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REVIEW 3 major objections 4 minor 42 references

Exploring Augmented Table Setup and Lighting Customization in a Simulated Restaurant to Improve the User Experience

T0 review · 3 major / 4 minor · reviewed 2026-08-12 · deepseek-v4-flash

Pith's one-line read Customizing augmented table decor and lighting in a simulated restaurant improves self-reported experience.

desk verdict A clean, small VR/AR restaurant study with a real confound between customization and active interaction; the causal claim about customization is unsupported, but it is a legitimate exploratory pilot that deserves review with revision. read the letter →

arxiv 2411.10230 v1 pith:M63X7DT3 submitted 2024-11-15 cs.HC

classification cs.HC
keywords augmentedrealityARglassesrestaurantexperiencecustomizationuserpsychologicalownershipsocialacceptabilityperceivedwaitingtime
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper tries to show that letting restaurant guests customize augmented-reality elements of their table and lighting improves the experience, compared with passively viewing a fixed AR setting. The authors built a restaurant scenario inside virtual reality and asked 19 participants to wait for an appetizer under default and customizable conditions, measuring perceived waiting time, emotional state, user experience quality, psychological ownership, and social acceptability. Statistically significant improvements appeared for both customizable table setup and customizable lighting on pragmatic and hedonic UX, pleasure, dominance, psychological ownership, and affect; customizable table setup additionally reduced perceived waiting time and increased arousal, while table-setup customization also lowered perceived safety. If the effect is real, restaurateurs and AR designers have a concrete reason to offer diners control over their immediate environment, and a method for testing such concepts before deployment.

What carries the argument

The central mechanism is the within-subjects pairwise comparison between a default and a customizable variant of each of two manipulable dimensions, table setup and lighting, all presented through an AR-in-VR simulation of a restaurant. Customization was implemented as an interactive tabletop UI operated by hand tracking, letting participants choose flower type and color, table-light type, and lighting intensity and color. The default conditions presented a fixed arrangement (three red roses and a candle; medium white lighting). Statistical significance was assessed with paired samples t-tests on the questionnaire scores.

What would settle it

Give a third group the same final-minute task of touching, selecting, and moving the virtual objects through the same hand-tracked interface, but without any effect on the appearance (a sham customization control); if their perceived waiting time, UX, ownership, and acceptability scores match the customizable conditions, the effects are due to activity rather than customization, and if they match the default condition the customization explanation is supported.

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Extended reading notes

Core claim

The central claim is that customizing an augmented table setup and lighting in a simulated restaurant yields broad self-reported benefits over default presentation. The authors report that customizable table setup significantly reduced perceived waiting time and improved SAM valence, arousal, and dominance; UEQ-S pragmatic, hedonic, and overall quality; POQ psychological ownership and affect; and SAQ interaction and isolation acceptability, while SAQ safety was rated significantly lower. Customizable lighting significantly improved SAM valence and dominance; UEQ-S pragmatic, hedonic, and overall quality; POQ psychological ownership and affect; and SAQ interaction acceptability, with no significant effect on perceived waiting time, arousal, isolation, or safety. These results are offered as evidence that these variables are worth considering for AR applications in restaurants, especially when offering customizable augmented table setup and lighting.

Load-bearing premise

The load-bearing assumption is that the benefits come from offering customization rather than from the extra activity required in the customizable conditions, because participants in those conditions actively selected and adjusted virtual objects during the final minute of the wait while default-condition participants simply waited; if activity or task novelty drives the improvements, the customization-specific conclusion is not supported.

