How does website design in the e-banking sector affect customer attitudes and behaviour?

This thesis researches the interface between ebanks and their customers. An industry traditionally based upon personal contact, the rise of ebanking has changed this relationship such that transactions are now mainly conducted via website interfaces. The resultant loss of personal contact between bank and customer has removed many of the cues available to customers upon which judgments of service, reliability and trust were made. The question raised by this change is: what factors influence consumer choice when viewing bank websites? The arguments of this thesis are that user evaluation of websites and their willingness to use those websites is based not only on user centred factors such as motivation, experience and knowledge but also upon their appraisal of website structure and content

UEyes: Understanding Visual Saliency across User Interface Types

Funding Information: This work was supported by Aalto University’s Department of Information and Communications Engineering, the Finnish Center for Artifcial Intelligence (FCAI), the Academy of Finland through the projects Human Automata (grant 328813) and BAD (grant 318559), the Horizon 2020 FET program of the European Union (grant CHISTERA-20-BCI-001), and the European Innovation Council Pathfnder program (SYMBIOTIK project, grant 101071147). We appreciate Chuhan Jiao’s initial implementation of the baseline methods for saliency prediction and active discussion with Yao (Marc) Wang. Publisher Copyright: © 2023 Owner/Author.While user interfaces (UIs) display elements such as images and text in a grid-based layout, UI types differ significantly in the number of elements and how they are displayed. For example, webpage designs rely heavily on images and text, whereas desktop UIs tend to feature numerous small images. To examine how such differences affect the way users look at UIs, we collected and analyzed a large eye-tracking-based dataset, UEyes (62 participants and 1,980 UI screenshots), covering four major UI types: webpage, desktop UI, mobile UI, and poster. We analyze its differences in biases related to such factors as color, location, and gaze direction. We also compare state-of-the-art predictive models and propose improvements for better capturing typical tendencies across UI types. Both the dataset and the models are publicly available.Peer reviewe

Investigating website usability and behavioural intention for online hotel reservations: a cognitive perspective

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The problem area identified for this research is to define the cognitive factors and Customers’ Critical Information Requirements (CCIRs) that affect the customer decision making process when they book their hotel reservations online. The purpose of this study is to define the CCIRs and the (re)design specifications of the website which will be noticed by the users through to completing the booking, without losing them during the decision making process. A combination of various cognitive analysis and eyetracking techniques were applied in order to understand in real time the customer’s decision making process during their online hotel booking process. This includes methods that identify user’s online previous and present experiences, methods that assess and result in the specification of usability and (re)design guidelines. Techniques for eliciting CCIRs in real time are facilitated through the simultaneous usage of eye tracking technology, think aloud expression and video recording. Finally, a validation study was conducted in order to confirm the research findings. A key outcome of this research is a novel, robust and precision approach that (i) combines cognitive task analysis, eye tracking techniques, statistical and clustering methods in order to facilitate the precise identification of both explicit and tacit CCIRs; (ii) for the first time provides a time frame analysis of CCIRs across each stage of the customer’s decision making process and identifies the concomitant decision points where the customer is most likely to abandon the web site; (iii) elicits the mental model of the customer together with the CCIRs and uses this knowledge as the basis for generating the re-design specification for the website; and, (iv) evaluates whether there is a significant improvement in the usability and cognitive utility of the redesigned website that is of practical value to hotels. A further theoretical contribution is the “CCIRs informed decision making process model” for the (re)design of hotel websites as a result of applying our novel and innovative approach. Moreover, I have demonstrated for the first time how our approach can be applied to theory building of CCIRs-based cognitive task models that explicitly define the customer’s decision making process. The above mentioned methodology and theoretical outputs of this research are generally applicable to other industry sectors beyond the hotel industry. For example, financial trading decision support systems, air traffic control displays, mobile phone apps, i.e. to name a few from the myriad of possible applications

Modelling stress levels based on physiological responses to web contents

Capturing data on user experience of web applications and browsing is important in many ways. For instance, web designers and developers may find such data quite useful in enhancing navigational features of web pages; rehabilitation therapists, mental-health specialists and other biomedical personnel regularly use computer simulations to monitor and control the behaviour of patients. Marketing and law enforcement agencies are probably two of the most common beneficiaries of such data - with the success of online marketing increasingly requiring a good understanding of customers' online behaviour. On the other hand, law enforcement agents have for long been using lie detection methods - typically relying on human physiological functions - to determine the likelihood of falsehood in interrogations. Quite often, online user experience is studied via tangible measures such as task completion time, surveys and comprehensive tests from which data attributes are generated. Prediction of users' stress level and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time interval. However, such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording errors. We propose a novel method - PHYCOB I - that addresses the foregoing issues. Primary data were obtained from laboratory experiments during which forty-four volunteers had their synchronized physiological readings - Skin Conductance Response, Skin Temperature, Eye tracker sensors and users activity attributes taken by a specially designed sensing device. PHYCOB I then collects secondary data attributes from these synchronized physiological readings and uses them for two purposes. Firstly, naturally arising structures in the data are detected via identifying optimal responses and high level tonic phases and secondly users are classified into three different stress levels. The method's novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates by simply computing the delay for each increase in amplitude in reaction to webpages contents. This addresses the problem of latency faced in most physiological readings. Performance comparisons are made with conventional predictive methods such as Neural Network and Logistic Regression whereas multiple runs of the Forward Search algorithm and Principal Component Analysis are used to cross-validate the performance. Results show that PHYCOB I outperforms the conventional models in terms of both accuracy and reliability - that is, the average recoverable natural structures for the three models with respect to accuracy and reliability are more consistent within the PHYCOB I environment than with the other two. There are two main advantages of the proposed method - its resistance to over-fitting and its ability to automatically assess human stress levels while dealing with specific web contents. The latter is particularly important in that it can be used to predict which contents of webpages cause stress-induced emotions to users when involved in online activities. There are numerous potential extensions of the model including, but not limited to, applications in law enforcement - detecting abnormal online behaviour; online shopping (marketing) - predicting what captures customers attention and palliative in biomedical application such as detecting levels of stress in patients during physiotherapy sessions

