The effect of repetition in Internet banner ads and the moderating role of animation

Swipe, tap, read? Unveiling the effects of Touchscreen devices on Emergent Literacy Development in preschoolers

Emergent literacy skills are vital for children's reading and writing development. While touchscreen devices have been linked to enhanced emergent literacy in developed countries, their impact in low- and middle-income countries (LMICs), with limited access to quality apps, is underexplored. Thailand, classified as an upper-middle-income country, presents a unique context with its specific challenges in educational technology, which have not been extensively studied. This study examined the relationship between touchscreen device usage and emergent literacy development in Thai preschool children. Using a cross-sectional design, we analyzed data from 317 Thai children aged 5-6 years, assessing their emergent literacy skills and examining the association with touchscreen device usage through logistic regression analysis. Our findings showed that 79.5% of participants engaged with touchscreen devices, and there was an observed trend suggesting that exclusive tablet users might exhibit enhanced phonological awareness, letter naming, and rapid automatized naming skills. However, these potential improvements did not reach statistical significance when primary caregiver characteristics were taken into account. Our findings highlight the complexity of this relationship and underscore the need for further research to elucidate the potential influences of application quality and screen time engagement on emergent literacy, particularly in LMICs.

Attempts to Attract Eyesight in E-Commerce May Have Negative Effects

E-commerce shop owners often want to attract user attention to a specific product to enhance the chances of sales, to cross-sell, or up-sell. The way of presenting a recommended item is as important as the recommendation algorithms are to gain that attention. In this study, we examined the following types of highlights: background, shadow, animation, and border, as well as the position of the item in a 5 × 2 grid in a furniture online store, and their relationships with user fixations and user interest. We wanted to verify the effects highlighting had on attracting user attention. Various levels of intensity were considered for each highlight: low, medium, and strong. Methods used for data collection were both implicit and explicit: eye tracking, tracking cart's contents, and a supplementary survey. Experimental results showed that a low-intensity background highlight should be the first-choice solution to best attract user attention in the presented shopping scenario, resulting in the best fixation times and most users' selections. However, in the case of the highest-intensity animations, highlighting seemed to have negative effects; despite successful attempts to attract eyesight and a long fixation time, users did not add the highlighted products to cart.

Can exposure to arguments pro and contra extraversion affect self-reports of the trait and the attitude toward it?

OBJECTIVE

Changeability of personality over short-term intervals has increasingly become a focus of research. However, the role played by argumentation interventions in short-term variations has scarcely been examined.

METHODS

In two experiments (N = 363 and 320), we investigated how processing positive and negative argumentation regarding extraversion (Study 1: watching a lecture; Study 2: elaborating self-invented arguments) affects self-reports on this trait and attitude toward it. The experiments included three waves of measurements with argument manipulation (in favor of or against extraversion) immediately prior to Time 2 (Study 2 also included a control group).

RESULTS

Mean-level changes in extraversion across time moments, measured with the longitudinal confirmatory factor analysis, were consistently negligible. Conversely, there were some indications that argumentation about extraversion could have immediate short-term effects on attitudes toward this trait. The random-intercept cross-lagged model showed that rank-order consistency stemmed from a trait-like intercept, which was particularly large for trait extraversion compared with the attitude. The autoregressive and cross-lagged effects of residual within-person variation were consistently small and mostly nonsignificant.

CONCLUSION

Our findings suggest that extraversion and the attitude toward it maintained their temporal continuity within 3 months, even under a single exposure to arguments pro and contra this trait.

Gaze and Event Tracking for Evaluation of Recommendation-Driven Purchase

Recommendation systems play an important role in e-commerce turnover by presenting personalized recommendations. Due to the vast amount of marketing content online, users are less susceptible to these suggestions. In addition to the accuracy of a recommendation, its presentation, layout, and other visual aspects can improve its effectiveness. This study evaluates the visual aspects of recommender interfaces. Vertical and horizontal recommendation layouts are tested, along with different visual intensity levels of item presentation, and conclusions obtained with a number of popular machine learning methods are discussed. Results from the implicit feedback study of the effectiveness of recommending interfaces for four major e-commerce websites are presented. Two different methods of observing user behavior were used, i.e., eye-tracking and document object model (DOM) implicit event tracking in the browser, which allowed collecting a large amount of data related to user activity and physical parameters of recommending interfaces. Results have been analyzed in order to compare the reliability and applicability of both methods. Observations made with eye tracking and event tracking led to similar results regarding recommendation interface evaluation. In general, vertical interfaces showed higher effectiveness compared to horizontal ones, with the first and second positions working best, and the worse performance of horizontal interfaces probably being connected with banner blindness. Neural networks provided the best modeling results of the recommendation-driven purchase (RDP) phenomenon.

