Готові списки джерел за темами / Personalized advertisements

Добірка наукової літератури з теми "Personalized advertisements"

Автор: Grafiati
Опубліковано: 19 червня 2021
Оновлено: 1 лютого 2022

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Зміст

  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій

Статті в журналах з теми "Personalized advertisements":

1

Debora Dhanya A and Uma Pricilda Jaidev. "Perceived Personalization, Privacy Concern, e-WOM and Consumers' Click Through Intention in Social Advertising." International Journal of E-Services and Mobile Applications 11, no. 4 (October 2019): 39–55. http://dx.doi.org/10.4018/ijesma.2019100103.

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Social advertising, ads in social media platforms, have become popular in recent years because of the evolution of internet technologies such as web analytics and big data mining. The content of the social advertisement is tailored in order to personalize the message to the target consumer groups. In an effort to reach the prospects, marketers should focus on the social leads on social networking sites (SNS) to promote and to sell their brands/products. Drawing on, online personalized advertising literature, e-WOM recommendations and increasing privacy concerns and perceived ad personalization (conceptualized as functions of psychological reactance) on SNS leads to avoid such advertisements. The goal of the study is to investigate the impact of perceived personalization, privacy concern, and e-WOM to consumers' behavioral click through intentions towards social ads. This study contributed to the theory of psychological reactance by indicating that the individuals with less privacy concern and personalized recommendations from their contacts on SNS have a smaller amount of reactance towards social advertisements than commercial advertisements by marketers. Suggestions for advertisers, social media marketing practitioners conclude the paper.
2

Dziemianko, Anna. "Smart advertising and online dictionary usefulness." International Journal of Lexicography 33, no. 4 (August 26, 2020): 377–403. http://dx.doi.org/10.1093/ijl/ecaa017.

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Abstract Today, online advertisements are smart. Based on targeting, they are highly personalized to match the interests of Internet users. Smart advertisements feature even in high-quality online dictionaries, which is a trade-off for free dictionary content. The aim of the paper is to investigate the influence of targeted advertisements in online dictionaries on language reception, production and learning. The study also identifies the effect of advertisement targeting on the time of online dictionary consultation. In addition, dictionary users’ attitudes to advertisements are explored. The results reveal that either targeted or non-targeted advertisements in online dictionaries do not significantly affect language reception, production and learning, irrespective of sense position in entries. Yet, both targeted and non-targeted advertisements prolong dictionary consultation. Non-targeted advertisements were found only marginally more disruptive than targeted ones, and the assessment of advertisements was not dependent on the experimental condition.
3

Noura, Abdaoui, Hadj Khalifa Ismahène, and Faiz Sami. "Process of Personalizing the Ubiquitous Advertisements." International Journal of Knowledge Society Research 8, no. 2 (April 2017): 13–35. http://dx.doi.org/10.4018/ijksr.2017040102.

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In this paper, we propose an approach combining behavioral and targeting techniques for a better reaction of the customer with a star product using a personalized ubiquitous advertisement. We use the clustering to study the customer's behavior and the association rules to estimate the probability of star product's purchases in the near future. In order to validate our approach, we develop a prototype to send a personalized advertisement to loyal customers and potential customers in ubiquitous environment. Each target receives the advertising according his classification and his degree of loyalty obtained by the behavioral analysis. Loyal customers are the first to receive the personalized advertising in the ubiquitous environment.
4

Du, Wei, and Jun Liang Chen. "Semantic Tags and Neutral Network Based Personalized Advertisement Recommendation System for Movies." Advanced Materials Research 488-489 (March 2012): 1727–31. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1727.

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With the rapid development of information especially internet technology, people have to choose the most suitable goods without any experience, so the recommendation system is seriously required. Yet no research on advertisement recommendation system for movie play is presented. Regarding this problem, the paper introduces the theory of semantic computing and annotates the semantic tags from the movie slices and the candidate advertisements, the potential preferences on them are predicted with neutral network model trained by some data set predefined. The user preference model and the predicting workflow are described in detail. Finally, the MovieLens dataset is employed to validate the validity of the system designed. The results of simulation experiments prove that the technology proposed can not only satisfy the requirement of matched advertisement recommendation but also outperform the traditional collaborative filtering algorithm.
5

Takeuchi, Ryosuke. "The Diversity of Consumer Perceptions toward Personalized Advertisements." Japan Marketing Journal 40, no. 1 (June 30, 2020): 43–55. http://dx.doi.org/10.7222/marketing.2020.034.