Editorial extensions

If this is right

  • If the effect is real, a restaurant offering AR glasses with editable table decor could shorten the subjectively experienced wait for food, because the table-setup customization condition had significantly lower perceived waiting time.
  • Customizable augmented lighting is a broad UX lever, improving pragmatic and hedonic quality, emotional valence and dominance, and psychological ownership, while leaving perceived waiting time and arousal statistically unchanged.
  • Psychological ownership and emotional affect toward restaurant elements rise when guests choose their own augmented decor or lighting, which the authors connect to prior work linking ownership with customer identification and willingness to pay more.
  • Active AR customization is rated more socially acceptable than passive AR viewing on interaction and, for table setup, isolation dimensions, but table-setup customization lowered perceived safety, so interaction design must address distraction.
  • The paper's stated next steps are to test the combined table-setup-plus-lighting condition, search for a threshold of choice overload, and study shared and social dining contexts; all remain necessary before generalizing to real restaurants.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Inference: The results do not separate customization from the act of actively manipulating the interface, because only customizable conditions asked participants to interact with the objects during the final minute; an active-control condition with the same hand gestures but without choosing would isolate the customization contribution.
  • Inference: The large standardized effects on psychological ownership, especially for lighting, suggest that ownership may be a mediator of the UX and acceptability gains, but the study does not test mediation; a path analysis or larger replication could.
  • Inference: The lowered safety rating for table-setup customization points to a design tension for real restaurants: interactive AR decor may be engaging but could distract diners from physical hazards; future work could test gaze-guided or voice-activated customization that requires less motor attention.
  • Inference: Because the simulated environment used a 360-degree VR image rather than a real physical restaurant, transferring these results to actual AR glasses requires field testing; the paper's AR-in-VR methodology is a reasonable first filter but not a guarantee of real-world equivalence.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 4 minor

Summary. This paper reports a controlled laboratory study (N=19) using a within-subject design in which participants experienced four conditions in a simulated restaurant rendered via a 360-degree VR scene: default table setup, customizable table setup, default lighting, and customizable lighting. The authors measured perceived waiting time, SAM (valence, arousal, dominance), UEQ-S (pragmatic, hedonic, overall), psychological ownership (POQ), and social acceptability (SAQ), and used paired samples t-tests to compare default versus customizable conditions. They report broad statistically significant benefits of customization for UX, emotional state, psychological ownership, and acceptability, and a reduction in perceived waiting time for customizable table setup. The central claim is that offering customizable augmented table setup and lighting improves the restaurant user experience.

Significance. The concept is timely, the use of VR to simulate AR is practical and resource-efficient, and the measurement suite is broad and well-established. If the causal interpretation were valid, the findings would be directly actionable for hospitality AR design and would motivate further field studies. The paper also reports effect sizes for all tests, which is a strength. However, the central causal claim is currently undermined by a systematic confound in the procedure: the customizable conditions differ from the default conditions in more than customization alone. Consequently, the significance of the paper depends on whether the authors can disentangle customization from the active interaction task, which is a fixable but load-bearing issue.

major comments (3)
  1. [Section II.D, Tables I and II] The customizable and default conditions differ not only in customization but also in whether participants performed an active interaction task during the final portion of the wait and whether the moderator prompted them. In customizable conditions, after 3 minutes the participant was asked to 'set up the table or lighting as they liked best' and to tell the moderator when finished, whereas in default conditions no such instruction was given and participants waited passively for the full 4 minutes. Therefore, the paired t-tests in Tables I and II contrast 'customization plus activity plus moderator prompting' against 'passive waiting'. This confound is load-bearing for the central claim that customization itself improves UX, perceived waiting time, and psychological ownership. The Discussion in Section IV explicitly attributes the perceived-waiting-time benefit to 'engaging in AR activities', which is exactly the confounded factor, and the limitations paragraph does not acknowledge this confound. An active control condition that holds interaction and prompting constant while removing choice is necessary to support the causal interpretation.
  2. [Section III.A-III.B] The manuscript reports 12 significant paired t-tests for table setup and 8 significant tests for lighting, all judged against a p<0.05 threshold, without any correction for multiple comparisons or a pre-registered analysis plan. Because the dependent variables are correlated constructs drawn from overlapping questionnaires (UEQ-S subscales, SAM dimensions, POQ subscales, SAQ dimensions), the familywise error rate is high, and borderline effects (e.g., SAQ Interaction p=.049 and SAQ Safety p=.031 in Table I) may arise from chance. The authors should report adjusted p-values or explicitly frame the analysis as exploratory.
  3. [Section II.D] The procedure does not state whether the order of the four within-subject conditions was counterbalanced or randomized, nor whether the moderator was blind to the research questions. With N=19 and repeated measures, order and carryover effects can materially change results, and the paper reports no check or model term for order. This omission is load-bearing for the claim that the observed differences are attributable to the manipulation rather than to presentation order, fatigue, or learning effects.
minor comments (4)
  1. [Abstract] The word 'Valence' appears as 'V alence' in the abstract; please remove the stray space.
  2. [Table I] The column header 't d f' appears to be a typographical error for 'df'; also consider labeling the effect-size column explicitly as Cohen's d.
  3. [Section II.D] The exact wording of the moderator's instruction in the customizable conditions is not reported; given the confound discussed above, including the verbatim script in a supplementary appendix would improve transparency.
  4. [Section IV] The limitations paragraph mentions fatigue and the need to imagine other people, but it does not mention the lack of an active control condition; adding this as an explicit limitation would be helpful.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: this is an empirical questionnaire study with no fitted parameters, equations, or self-referential derivations.

