Online Advertising Specifics with regards to Unfair Competition Law Abstract This thesis analyses advertising which is strictly connected to the internet environment with regards to the unfair competition law. The importance of unfair competition regulations in the dynamic internet environment is emphasized by presenting the most problematic areas of online advertising. The great flexibility of the general clause is often the only possible way how to prosecute the new methods of online advertising. Due to the insufficient development of the Czech jurisprudence in online advertising, there are judgments of the European Court of Justice and the judgments from other member states presented in this thesis. There are detailed analyses of six different advertising practices - keywords abuse, metatags abuse, linking, fake online reviews, advertisements on online platforms, and ad blocking software. The main goal of the paper is to draw the limits of these six advertising practices by analysing and comparing various fact patterns in foreign judgments. Some of the judgments presented in the thesis are introduced in the Czech legal environment for the first time. Furthermore, the thesis focuses on the specifics which distinguish online advertising from the traditional ones. The specific characteristics of internet...

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21390号 / 情博第676号 / 新制||情||117(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 鹿島 久嗣, 教授 山本 章博, 教授 下平 英寿 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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廣告界有句名言「我知道廣告費有一半是浪費掉了，但問題是，不知道浪費的是哪一半?」 隨著網路普及與近幾年關鍵字廣告興起，可以看出廣告主越來越要求廣告的精準與效益，網路廣告的進化過去傳統以CPM（Cost Per Thousand impressions）每千人的曝光數來計算、到CPC（Cost Per Click）以點擊數來計算如關鍵字廣告、到後來有人提出CPA（Cost Per Action），即保證績效型廣告，以實際銷售業績來計算廣告費，本論文就是在研究一家專門在做保證績效型廣告的公司，也就是通路王。 繼Web2.0被提出後，後來有人提出EC2.0的概念，強調社群的參與，而所有的成交交易均來自網友的推薦。國內前幾名的EC網站都不約而同地推出網路推薦分紅計畫：例如PChome的分紅網、Yahoo!購物中心的興奇大聯盟、博客來的AP策略聯盟。他們的目的無非是想要透過網友的推薦力量以吸引更多新顧客以及增加銷售。而這樣的機制就是所謂聯盟行銷或夥伴計畫。 聯盟行銷在國外行之多年，相關介紹或研究多以推廣者角度，說明如何在上班之外增加其他收入，方法例如可以寫文章賺錢、運用聯盟行銷賺錢等，較少著墨於網路聯盟平台與廣告主之間的合作關係。為使國內聯盟行銷能發展更成熟，本研究除列舉國內外幾家運用聯盟行銷之實例，另以個案「網路聯盟平台」業者之經營模式及其合作廠商之關係，以本研究相關文獻理論進行檢視與驗證，並選定三家廣告主以深度訪談方式進行分析。 從研究結果發現，網際網路之聯盟行銷技術，對於建立顧客關係、增加商品銷售為有幫助之作法；網路聯盟平台的推廣者是成交的關鍵，推廣者品質關係到銷售力道，因此建議通路王應加強平台推廣者的訓練與管理，以強化與廣告主的合作關係。

