Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments

Classifying information search behavior helps tailor recommender systems to individual customers’ shopping motives. But how can we identify these motives without requiring users to exert too much effort? Our research goal is to demonstrate that eye tracking can be used at the point of sale to do so. We focus on two frequently investigated shopping motives: goal-directed and exploratory search. To train and test a prediction model, we conducted two eye-tracking experiments in front of supermarket shelves. The first experiment was carried out in immersive virtual reality; the second, in physical reality—in other words, as a field study in a real supermarket. We conducted a virtual reality study, because recently launched virtual shopping environments suggest that there is great interest in using this technology as a retail channel. Our empirical results show that support vector machines allow the correct classification of search motives with 80% accuracy in virtual reality and 85% accuracy in physical reality. Our findings also imply that eye movements allow shopping motives to be identified relatively early in the search process: our models achieve 70% prediction accuracy after only 15 seconds in virtual reality and 75% in physical reality. Applying an ensemble method increases the prediction accuracy substantially, to about 90%. Consequently, the approach that we propose could be used for the satisfiable classification of consumers in practice. Furthermore, both environments’ best predictor variables overlap substantially. This finding provides evidence that in virtual reality, information search behavior might be similar to the one used in physical reality. Finally, we also discuss managerial implications for retailers and companies that are planning to use our technology to personalize a consumer assistance system

Opportunities for using eye tracking technology in manufacturing and logistics: Systematic literature review and research agenda

Workers play essential roles in manufacturing and logistics. Releasing workers from routine tasks and enabling them to focus on creative, value-adding activities can enhance their performance and wellbeing, and it is also key to the successful implementation of Industry 4.0. One technology that can help identify patterns of worker-system interaction is Eye Tracking (ET), which is a non-intrusive technology for measuring human eye movements. ET can provide moment-by-moment insights into the cognitive state of the subject during task execution, which can improve our understanding of how humans behave and make decisions within complex systems. It also enables explorations of the subject’s interaction mode with the working environment. Earlier research has investigated the use of ET in manufacturing and logistics, but the literature is fragmented and has not yet been discussed in a literature review yet. This article therefore conducts a systematic literature review to explore the applications of ET, summarise its benefits, and outline future research opportunities of using ET in manufacturing and logistics. We first propose a conceptual framework to guide our study and then conduct a systematic literature search in scholarly databases, obtaining 71 relevant papers. Building on the proposed framework, we systematically review the use of ET and categorize the identified papers according to their application in manufacturing (product development, production, quality inspection) and logistics. Our results reveal that ET has several use cases in the manufacturing sector, but that its application in logistics has not been studied extensively so far. We summarize the benefits of using ET in terms of process performance, human performance, and work environment and safety, and also discuss the methodological characteristics of the ET literature as well as typical ET measures used. We conclude by illustrating future avenues for ET research in manufacturing and logistics

A brain-machine interface for assistive robotic control

Brain-machine interfaces (BMIs) are the only currently viable means of communication for many individuals suffering from locked-in syndrome (LIS) – profound paralysis that results in severely limited or total loss of voluntary motor control. By inferring user intent from task-modulated neurological signals and then translating those intentions into actions, BMIs can enable LIS patients increased autonomy. Significant effort has been devoted to developing BMIs over the last three decades, but only recently have the combined advances in hardware, software, and methodology provided a setting to realize the translation of this research from the lab into practical, real-world applications. Non-invasive methods, such as those based on the electroencephalogram (EEG), offer the only feasible solution for practical use at the moment, but suffer from limited communication rates and susceptibility to environmental noise. Maximization of the efficacy of each decoded intention, therefore, is critical. This thesis addresses the challenge of implementing a BMI intended for practical use with a focus on an autonomous assistive robot application. First an adaptive EEG- based BMI strategy is developed that relies upon code-modulated visual evoked potentials (c-VEPs) to infer user intent. As voluntary gaze control is typically not available to LIS patients, c-VEP decoding methods under both gaze-dependent and gaze- independent scenarios are explored. Adaptive decoding strategies in both offline and online task conditions are evaluated, and a novel approach to assess ongoing online BMI performance is introduced. Next, an adaptive neural network-based system for assistive robot control is presented that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. Exploratory learning, or “learning by doing,” is an unsupervised method in which the robot is able to build an internal model for motor planning and coordination based on real-time sensory inputs received during exploration. Finally, a software platform intended for practical BMI application use is developed and evaluated. Using online c-VEP methods, users control a simple 2D cursor control game, a basic augmentative and alternative communication tool, and an assistive robot, both manually and via high-level goal-oriented commands

