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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.

This study aims to examine the effect of cybersecurity threat and efficacy upon click-through, response to a phishing attack: persuasion and protection motivation in an organizational context.

In a simulated field trial conducted in a financial institute, via PhishMe, employees were randomly sent one of five possible emails using a set persuasion strategy. Participants were then invited to complete an online survey to identify possible protective factors associated with clicking and reporting behavior (N = 2,918). The items of interest included perceived threat severity, threat susceptibility, response efficacy and personal efficacy.

The results indicate that response behaviors vary significantly across different persuasion strategies. Perceptions of threat susceptibility increased the likelihood of reporting behavior beyond clicking behavior. Threat susceptibility and organizational response efficacy were also associated with increased odds of not responding to the simulated phishing email attack.

This study again highlights human susceptibility to phishing attacks in the presence of social engineering strategies. The results suggest heightened awareness of phishing threats and responsibility to personal cybersecurity are key to ensuring secure business environments.

The authors extend existing phishing literature by investigating not only click-through behavior, but also no-response and reporting behaviors. Furthermore, the authors observed the relative effectiveness of persuasion strategies used in phishing emails as they compete to manipulate unsafe email behavior.

This paper aims to develop and test a method of automating, for online retailers, the practice of adaptive selling, which is typically used by salespeople in face-to-face interactions. This method customizes persuasive messages for individual customers as they navigate a retailer’s website.

This paper demonstrates a method for the online implementation of automated adaptive selling using sales influence tactics. Automated adaptive selling is compared to nonadaptive selling in three e-commerce field studies.

The results reveal that adaptive selling is more effective than nonadaptive selling. The click-through rates increased significantly when adaptive selling was used.

This paper highlights the effectiveness of existing theories concerning adaptive human-to-human selling and their utility to online selling. The authors demonstrate the added value of adaptive selling in e-commerce, thereby opening up a novel area of research into adaptive selling online. While the paper focuses on the adjustment of sales influence tactics, other factors could be investigated for adjustment in future research (e.g. prices).

The methods, described in detail, are readily available for implementation by online retailers. The implementations are timely and increasingly valuable as e-commerce expands into interpersonal channels (e.g. instant messengers and social media).

To the authors’ knowledge, this paper is the first to formally implement automated adaptive selling as described in the ISTEA model in an e-commerce setting.

The purpose of this paper is to identify potential competitive relationships among brands by analyzing the dynamic clicking behavior of consumers.

Consumer sequential online click data, collected from JD.com, is used to analyze the dynamic competitive relationship between brands. It is found that the competition intensity across categories of products can differ considerably. Consumers exhibit big differences in purchasing time of durable-like goods, that is, the purchasing probability of such products changes considerably over time. The local polynomial regression model (LPRM) is used to analyze the relationship between brand competition of durable-like goods and the purchasing probability of a particular brand.

The statistical results of collective behaviors show that there is a 90/10 rule for the category durable-like goods, implying that ten percent of the brands account for 90 percent market share in terms of both clicking and purchasing behavior. The dynamic brand cognitive process of impulsive consumers displays an inverted V shape, while cautious consumers display a double V shaped cognitive process. The dynamic consumers’ cognition illustrates that when the brands capture a half of the click volume, the brands’ competitiveness reaches to its peak and makes no significant different from brands accounting for 100 percent of the click volume in terms of the purchasing probability.

There are some limitations to the research, including the limitations imposed by the data set. One of the most serious problems in the data set is that the collected click-stream is desensitized severely, restricting the richness of the conclusions of this study. Second, the data set consists of many other consumer behavioral data, but only the consumer’s clicking behavior is analyzed in this study. Therefore, in future research, the parameters brand browsing by consumers and the time of browsing in each brand should be added as indicators of brand competitive intensity.

