Factors determining customers desire to analyse supply chain management in intelligent IoT

被引:2
|
作者
Ferinia, Rolyana [1 ]
Kumar, Dasari Lokesh Sai [2 ]
Kumar, B. Santhosh [3 ]
Muthu, Bala Anand [4 ]
Asaad, Renas Rajab [5 ]
Ramamoorthi, Jaya Subalakshmi [6 ]
Daniel, J. Alfred [7 ]
机构
[1] Univ Advent Indonesia, Jawa Barat, Indonesia
[2] PVP Siddhartha Inst Technol, Comp Sci & Engn, Vijayawada, India
[3] Guru Nanak Inst Technol Hyderabad, Dept Comp Sci & Engn, Hyderabad, Telangana, India
[4] Tagore Inst Engn & Technol, Dept Comp Sci & Engn, Attur, India
[5] Nawroz Univ, Dept Comp Sci, Duhok, Kurdistan, Iraq
[6] Vellore Inst Technol, Sch Comp Sci & Engn, Vellore, India
[7] Karpagam Acad Higher Educ, Coimbatore, India
关键词
Attitude analysis; Audience behavior; Intelligent identification; Intelligent IoT model; Supply chain management; DIMENSIONS;
D O I
10.1007/s10878-023-01007-8
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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%).
引用
收藏
页数:25
相关论文
共 50 条
  • [41] Multi-agent Based Intelligent Supply Chain Management
    Wang, Ye
    Wang, Denial
    PROCEEDINGS OF THE NINTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, 2015, 362 : 305 - 312
  • [42] Special Issue on Towards the Intelligent Supply Chain Management Preface
    Patnaik, Srikanta
    Qu, Xilong
    Shen, Tao
    Hu, Bin
    INTERNATIONAL JOURNAL OF INFORMATION SYSTEMS AND SUPPLY CHAIN MANAGEMENT, 2019, 12 (02) : VI - VIII
  • [43] Intelligent agents in supply chain management as an early warning mechanism
    Wei-Shuo Lo
    Tzung-Pei Hong
    Rong Jeng
    Jian-Ping Liu
    2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, : 2161 - +
  • [44] Study on the Operation Mode of Customers Relationship Management Based on Supply Chain Integration
    Jiang, Wenqin
    Li, Songqing
    PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON OPERATIONS AND SUPPLY CHAIN MANAGEMENT (ICOSCM 2010), 2010, 4 : 714 - 717
  • [45] Intelligent supply chain management using adaptive critic learning
    Shervais, S
    Shannon, TT
    Lendaris, GG
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2003, 33 (02): : 235 - 244
  • [46] On the Integration of Intelligent Maintenance and Spare Parts Supply Chain Management
    Hellingrath, Bernd
    Pereira, Carlos E.
    Espindola, Danubia
    Frazzon, Enzo M.
    Cordes, Ann-Kristin
    Saalmann, Philipp
    Zuccolotto, Marcos
    IFAC PAPERSONLINE, 2015, 48 (03): : 983 - 988
  • [47] Intelligent Collaborative Quality Assurance System for Wind Turbine Supply Chain Management Intelligent Collaborative Quality Assurance System for Wind Turbine Supply Chain Management
    Song, B. L.
    Liao, W.
    Lee, J.
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2013, 4 (02) : 36 - 45
  • [48] Intelligent Logistics Supply Chain Management: Cost Management and Service Quality Improvement
    Liu, Cuiping
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [49] IoT-based supply chain management: A systematic literature review
    Taj, Soonh
    Imran, Ali Shariq
    Kastrati, Zenun
    Daudpota, Sher Muhammad
    Memon, Raheel Ahmed
    Ahmed, Javed
    INTERNET OF THINGS, 2023, 24
  • [50] Blockchained supply chain management based on IoT tracking and machine learning
    Dong, Zhongping
    Liang, Wei
    Liang, Yan
    Gao, Weibo
    Lu, Yi
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2022, 2022 (01)