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Explores one of the many exciting advertising research possibilities spawned by the Web, namely the efficacy of banner advertisements designed to lure the browser to an external Web page. Traditional advertising research usually relies on self‐report or memory. With Web advertisement banners, on the other hand, we can track actual behavior. In our pilot study, we demonstrate conclusively that click‐through rate, the percentage of visitors to a Web page clicking on an advertisement banner, can vary according to the advertisement copy. We also find that the imperative call for behavior, “Click here”, has a positive effect. These findings, using a new research method with a new medium, open the door to further advertising and communication research on Web advertisement banners.

This study aims to analyze whether average video watch time or click-through rates (CTR) on YouTube videos are more closely associated with high numbers of views per subscriber using linear regressions.

In 2018, YouTube began releasing CTR data to its video creators. Since 2012, YouTube has emphasized how it favors watch time over clicks in its recommendations to viewers. To the best of the author’s knowledge, this is the first academic study looking at that CTR data to test what matters more for views on YouTube. Is watch time or CTR more important to getting views on YouTube?

The author analyzed new video releases on YouTube. This paper finds almost no or limited evidence that higher percent audience retention or total average watch time per view, respectively, are associated with more views on YouTube. Instead, videos with higher CTR got significantly more views.

The author knows no other study that tests the relative importance of CTR or watch time per view in predicting views for new videos on YouTube.

Endorsement marketing has been widely used to generate consumer attention, interest and purchase decisions among targeted audiences. Internet celebrities who become famous on the Internet are dependent on strategic intimacy to appeal to their followers. Our study aims to examine how multiple exposures to Internet celebrity endorsements influence consumers’ click and purchase decisions in the context of influencer marketing.

Based on a unique and representative dataset, the authors first model consumers’ choices for clicks and purchases with two panel fixed-effect logit models linking clicks and purchases with the frequency of exposure to Internet celebrity endorsement. To further control the endogeneity produced by the intercorrelation between the click and purchase models, the authors also adopt the two-stage Heckman probit structure to jointly estimate the two models using Maximum Likelihood Estimation. Robustness checks confirm the effectiveness of the models.

The results suggest that Internet celebrity endorsement plays a significant role in bringing referral traffic to e-commerce sites but is less helpful in affecting conversion to sales. The impact of repetitive Internet celebrity endorsements on consumers’ click decisions is U-shaped, but the role of Internet celebrities as online retailers will “shape-flip” this relationship to a negative linear relation.

Our study is the first to investigate the repetitive exposure effect of Internet celebrity endorsement. The results show a contradictory pattern with a wear-out effect of repetition in the advertising literature. This is the first study to show how the endorsing self, which is a common business model in influencer marketing, moderates the effectiveness of influencer marketing.

The aim of this paper is to examine the impact of three main technologies on converting browsers into customers: impact of review rating (location rating and service rating), recommendation and search listings.

This paper estimates conversion rate model parameters using a quasi-likelihood method with the Bernoulli log-likelihood function and parametric regression model based on the beta distribution.

The results show that a high rank in search listings, a high number of recommendations and location rating have a significant and positive impact on conversion rates. However, service rating and star rating do not have a significant effect on conversion rate. Furthermore, room price and hotel size are negatively associated with conversion rate. It was also found that a high rank in search listings, a high number of recommendations and location rating increase online hotel bookings. Furthermore, it was found that a high number of recommendations increase the conversion rate of hotels with low ranks.

The findings show that hotels’ location ratings are more important than both star and service ratings for the conversion of visitors into customers. Thus, hotels that are located in convenient locations can charge higher prices. The results may also help entrepreneurs who are planning to open new hotels to forecast the conversion rates and demand for specific locations. It was found that a high number of recommendations help to increase the conversion rate of hotels with low ranks. This result suggests that a high numbers of recommendations mitigate the adverse effect of a low rank in search listings on the conversion rate.

This paper contributes to the understanding of the drivers of conversion rates in online channels for the successful implementation of hotel marketing.

To describe how a personal librarian program at a large university developed, has evolved, and continues to function. This paper aims to assist other librarians in developing their own personal librarian programs. It will also assist librarians who are working to connect to students.

To produce this paper, internal documents were reviewed, existing data were investigated, those who assisted in the development of the program were consulted and literature on personal librarian programs was reviewed.

Personal librarian programs can be an efficient way to connect to students and can create awareness about library services, especially without a formal orientation for new students. The personal librarian program discussed here connects the library to a large number of students with little time and effort. Planning is important in developing a working program.

Librarians can use this article to understand how a personal librarians program functions and how it can benefit their libraries. The paper emphasizes revising an existing program to work more effectively and using planning documents and assessment to help an outreach program run smoothly.

This paper details how a personal librarian program was developed and has evolved as well as how the program functions. The value is in the ways in which the program has been revised and has evolved and in the role that planning has taken in creating an effective program.

