arXiv:1704.02665 by other author
Consumption practices, conflict resolution and behaviour change in the UK smokers market
In the UK tobacco denormalisation strategies (i.e. indoor smoking ban and display
ban), have been acknowledged as important strategies to encourage behaviour
change in smokers, through quitting or at least minimising it. This study examines the
impact of these strategies on smokers and their behaviours in retail establishments
and shared consumption spaces. It extends the work of Festinger (1957) on
dissonance manifestation and behaviour, and of Michie and West’s (2011) concept of
behaviour change interventions, through the examination of smokers as consumers.
The strategy of ‘denormalising’ tobacco use has become one of the cornerstones of
the global tobacco control movement. In the UK, tobacco denormalisation was born
out of a need to protect non-smokers from the dangers of second-hand smoke and
curb increasing numbers of deaths in smokers. These policies are overseen by the
WHO Framework Convention on Tobacco Control (WHO FCTC), to which the UK
became a signatory in 2002. Although the UK has strict tobacco denormalisation
strategies and leads the way in tobacco control in Europe, there remains a dearth of
UK-centric qualitative studies from a consumer standpoint exploring smoking
behaviours and the impact of tobacco denormalisation.
An interpretivist theoretical perspective and the phenomenology research design is
adopted for this study, drawing on qualitative data using interviews with 25 individuals
(current smokers, ex-smokers, and non-smokers, retailers and industry personnel),
living and working in and around the town of Huddersfield and the region of West
Yorkshire, as well as three separate participant observations held in a stop-smoking
clinic in the town of Huddersfield. Data was analysed using the strategy recommended
by Miles & Huberman (1984), aided using NVIVO 11 data analysis software to identify
emergent themes recommended by Bazeley & Jackson (2013).
Results of this study’s analysis of data suggest that tobacco control strategies have
overseen behaviour change in smoking participants during purchase and
consumption, and whilst in shared consumption spaces but not in the way intended.
Smoking participants continue to adopt, purchase and consume tobacco products in
the face of mounting social and cultural opposition. However, behaviour change is
manifested in ways they circumvent “barriers to purchase, consumption and use”. For
example, making friends with other smokers whilst standing outside to smoke,
adopting new or alternative products such as e-cigarettes, engaging in brand switching
and bulk buying, becoming brand knowledgeable and more informed about location of
products stored in gantries, but also engaging in compensatory health behaviours to
justify smoking continuation. The behaviour of smoking participants suggests
observation and rejection of tobacco control strategies occur in parallel (i.e. take place
at the same time). Findings therefore raise questions about the ethical and practical
extent to which tobacco denormalisation strategies influence and encourage smokers
to change behaviours
IFIP TC 13 Seminar: trends in HCI proceedings, March 26, 2007, Salamanca (Spain)
Actas del 13o. Seminario de la International Federation for Information Processing (IFIP), celebrado en Salamanca el 26 de marzo de 2007, sobre las nuevas líneas de investigación en la interacción hombre-máquina, gestión del conocimiento y enseñanza por la Web
CPA\u27s handbook of fraud and commercial crime prevention
https://egrove.olemiss.edu/aicpa_guides/1823/thumbnail.jp
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