The association of early touchscreen media use with the development of visual attention and executive function

Attention plays a pivotal role in information processing by filtering the potential information available based on individual goals, states, and past experiences. Early attention control is thought to underpin and support executive functions (EFs), which in turn are predictive of later behavioural outcomes. The development of attention and EF is partly subject to environmental influences, such as the use of digital media. There is a rapid increase in accessibility and usability of mobile touchscreen devices (i.e. smartphones and tablets) in the family environment, but rigorous scientific research investigating the impact on the developing mind lags behind the widespread usage. To address this, children with different levels of touchscreen use were followed longitudinally at 12 months, 18 months, and 3.5 years, and tested on attention control (bottom-up, and top-down), and EF (updating, shifting, and inhibiting). Children with high touchscreen use were faster on single (i.e. pop-out) visual search, with the amount of concurrent use associated with the speed of bottom-up attention in a linear manner. This saliency bias was repeatedly found on saccadic control tasks, where steady longitudinal high use was associated with a quickening of attention to peripheral salient onsets with a resulting detriment to top-down performance, i.e. disengagement and inhibition of attention. Finally, top-down difficulties were also seen in EF tasks in high users at 3.5 years, particularly in processes of updating and shifting between abstract mental sets. These results point to an influence of touchscreens use on the emerging attention and EF systems, in a way that experience of salient and contingent digital content elicits automatic biases to bottom-up processing, and displaces competency of top-down control and/or increases reliance on stimulus-response pairings. Future studies are needed to demonstrate causality, and to understand long-term trajectories and the interplay between bottom-up and top-down processes over time

Кибербезопасность в образовательных сетях

The paper discusses the possible impact of digital space on a human, as well as human-related directions in cyber-security analysis in the education: levels of cyber-security, social engineering role in cyber-security of education, “cognitive vaccination”. “A Human” is considered in general meaning, mainly as a learner. The analysis is provided on the basis of experience of hybrid war in Ukraine that have demonstrated the change of the target of military operations from military personnel and critical infrastructure to a human in general. Young people are the vulnerable group that can be the main goal of cognitive operations in long-term perspective, and they are the weakest link of the System.У статті обговорюється можливий вплив цифрового простору на людину, а також пов'язані з людиною напрямки кібербезпеки в освіті: рівні кібербезпеки, роль соціального інжинірингу в кібербезпеці освіти, «когнітивна вакцинація». «Людина» розглядається в загальному значенні, головним чином як та, що навчається. Аналіз надається на основі досвіду гібридної війни в Україні, яка продемонструвала зміну цілей військових операцій з військовослужбовців та критичної інфраструктури на людину загалом. Молодь - це вразлива група, яка може бути основною метою таких операцій в довгостроковій перспективі, і вони є найслабшою ланкою системи.В документе обсуждается возможное влияние цифрового пространства на человека, а также связанные с ним направления в анализе кибербезопасности в образовании: уровни кибербезопасности, роль социальной инженерии в кибербезопасности образования, «когнитивная вакцинация». «Человек» рассматривается в общем смысле, в основном как ученик. Анализ представлен на основе опыта гибридной войны в Украине, которая продемонстрировала изменение цели военных действий с военного персонала и критической инфраструктуры на человека в целом. Молодые люди являются уязвимой группой, которая может быть главной целью когнитивных операций в долгосрочной перспективе, и они являются самым слабым звеном Систем

The Use of Eye-tracking in Information Systems Research: A Literature Review of the Last Decade

Eye-trackers provide continuous information on individuals’ gaze behavior. Due to the increasing popularity of eye- tracking in the information systems (IS) field, we reviewed how past research has used eye-tracking to inform future research. Accordingly, we conducted a literature review to describe the use of eye-tracking in IS research based on a sample of 113 empirical papers published since 2008 in IS journals and conference proceedings. Specifically, we examined the methodologies and experimental settings used in eye-tracking IS research and how eye-tracking can be used to inform the IS field. We found that IS research that used eye-tracking varies in its methodological and theoretical complexity. Research on pattern analysis shows promise since such research develops a broader range of analysis methodologies. The potential of eye-tracking remains unfulfilled in the IS field since past research has mostly focused on attention-related constructs and used fixation count metrics on desktop computers. We call for researchers to utilize eye-tracking more broadly in IS research by extending the type of metrics they use, the analyses they perform, and the constructs they investigate