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This conceptual paper provides an overview of eye-tracking technology (ETT) as a process-tracing method to study children’s consumer behavior. This paper aims to provide a literature review of the child as consumer-focused eye-tracking research, identifying theoretical and research gaps. This paper discusses the benefits, drawbacks and ethical implications of ETT and highlights opportunities and best practices for future research.

This paper details eye movement and how ETT captures it. This paper delivers a typology of different approaches to eye-tracking research and presents information about ETT equipment and metrics. This paper also summarizes previous studies using eye tracking to study children. This paper concludes with research questions and topics for future research where ETT can be used to study child consumers in contexts such as playing advergames, using social media and shopping (in-person and online).

ETT is commonly used to assess children’s behavior in a variety of contexts but has scarcely been used to study children’s consumer behavior. ETT has great potential to be used to better understand children as consumers.

To the best of the authors’ knowledge, this is the first paper to review using ETT to study children’s consumer behavior.

In spite of offering clear benefits and increased availability, relatively few service research studies rely on eye-tracking. Therefore, this paper aims to assist service researchers in harnessing the vast capabilities of eye-tracking technologies and methods for their own inquiries.

In addition to systematically reviewing extant research in the service domain and the wider marketing field with respect to the fundamentals and practices of eye-tracking, this paper presents a concise, empirical eye-tracking demonstration. These contributions suggest future outlooks for how to incorporate eye-tracking more effectively in service research.

The systematic literature review informs a comprehensive framework for integrating eye-tracking in service research that comprises research question focus regarding higher-order psychological constructs of interest, appropriate study settings, sample composition, optimal eye-tracking equipment and operationalization considerations.

By establishing a common ground and recommended uses of eye-tracking for service research, this study equips service scholars with the knowledge they need regarding eye-tracking fundamentals, common practices and future outlooks. A simple, empirical example further demonstrates some options for unlocking the unique capabilities of eye-tracking in service research and uncovering the complexities inherent to service experiences and other core service concepts.

This paper compiles and contextualizes insights from existing eye-tracking research, which it uses to draw important lessons for deploying eye-tracking in service domains.

Visual stimuli are integral for the destination selection process, as well as for the delivery of unique, novel and compelling tourist experiences. Emerging techniques, such as eye-tracking, are effective for mapping tourists' visual interests and paths, presenting an opportunity to identify patterns of visual attention, which provide insights into the underlying cognitive processes which underpin experiences. Building on a systematic review of the progress and development of eye-tracking in tourism field, this chapter summarises five main current research contexts for application and five future research directions. It also narrows the gap between eye-tracking and cognitive psychology by critically examining bottom-up and top-down attentional mechanisms.

This paper aims to test the similarity of the results of on-screen eye tracking compared to mobile eye tracking in the context of first fixation location on stimuli.

Three studies were conducted altogether with 117 participants, where the authors compared both methods: stationary eye tracking (Tobii Pro X2-60) and mobile eye tracking (Tobii Pro Glasses 2).

The studies revealed that the reported average first fixation locations from stationary and mobile eye tracking are different. Stationary eye tracking is more affected by a centre fixation bias. Based on the research, it can be concluded that stationary eye tracking is not always suitable for studying consumer perception and behaviour because of the centre viewing bias.

When interpreting the results, researchers should take into account that stationary eye tracking results are affected by a centre fixation bias. Previous stationary eye tracking research should be interpreted with the centre fixation bias in mind. Some of this previous work should be retested using mobile eye tracking. If possible small-scale pilot studies should be included in papers to show that the more appropriate method, less affected by attention biases, was chosen.

Managers should trust research where the ability of package design to attract attention on a shelf is tested using mobile eye tracking. The authors suggest using mobile eye tracking to optimise store shelf planograms, point-of-purchase materials, and shelf layouts. In package design, interpretations of research using stationary eye tracking should consider its centre fixation bias. Managers should also be cautious when interpreting previous stationary eye tracking research (both applied and scientific), knowing that stationary eye tracking is more prone to a centre fixation bias.

While eye tracking research has become more and more popular as a marketing research method, the limitations of the method have not been fully understood by the field. This paper shows that the chosen eye tracking method can influence the results. No such comparative paper about mobile and stationary eye tracking research has been done in the marketing field.