full rationale

The paper reports a controlled user study comparing default versus customizable AR table setup and lighting in a simulated restaurant. Its results are paired-sample t-tests on self-reported questionnaire scales (PWT, SAM, UEQ-S, POQ, SAQ). None of these dependent variables is defined in terms of the independent variable, and no parameter is fitted to a subset of the data and then renamed as a prediction. There are no equations whose inputs equal the claimed outputs. The authors cite their own prior work [20] for the SAQ dimensions, but this citation is for scale provenance and does not carry the argument: the reported effects are measured responses, not consequences of that cited framework. The main validity threat is that the customizable conditions required active hand-tracking interaction and moderator prompting after 3 minutes while default conditions involved passive waiting (Section II.D), which could confound activity with customization and undermine causal attribution. That is an experimental design issue, not circularity in the derivation-chain sense targeted by this analysis. No circular step can be quoted because none exists, so the appropriate score is 0.

Assumptions & free parameters 2 free parameters · 5 assumptions · 0 invented entities

The central claim rests on several domain assumptions about simulation validity, self-report validity, and order effects, plus two hand-chosen design parameters. No new physical entities, forces, or theoretical objects are introduced; the concept model organizes existing constructs rather than postulating new ones.

free parameters (2)
  • Waiting duration = 4 minutes
    The fixed wait time chosen by the experimenters before the virtual appetizer arrives. Perceived waiting time is measured after this interval, so the absolute values and some comparisons depend on this hand-chosen design constant.
  • Customization window = 3 minutes
    In the customizable conditions, participants were asked to set up the table or lighting after 3 minutes. This active engagement phase likely drives the differences in engagement, waiting perception, and affect, and is not matched in the default conditions.
assumptions (5)
  • domain assumption The 360-degree VR simulation of the AR restaurant reproduces the relevant psychological experience of real AR glasses in a physical restaurant.
    Cited from prior work [9]-[11], but not validated for social acceptability, waiting time, or restaurant context in this paper. Invoked in Sections II.B and II.D.
  • domain assumption Participants comply with the instruction to imagine themselves in a restaurant with other people and respond as if in a real social setting.
    The procedure script tells participants to imagine the scenario, but no manipulation check for social presence or realism is reported. Section II.D.
  • domain assumption The adapted self-report scales (UEQ-S, SAM, POQ, SAQ) validly measure the intended constructs in this population and context.
    The scales are established, but POQ and SAQ are adapted without reporting validation data for this specific AR restaurant scenario. Section II.D.
  • ad hoc to paper There are no order or carryover effects between the four within-subject conditions.
    No counterbalancing, randomization, or order analysis is described. This assumption is necessary for the paired comparisons to be unbiased. Section II.D.
  • standard math Paired t-test assumptions, including normality of difference scores, are satisfied.
    All inferential claims rest on paired t-tests (Section III), which require these assumptions for valid p-values, especially given the small sample size.