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6

Nyheim, Peter, Shi Xu, Lu Zhang, and Anna S. Mattila. "Predictors of avoidance towards personalization of restaurant smartphone advertising." Journal of Hospitality and Tourism Technology 6, no. 2 (August 17, 2015): 145–59. http://dx.doi.org/10.1108/jhtt-07-2014-0026.

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Purpose – This paper aims to examine the effect of privacy concern, irritation and personalization on Millennials’ perceptions of personalized smartphone advertising avoidance in a restaurant context. The hospitality industry has witnessed a huge surge in mobile activity over the past few years. Mobility opens up a new communication channel and allows industry to connect with their guests in a more personalized way. However, not all customers welcome the personalized advertisements. Design/methodology/approach – Data were collected from 159 Millennials enrolled in a large state university in the Eastern USA using an online self-administered survey. These Millennials were asked to use a restaurant’s smartphone application for 30 days and then complete a survey based on their perceptions of personalized advertising. Descriptive analysis, reliability, factor analysis and regression analysis were used to evaluate the relationships among the four constructs: privacy concern, irritation, personalization and advertising avoidance, with the first three variables as predictors and advertising avoidance as an outcome. Findings – The results suggest that advertising irritation is positively related to advertising avoidance, perceived personalization is related with less advertising avoidance, while privacy concern is not related to advertising avoidance. Originality/value – Although advertising avoidance has previously been studied for the past few decades, little research has explored the underlying mechanisms of the Millennials’ avoidance of personalized smartphone advertising in a restaurant context. The current research suggests information pertinent to strategies for marketing personalized smartphone advertisement for restaurant companies.
7

Kim, Jong Woo, Kyung Mi Lee, Michael J. Shaw, Hsin-Lu Chang, Matthew Nelson, and Robert F. Easley. "A preference scoring technique for personalized advertisements on Internet storefronts." Mathematical and Computer Modelling 44, no. 1-2 (July 2006): 3–15. http://dx.doi.org/10.1016/j.mcm.2004.12.011.

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8

REENA, Mehta, and Kulkarni UDITA. "Impact of Personalized Social Media Advertisements on Consumer Purchase Intention." Annals of Dunarea de Jos University of Galati. Fascicle I. Economics and Applied Informatics 26, no. 2 (August 31, 2020): 15–24. http://dx.doi.org/10.35219/eai15840409101.

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9

Tran, Trang P., Michelle van Solt, and James E. Zemanek Jr. "How does personalization affect brand relationship in social commerce? A mediation perspective." Journal of Consumer Marketing 37, no. 5 (March 20, 2020): 473–86. http://dx.doi.org/10.1108/jcm-12-2017-2499.

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Purpose This paper aims to tests a conceptual model capturing the influence of personalized advertising on customer perceptions of brands in social media and identifies three market segments based on customers’ reactions to personalized ads. Design/methodology/approach Two studies are developed to test the model using partial least squares structural equation modeling (PLS-SEM). Additionally, cluster analysis, multi-group analysis (MGA) and serial mediation tests are also conducted to provide better insights into the results. Findings The results of the two studies show that all nine hypotheses are supported except for H4 in Study 1. Three market segments (ad lovers, ad adjusters and ad haters) are identified. Each segment has a typical attitude toward personalized advertisements. Research limitations/implications Built on self-congruence literature, the current research posits that consumer-brand self-congruence can be established when a customer sees a brand advertised on Facebook after searching for that brand online. Consistently, this paper finds that through self-congruence, personalized advertising has a positive impact on brand-related outcomes. Practical implications Three segments identified – “ad lovers,” “ad adjusters” and “ad haters” are important for marketers. Companies should develop an appropriate advertising campaign for each segment, especially once the general data protection regulation is in place. Companies will be subject to a noncompliance penalty if an advertisement is posted on a user s account without approval. Identifying this segment promptly will not only enable companies to save resources but also help avoid legal complications associated with privacy concerns. Originality/value This research sheds light on the effects of personalized advertising on customer perceptions of brands in social commerce.
10

Kim, Jong Woo, Byung Hun Lee, Michael J. Shaw, Hsin-Lu Chang, and Matthew Nelson. "Application of Decision-Tree Induction Techniques to Personalized Advertisements on Internet Storefronts." International Journal of Electronic Commerce 5, no. 3 (March 2001): 45–62. http://dx.doi.org/10.1080/10864415.2001.11044215.