Cette thèse est consacrée à l’étude des systèmes de recommandation basés sur des réseaux de neurones artificiels appris pour faire de l'ordonnancement de produits avec des retours implicites (sous forme de clics). Dans ce sens, nous proposons un nouveau modèle neuronal qui apprend conjointement la représentation des utilisateurs et des produits dans un espace latent, ainsi que la relation de préférence des utilisateurs sur les produits. Nous montrons que le modèle proposé est apprenable au sens du principe de la minimisation du risque empirique et performant par rapport aux autres modèles de l'état de l'art sur plusieurs collections. En outre, nous contribuons à la création de deux nouvelles collections, produites grâce aux enregistrements des comportements de clients de Kelkoo (https://www.kelkoo.com/); le leader européen de la publicité programmatique et de Purch (http://www.purch.com/). Les deux jeux de données recueillent des retours implicites des utilisateurs sur des produits, ainsi qu’un grand nombre d'informations contextuelles concernant à la fois les clients et les produits. La collections de données de Purch contient en plus une information sur la popularité des produits ainsi que des commentaires textuelles associés. Nous proposons, une stratégie simple et efficace sur la manière de prendre en compte le biais de la popularité ainsi qu'un modèle probabiliste latent temporel pour extraire automatiquement les thèmes des textes des commentaires.Mots clés. Systèmes de recommandation, apprentissage d'ordonnancement, réseaux de neurones, recommandations avec des retours implicites, Modèles probabilistes latents temporels / This thesis is dedicated to the study of Recommendation Systems for implicit feedback (clicks) mostly using Learning-to-rank and neural network based approaches. In this line, we derive a novel Neural-Network model that jointly learns a new representation of users and items in an embedded space as well as the preference relation of users over the pairs of items and give theoretical analysis. In addition we contribute to the creation of two novel, publicly available, collections for recommendations that record the behavior of customers of European Leaders in eCommerce advertising, Kelkoofootnote{url{https://www.kelkoo.com/}} and Purchfootnote{label{purch}url{http://www.purch.com/}}. Both datasets gather implicit feedback, in form of clicks, of users, along with a rich set of contextual features regarding both customers and offers. Purch's dataset, is affected by popularity bias. Therefore, we propose a simple yet effective strategy on how to overcome the popularity bias introduced while designing an efficient and scalable recommendation algorithm by introducing diversity based on an appropriate representation of items. Further, this collection contains contextual information about offers in form of text. We make use of this textual information in novel time-aware topic models and show the use of topics as contextual information in Factorization Machines that improves performance. In this vein and in conjunction with a detailed description of the datasets, we show the performance of six state-of-the-art recommender models.Keywords. Recommendation Systems, Data Sets, Learning-to-Rank, Neural Network, Popularity Bias, Diverse Recommendations, Contextual information, Topic Model.

The advent of social media networks is radically changing the way we communicate, shareand socialize. These networks are also creating impact on consumer behavior. In this study,we tried to analyze the factors working behind the intrinsic motivation of people upon whichthey are interacting in the social networks and formulating their preferences.Based on the theory of intrinsic motivation, we identified five factors to be most relevant withthe phenomena we attempted to address which are Curiosity, Power, Status, Tranquility, andIndependence. Among these five factors, we tried to analyze the relative importance of eachone on the buying behavior of users in the form of choosing social media platforms. Westretched out inquiry to the identification of the influence of demographic factors as well.According to our analysis, it has been revealed that the relative importance of curiosity ismore than any other factors and it also has a strong association with the nationality of theuser. Again, status has been identified as the second most important factor however; itshowed no association with any demographic factor.To conduct this study, we have taken a qualitative approach. Our philosophical underpinningsare based on the positivist and objectivist perspective which defined how we are going toreceive and interpret reality as researchers. However, on more practical terms, we chosesurvey as our data collection method as it allows us to collect mentionable amount of datawithin a short time span and keeps the opportunity of higher statistical analysis open.Regarding the sampling method, we have followed both the non-probability conveniencesampling and Quota sampling method. We have collected our 206 respondents from UmeaUniversity, which was divided by equal half of male and female quota. After collecting thedata, we analyzed it and presented the empirical findings in the chapter 5. Then the analysisrelating to the research question and the hypotheses was presented in the chapter 6 where wealso decided about the null hypotheses on the basis of stringent statistical tests. At the end, wesummed up out findings and proposed some implications and future research possibilities.This study can be helpful to understand the links between human motivation and the userinteraction in the social networks. This kind of relationships has not been fully appreciated inthe literature so far. From a managerial perspective, social media platforms are continuouslybecoming one great route to reach the consumers and engage them with the brands. Thus,understanding the motivation of the users might help the marketers to formulate their strategybetter and they can also take better decisions regarding which kind of social media is to use topromote the products on. As we also studied the demographic factors and one of the uniquecapacities of social media networks is the ability to identify demographic segments veryspecifically, the managers can capitalize on our demographic findings to differentiate theirpromotion on the basis of demographics across various social media platforms.This study has several limitations as time and resource scarcity did not allow us to explore theissue more profoundly. Thus, it has kept many research opportunities open such as exploringthe influence of psychographic factors on the choice of social media, use of user generatedcontent to build a stronger brand profile, identification of extrinsic motivators behind thebuying behavior of users and so on.