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Cite this review

Pith. "Pith review of Exploring Augmented Table Setup and Lighting Customization in a Simulated Restaurant to Improve the User Experience." pith.science (2026). https://pith.science/paper/M63X7DT3

@misc{pith2026241110230,
  author       = {Pith},
  title        = {Pith review of: Exploring Augmented Table Setup and Lighting Customization in a Simulated Restaurant to Improve the User Experience},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/M63X7DT3}},
  note         = {Machine review of arXiv:2411.10230}
}
read the original abstract

This study explored a concept for using Augmented Reality (AR) glasses to customize augmented table setup and lighting in a restaurant. The aim was to provide insights into AR usage in restaurants and contribute to existing research by introducing an extendable and versatile concept for scholars and restaurateurs. A controlled laboratory study, using a within-subjects design, was conducted to investigate the effects of a customizable augmented table setup and lighting on user experience (UX), perceived waiting time, psychological ownership, and social acceptability. A simulated restaurant environment was created using a 360-degree image in Virtual Reality (VR). The study implemented default and customizable table setup and lighting. Results from a paired samples t-test showed a statistically significant effect of table setup and lighting on the pragmatic quality of UX, hedonic quality of UX, overall UX, valence, dominance, psychological ownership, and affect. Furthermore, table setup had a significant effect on arousal and perceived waiting time. Moreover, table setup significantly affected AR interaction, isolation, and safety acceptability, while lighting only affected AR interaction acceptability. Findings suggest that these investigated variables are worth considering for AR applications in a restaurant, especially when offering customizable augmented table setup and lighting.

Figures

Figures reproduced from arXiv: 2411.10230 by the authors.

Figure 1
Figure 1. Concept Model Customers can customize table setup elements in terms of type (and color) and the lighting in terms of intensity and color. Central to this concept are the customers who can benefit from the customization, whether dining alone, in pairs, or groups. This study investigates the solo experience, shown in black in [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 3
Figure 3. Collage of all lighting intensities in example colors in the lighting [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗

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Reference graph

Works this paper leans on

42 extracted references · 42 canonical work pages

  1. [1]

    AR & VR - worldwide ,

    Statista Market Insights, “ AR & VR - worldwide ,” 2024. [Online]. Available: https://www.statista.com/outlook/amo/ar-vr/worldwide

  2. [2]

    How augmented reality (AR) is transforming the restaurant sector: Investigating the impact of “Le Petit Chef

    W. Batat, “How augmented reality (AR) is transforming the restaurant sector: Investigating the impact of “Le Petit Chef” on customers’ dining experiences,” Technological Forecasting and Social Change , vol. 172, 2021, Art. no. 121013

  3. [3]

    An intelligent dining scene experience,

    A. Kanak, A. ¨Ozl¨u, S. O. Polat, and ¨O. ¨Ozt¨urk Erg ¨un, “An intelligent dining scene experience,” in 2018 26th Signal Processing and Commu- nications Applications Conference (SIU) , 2018

  4. [4]

    Caboni, R

    F. Caboni, R. Bruni, and A. Colamatteo, Applying Augmented Reality in the Italian Food and Dining Industry: Cultural Heritage Perspectives . Springer Series on Cultural Computing, 2021, pp. 293–307

  5. [5]

    Getting started with virtual reality for sensory and consumer science: Current practices and future perspectives,

    Q. J. Wang, F. Barbosa Escobar, P. Alves Da Mota, and C. Velasco, “Getting started with virtual reality for sensory and consumer science: Current practices and future perspectives,” Food Research International, vol. 145, 05 2021, Art. no. 110410

  6. [6]

    From tablet to table: How aug- mented reality influences food desirability,

    W. Fritz, R. Hadi, and A. Stephen, “From tablet to table: How aug- mented reality influences food desirability,” Journal of the Academy of Marketing Science, vol. 51, pp. 503–529, 05 2023