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Статті в журналах Дисертації

Дисертації з теми "Personalized advertisements":

1

Adolfsson, Henrik, and Elias Davidsson. "Why even bother? : Exploring consumer perceived risks and benefits of online personalized advertisements." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-65298.

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The use of online personalized advertisements has drawn attention among firms, in efforts of acquiring and maintaining competitive advantage. By collecting individual consumer information, firms are able to personalize advertisements to specific individuals in online contexts. The collection and use of individuals’ personal information have given rise to privacy concerns among consumers. However, contemporary research displays disparate conclusions regarding the extent to which these privacy concerns influence the effectiveness of online personalized advertisements. In order to provide insights regarding this discrepancy, this study explored the theoretical foundations of consumer perceived benefits and risks, upon which contemporary research was based. Two focus groups were conducted to explore how consumers perceive benefits and risks of online personalized advertisements. Using pattern matching, the interpretation of the empirically gathered material implied that consumer perceived benefits, in form of perceived relevance, appears to be insufficient in appealing to the interests and preferences of consumers. Instead, consumers’ perceptions of relevance appear to be dependent on several elements. Furthermore, the findings imply that consumers are aware of the risks through personal information disclosure, yet appear to be unconcerned by them. Instead, consumers seem to possess a sense of hopelessness in online environments, that attempts to restrict the availability of their personal information are pointless.
2

Wallgren, Joel, and Nicklas Nordmark. "Do you even care? : A quantitative study on personalized smartphone advertisements and privacy concerns." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-77049.

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Purpose: The purpose of this paper is to explain how privacy concerns impact the relationship between personalization and the factors of advertising value on smartphone advertising. Design/methodology/approach: A explanatory research design with a quantitative approach was conducted, utilizing an online questionnaire with a total of 103 respondents. Conclusion: The result indicates that privacy concerns only moderates the relationship between personalization and entertainment. It was also shown that privacy concerns had a direct impact on irritation Research limitations: The result is not generalizable as a non-probability sample was used, and only respondents between the 18-35 answered the questionnaire. Originality/value: A new perspective of how the moderation of privacy concerns impacts the relationship between personalization and the factors of advertising value. Keywords: Smartphone advertising, advertising value, informativeness, entertainment, irritation, credibility, incentives, privacy concerns. Paper type: Research paper
3

Idberg, Lovisa, Sofia Orfanidou, and Oona Karppinen. "Privacy for sale! : An exploratory study of personalization privacy paradox in consumers’ response to personalized advertisements on social networking sites." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105022.

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Social networking sites are channels that allow companies to appeal to their target audience through personalized advertising which has become an increasingly common way for companies to reach their target customers. Personalization is possible through the use of customer data which allows designing an advertisement based on individual consumers' preferences benefiting the consumers with more personally appealing advertisements. However, the collection of the data has led to consumers’ experiencing costs from the personalization involving concerns for the safety of personal information. Because of the tension between benefits and costs of personalization, consumers' behavior has become paradoxical. The consumers’ behaviour does not always correspond to their concerns by which the consumers trade off their privacy to receive benefits from the personalization in return. With that said, this study aims to explore how the personalization privacy paradox appears in the consumers’ response to personalized advertisements on social networking sites by assessing their perception of the benefits and costs of personalized advertisements. Semi-structured interviews of eight participants lead to the main findings of this research identifying four factors that have an impact on consumers’ interaction with the advertisement; (1) simplified purchase decisions, (2) personal interest, (3) personal gain, and (4) trustworthiness. In addition, the research revealed additional findings indicating that consumers' concern for data collection could be changing from privacy risks regarding themselves to concerns about the consequence of data collection on a societal level. Furthermore, the findings show an indication for an emerging dilemma of personalized advertising for companies to overcome. Finally, this research provides implications for both academia as well as practitioners.
4

Wetterstrand, Adam, Albin Fransson, and Julius Nordmark. "Concepts that influence users’ feeling of non-intrusiveness in native advertising : A quantitative study testing the conceptualization of effective native advertisements’ influence on users’ feeling of non-intrusiveness." Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-85740.