This dissertation explores several aspects of the theory in industrial organization. The first chapter builds a model with two cost asymmetric firms who not only have Cournot competition in the spot market but also have the opportunity to trade forward contracts. It is shown that with forward trading, low cost firm not always produces more than high cost firm. In an interior equilibrium, both total output and consumer welfare increase compared to the case without forward trading. When cost function is linear, forward trading is socially beneficial in that low cost firm has higher market share as well as profit share, and that total output, consumer welfare and social welfare increase. The second chapter analyzes duopoly firms' choices among ad-free and ad-supported service with different advertising displays: mandatory advertising where ads are integrated with the main content and cannot be dismissed by users; or optional advertising where users are allowed to dismiss ads at will. The model also takes into account the effect of consumers' heterogeneous ad tastes on their contribution to ad revenues. The results reveal that ad revenues intensify competition, suppress equilibrium prices and profits, and diminish the differentiation effect. The third chapter studies firms' business model choices and pricing decisions when they can choose to provide ad-free service, ad-supported service with cost-per-click (CPC) revenue model or cost-per-mille (CPM) revenue model, or a combination of them in monopoly or duopoly environment. It's shown that offering both types of ad-supported services is not an optimal strategy for a monopolist and that its optimal strategy is to vertically differentiate by providing an ad-supported service and an ad-free service. Furthermore, when the monopolist adopts the CPM-based ad revenue model, the price of the ad-supported service is more sensitive to increases in the marginal ad revenue than the case with the CPC-based model. In the equilibrium of competitive setting, exactly one firm offers an ad-supported service alone while the other firm offers the ad-free service with or without the same type of ad-supported service depending on the ad revenues. / text

Purpose: The aim of this paper is to explain and to create an understanding if personalized advertising online creates value for customers.  Design/methodology/approach: A qualitative study through 14 semi-structured interviews.  Findings: The study found personalized advertising to be seen as value co-creation in some cases, but because privacy concerns exist and affect the perception of advertising, it can in many cases lead to value co-destruction instead. It is thus a consideration between privacy concerns and the perceived value of the personalized advertising that decides if the offering will co-create or co-destroy value.  Research limitations/implications for future research: Our study did not involve respondents’ younger than 21 years old, which could have affected the result as this is a generation seen as technology savvy. Through a quantitative study, future research could try to find extremes in personalities by conducting a survey with a large sample of people in different ages, nationalities, gender, active online, etc. in order to see if there are correlations between for example age and privacy concerns.  Practical implications: One purpose of the study is to provide companies with insights of how different customers perceive personalized advertising online in terms of customer value in order for companies to know how to think when targeting their customers.  Keywords: online advertising, personalized advertising, personalized-privacy paradox, privacy concerns, value creation, value co-creation, value co-destruction.

This master´s thesis aims to analyse the perception of online advertising by the Czech online population and its subsequent segmentation to provide recommendations on how to efficiently use online advertising tools in the Czech internet environment. The thesis is divided into three parts - theoretical, methodological and practical. The theoretical part describes the online advertising environment as such, defines the basic concepts and describes research methods used in the thesis. The methodological part delves deeper into these methods and justifies the reasons behind using them. Finally, the practical part offers detailed insights into the perception of online advertising through in-depth semi-structured interviews that have been further elaborated on and verified using the author´s own questionnaire-based quantitative research, representing the entire Czech online population. The obtained data is used to uncover segments in the Czech online population by means of factor and cluster analyses, after which the profiles of the segments are characterised using the contingency tables. Building on the findings, the final chapter provides recommendations on how best to use different types of online advertising and how to address the individual segments in the most efficient way.

The aim of this diploma thesis is to determine how shopping preferences and customer behavior across selected European markets differentiate in the concept of online stores, how to direct marketing appropriately for the individual markets, thus prepare a local startup e-shop for effective entry into foreign markets. The methods of analysis include basic questionnaire survey of individual markets, comparison and evaluation of own real data from conducted online advertising campaigns, or analysis of internal access statistics from individual e-shops. In conclusion overall results and analyzes of each market are presented, for each market a summary of lessons learned and suitable recommendations to potential effective input is made.