  7. [7]

    Restaurant menus with augmented reality ,

    Onirix, “ Restaurant menus with augmented reality ,” 2024. [Online]. Available: https://www.onirix.com/menus-in-augmented-reality-for-res taurants/

  8. [8]

    We eat first with our (digital) eyes: Enhancing mental simulation of eating experiences via visual- enabling technologies,

    O. Petit, A. Javornik, and C. Velasco, “We eat first with our (digital) eyes: Enhancing mental simulation of eating experiences via visual- enabling technologies,” Journal of Retailing, vol. 98, no. 2, pp. 277–293, 2022

Show all 42 references
  1. [9]

    Evaluating usability and user experience of AR applications in VR simulation,

    J. Lacoche, E. Villain, and A. Foulonneau, “Evaluating usability and user experience of AR applications in VR simulation,” Frontiers in Virtual Reality, vol. 3, 07 2022, Art. no. 881318

  2. [10]

    A prototyping method to simulate wearable augmented reality interaction in a virtual environment - a pilot study,

    G. Alce, K. Hermodsson, M. Wallerg ˚ard, L. Thern, and T. Hadzovic, “A prototyping method to simulate wearable augmented reality interaction in a virtual environment - a pilot study,” International Journal of Virtual World and Human Computer Interaction (VWHCI) , vol. 3, pp. 1...

  3. [11]

    ExProtoV AR: A lightweight tool for experience-focused prototyping of augmented reality applications using virtual reality,

    N. Pfeiffer-Leßmann and T. Pfeiffer, “ExProtoV AR: A lightweight tool for experience-focused prototyping of augmented reality applications using virtual reality,” in HCI International 2018 – Posters’ Extended Abstracts, 2018, pp. 311–318

  4. [12]

    The physical environment as a driver of customers’ service experiences at restaurants,

    U. Walter and B. Edvardsson, “The physical environment as a driver of customers’ service experiences at restaurants,” International Journal of Quality and Service Sciences , vol. 4, no. 2, pp. 104–119, 2012

  5. [13]

    A dining table without food: the floral experience at ethnic fine dining restaurants,

    Y .-C. Chen, P.-L. Tsui, H.-I. Chen, H.-L. Tseng, and C.-S. Lee, “A dining table without food: the floral experience at ethnic fine dining restaurants,” British Food Journal , vol. 122, no. 6, pp. 1819–1832, 05 2020

  6. [14]

    The effects of dining atmospherics: An extended mehrabian–russell model,

    Y . Liu and S. S. Jang, “The effects of dining atmospherics: An extended mehrabian–russell model,” International journal of hospitality management, vol. 28, no. 4, pp. 494–503, 2009

  7. [15]

    Desired privacy and the impact of crowding on customer emotions and approach-avoidance responses: Waiting in a virtual reality restaurant,

    J. Hwang, S.-Y . Yoon, and L. J. Bendle, “Desired privacy and the impact of crowding on customer emotions and approach-avoidance responses: Waiting in a virtual reality restaurant,” International Journal of Contemporary Hospitality Management , vol. 24, no. 2, pp. 224–250, 2012

  8. [16]

    Tasting atmospherics: Taste associations with colour parameters of coffee shop interiors,

    K. Motoki, A. Takahashi, and C. Spence, “Tasting atmospherics: Taste associations with colour parameters of coffee shop interiors,” Food Quality and Preference , vol. 94, 06 2021, Art. no. 104315

  9. [17]

    Interior design in restaurants as a factor influencing customer satisfaction,

    M. Pecoti ´c, V . Bazdan, and J. Samardˇzija, “Interior design in restaurants as a factor influencing customer satisfaction,” RIThink, vol. 4, pp. 10–14, 2014. [Online]. Available: https://rithink.hr/brochure/pdf/vol4 2 014/10-14.pdf

  10. [18]

    Assessing the impact of the tableware and other contextual variables on multisensory flavour perception,