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Abstract Background “Traditional digital advertising has become wallpaper. It doesn’t improve anyone’s experience on a site and readers, myself included, pretty much look past it” stated by Jason Hill, Global Head of Media Strategies (Adage.com, 2019). Marketing managers attempt and fail in adapting traditional marketing strategies to the unfamiliar digital landscape. Traditional techniques e.g. banner ads appear as intrusive and unwanted according to consumers. Brands have in response strategically changed its communication to a rather subtle approach that aims to be non-intrusive. Aforesaid strategy is referred to as native advertising. Native advertising however is not unproblematic as said approach may be exploited to be deceptive, intrusive and secretive, brand whom implements such a strategy may be rewarded with short term positives. However the long term effects of said strategy prove negatives in various aspects of the brand. Purpose The purpose of this thesis is to explain how the conceptualization of native ads influence users’ feeling of non-intrusiveness. Method The conducted study implemented a deductive approach to research, including an explanatory purpose as previously elaborated upon. The study is further characterized as a cross-sectional design in which the researchers aimed to test the conceptualization of non-intrusive native advertising. The researchers further conducted a self administrated questionnaire with a total of 158 respondents. The data was cleaned in SPSS and further tested for reliability, validity and hypothesis testing. Conclusion The findings of the conducted study concludes that personalized advertising positively contributes to users’ feeling of non-intrusiveness. On the other hand, contextual relevance, 1 transparency, emotional appeal and informational appeal were rejected as such variables were not statistically significant in explaining non-intrusiveness. Therefore, the researchers rejected hypothesis H1, H2, H3, H4 and therefore rejected previous research stating that these variables contributes to users’ feeling of non-intrusiveness. However H5 was accepted, therefore theories that suggests that personalization according to one’s interest, previous interactions and real-time data to influence users feeling of non-intrusiveness were confirmed.
5

Al, Qudah Dana. "A framework for adaptive personalised e-advertisements." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/78507/.

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The art of personalised e-advertising relies on attracting the user‟s attention to the recommended product, as it relates to their taste, interest and data. Whilst in practice, companies attempt various forms of personalisation; research of personalised e-advertising is rare, and seldom routed on solid theory. Adaptive hypermedia (AH) techniques have contributed to the development of personalised tools for adaptive content delivery, mostly in the educational domain. This study explores the use of these theories and techniques in a specific field – adaptive e-advertisements. This is accomplished firstly by structuring a theoretical framework that roots adaptive hypermedia into the domain of e-advertising and then uses this theoretical framework as the base for implementing and evaluating an adaptive e-advertisement system called “MyAds”. The novelty of this approach relies on a systematic design and evaluation based on adaptive hypermedia taxonomy. In particular, this thesis uses a user centric methodology to design and evaluate the proposed approach. It also reports on evaluations that investigated users‟ opinions on the appropriate design of MyAds. Another set of evaluations reported on users‟ perceptions of the implemented system, allowing for a reflection on the users‟ acceptance level of e-advertising. The results from both implicit and explicit feedback indicated that users found the MyAds system acceptable and agreed that the implemented user modelling and AH features within the system contributed to achieving acceptance, within their e-advertisement experience due to the different personalisation methods.
6

Taveira, Rafael Brandão. "Exibição de Propaganda Personalizada com o uso de Realidade Aumentada." Universidade do Estado do Rio de Janeiro, 2013. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=6447.