Summarizes the papers presented at The Second Marketing Science and the Internet Conference entitled: “Understanding Consumer Behaviour on the Internet”, held in Los Angeles, 28‐30 April 2000. Identifies key topical issues and future research agendas. Starts from the premise that research into consumer behaviour in the e‐marketplace is in its infancy, and that a variety of different types of contributions will be necessary to achieve a more informed understanding of consumer behaviour in this new context. Groups current work under four headings: cognition – concerned with the consumer response to specific features embedded in the interface between the consumer and the organisation; customisation – which reviews the various options for personalisation in the marketing exchange, and their effectiveness and acceptability to the consumer; cumulation – which explores the cumulative effect of consumer behaviour on the marketplace; and context – concerned with the relativities between online and traditional retailing and business environments.

The main purpose of this study was to determine whether users of the online social network site, Facebook, actually look at the ads displayed (briefly, to test the existence of the phenomenon known as “banner blindness” in this website), thus ascertaining the effectiveness of paid advertising, and comparing it with the number of friends' recommendations seen.

In order to achieve this goal, an experiment using eye‐tracking technology was administered to a total of 20 participants from a major university in the USA, followed by a questionnaire.

Findings show that online ads attract less attention levels than friends' recommendations. A possible explanation for this phenomenon may be related to the fact that ads on Facebook are outside of the F‐shaped visual pattern range, causing a state of “banner blindness”. Results also show that statistically there is no difference in ads seen and clicked between women and men.

The sample type (undergraduate and graduate students) and the sample size (20 participants) inhibit the generalization of the findings to other populations.

The paper includes implications for the development of an effective online advertising campaign, as well as some proposed conceptualizations of the terms social network site and advertising, which can be used as platforms for discussion or as standards for future definitions.

This study fulfils some identified needs to study advertising effectiveness based on empirical data and to assess banner blindness in other contexts, representative of current internet users' habits.

Many recommender systems are generally unable to provide accurate recommendations to users with limited interaction history, which is known as the cold-start problem. This issue can be resolved by trivial approaches that select random items or the most popular one to recommend to the new users. However, these methods perform poorly in many cases. This paper aims to explore the problem that how to make accurate recommendations for the new users in cold-start scenarios.

In this paper, the authors propose embedded-bandit method, inspired by Word2Vec technique and contextual bandit algorithm. The authors describe user contextual information with item embedding features constructed by Word2Vec. In addition, based on the intelligence measurement model in Crowd Science, the authors propose a new evaluation method to measure the utility of recommendations.

The authors introduce Word2Vec technique for constructing user contextual features, which improved the accuracy of recommendations compared to traditional multi-armed bandit problem. Apart from this, using this study’s intelligence measurement model, the utility also outperforms.

Improving the accuracy of recommendations during the cold-start phase can greatly raise user stickiness and increase user favorability, which in turn contributes to the commercialization of the app.

The algorithm proposed in this paper reflects that user contextual features can be represented by clicked items embedding vector.

Behavioral targeting has become a popular marketing strategy among brands as it enables advertisers to display ads to consumers based on their previous surfing behaviors. The purpose of this paper is to investigate the effectiveness of behaviorally targeted ads for luxury brands and to explore how and when behavioral targeting works.

A 2 (targeted vs non-targeted ads) ×2 (culture: China vs the Netherlands) between-subjects factorial design is conducted to test the hypothesis.

The result reveals that as for luxury brands, behavioral targeting can shorten the psychological distance and in turn lead to a more positive attitude toward the ad. However, the effect of behavioral targeting depends on the culture. In the Netherlands, behavioral targeting can enhance the attitude toward the ad by lowering the psychological distance. However, in China, these effects are mitigated.

This study contributes to the research of online luxury marketing. First, luxury brands should adapt their marketing strategy to different regional markets. In addition, luxury marketers should not worry about a shorter distance with consumers caused by the use of internet. A shorter distance does not mean to reduce an aura of mystery, but to build up a closer relationship with consumers. Luxury brands are not necessary to be aloof and supercilious like an indifferent robot. A closer relationship with consumers brings more positive effects.

The current research makes important contributions both to the scientific literature and to the luxury industry. First, this research reveals the effectiveness and underlying mechanisms of behavioral targeting for luxury brands and also compares the effectiveness of behavioral targeting in two cultures, which contributes to the current cross-cultural studies and international marketing research. Second, this study also helps luxury marketers to realize the importance of behavioral targeting and to know how and when they can use this new marketing strategy in a global environment.

Two recently graduated MBA students are tasked with developing an ad-serving learning algorithm for a mobile ad-serving company. The case illustrates the way in which hypotheses can be tested in an A/B format or “horse race” in order to establish customer preferences and superior profitability. The case was written for a course elective covering hypothesis testing.