    C. Spence, V . Harrar, and B. Piqueras-Fiszman, “Assessing the impact of the tableware and other contextual variables on multisensory flavour perception,” Flavour, vol. 1, 2012, Art. no. 7

  11. [19]

    Spence, Atmospheric Effects on Eating and Drinking: A Review

    C. Spence, Atmospheric Effects on Eating and Drinking: A Review . Springer Nature Switzerland AG 2020, 05 2020, pp. 257–275

  12. [20]

    Influence of interactivity and social environments on user experience and social acceptability in virtual reality,

    M. Vergari, T. Koji ´c, F. V ona, F. Garzotto, S. M ¨oller, and J.-N. V oigt- Antons, “Influence of interactivity and social environments on user experience and social acceptability in virtual reality,” in 2021 IEEE Virtual Reality and 3D User Interfaces (VR) , 2021, pp. 695–704

  13. [21]

    Performer vs. observer: whose comfort level should we consider when examining the social acceptability of input modalities for head-worn display?

    F. Alallah, A. Neshati, Y . Sakamoto, K. Hasan, E. Lank, A. Bunt, and P. Irani, “Performer vs. observer: whose comfort level should we consider when examining the social acceptability of input modalities for head-worn display?” in VRST ’18: Proceedings of the 24th ACM Symposiu...

  14. [22]

    Augmented reality smart glasses (ARSG) visitor adoption in cultural tourism,

    D.-I. D. Han, M. C. tom Dieck, and T. Jung, “Augmented reality smart glasses (ARSG) visitor adoption in cultural tourism,” Leisure Studies , vol. 38, no. 5, pp. 618–633, 2019

  15. [23]

    In situ with bystanders of aug- mented reality glasses: Perspectives on recording and privacy-mediating technologies,

    T. Denning, Z. Dehlawi, and T. Kohno, “In situ with bystanders of aug- mented reality glasses: Perspectives on recording and privacy-mediating technologies,” in CHI’14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , 2014, p. 2377–2386

  16. [24]

    Don’t look at me that way! - Un- derstanding user attitudes towards data glasses usage,

    M. Koelle, M. Kranz, and A. M ¨oller, “Don’t look at me that way! - Un- derstanding user attitudes towards data glasses usage,” inMobileHCI’15: Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services , 2015, p. 362–372

  17. [25]

    Social acceptability of virtual reality interaction: Experiential factors and design implications,

    P. Eghbali, “Social acceptability of virtual reality interaction: Experiential factors and design implications,” Master’s Thesis, Tampere University of technology, 2018. [Online]. Available: https://urn.fi/URN: NBN:fi:tty-201811212690

  18. [26]

    Who owns what? Psycho- logical ownership in shared augmented reality,

    L. Poretski, O. Arazy, J. Lanir, and O. Nov, “Who owns what? Psycho- logical ownership in shared augmented reality,” International Journal of Human-Computer Studies, vol. 150, 2021, Art. no. 102611

  19. [27]

    Psychological ownership theory: An ex- ploratory application in the restaurant industry,

    V . Asatryan and H. Oh, “Psychological ownership theory: An ex- ploratory application in the restaurant industry,” Journal of Hospitality & Tourism Research, vol. 32, no. 3, pp. 363–386, 2008

  20. [28]

    What’s mine is a hologram? How shared augmented reality augments psychological ownership,

    A. Carrozzi, M. Chylinski, J. Heller, T. Hilken, D. I. Keeling, and K. de Ruyter, “What’s mine is a hologram? How shared augmented reality augments psychological ownership,” Journal of Interactive Mar- keting, vol. 48, no. 1, pp. 71–88, 2019

  21. [29]

    Perceived waiting time and waiting satisfaction: a systematic literature review,

    J. Worlitz, D. Linh, L. Hettling, and R. Woll, “Perceived waiting time and waiting satisfaction: a systematic literature review,” in 22th Quality Manage. and Organisational Develop. Int. Conf. on Quality and Service Sciences (QMOD/ICQSS ‘19) , 01 2020