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É apresentado como problema atual na área de Publicidade e Propaganda a exibição de conteúdo personalizado para nichos específicos. A propaganda acaba se concentrando nos produtos de maior sucesso, tendo como foco alguns públicos-alvo previamente determinados. Assim, o estudo pretende avaliar um novo canal para exibição de propaganda em nível individual, através das perspectivas da Cauda Longa e da Realidade Aumentada (R.A.). O ponto principal desse trabalho é, portanto, mostrar a quantidade de nichos existentes e sugerir uma personalização da propaganda a um nível praticamente individual, como uma ligação direta entre produto e consumidor, usando como suporte tecnológico a R.A. A partir da análise de trabalhos de Romero Tori, Paul Milgram, Ronald Azuma, Cláudio Kirner, Robson Siscouto, Lúcia Santaella, entre outros autores, foi feita uma avaliação dos principais pontos de interesse da tecnologia de Realidade Aumentada para profissionais da área do Design. Discorrendo não só sobre suas características como também identificando problemas e questionamentos atuais, tanto para esses profissionais como para o consumidor final. A tese se enquadra na linha de pesquisa de Design e Tecnologia ao passo que os profissionais desta área de conhecimento são responsáveis diretos por pensar as formas de interação de modo que sejam mais orgânicas e intuitivas para os usuários. Existe muito trabalho a ser realizado, no tocante à Ergonomia e Usabilidade, nas soluções que usam a Realidade Aumentada, principalmente na forma como se dá a sobreposição da informação digital ao ambiente real capturado pela câmera e sua manipulação pelo indivíduo.
Show custom content for specific market segments is a current problem in the Advertising industry. The advertisement ends up prioritizing the most successful products, with the focus on some predetermined audiences. With that in mind, this study evaluates a new channel for advertising on an individual level, through the perspectives of the Long Tail and Augmented Reality (AR). For that reason, the main point of this work is demonstrate the amount of existing niches and suggest customized ads to an individual level, as a direct link between product and consumer, using as technological support AR. From the analysis of the authors Romero Tori, Paul Milgram, Ronald Azuma, Claudio Kirner, Robson Siscouto, Lucia Santaella, among others, an assessment was made about the main points of interest in AR to the field of professional designers. Reflecting not only about their characteristics as well as identifying current problems and questions , both for these professionals and to the final consumer. The work fits the Design and Technology area because their professionals are directly responsible for thinking ways of interaction in order to be more intuitive for users. There is much more work to be done with regards to Ergonomics and Usability in the solutions that use Augmented Reality, especially in the way the digital information overlays the environment captured by the camera and its manipulation by the individual.
7

Xiao, Guang Yi. "Personalized scheduling search advertisement by mining the history behaviors of users." Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b2119532.

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8

Jonsson, Amanda, and Ekeroth Julia Darnéus. "The Effectiveness of Personalised Advertising : An exploratory study on personalised advertising done on Facebook." Thesis, Mälardalens högskola, Akademin för ekonomi, samhälle och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54413.

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Carlsson, Mina, Maria Arvidsson, and Iris Qvennerberg. "Personalized marketing: Do consumers create their own advertisement? : A qualitative study of how consumers experience personalized marketing messages designed using their private mobile data." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-106257.

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Background: Companies collect private data about consumers for marketingpurposes. Mobile devices provide marketers with valuable insights intoconsumers' hyper-context information concerning specific consumersituations such as location, time, and environment. Consumers, on the otherhand, may have a different attitude towards how marketers use their privatedata. Purpose: The purpose of this thesis is to analyse and gain insight into theemotional experience of consumers when receiving personalized marketingmessages that are designed using their private data collected from mobiledevices. Method: A qualitative study was implemented and primary data werecollected from semi-structured interviews. The conducted data were analysedto understand the underlying concepts of this thesis research question. Anabductive approach was used and involved back-and-forth engagement withthe empirical findings of the social world for theoretical ideas and with thesecondary sources of literature. Conclusion: Consumers’ can experience both positive and negative feelingssimultaneously. The authors conclude that it was not the personalizedmarketing messages themselves that created negative emotions amongconsumers, it was the knowledge and the feeling of knowing that theadvertisements were created from their 'private data. The positive emotionswere connected to the benefits of receiving advertisements that matched theirinterests.
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Rabbi, Ahm Fazle. "Mobile advertisement : a model for designing personalised visual ads for effective brand memory building." Thesis, Southampton Solent University, 2011. http://ssudl.solent.ac.uk/3004/.