Avoiding Ad Avoidance: Factors Affecting The Perception Of Online Banner Ads

This dissertation examined the effect of search type, ad saliency, and ad repetition on the perception of online banner advertisements. In the first study, 48 student participants conducted simulated search tasks using mixed factorial design where search type (known-item vs. exploratory) was manipulated within-subject and the banner saliency level (low (black and white) vs. medium (color) vs. high (color animation)) was manipulated between subjects. The results showed a significant effect for search type, such that during an exploratory search task the participants had a higher average number of eye fixations on the banner ads compared with known-item search. In addition, there was a significant difference between high and low ad saliency levels, such that participants exposed to low salient ads had a higher average number of eye fixations on the banner ads as compared with high salient ads. There was no significant effect of ad repetition on ad perception. A second study replicated the original experimental design but used four novice Internet users. The results from the second study provide preliminary support to the asymptotic habituation model, which predicts an inverse decline of an orienting response to banner ads as a function of repetition. This dissertation concludes with applicable design recommendation for banner ad deployment to ensure visibility while maintaining a positive user experience.Doctor of Philosoph

A neuroscientific method for assessing effectiveness of digital vs. print ads: using biometric techniques to measure cross-media ad experience and recall

Marketers can choose among various media to convey advertising, ranging from printed advertising on paper to websites through the Internet and mobile through smartphones and tablets. Which medium is the most effective in terms of information memory or reading behavior is not clear, however. In this study, advertisements from an Italian newspaper were presented in three media formats: website (through the Internet with a desktop PC), paper, and a PDF version displayed on a tablet device. Responses to the same news and advertising were measured with eye tracker, electroencephalography brain scanner, and memory test

Visual complexity in human-machine interaction = Visuelle Komplexität in der Mensch-Maschine Interaktion

Visuelle Komplexität wird oft als der Grad an Detail oder Verworrenheit in einem Bild definiert (Snodgrass & Vanderwart, 1980). Diese hat Einfluss auf viele Bereiche des menschlichen Lebens, darunter auch solche, die die Interaktion mit Technologie invol-vieren. So wurden Effekte visueller Komplexität etwa im Straßenverkehr (Edquist et al., 2012; Mace & Pollack, 1983) oder bei der Interaktion mit Software (Alemerien & Magel, 2014) oder Webseiten (Deng & Poole, 2010; Tuch et al., 2011) nachgewie-sen. Obwohl die Erforschung visueller Komplexität bereits bis auf die Gestaltpsycho-logen zurückgeht, welche etwa mit dem Gestaltprinzip der Prägnanz die Bedeutung von Simplizität und Komplexität im Wahrnehmungsprozess verankerten (Koffka, 1935; Wertheimer, 1923), sind weder die Einflussfaktoren visueller Komplexität, noch die Zusammenhänge mit Blickbewegungen oder mentaler Beanspruchung bisher ab-schließend erforscht. Diese Punkte adressiert die vorliegende Arbeit mithilfe von vier empirischen Forschungsarbeiten. In Studie 1 wird anhand der Komplexität von Videos in Leitwarten sowie der Effekte auf subjektive, physiologische und Leistungsparameter mentaler Beanspruchung die Bedeutung des Konstruktes im Bereich der Mensch-Maschine Interaktion untersucht. Studie 2 betrachtet die dimensionale Struktur und die Bedeutung verschiedener Ein-flussfaktoren visueller Komplexität genauer, wobei unterschiedliches Stimulusmaterial genutzt wird. In Studie 3 werden mithilfe eines experimentellen Ansatzes die Auswir-kungen von Einflussfaktoren visueller Komplexität auf subjektive Bewertungen sowie eine Auswahl okularer Parameter untersucht. Als Stimuli dienen dabei einfache, schwarz-weiße Formenmuster. Zudem werden verschiedene computationale und oku-lare Parameter genutzt, um anhand dieser Komplexitätsbewertungen vorherzusagen. Dieser Ansatz wird in Studie 4 auf Screenshots von Webseiten übertragen, um die Aussagekraft in einem anwendungsnahen Bereich zu untersuchen. Neben vorangegangenen Forschungsarbeiten legen insbesondere die gefundenen Zusammenhänge mit mentaler Beanspruchung nahe, dass visuelle Komplexität ein relevantes Konstrukt im Bereich der Mensch-Maschine Interaktion darstellt. Dabei haben insbesondere quantitative und strukturelle, aber potentiell auch weitere Aspekte Einfluss auf die Bewertung visueller Komplexität sowie auf das Blickverhalten der Be-trachter. Die gewonnenen Ergebnisse erlauben darüber hinaus Rückschlüsse auf die Zusammenhänge mit computationalen Maßen, welche in Kombination mit okularen Parametern gut für die Vorhersage von Komplexitätsbewertungen geeignet sind. Die Erkenntnisse aus den durchgeführten Studien werden im Kontext vorheriger For-schungsarbeiten diskutiert. Daraus wird ein integratives Forschungsmodell visueller Komplexität in der Mensch-Maschine-Interaktion abgeleitet

4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022)

Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 4th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges. Due to the covid pandemic, CARMA 2022 is planned as a virtual and face-to-face conference, simultaneouslyDoménech I De Soria, J.; Vicente Cuervo, MR. (2022). 4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2022.2022.1595