The authors study brand competitiveness by analyzing the relationship between the click rate and the purchase likelihood of individual brands for durable-like products. When the brand competitiveness is less than 50 percent, consumers tend to seek a variety of new brands, and their purchase likelihood is positively correlated with the brand competitiveness. Once consumers learn about a particular brand excessively among all other brands at a period of time, the purchase likelihood of its products decreases due to the thinner consumer’s short-term loyalty the brand. Till the brand competitiveness runs up to 100 percent, consumers are most likely to purchase a brand and its product. That indicates brand competitiveness maintain 50 percent of the whole market is most efficient to be profitable, and the performance of costing more to improve the brand competitiveness might make no difference.

There are many studies on brand competition, but most of these research works analyze the brand’s marketing strategy from the perspective of the company. The limitation of this research is that the data are historical and failure to reflect time-variant competition. Some researchers have studied brand competition through consumer behavior, but the shortcoming of these studies is that it does not consider sequentiality of consumer behavior as this study does. Therefore, this study contributes to the literature by using consumers’ sequential clicking behavior and expands the perspective of brand competition research from the angle of consumers. Simultaneously, this paper uses the LPRM to analyze the relationship between consumer clicking behavior and brand competition for the first time, and expands the methodology accordingly.

The purpose of this paper is to focus specifically on the examination of factors influencing the effectiveness of product placement in social media.

Two field experiments were used to test research models and questions. In each experiment, random sampling was used to assign volunteers into groups, controlled by different experimental settings. Questionnaires were distributed to the volunteers in order to collect their attitude toward advertisement, brand impression, and intention to click the advertisement. Their browsing behavior was measured by click through rate, browse depth, and browsing time.

The paper found that the effects of product placement conducts (product prominence and presentation) in social media are similar to the effects of product placement in other media. Also, a match between the vehicle and product would create deeper browsing depth and longer browsing time on the product web site. Product placement on a higher awareness vehicle would be more effective for marketing.

This study makes its contribution in understanding the effectiveness of product placement in social media on delivering a marketing message. The results further highlight the importance of “integrating” the product placement content with its context and its vehicle.

This study aims to address the following research questions: Do the two types of service firms (individual or aggregator) have similar competitiveness on online search ads? How should the two types of service firms select optimal branded keywords to improve search performance? In addition, how do consumers’ search queries influence the service search performance of the two types of service firms?

In this study, the authors conduct an empirical analysis by building a two-stage choice modeling on the process of search engine ranking and consumer click-through decisions. The authors estimate the parameter coefficients and test the hypotheses using maximum likelihood estimation in the logistic regression model.

The empirical findings suggest that consumer response rates are highly dependent upon three aspects (service types, branded keyword strategy and consumer search query). First, the authors found that service aggregators receive greater consumer responses than individual service providers. Second, depending upon the various branded keyword strategies (e.g. generic vs branded, “within-type” vs “cross-type”) implemented by service aggregators or individual firms, the expected consumer responses could be quite different. Finally, customer’s search query, being either generic or branded, also has direct effect and interactive effect with service type on how consumers would response to the sponsored ads in the service search process.

The limitation of the research is twofold. First, conversion rate is not considered in the model estimation due to the nature of the data set. Second, the discussion about the keywords selection strategies is focusing on the hospitality industry. Future research shall further validate the generalizability into other industries.

First, given this competitive advantage, service aggregators should take an aggressive approach to adopting paid search strategy in acquiring new users and enhance its brand salience in the service ecosystem. Second, when considering other competitor’s brand names to include, if a firm is a service provider (e.g. hotel), a strategy that can help it receive higher consumer response would be to use “within-type” rather than “cross-type” branded keyword strategy. If a firm is a service aggregator, a better branded keyword strategy would be to use “across-type” instead of “within-type” approach. In addition, given that consumer’s brand awareness can influence the effectiveness of branded keyword strategy, online service search should target consumers in earlier stages of a decision journey.

The authors believe their theoretical framework can provide actionable solutions to service firms to ease customer’s search process, increase customer’s stickiness using search engines and add value to the customer relationships with all services entities within the digital ecosystem.

