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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.

Individuals only click on a very small fraction of the in-app advertisements (ads) they are exposed to. Despite this fact, organizations spend generously placing in-app ads without theoretical knowledge of how the structure and the semantics of in-app ads influence individuals’ clicking behavior. This study aims to identify how the processing of structural and semantic factors leads to clicking behavior.

Based on the limited capacity theory, this paper proposes that the sequential processing of structural and semantic factors leads to clicking behavior. To mirror the sequential process, this paper applies a process-oriented configurational approach and performs a two-step qualitative comparative analysis (QCA) using 262 incidents of exposure to in-app ads.

The results support the proposed sequential processing and show that neither structural nor semantic factors alone lead to clicking behavior. This paper reveals four different paths of sequential processing of in-app ads that lead to clicking behavior. The results show that individuals click on non-animated in-app ads even though these are perceived as irritating or privacy-concerning. When the in-app ads are animated, individuals do only click on them when these are not irritating, privacy-concerning and personalized.

Organizations can use these findings to improve their in-app ads and generate more clicks. This study recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and use bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns.

Organizations can use these findings to improve their in-app ads and generate more clicks. This paper recommends that organizations place in-app ads in a prominent location, design them similar to the design of the app and with bright colors. The advertising message needs to have new and relevant information in a credible and entertaining way. Depending on the degree of personalization, organizations should use different sizes of the in-app ad and only use animation if it is unlikely that the in-app ad caused irritation or privacy concerns.

From the in-app ad perspective, this study is the first to theoretically develop and empirically show the sequential processing of structural and semantic factors of in-app ads. From the methodological perspective, this study applies an advanced configurational two-step QCA approach, which is capable of analyzing sequential processes and is new to marketing research.

From the perspectives of service-dominant logic and social identity theory, this study aims to assess social networking site (SNS) users’ likes as a form of social endorsement as well as its effects on like-clicking behavior, perceived brand value, customer-brand identification and purchase intention. Furthermore, the different effects of social endorsement on the perceived functional, hedonic, social and monetary brand value were investigated so as to support SNS users’ role as value cocreators.

An online survey was administered as a pretest of customer perceptions regarding brands that are liked on SNSs. Next, an experiment was conducted to verify the effects of social endorsement. A mixed-method approach including partial least squares (PLS) and fuzzy set qualitative comparative analysis (fsQCA) was adopted for the data analysis.

The results revealed that like-clicking behavior could be contagious because SNS users exposed to others’ likes were more likely to click the like button themselves. Like-clicking behavior positively influenced the perceived functional, hedonic, social and monetary value of the liked brand. Perceived brand value strengthened customer-brand identification, thereby increasing purchase intention.

Like-based social endorsements were confirmed as a type of value cocreation behavior that benefits the endorsed brand by spreading brand awareness, and increasing customer acquisition and retention. An fsQCA approach was developed to measure the moderating effect of users’ propensity to click the like button on perceived brand value, thus contributing to the advancement of fsQCA.

This study aims to investigate and compare mobile and desktop user search behaviours of the 1300K site, a Korean shopping search engine, by using transaction log analysis.

Transaction logs of 1300K site were collected over a three months’ period, from 1 January to 31 March 2018. The data set of this study consists of 1,149,690 desktop queries, 2,346,938 mobile queries, 2,481,747 desktop browsing activities and 2,550,309 mobile browsing activities. This study quantitatively analyses transaction log of 1300K site.

The results of this study show that mobile usage is higher than desktop usage: there are more mobile sessions than desktop sessions and the number of mobile queries is more than double of desktop queries. Overall, mobile query search behaviours are more simple, targeted and focused than desktop query search behaviours. Also, mobile browsing behaviours are more simple and passive than desktop browsing behaviours. However, mobile click behaviours are more active than desktop click behaviours.

To the best of the authors’ knowledge, this study appears to be the first of its type in Korea that compared search behaviours of a large number of users on desktop computers and mobile phones. To identify various characteristics of user search behaviours, this study analyses users’ directory browsing behaviour and click behaviour as well as query search behaviour. The results of this study can be implemented to address the effective improvement and development of search services and interfaces for different devices.

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.

Since researchers have utilized text signals to develop a mass of within-document visualization analysis tools for reading aid in a long document, there is an increasing need to study the relationship between readers’ behavior of using text signals for navigation and their reading performance in the tools. The purpose of this paper is to combine the text signals using behavior and reading performance in two kinds of analysis tools to verify their relationship and discover whether there is any efficient reading strategy when using text signals to navigate a long document.

The methodology is a case study. The authors reviewed related literature first. After explaining the design ideas, interface and functions of THC-DAT and BOOKMARK, which are two reading tools utilizing two main kinds of text signals, one utilizing topics and the other utilizing headings for reading aid, a case study was presented to collect click data on the text signals of participants and their reading effectiveness (score) and efficiency (time).

The results confirm that the text signals using behavior for navigation has a significant impact on reading efficiency and no impact on reading effectiveness in both BOOKMARK and THC-DAT. The discrete degree of clicks behavior on text signals has an impact on reading efficiency. The using behavior of different types of text signals has different impacts on reading efficiency.

Using text signals for navigation time evenly can help improve reading efficiency. And a basic strategy suggested to readers is focusing on reducing their time to find answers when using text signals for navigation in a long document. As to utilizing the two different kinds of text signals, readers can have different strategies. Accordingly, personalized recommendation based on interval of adjacent clicks will help to improve computer-aided reading tools.

This paper combines the text signals using behavior for navigation and reading performance in two kinds of visual analysis tools, studied the relationship between them and discovers some efficient reading strategies when using text signals for navigation to read a long document.

