Determinants of Emotion Recognition System Adoption: Empirical Evidence from Malaysia

被引:0
作者
Yamin, Muhammad Nadzree Mohd [1 ]
Aziz, Kamarulzaman Ab. [1 ]
Siang, Tan Gek [1 ]
Aziz, Nor Azlina Ab. [2 ]
机构
[1] Multimedia Univ, Fac Business, Melaka 75450, Malaysia
[2] Multimedia Univ, Fac Engn & Technol, Melaka 75450, Malaysia
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 21期
关键词
emotion recognition system; fourth industrial revolution; fifth industrial revolution; artificial intelligence; Theory of Planned Behavior; technology adoption; Malaysian; youth; FACILITATING CONDITIONS; INFORMATION-TECHNOLOGY; COEFFICIENT ALPHA; ACCEPTANCE; BEHAVIOR; MODELS;
D O I
10.3390/app132111854
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Featured Application This study focuses on Emotion Recognition System an important application of Artificial Intelligence, Affective Computing, and Human-Computer Interaction.Abstract Emotion recognition systems (ERS) are an emerging technology with immense potential, exemplifying the innovative utilization of artificial intelligence (AI) within the context of the fourth industrial revolution (IR 4.0). Given that personalization is a key feature of the fifth industrial revolution (IR 5.0), ERS has the potential to serve as an enabler for IR 5.0. Furthermore, the COVID-19 pandemic has increased the relevance of this technology as work processes were adapted for social distancing and the use of face masks. Even in the post-pandemic era, many individuals continue to wear face masks. Therefore, ERS offers a technological solution to address communication challenges in a masked world. The existing body of knowledge on ERS primarily focuses on exploring modalities or modes for emotion recognition, system development, and the creation of applications utilizing emotion recognition functions. However, to enhance the development of impactful ERS, it is essential for researchers and innovators to understand the factors that influence its usage and adoption among the intended users. Therefore, this study presents a framework that combines technology adoption theories to identify the determinants of ERS adoption among Malaysian youth. Data for this study were collected through a survey involving 386 respondents. The findings revealed attitudes, subjective norms, perceived behavioral control, and awareness as significant determinants of ERS adoption. Additionally, the study found that technology aptitude plays a moderating role. These insights can inform the formulation of effective policies and programs to encourage and facilitate the development of innovative ERS solutions.
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页数:30
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共 114 条
  • [1] Awareness and Readiness of Malaysian University Students for Emotion Recognition System
    Ab Aziz, Nor Azlina
    Aziz, Nor Hidayati Abdul
    Ismail, Sharifah Noor Masidayu Sayed
    Khan, Chy Tawsif
    Hasnul, Muhammad Anas
    Rahman, Md. Armanur
    Ab Rahman, Tasiransurini
    Ab Aziz, Kamarulzaman
    [J]. INTERNATIONAL JOURNAL OF INTEGRATED ENGINEERING, 2021, 13 (06): : 299 - 309
  • [2] Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion
    Ab Hamid, M. R.
    Sami, W.
    Sidek, M. H. Mohmad
    [J]. 1ST INTERNATIONAL CONFERENCE ON APPLIED & INDUSTRIAL MATHEMATICS AND STATISTICS 2017 (ICOAIMS 2017), 2017, 890
  • [3] Ajzen I., 2019, TPB questionnaire construction constructing a theory of planned behaviour questionnaire, P1
  • [4] TEACHERS' BELIEFS AND THE FORMATION OF ENTREPRENEURIAL POTENTIAL IN STUDENTS
    Cruz, Tamara de la Torre
    Escolar-Llamazares, Maria-Camino
    Valle, Cristina Di Giusto
    Rico, Isabel Luis
    Eguizabal, Alfredo Jimenez
    Jimenez, Alfredo
    [J]. INTERCIENCIA, 2023, 48 (08) : 398 - 408
  • [5] Akinnuwesi Boluwaji A., 2016, International Journal of Business Information Systems, V23, P482
  • [6] Mobile banking adoption of the youth market Perceptions and intentions
    Akturan, Ulun
    Tezcan, Nuray
    [J]. MARKETING INTELLIGENCE & PLANNING, 2012, 30 (04) : 444 - 459
  • [7] Developing a general extended UTAUT model for M-payment adoption
    Al-Saedi, Karrar
    Al-Emran, Mostafa
    Ramayah, T.
    Abusham, Eimad
    [J]. TECHNOLOGY IN SOCIETY, 2020, 62
  • [8] Alavion SJ, 2017, J INT FOOD AGRIBUS M, V29, P1, DOI 10.1080/08974438.2016.1229242
  • [9] SAFEPA: An Expandable Multi-Pose Facial Expressions Pain Assessment Method
    Alghamdi, Thoria
    Alaghband, Gita
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (12):
  • [10] Machine-Learning-Based Emotion Recognition System Using EEG Signals
    Alhalaseh, Rania
    Alasasfeh, Suzan
    [J]. COMPUTERS, 2020, 9 (04) : 1 - 15