This study is the first to expand online search marketing into granule examinations (main and interactive effects of three key factors) in the service search domain. First, the authors differentiate service firms into two categories – online travel aggregators and individual hotels in the model. Second, the authors introduce two sets of new classifications of branded keywords for online service search research (i.e. own versus other brand and “cross-type” versus “within-type” branded keywords). Third, this study integrates service consumers’ search word specificity into the conceptual framework which is often missing in previous online search research.

The study contributes to our understanding of search engine advertising in two main ways. Firstly, we analyze the comparative effectiveness of its campaign parameters. Secondly, we examine the effect of print advertising on search engine advertising

Based on advertising data for a three-year period, we test the hypotheses by means of a path model with the aid of partial least squares.

The advertising budget and the degree of keyword matching yield the greatest effect on the number of signed contracts. The click-through rate and the bid amount contribute, to a lesser extent, to explaining this financial target variance. The number of keywords had no significant effect. The study did not yield significant evidence of print advertising, directly affecting the number of search engine advertisement impressions, but showed an indirect effect of print advertising on the number of conversions, induced directly by search engine advertising.

The multichannel relationship of print and search engine advertising, including its campaign parameters, provides a starting point for future research to provide a coherent methodology for capturing the necessary data, processing the underlying information and evaluating the advertising effects.

The multichannel effect needs to be quantified and taken into account when evaluating print advertising and search advertising campaigns and the future advertising mix is planned.

The study extends the field of search engine advertising in the direction of multichannel effects. In comparison to previous research, empirical evidence on the multichannel usage of print advertising and search engine advertising, related to an overall economic target, is provided.

This paper aims to demonstrate that Facebook likes affect outcomes in nonprofit settings. Specifically, Facebook likes influence affinity to nonprofits, which, in turn, affects fundraising outcomes.

The authors report three studies that establish that relationship. To examine social contagion, Study 1 – an auction field study – relies on selling artwork created by underprivileged youth. To isolate signaling, Study 2 manipulates the number of total Facebook likes on a page. To isolate commitment escalation, Study 3 manipulates whether a participant clicks a Facebook like.

The results show that Facebook likes increase willingness to contribute in nonprofit settings and that the process goes through affinity, as well as through Facebook impressions and bidding intensity. The total number of Facebook likes has a direct signaling effect and an indirect social contagion effect.

The effectiveness of the proposed mechanisms is limited to nonprofit settings and only applies to short-term effects.

Facebook likes serve as both a quality signal and a commitment mechanism. The magnitude of commitment escalation is larger, and the relationship is moderated by familiarity with the organization. Managers should target Facebook likes at those less familiar with the organization and should prioritize getting a potential donor to leave a like as a step leading to donation, in essence mapping a donor journey from prospective to active, where Facebook likes play an essential role in the journey. In a charity auction setting, the donor journey involves an additional step of bidder intensity.

The approach the authors study is shown effective in nonprofit settings but does not appear to extend to corporate social responsibility more broadly.

To the best of the authors’ knowledge, this study is the first investigation to map Facebook likes to a seller’s journey through signals and commitment, as well as the only investigation to map Facebook likes to charity auctions and show the effectiveness of this in the field.

The purpose of this paper is to conceptualize a model for sponsored search advertising by incorporating a number of factors which affect the performance of these ads.

The authors draw upon the professional experience and practitioner as well as academic literature to build and analyze the model. Propositions have been forwarded to delineate the various relationships at work in a sponsored search process.

The extant literature on this topic has so far been unable to provide a holistic overview. The paper offers propositions for explaining the role of various factors like the ad rank, branding, role of ad extensions and how impact of these factors may be sensitive to the device used for search.

This work is derived primarily from practice. It is hope that after due empirical validation, advertisers, users as well as search engines will benefit from this stream of research.

This is one of the first works to analyze a sponsored search ad at a micro level. It brings into focus one of the largely unexplored facets of sponsored search advertising.