TY - GEN
T1 - Strategy to Increase the Intention of Using Industry 4.0 Technology, Manufacture Production Monitoring System-Web Based Case Study
T2 - 6th International Conference on Industrial and Business Engineering, ICIBE 2020
AU - Nabilah, Annisa Z.
AU - Loretta, Joanna M.
AU - Moch, Boy N.
AU - Muslim, Erlinda
N1 - Publisher Copyright:
© 2020 ACM.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/9/27
Y1 - 2020/9/27
N2 - Many technologies to embrace industry 4.0 has developed in manufacture industry to improve their product activities such as monitoring system. The scope of this work to develop models for assessing critical aspects of employee use and acceptance of technology-based products and services. The researches use Technology Readiness Index Model and Technology Acceptance Model that combine knowing as Technology Readiness Acceptance Model which adoption model by Chien Hsin Lin, Hsin-Yu Shih and Peter J. Sher. T (2007). Technology Readiness Model that consist of four variables are Optimism, Innovativeness, Discomfort and Insecurity was carried out to test whether the influencing factors among that variables could be antecedents to the main construct of the technology acceptance model with variables are Perceived ease of use, Perceived Usefulness as observed to be a significant antecedent of the behavior intention to use manufacture production monitoring system web based. The data collected from 43 employees of Automotive Manufacturing Industry and processed using Partial Least Square - Structural Equation Model (SEM). After the influencing factors has determined, the recommendation strategy was designed using Importance Performance Analysis to create an appropriate strategy to increase the intention of Using Industry 4.0 Technology, Manufacture Production Monitoring System Web Based.
AB - Many technologies to embrace industry 4.0 has developed in manufacture industry to improve their product activities such as monitoring system. The scope of this work to develop models for assessing critical aspects of employee use and acceptance of technology-based products and services. The researches use Technology Readiness Index Model and Technology Acceptance Model that combine knowing as Technology Readiness Acceptance Model which adoption model by Chien Hsin Lin, Hsin-Yu Shih and Peter J. Sher. T (2007). Technology Readiness Model that consist of four variables are Optimism, Innovativeness, Discomfort and Insecurity was carried out to test whether the influencing factors among that variables could be antecedents to the main construct of the technology acceptance model with variables are Perceived ease of use, Perceived Usefulness as observed to be a significant antecedent of the behavior intention to use manufacture production monitoring system web based. The data collected from 43 employees of Automotive Manufacturing Industry and processed using Partial Least Square - Structural Equation Model (SEM). After the influencing factors has determined, the recommendation strategy was designed using Importance Performance Analysis to create an appropriate strategy to increase the intention of Using Industry 4.0 Technology, Manufacture Production Monitoring System Web Based.
KW - Importance Performance Analysis
KW - Industry 4.0
KW - Manufacture Production Monitoring System
KW - Partial Least Square
KW - Structural Equation Model
KW - Technology Readiness Acceptance Model
UR - http://www.scopus.com/inward/record.url?scp=85098146248&partnerID=8YFLogxK
U2 - 10.1145/3429551.3429563
DO - 10.1145/3429551.3429563
M3 - Conference contribution
AN - SCOPUS:85098146248
T3 - ACM International Conference Proceeding Series
SP - 25
EP - 31
BT - ICIBE 2020 - 2020 6th International Conference on Industrial and Business Engineering
PB - Association for Computing Machinery
Y2 - 27 September 2020 through 29 September 2020
ER -