Author
Listed:
- Rolyana Ferinia
(Universitas Advent Indonesia)
- Dasari Lokesh Sai Kumar
(P.V.P. Siddhartha Institute of Technology)
- B. Santhosh Kumar
(Guru Nanak Institute of Technology Hyderabad)
- Bala Anand Muthu
(Tagore Institute of Engineering and Technology)
- Renas Rajab Asaad
(Nawroz University)
- Jaya Subalakshmi Ramamoorthi
(Vellore Institute of Technology)
- J. Alfred Daniel
(Karpagam Academy of Higher Education)
Abstract
This article discussed customers' desire to analyze the supply chain management in "chokhi Dhani village" resort using exploratory factor analysis for audience behavior intelligence identification using an intelligent IoT model. This innovative IoT model greatly impacted the Indian Perspective of culture concerning supply chain management. This research uses the Intelligent IoT model exploratory factor analysis against the "Chokhi Dhani village" resort to know the different services needed to maintain the audience behavior on culture meet or regard with the resort. This analysis will reflect the audience behavior regarding the intelligent identification using the Intelligent IoT model concerning the creation of the IoT model for "Attitude analysis" to determine practical exploratory factor analysis. Five modes are created based on the other user's Attitude analyses—namely Model of (Teenagers, influence peoples, children, senescence, and disability persons Attitude analysis. Moreover, the IoT general idea enforced each person's Attitude analysis to investigate the state of connectedness between the different audiences. The independent variables had a combined exploratory factor analysis variance of 52%; the most significant variance was found in finding meaning (24.78%), linking ideas (42.3%), using evidence (55.67%), being interested in ideas (68.3%), and evaluating effectiveness (70.5%). The outcome generated some viewership and percentage. The number of viewers and the percentage used to gauge central tendency is the foundations for audience behavior identification. The audience ranges in age from 5 to 21, and the enhanced accuracy is 41%. By applying the Log-Likelihood Test, the accuracy of this logistic regression model have assessed for any create (46%), comedy (22%), historical (10%), message-oriented (18%), musical (36%), biographical (24%) and social (64%).
Suggested Citation
Rolyana Ferinia & Dasari Lokesh Sai Kumar & B. Santhosh Kumar & Bala Anand Muthu & Renas Rajab Asaad & Jaya Subalakshmi Ramamoorthi & J. Alfred Daniel, 2023.
"Factors determining customers desire to analyse supply chain management in intelligent IoT,"
Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-25, March.
Handle:
RePEc:spr:jcomop:v:45:y:2023:i:2:d:10.1007_s10878-023-01007-8
DOI: 10.1007/s10878-023-01007-8
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:45:y:2023:i:2:d:10.1007_s10878-023-01007-8. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.