Adapting Human-Computer-Interaction of Attentive Smart Glasses to the Trade-Off Conflict in Purchase Decisions: An Experiment in a Virtual Supermarket

Pfeiffer, Jella; Pfeiffer, Thies; Greif-Winzrieth, Anke; Meißner, Martin; Renner, Patrick; Weinhardt, Christof

doi:10.1007/978-3-319-58628-1_18

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…ET has a rich history of research in a wide range of contexts, including, in particular, consumer behavior, due to its non-invasiveness. Several studies have used ET to examine, for example, the effect of smell on eye-catching behavior and memory ( Tomono et al, 2011 ), information processing and attention ( Pfeiffer et al, 2017 ), customer’s impulsivity ( Moghaddasi et al, 2021 ), perceived realism ( Carlson et al, 2011 ; Meißner et al, 2017 ) and perceived presence ( Tonkin et al, 2011 ), product or brand choice ( Siegrist et al, 2019 ), and purchase decisions ( Bigné et al, 2016 ). Khatri et al (2020) also used eye gazes to classify consumers’ ages in a virtual store.…”

Section: Literature Reviewmentioning

confidence: 99%

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store

et al. 2022

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Virtual reality (VR) is a useful tool to study consumer behavior while they are immersed in a realistic scenario. Among several other factors, personality traits have been shown to have a substantial influence on purchasing behavior. The primary objective of this study was to classify consumers based on the Big Five personality domains using their behavior while performing different tasks in a virtual shop. The personality recognition was ascertained using behavioral measures received from VR hardware, including eye-tracking, navigation, posture and interaction. Responses from 60 participants were collected while performing free and directed search tasks in a virtual hypermarket. A set of behavioral features was processed, and the personality domains were recognized using a statistical supervised machine learning classifier algorithm via a support vector machine. The results suggest that the open-mindedness personality type can be classified using eye gaze patterns, while extraversion is related to posture and interactions. However, a combination of signals must be exhibited to detect conscientiousness and negative emotionality. The combination of all measures and tasks provides better classification accuracy for all personality domains. The study indicates that a consumer’s personality can be recognized using the behavioral sensors included in commercial VR devices during a purchase in a virtual retail store.

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Section: Literature Reviewmentioning

confidence: 99%

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store

et al. 2022

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“…The research activities of the chair mainly focused on VR shopping environments (Peukert et al 2018a;b, Pfeiffer et al 2017). Various questions concerning the acceptance of VR shopping environments were addressed (Peukert et al 2019a;, but also how user assistance systems for virtual shopping environments can be designed (Peukert et al 2018a;, Pfeiffer et al 2017. In particular, the concept of detecting different phases in consumers' decision-making process based on real-time analysis of eyetracking data was introduced, aiming at designing context-aware user assistance systems (Peukert et al 2020).…”

Section: User Experience In Immersive Systemsmentioning

confidence: 99%

Information and Market Engineering at KIT: Quo Vadis?

et al. 2021

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Information systems (IS) are nowadays at the core of many personal and institutional activities and influence daily life more than ever before. To understand, evaluate and envision the forms of how we interact with IS, interdisciplinary and multifaceted research efforts are required. At the Information and Market Engineering chair at the Karlsruhe Institute of Technology, this task is taken head-on via research that stretches from user experiences to system design. In this review, the present research foci at the department are outlined, together with a brief description of its origins and the global developments that underly the necessity of conducting these particular IS studies.

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“…Eye gaze research has progressed to include multiple user platforms with increasing number of applications in human computer interactions [ 6 , 7 , 8 ] marketing, psychology and ecommerce [ 9 , 10 ]. A major aim of eye tracking system design is to achieve high accuracy and consistency in results.…”

Section: Related Work: Accuracy Estimates and Visualizations In Gmentioning

confidence: 99%

Performance Evaluation Strategies for Eye Gaze Estimation Systems with Quantitative Metrics and Visualizations

Kar

Corcoran

2018

Sensors

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An eye tracker’s accuracy and system behavior play critical roles in determining the reliability and usability of eye gaze data obtained from them. However, in contemporary eye gaze research, there exists a lot of ambiguity in the definitions of gaze estimation accuracy parameters and lack of well-defined methods for evaluating the performance of eye tracking systems. In this paper, a set of fully defined evaluation metrics are therefore developed and presented for complete performance characterization of generic commercial eye trackers, when they operate under varying conditions on desktop or mobile platforms. In addition, some useful visualization methods are implemented, which will help in studying the performance and data quality of eye trackers irrespective of their design principles and application areas. Also the concept of a graphical user interface software named GazeVisual v1.1 is proposed that would integrate all these methods and enable general users to effortlessly access the described metrics, generate visualizations and extract valuable information from their own gaze datasets. We intend to present these tools as open resources in future to the eye gaze research community for use and further advancement, as a contribution towards standardization of gaze research outputs and analysis.

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Adapting Human-Computer-Interaction of Attentive Smart Glasses to the Trade-Off Conflict in Purchase Decisions: An Experiment in a Virtual Supermarket

Cited by 5 publications

References 22 publications

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store

Information and Market Engineering at KIT: Quo Vadis?

Performance Evaluation Strategies for Eye Gaze Estimation Systems with Quantitative Metrics and Visualizations

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