The purpose of this paper is to present a systematic literature review of the application of eye-tracking technology within the field of library and information science. Eye-tracking technology has now reached a level of maturity, which makes the use of the technology more accessible. Subsequently, a growing interest in employing eye tracking as a methodology within library and information science research must be anticipated.

The review follows the guidelines set in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. Two reference databases are searched for relevant references: Library and Information Science Abstracts and Library, Information Science and Technology Abstracts. The main selection criteria are peer-reviewed literature that describes the experimental setting, including which eye-tracking equipment was used, the number of test persons and reports on the eye-tracking measures. Furthermore, this study will report which other methods were applied in combination with eye tracking.

The number of published research utilizing eye-tracking technologies within library and information science (LIS) is still limited although an increase in the use of eye-tracking technologies is observed during recent years.

To the knowledge of the author, this is the first systematic review on eye-tracking technology and application in LIS.

Business process modeling can involve multiple stakeholders, so it is natural that problems may occur during the designing and understanding processes. One way to perceive these problems is to evaluate the comprehension of business process models through the collection of data related to the readers' eye movement via an eye-tracking device. The purpose of this paper is to provide a comprehensive overview of the use of eye-trackers in understanding process models and to offer a research roadmap to challenge the community to address the identified limitations and open issues that require further investigation.

To achieve this goal, Systematic Literature Review (SLR) was performed following good practices from the Evidence-Based Software Engineering's (EBSE) field.

This study resulted in 10 primary studies selected for analysis and data extraction, from the 1,482 initially retrieved. The major findings indicate that the business process community still benefits little from the use of eye-tracking, e.g. not offering sufficient support for inexperienced designers and not having an explicit standardization in its use. These and other findings are synthesized in a research roadmap which results would benefit researchers and practitioners.

In the studies found, the methods used to explore eyes' movement in process models' comprehension analysis were presented as an advantage of the current study. Additionally, another aspect presented in this SRL as an originality is presenting a set of open questions, suggesting valuable topics for future research through a research script (research roadmap).

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

To understand the meaning of a sentence, humans can focus on important words in the sentence, which reflects our eyes staying on each word in different gaze time or times. Thus, some studies utilize eye-tracking values to optimize the attention mechanism in deep learning models. But these studies lack to explain the rationality of this approach. Whether the attention mechanism possesses this feature of human reading needs to be explored.

The authors conducted experiments on a sentiment classification task. Firstly, they obtained eye-tracking values from two open-source eye-tracking corpora to describe the feature of human reading. Then, the machine attention values of each sentence were learned from a sentiment classification model. Finally, a comparison was conducted to analyze machine attention values and eye-tracking values.

Through experiments, the authors found the attention mechanism can focus on important words, such as adjectives, adverbs and sentiment words, which are valuable for judging the sentiment of sentences on the sentiment classification task. It possesses the feature of human reading, focusing on important words in sentences when reading. Due to the insufficient learning of the attention mechanism, some words are wrongly focused. The eye-tracking values can help the attention mechanism correct this error and improve the model performance.

Our research not only provides a reasonable explanation for the study of using eye-tracking values to optimize the attention mechanism but also provides new inspiration for the interpretability of attention mechanism.

This paper aims to examine the effect of domain knowledge on eye-tracking measures and predict readers’ domain knowledge from these measures in a navigational table of contents (N-TOC) system.

A controlled experiment of three reading tasks was conducted in an N-TOC system for 24 postgraduates of Wuhan University. Data including fixation duration, fixation count and inter-scanning transitions were collected and calculated. Participants’ domain knowledge was measured by pre-experiment questionnaires. Logistic regression analysis was leveraged to build the prediction model and the model’s performance was evaluated based on baseline model.

The results showed that novices spent significantly more time in fixating on text area than experts, because of the difficulty of understanding the information of text area. Total fixation duration on text area (TFD_T) was a significantly negative predictor of domain knowledge. The prediction performance of logistic regression model using eye-tracking measures was better than baseline model, with the accuracy, precision and F(β = 1) scores to be 0.71, 0.86, 0.79.

Little research has been reported in literature on investigation of domain knowledge effect on eye-tracking measures during reading and prediction of domain knowledge based on eye-tracking measures. Most studies focus on multimedia learning. With respect to the prediction of domain knowledge, only some studies are found in the field of information search. This paper makes a good contribution to the literature on the effect of domain knowledge on eye-tracking measures during N-TOC reading and predicting domain knowledge.