User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach

Sheikh Muhamad Hizam; Waqas Ahmed; Muhammad Fahad; Habiba Akter; Ilham Sentosa; Jawad Ali

doi:10.1007/978-3-030-73103-8_75

User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach

Sheikh Muhamad Hizam
, Waqas Ahmed^*
, Muhammad Fahad
, Habiba Akter
, Ilham Sentosa
, Jawad Ali

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Scopus citations

Abstract

A smart home is grounded on the sensors that endure automation, safety, and structural integration. The security mechanism in digital setup possesses vibrant prominence and the biometric facial recognition system is novel addition to accrue the smart home features. Understanding the implementation of such technology is the outcome of user behavior modeling. However, there is the paucity of empirical research that explains the role of cognitive, functional, and social aspects of end-user’s acceptance behavior towards biometric facial recognition systems at homes. Therefore, a causal research survey was conducted to comprehend the behavioral intention towards the use of a biometric facial recognition system. Technology Acceptance Model (TAM) was implied with Perceived System Quality (PSQ) and Social Influence (SI) to hypothesize the conceptual framework. Data was collected from 475 respondents through online questionnaires. Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) were employed to analyze the surveyed data. The results showed that all the variables of the proposed framework significantly affected the behavioral intention to use the system. The PSQ appeared as the noteworthy predictor towards biometric facial recognition system usability through regression and sensitivity analyses. A multi-analytical approach towards understanding the technology user behavior will support the efficient decision-making process in Human-centric computing.

Original language	English
Title of host publication	Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC
Editors	Kohei Arai
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1037-1050
Number of pages	14
ISBN (Print)	9783030731021
DOIs	https://doi.org/10.1007/978-3-030-73103-8_75
State	Published - 2021
Externally published	Yes
Event	Future of Information and Communication Conference, FICC 2021 - Virtual, Online Duration: 29 Apr 2021 → 30 Apr 2021

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1364 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Future of Information and Communication Conference, FICC 2021
City	Virtual, Online
Period	29/04/21 → 30/04/21

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Facial recognition
SEM-Neural
Technology acceptance

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-030-73103-8_75

Cite this

Hizam, S. M., Ahmed, W., Fahad, M., Akter, H., Sentosa, I., & Ali, J. (2021). User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach. In K. Arai (Ed.), Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC (pp. 1037-1050). (Advances in Intelligent Systems and Computing; Vol. 1364 AISC). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-73103-8_75

Hizam, Sheikh Muhamad ; Ahmed, Waqas ; Fahad, Muhammad et al. / User Behavior Assessment Towards Biometric Facial Recognition System : A SEM-Neural Network Approach. Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. editor / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2021. pp. 1037-1050 (Advances in Intelligent Systems and Computing).

@inproceedings{4804a4dec3b94caba554de4f97a0928a,

title = "User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach",

abstract = "A smart home is grounded on the sensors that endure automation, safety, and structural integration. The security mechanism in digital setup possesses vibrant prominence and the biometric facial recognition system is novel addition to accrue the smart home features. Understanding the implementation of such technology is the outcome of user behavior modeling. However, there is the paucity of empirical research that explains the role of cognitive, functional, and social aspects of end-user{\textquoteright}s acceptance behavior towards biometric facial recognition systems at homes. Therefore, a causal research survey was conducted to comprehend the behavioral intention towards the use of a biometric facial recognition system. Technology Acceptance Model (TAM) was implied with Perceived System Quality (PSQ) and Social Influence (SI) to hypothesize the conceptual framework. Data was collected from 475 respondents through online questionnaires. Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) were employed to analyze the surveyed data. The results showed that all the variables of the proposed framework significantly affected the behavioral intention to use the system. The PSQ appeared as the noteworthy predictor towards biometric facial recognition system usability through regression and sensitivity analyses. A multi-analytical approach towards understanding the technology user behavior will support the efficient decision-making process in Human-centric computing.",

keywords = "Facial recognition, SEM-Neural, Technology acceptance",

author = "Hizam, \{Sheikh Muhamad\} and Waqas Ahmed and Muhammad Fahad and Habiba Akter and Ilham Sentosa and Jawad Ali",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Future of Information and Communication Conference, FICC 2021 ; Conference date: 29-04-2021 Through 30-04-2021",

year = "2021",

doi = "10.1007/978-3-030-73103-8\_75",

language = "English",

isbn = "9783030731021",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "1037--1050",

