Augmented Reality Aided Analysis of Customer Satisfaction based on Taste-Induced Facial Expression Recognition Using Affdex Software Developer's Kit

Balbin, Jessie R.; Paglinawan, Charmaine C.; Castro, Mary Josanne A. de; Llamas, Jared Kobe C.; Medina, Mikka Ellah T.; Pangilinan, John Jomel O.; Valiente, Flordeliza L.

doi:10.1145/3326172.3326221

Cited by 8 publications

(3 citation statements)

References 4 publications

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“…The examination of research titles in FER-related studies within the hospitality and tourism industry revealed six distinct sub-themes, predominantly emphasizing "measures" at 39.7%, wherein the concept of emotion (Gomez-Diaz, 2019;Gonz alez-Rodr ıguez et al, 2020;Hadinejad et al, 2019;Jacob-Dazarola et al, 2024;Lee et al, 2022;Pelegr ın-Borondo et al, 2015;Rahmani et al, 2019;Wang et al, 2023; was most frequently utilized, coded 18 times, followed by user experience (Kempapidis et al, 2020), customer satisfaction (Balbin et al, 2019;Lee and Hwang, 2020), and basic emotions (Faullant et al, 2011;Pelegr ın-Borondo et al, 2015). In addition, the concept of emotion was often used in the titles of FER-related studies in the hospitality and tourism industry.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

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Facial emotion recognition research in the hospitality and tourism industry: a thematic content analysis

Kement,

Cavusoglu,

Başar

et al. 2024

WHATT

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PurposeThe purpose of this study is to conduct a thematic content analysis of facial emotion recognition (FER) research within the context of the hospitality and tourism industry. Through this analysis, the study aims to identify key themes, trends and implications of the utilization of FER technology in enhancing customer emotions and experiences within hospitality and tourism settings.Design/methodology/approachThis is qualitative research that utilizes thematic content analysis. The research data were obtained from the Scopus database. A total of 45 articles (titles, abstracts and keywords) were coded into MAXQDA and VOSWiever programs for data analyses and mapping.FindingsBased on the analyses, the predominant term used in titles was emotion, indicating its centrality in the research domain. Moreover, the most prevalent concepts in this field were emotion and experience. Notably, facial emotion recognition emerged as the most frequently utilized term within this context. Within the hospitality and tourism industry, FER was primarily employed within the travel sub-branch. Finally, the research culminated in the visualization of the theoretical framework and conceptual background, offering a comprehensive overview of the field.Originality/valueThere is a growing demand for using FER technology specifically within the hospitality and tourism industry context; therefore, growing scientific research has been conducted on this topic recently. By conducting a thematic content analysis, this study uncovered novel insights into the utilization of this technology to enhance customer emotions and experiences, thereby contributing to a deeper understanding of its potential implications and applications within the hospitality and tourism industry.

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Section: Conclusion and Discussionmentioning

confidence: 99%

“…, 2023) was most frequently utilized, coded 18 times, followed by user experience (Kempapidis et al. , 2020), customer satisfaction (Balbin et al ., 2019; Lee and Hwang, 2020), and basic emotions (Faullant et al. , 2011; Pelegrín-Borondo et al.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Facial emotion recognition research in the hospitality and tourism industry: a thematic content analysis

Kement,

Cavusoglu,

Başar

et al. 2024

WHATT

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“…These can be analyzed by playback data to reveal precisely when users smile or become confused, bored or upset watching a commercial. While several facial expression software is available, Affdex is currently one of the most used standard development kits for classifying emotional states and is known for its reliability in emotional recognition due to its large and spontaneous facial data set (Balbin et al, 2019;Kulke et al, 2020). Biometric measures such as facial expressions provide insight into how the human mind works and how that translates into emotions and identities.…”

Section: Face Analytics Methodsmentioning

confidence: 99%

Bridging social marketing and technology in the disability field: an empirical study on the role of cybernetic avatar and social inclusion

Moriuchi

2023

JSOCM

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Purpose This study aims to determine the perception and attitude of consumers toward the presence of cybernetic avatars (CAs) as part of a social inclusion initiative. Design/methodology/approach A mixed method was used to conduct the study using facial recognition expressions and surveys. Three studies were conducted. Study 1 examines consumers’ attitudes and perceptions of a CA and what it can do to promote social inclusivity among people who have mobility disabilities but wish to work. Study 2 tests a conceptual model to determine the factors that affect consumers’ intention to visit an establishment that uses CAs as their employees. Study 3 extends Study 2 and tests two moderators predicted to influence consumers’ attitudes toward CAs and their intention to visit an establishment that uses CAs. Findings The results show that consumers generally accept and are excited about such technological developments. Study 2 further supports this positive perception with its conceptual model. Study 3 provides insights into how the moderating factors influence a consumer’s attitude toward CAs and their intention to visit the establishment. Between consumers who have a mobility disability and those who do not, those who have mobility disabilities showed a more positive attitude and intention to patronize such an establishment. Originality/value Studies on CAs are still in the infancy stage. This study provides insight into how society can use technology to promote social inclusion, contrary to prior opposing arguments towards integrating robots into society.

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Review of Applications of VR Tools, New Opportunities, and Limitations

Stelick¹

2022

Product Innovation Toolbox

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Augmented Reality Aided Analysis of Customer Satisfaction based on Taste-Induced Facial Expression Recognition Using Affdex Software Developer's Kit

Cited by 8 publications

References 4 publications

Facial emotion recognition research in the hospitality and tourism industry: a thematic content analysis

Facial emotion recognition research in the hospitality and tourism industry: a thematic content analysis

Bridging social marketing and technology in the disability field: an empirical study on the role of cybernetic avatar and social inclusion

Review of Applications of VR Tools, New Opportunities, and Limitations

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