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Книги з теми "Personalized advertisements":

1

Kant, Tanya. Making it Personal. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190905088.001.0001.

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The encounter of “personalized experiences”—targeted advertisements, tailored information feeds, and “recommended” content, among other things—is now a common and somewhat inescapable component of digital life. More often than not however, “you” the user are not primarily responsible for personalizing your web engagements: instead, with the help of your search, browsing, and purchase histories, your “likes,” your click-throughs, and a multitude of other data you produce as you go about your day, your experience can “conveniently”—and computationally—be personalized on your behalf. This book explores a host of new questions that emerge from web users’ encounters with these forms of algorithmic personalization. What do users “know” about the algorithms that apparently “know” them? If personalization practices seek to act on users’ behalf (for instance, by deciding what content is personally relevant), then how do users retain or relinquish their autonomy? Indeed, what kinds of selfhoods are made possible when personalization algorithms intervene in identity construction? Making It Personal is the first full-length monograph to critically analyze the sociocultural implications of algorithmic personalization through the accounts and testimonies of web users themselves. At the heart of the book are interviews and focus groups with web users who—through a myriad of resistant, tactical, resigned, or trusting engagements—encounter algorithmic personalization as part of their lived experience on the web. The book proposes that for those who encounter it, algorithmic personalization creates new implications for knowledge production, autonomy, cultural capital, and formations of self.

Частини книг з теми "Personalized advertisements":

1

Shahid, Suleman, Nicole Heise, and Sundas Zaman. "Personalized Persuasion in Online Advertisements: A Case Study of a Micro-Funding Website." In Human-Computer Interaction – INTERACT 2017, 433–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67687-6_29.

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Wang, Jingbing, Zhuolin Hao, Minping Zhou, Jiaze Chen, Hao Zhou, Zhenqiao Song, Jinghao Wang, Jiandong Yang, and Shiguang Ni. "Generating Personalized Titles Incorporating Advertisement Profile." In Database Systems for Advanced Applications, 529–40. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73200-4_37.

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3

Stühmer, Roland, Darko Anicic, Sinan Sen, Jun Ma, Kay-Uwe Schmidt, and Nenad Stojanovic. "Client-Side Event Processing for Personalized Web Advertisement." In On the Move to Meaningful Internet Systems: OTM 2009, 1069–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05151-7_23.

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4

Mogaji, Emmanuel, Sunday Olaleye, and Dandison Ukpabi. "Using AI to Personalise Emotionally Appealing Advertisement." In Digital and Social Media Marketing, 137–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24374-6_10.

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Paolino, Luca, Monica Sebillo, Genoveffa Tortora, Alessandro M. Martellone, David Tacconi, and Giuliana Vitiello. "Dynamic User Modeling for Personalized Advertisement Delivery on Mobile Devices." In Lecture Notes in Business Information Processing, 508–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01112-2_51.

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6

Paolino, Luca, Monica Sebillo, Genoveffa Tortora, Giuliana Vitiello, Alessandro M. Martellone, and David Tacconi. "Dynamic User Modeling for Personalized Advertisement Delivery on Mobile Devices." In Management of the Interconnected World, 411–18. Heidelberg: Physica-Verlag HD, 2010. http://dx.doi.org/10.1007/978-3-7908-2404-9_48.

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Xiao, Guangyi, and Zhiguo Gong. "Personalized Delivery of On–Line Search Advertisement Based on User Interests." In Advances in Data and Web Management, 198–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00672-2_19.

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8

Min, Wook-Hee, and Yun-Gyung Cheong. "An Interactive-Content Technique Based Approach to Generating Personalized Advertisement for Privacy Protection." In Lecture Notes in Computer Science, 185–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02559-4_21.

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9

Chaudhuri, Sougata, Georgios Theocharous, and Mohammad Ghavamzadeh. "Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display." In Machine Learning and Data Mining in Pattern Recognition, 32–46. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62416-7_3.

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10

Debora Dhanya A and Uma Pricilda Jaidev. "Perceived Personalization, Privacy Concern, e-WOM and Consumers' Click Through Intention in Social Advertising." In Research Anthology on Privatizing and Securing Data, 1880–98. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8954-0.ch091.