  22. [30]

    The influence of colour of lighting on customers’ waiting time perceptions,

    B. Bilgili, E. Ozkul, and E. Koc, “The influence of colour of lighting on customers’ waiting time perceptions,” Total Quality Management & Business Excellence, vol. 31, no. 9-10, pp. 1098–1111, 04 2020

  23. [31]

    Waiting time influence on the satisfaction- loyalty relationship in services,

    F. Bielen and N. Demoulin, “Waiting time influence on the satisfaction- loyalty relationship in services,” Managing Service Quality: An Inter- national Journal, vol. 17, no. 2, pp. 174–193, 03 2007

  24. [32]

    Effects of waiting on the satisfaction with the service: Beyond objective time measures,

    A. Pruyn and A. Smidts, “Effects of waiting on the satisfaction with the service: Beyond objective time measures,” International Journal of Research in Marketing , vol. 15, no. 4, pp. 321–334, 10 1998

  25. [33]

    Customers’ identification of acceptable waiting times in a multi-stage restaurant system,

    J. Hwang and C. U. Lambert, “Customers’ identification of acceptable waiting times in a multi-stage restaurant system,” Journal of Foodservice Business Research, vol. 8, no. 1, pp. 3–16, 2006

  26. [34]

    Multisensory experiences: Where the senses meet technol- ogy,

    M. Obrist, “Multisensory experiences: Where the senses meet technol- ogy,” Human-Computer Interaction – INTERACT 2021: 18th IFIP TC 13 International Conference , pp. 11–13, 2021

  27. [35]

    A personal resource for technology interaction: Development and validation of the affinity for technology interaction (ATI) scale,

    T. Franke, C. Attig, and D. Wessel, “A personal resource for technology interaction: Development and validation of the affinity for technology interaction (ATI) scale,” International Journal of Human–Computer Interaction, vol. 35, no. 6, pp. 456 – 467, 07 2019

  28. [36]

    Measuring emotion: the self-assessment manikin and the semantic differential,

    M. M. Bradley and P. J. Lang, “Measuring emotion: the self-assessment manikin and the semantic differential,” Journal of Behavior Therapy and Experimental Psychiatry, vol. 25, no. 1, pp. 49–59, 1994

  29. [37]

    Schrepp, User Experience Questionnaire Handbook , 2015

    M. Schrepp, User Experience Questionnaire Handbook , 2015

  30. [38]

    The hedonic/pragmatic model of user experience,

    M. Hassenzahl, “The hedonic/pragmatic model of user experience,” Towards a UX manifesto , pp. 10–14, 2007

  31. [39]

    Application of the concept of multi-phase experience to wait management in restaurant services,

    J.-H. Kim, “Application of the concept of multi-phase experience to wait management in restaurant services,” Asia Pacific Journal of Tourism Research, vol. 16, no. 4, pp. 379–394, 08 2011

  32. [40]

    To see and be seen—Perceived ethics and acceptability of pervasive augmented reality,

    H. Regenbrecht, A. Knott, J. Ferreira, and N. Pantidi, “To see and be seen—Perceived ethics and acceptability of pervasive augmented reality,” in IEEE Access, vol. 12, 2024, pp. 32 618–32 636

  33. [41]

    More is not always better: determinants of choice overload and satisfaction with customization in fast casual restaurants,

    S. Park and J. Kang, “More is not always better: determinants of choice overload and satisfaction with customization in fast casual restaurants,” Journal of Hospitality Marketing & Management , vol. 31, no. 2, pp. 205–225, 2022

  34. [42]

    Mood Worlds: A virtual environment for autonomous emotional expression,

    N. Wagener, J. Niess, Y . Rogers, and J. Sch ¨oning, “Mood Worlds: A virtual environment for autonomous emotional expression,” in CHI’22: Proceedings of the 2022 CHI Conference on Human Factors in Com- puting Systems, 03 2022, Art. no. 22

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