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}

Hizam, SM, Ahmed, W, Fahad, M, Akter, H, Sentosa, I & Ali, J 2021, User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach. in K Arai (ed.), Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. Advances in Intelligent Systems and Computing, vol. 1364 AISC, Springer Science and Business Media Deutschland GmbH, pp. 1037-1050, Future of Information and Communication Conference, FICC 2021, Virtual, Online, 29/04/21. https://doi.org/10.1007/978-3-030-73103-8_75

User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach. / Hizam, Sheikh Muhamad; Ahmed, Waqas; Fahad, Muhammad et al.
Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. ed. / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2021. p. 1037-1050 (Advances in Intelligent Systems and Computing; Vol. 1364 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - User Behavior Assessment Towards Biometric Facial Recognition System

T2 - Future of Information and Communication Conference, FICC 2021

AU - Hizam, Sheikh Muhamad

AU - Ahmed, Waqas

AU - Fahad, Muhammad

AU - Akter, Habiba

AU - Sentosa, Ilham

AU - Ali, Jawad

PY - 2021

Y1 - 2021

N2 - A smart home is grounded on the sensors that endure automation, safety, and structural integration. The security mechanism in digital setup possesses vibrant prominence and the biometric facial recognition system is novel addition to accrue the smart home features. Understanding the implementation of such technology is the outcome of user behavior modeling. However, there is the paucity of empirical research that explains the role of cognitive, functional, and social aspects of end-user’s acceptance behavior towards biometric facial recognition systems at homes. Therefore, a causal research survey was conducted to comprehend the behavioral intention towards the use of a biometric facial recognition system. Technology Acceptance Model (TAM) was implied with Perceived System Quality (PSQ) and Social Influence (SI) to hypothesize the conceptual framework. Data was collected from 475 respondents through online questionnaires. Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) were employed to analyze the surveyed data. The results showed that all the variables of the proposed framework significantly affected the behavioral intention to use the system. The PSQ appeared as the noteworthy predictor towards biometric facial recognition system usability through regression and sensitivity analyses. A multi-analytical approach towards understanding the technology user behavior will support the efficient decision-making process in Human-centric computing.

AB - A smart home is grounded on the sensors that endure automation, safety, and structural integration. The security mechanism in digital setup possesses vibrant prominence and the biometric facial recognition system is novel addition to accrue the smart home features. Understanding the implementation of such technology is the outcome of user behavior modeling. However, there is the paucity of empirical research that explains the role of cognitive, functional, and social aspects of end-user’s acceptance behavior towards biometric facial recognition systems at homes. Therefore, a causal research survey was conducted to comprehend the behavioral intention towards the use of a biometric facial recognition system. Technology Acceptance Model (TAM) was implied with Perceived System Quality (PSQ) and Social Influence (SI) to hypothesize the conceptual framework. Data was collected from 475 respondents through online questionnaires. Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) were employed to analyze the surveyed data. The results showed that all the variables of the proposed framework significantly affected the behavioral intention to use the system. The PSQ appeared as the noteworthy predictor towards biometric facial recognition system usability through regression and sensitivity analyses. A multi-analytical approach towards understanding the technology user behavior will support the efficient decision-making process in Human-centric computing.

KW - Facial recognition

KW - SEM-Neural

KW - Technology acceptance

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U2 - 10.1007/978-3-030-73103-8_75

DO - 10.1007/978-3-030-73103-8_75

M3 - Conference contribution

AN - SCOPUS:85105926991

SN - 9783030731021

T3 - Advances in Intelligent Systems and Computing

SP - 1037

EP - 1050

BT - Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC

A2 - Arai, Kohei

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 29 April 2021 through 30 April 2021

ER -

Hizam SM, Ahmed W, Fahad M, Akter H, Sentosa I, Ali J. User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach. In Arai K, editor, Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. Springer Science and Business Media Deutschland GmbH. 2021. p. 1037-1050. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-73103-8_75

User Behavior Assessment Towards Biometric Facial Recognition System: A SEM-Neural Network Approach

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this