The Effects of the Content Elements of Online Banner Ads on Visual Attention: Evidence from An-Eye-Tracking Study

The aim of this paper is to examine the influence of the content elements of online banner ads on customers’ visual attention, and to evaluate the impacts of gender, discount rate and brand familiarity on this issue. An eye-tracking study with 34 participants (18 male and 16 female) was conducted, in which the participants were presented with eight types of online banner ads comprising three content elements—namely brand, discount rate and image—while their eye movements were recorded. The results showed that the image was the most attractive area among the three main content elements. Furthermore, the middle areas of the banners were noticed first, and areas located on the left side were mostly noticed earlier than those on the right side. The results also indicated that the discount areas of banners with higher discount rates were more attractive and eye-catching compared to those of banners with lower discount rates. In addition to these, the participants who were familiar with the brand mostly concentrated on the discount area, while those who were unfamiliar with the brand mostly paid attention to the image area. The findings from this study will assist marketers in creating more effective and efficient online banner ads that appeal to customers, ultimately fostering positive attitudes towards the advertisement.

Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities

Recommender systems are widely used to provide users with recommendations based on their preferences. With the ever-growing volume of information online, recommender systems have been a useful tool to overcome information overload. The utilization of recommender systems cannot be overstated, given its potential influence to ameliorate many over-choice challenges. There are many types of recommendation systems with different methodologies and concepts. Various applications have adopted recommendation systems, including e-commerce, healthcare, transportation, agriculture, and media. This paper provides the current landscape of recommender systems research and identifies directions in the field in various applications. This article provides an overview of the current state of the art in recommendation systems, their types, challenges, limitations, and business adoptions. To assess the quality of a recommendation system, qualitative evaluation metrics are discussed in the paper.

Congruence Effects on the Effectiveness of Sponsorship of Sport Event Websites: An Experimental Approach

Emerging online marketing strategies are an opportunity for the sport sponsorship industry as a way of complementing traditional methods. However, in-depth attention has not been given to the study of congruence effects on the effectiveness of sponsorship of sport event websites, and specifically to study the role and effects of sponsor logos. The main aim of this study was to evaluate the congruence effect of sponsor brands featured on the website of a sports event on sponsorship effectiveness in visual, attitude-related and behavioural terms, using an eye-tracker to monitor memory activation and changes in attitudes and intentions. In study 1, the role of congruence on website sponsorship was analysed, using real brands sponsoring the ninth edition of the “Mallorca 312” Cycletourist Tour (42 participants). In study 2, the congruence of fictitious brands was analysed on the effects of website sponsorship of the 37th edition of the MAPFRE (competitions brand name) Copa del Rey regatta (101 participants). Congruence is preferable to incongruence in sponsor brands, except when the sponsorship aims to boost a recall of new market brands. The results validate the importance of managing congruence levels in the online sponsorship of sports events due to the influence on sponsorship effectiveness and its impact on cognitive processing.

Deep Learning-Enhanced Framework for Performance Evaluation of a Recommending Interface with Varied Recommendation Position and Intensity Based on Eye-Tracking Equipment Data Processing

The increasing amount of marketing content in e-commerce websites results in the limited attention of users. For recommender systems, the way recommended items are presented becomes as important as the underlying algorithms for product selection. In order to improve the effectiveness of content presentation, marketing experts experiment with the layout and other visual aspects of website elements to find the most suitable solution. This study investigates those aspects for a recommending interface. We propose a framework for performance evaluation of a recommending interface, which takes into consideration individual user characteristics and goals. At the heart of the proposed solution is a deep neutral network trained to predict the efficiency a particular recommendation presented in a selected position and with a chosen degree of intensity. The proposed Performance Evaluation of a Recommending Interface (PERI) framework can be used to automate an optimal recommending interface adjustment according to the characteristics of the user and their goals. The experimental results from the study are based on research-grade measurement electronics equipment Gazepoint GP3 eye-tracker data, together with synthetic data that were used to perform pre-assessment training of the neural network.