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Анотація:
Social advertising, ads in social media platforms, have become popular in recent years because of the evolution of internet technologies such as web analytics and big data mining. The content of the social advertisement is tailored in order to personalize the message to the target consumer groups. In an effort to reach the prospects, marketers should focus on the social leads on social networking sites (SNS) to promote and to sell their brands/products. Drawing on, online personalized advertising literature, e-WOM recommendations and increasing privacy concerns and perceived ad personalization (conceptualized as functions of psychological reactance) on SNS leads to avoid such advertisements. The goal of the study is to investigate the impact of perceived personalization, privacy concern, and e-WOM to consumers' behavioral click through intentions towards social ads. This study contributed to the theory of psychological reactance by indicating that the individuals with less privacy concern and personalized recommendations from their contacts on SNS have a smaller amount of reactance towards social advertisements than commercial advertisements by marketers. Suggestions for advertisers, social media marketing practitioners conclude the paper.

Тези доповідей конференцій з теми "Personalized advertisements":

1

Guo, Jing, Caixia Zhang, and Xu Zhang. "System and method for providing personalized advertisements to offline retailer users." In 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS). IEEE, 2017. http://dx.doi.org/10.1109/icsess.2017.8343014.

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2

Liapis, Dimitris, Spyridon Vassilaras, and Gregory S. Yovanof. "Implementing a low-cost, personalized and location based service for delivering advertisements to mobile users." In 2008 3rd International Symposium on Wireless Pervasive Computing (ISWPC). IEEE, 2008. http://dx.doi.org/10.1109/iswpc.2008.4556182.

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3

Zhapparov, Ratbek, and Magauiya Zhussip. "Intelligent Mirror — Personalized Advertisement." In Advances in Memristor Circuits and Bioinspired Systems (WSCAS-2015). Singapore: Research Publishing Services, 2015. http://dx.doi.org/10.3850/978-981-09-4424-7_75.

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4

De Silva, Hansi, Poorna Jayasinghe, Ashen Perera, Sithira Pramudith, and Dharshana Kasthurirathna. "Social media based personalized advertisement engine." In 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA). IEEE, 2017. http://dx.doi.org/10.1109/skima.2017.8294102.

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5

Oshiba, Takashi, Yuichi Koike, Masahiro Tabuchi, and Tomonari Kamba. "Personalized advertisement-duration control for streaming delivery." In the tenth ACM international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/641007.641012.

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6

Kilic, Kemal. "Personalized Advertisement System Based On Computational Intelligence." In 11th Joint Conference on Information Sciences. Paris, France: Atlantis Press, 2008. http://dx.doi.org/10.2991/jcis.2008.5.

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7

Stühmer, Roland, Darko Anicic, Nenad Stojanovic, and Sinan Sen. "Client-side event processing for personalized web advertisement." In the Third ACM International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1619258.1619307.

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8

Al Qudah, Dana A., Alexandra I. Cristea, Suncica Hadzidedic Bazdarevic, Samar Al-Saqqa, and Rizik M. H. Al-Sayyad. "A Taxonomy-Based Evaluation of Personalized E-Advertisement." In 2015 IEEE International Conferences on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; and Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM). IEEE, 2015. http://dx.doi.org/10.1109/cit/iucc/dasc/picom.2015.56.

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Al Qudah, Dana A., Alexandra I. Cristea, Suncica Hadzidedic Bazdarevic, Samar Al-Saqqa, Ali Rodan, and Wei Yang. "Personalized E-Advertisement and Experience: Recommending User Targeted Ads." In 2015 IEEE 12th International Conference on e-Business Engineering (ICEBE). IEEE, 2015. http://dx.doi.org/10.1109/icebe.2015.19.

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10

Hwang, Wei-Hao, Yeong-Sheng Chen, and Tsang-Ming Jiang. "Personalized Internet Advertisement Recommendation Service Based on Keyword Similarity." In 2015 IEEE 39th Annual Computer Software and Applications Conference (COMPSAC). IEEE, 2015. http://dx.doi.org/10.1109/compsac.2015.202.

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