This paper aims to uncover the drivers of consumer-brand engagement on Facebook, understood here as users’ behavioral responses in the form of clicks, likes, shares and comments. We highlight which content components, interactivity cues (calls to action [CTA]) and media richness (e.g. video, photo and text) are most effective at inducing consumers to exhibit clicking, liking, commenting and sharing behaviors toward branded content.

This study analyzes 757 Facebook-based brand posts from a media and entertainment brand over a 15-week period. It investigates the relationship between interactive cues and media richness with consumer engagement using a negative binomial model.

Results show positive relationships for both interactivity cues and media richness content components on increasing consumer-brand engagement outcomes. The findings add clarity to previous inconsistent findings in the marketing literature. CTAs enhance all four engagement behaviors. Media richness also strongly influences all engagement behaviors, with visual imagery (photos and videos) attracting the most consumer responses.

The sampled posts pertain to one brand (a radio station) and are thus concentrated within the media/entertainment industry, which limits the generalizability of findings. In addition, the authors limit their focus to Facebook but recognize that findings may differ across more visual or textual social networking sites.

The authors uncover the most effective pairings of media richness and interactivity components to trigger marketer-desired, behavioral responses. For sharing, for example, the authors show that photo-based posts are more effective on average than video-based posts. The authors also show that including an interactive call to act to encourage one type of engagement behavior has a near-universal effect in increasing all engagement behaviors.

This study takes two widely used concepts within the communications and advertising literatures – interactivity cues and media richness – and tests their relationship with engagement using real and actual users’ data available via Facebook Insights. This method is more robust than surveys or wall scrapping, as it mitigates Facebook’s algorithm effect. The results produce more consistent relationships than previous content marketing studies to date.

Photos are powerful tools to attract individuals’ attention and convey service experiences. Yet exactly how visual cues in a photo contribute to the perceptions of the staged servicescape, and how these perceptions inspire online booking/reservation behaviors, remains underexplored. Addressing the gap, this study aims to uncover (1) how perceptual information mediated by an online photo contributes to the formation of consumers' holistic perceptions of the service environment and (2) how such consumers' holistic perceptions further influence customers' online purchasing behaviors.

This research adopts an innovative crowdsourcing approach and refers to field data on consumers' online hotel booking behaviors to examine relationships among inferred servicescape dimensions, consumers' holistic perceptions of the mediated servicescape and their actual online booking/reservation behaviors (e.g. page-view and meta-click behaviors).

Confirmatory factor analysis and path analysis indicated that five mediated servicescape dimensions (i.e. color, lighting, furnishings, layout and style) contribute significantly to consumers' perceptions of the mediated servicescape (CPMS) and exert different impacts on CPMS. Connecting the crowdsourced rating and consumer behavioral data, CPMS is found to influence consumers' aggregated page-view and meta-click behavior, especially in the US market.

Building upon servicescape theory, the medium theory and the online booking literature, this research proposes a novel conceptual framework of CPMS to theorize the process by which visual cues in online photos contribute to CPMS and subsequent online purchase behaviors. Findings from this research extend Bitner's servicescape framework to mediated service contexts and provide practical implications for promoting service businesses.

Incorporating users’ behavior patterns could help in the ranking process. Different click models (CMs) are introduced to model the sophisticated search-time behavior of users among which commonly used the triple of attractiveness, examination and satisfaction. Inspired by this fact and considering the psychological definitions of these concepts, this paper aims to propose a novel learning to rank by redefining these concepts. The attractiveness and examination factors could be calculated using a limited subset of information retrieval (IR) features by the random forest algorithm, and then they are combined with each other to predicate the satisfaction factor which is considered as the relevance level.

The attractiveness and examination factors of a given document are usually considered as its perceived relevance and the fast scan of its snippet, respectively. Here, attractiveness and examination factors are regarded as the click-count and the investigation rate, respectively. Also, the satisfaction of a document is supposed to be the same as its relevance level for a given query. This idea is supported by the strong correlation between attractiveness-satisfaction and the examination-satisfaction. Applying random forest algorithm, the attractiveness and examination factors are calculated using a very limited set of the primitive features of query-document pairs. Then, by using the ordered weighted averaging operator, these factors are aggregated to estimate the satisfaction.

Experimental results on MSLR-WEB10K and WCL2R data sets show the superiority of this algorithm over the state-of-the-art ranking algorithms in terms of P@n and NDCG criteria. The enhancement is more noticeable in top-ranked items which are reviewed more by the users.

This paper proposes a novel learning to rank based on the redefinition of major building blocks of the CMs which are the attractiveness, examination and satisfactory. It proposes a method to use a very limited number of selected IR features to estimate the attractiveness and examination factors and then combines these factors to predicate the satisfactory which is regarded as the relevance level of a document with respect to a given query.

The headlines of online news are created carefully to influence audience news selection today. The purpose of this paper is to investigate the relationships between news headline presentation and users’ clicking behavior.

Two types of unobtrusive data were collected and analyzed jointly for this purpose. A two-month server log file containing 39,990,200 clickstream records was obtained from an institutional news site. A clickstream data analysis was conducted at the footprint and movement levels, which extracted 98,016 clicks received by 7,120 headlines ever displayed on the homepage. Meanwhile, the presentation of these headlines was characterized from seven dimensions, i.e. position, format, text length, use of numbers, use of punctuation marks, recency and popularity, based on the layout and content crawled from the homepage.

This study identified a series of presentation characteristics that prompted users to click on the headlines, including placing them in the central T-shaped zones, using images, increasing text length properly for greater clarity, using visually distinctive punctuation marks, and providing recency and popularity indicators.

The findings have valuable implications for news providers in attracting clicks to their headlines. Also, the successful application of nonreactive methods has significant implications for future user studies in both information science and journalism.