Presenting the management model of the intelligent operating system of behavioral responses in the blockchain platform (Case study: sports teachers using club shoes)
Subject Areas : Marketing
1 - Assistant Professor, Sports Management Department, Firoozabad Branch, Islamic Azad University, Firoozabad, Iran
Keywords: intelligent operating system management, behavioral responses, blockchain.,
Abstract :
The management of the intelligent operating system of behavioral responses is a software entity of an artificial intelligence system that has the power of perception and decision-making and based on its knowledge and experiences, while examining the dimensions of the behavioral responses of sports teachers in using club shoes automatically and intelligently , analyzes their behavior in the three stages of reaction, confrontation and adaptation and decides which optimal behavior model to use to have maximum impact on sports teachers' behaviors and habits. The purpose of this article is to present the management model of the intelligent operating system of behavioral responses in the blockchain platform.
This research is a qualitative research in terms of its purpose, application and in terms of the way of collecting information. The statistical community includes sports experts. The sample size was estimated with theoretical saturation of 14 people using purposive sampling. Data collection tool in
The qualitative part was a semi-structured interview. The validity and reliability of the work were used by Goba and Lincoln's criteria. Max Kyuda 20 software was used for coding. To analyze the data, the systematic method of Strauss and Corbin was done with open, axial and selective coding.
In this research, the intelligent agent of sports teachers' behavioral responses as a central phenomenon and the most important antecedents affecting it include the level of preparation and maturity of technology, augmented and virtual reality, technological capabilities, big data, smart digital sensors, smart digital actors, Internet of Things, recovery Intelligent information, information organization, content knowledge, intelligent analysis, intelligent website, robotic process automation, digital process automation, intelligent communication. The current research led to the presentation of a paradigm model with the title of presentation of the management model of the intelligent operating system of behavioral responses in the blockchain platform.
1- Alkinania,MH. AliAlmazroib,A. Adhikaric,M. Menond,VG. (2023).Design and analysis of logistic agent-based swarm-neural network for intelligent transportation system, Alexandria Engineering Journal, Volume 61, pp 8325-8334.
2- Binos,T. Bruno,V. (2024).Intelligent agent based framework to augment warehouse management systems for dynamic demand environments, Australasian Conference on Information Systems,PP198-216.
3- Brandsen, T, Verberne,S. Lambers,K.Wansleeben,M. (2022). Can BERT Dig It? Named Entity Recognition for Information Retrieval in the Archaeology Domain, Journal on Computing and Cultural Heritage,pp452-473.
4- Chen,S.Wenting, C. (2022). Advanced Sensing Materials for Internet of Things Sensors,journal of sensors,pp68-74.
5- Doguc,O. (2022).Robot Process Automation (RPA) and Its Future, IGI Global’s Online Bookstore Extended,PP269-287.
6- Fathima,KM. Santhiyakumari,N. Suganthi,M. (2024).Augmentation of Intelligent Agent for Multiple Access Protocols in Wireless Sensor Networks, Second International Conference on Artificial Intelligence and Smart Energy,PP61-78.
7- Guba, E. G. & Lincoln, Y. S. (2005). Paradigmatic Controversies, Contradictions, and Emerging Confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of qualitative research ,pp. 191–215.
8- Hassanzadeh, Mohammad, Mohammadkhani, Arash. (2009). A review of intelligent agents and their role in library services, Paik Noor - Human Sciences, Summer, Volume 6, Number 2, Page 42-52.
9- Hassanzadeh, Mohammad. (2021). The fifth data revolution, the irreplaceable role of intelligent agents and the necessity of the National Data Organization, Information Management Sciences and Techniques, Autumn - Number 24, Volume 7, Number 3, Page 7-16.
10- Jyh-Jeng,W.Haider,KH. Shu-Hua,Ch. Chi-Hsiang,W. (2022).Effect of customization, core self-evaluation, and information richness on trust in online insurance service: Intelligent agent as a moderating variable,Asia Pacific Management Review, Volume 27, Issue 1, PP 18-27.
11- Kaswan,KS. Dhatterwal,JS. Balyan,A. (2023).Intelligent Agents based Integration of Machine Learning and Case Base Reasoning System International Conference on Advance Computing and Innovative Technologies in Engineering,pp
12- Kim,j,Sung,Y. (2024). Artificial Intelligence Is Safer for My Privacy: Interplay Between Types of Personal Information and Agents on Perceived Privacy Risk and Concerns,Cyberpsychology, Behavior, and Social NetworkingVol. 25,PP587-611.
13- Khan Mohammadi, Mohammad. (2021). Investigating the obstacles to the use of intelligent agents in independent auditing, Accounting and Management Perspectives Journal, Spring, Volume 4, Number 38 - Serial Number 38, Page 100-114.
14- Moradi, Masoumeh, Aghaei, Abdullah, Hosseini, Munira. (2012). Application of intelligent multi-agent system in decision making with knowledge management approach, Information Technology Management, Winter, Volume 5, Number 4, Page 219-244.
15- Moussawi,S. Koufaris,M. Benbunan-Fich,R. (2022).The role of user perceptions of intelligence, anthropomorphism, and self-extension on continuance of use of personal intelligent agents, European Journal of Information Systems,PP22-41.
16- Mukherjee,S. Chittipaka,V. (2024).Analysing the Adoption of Intelligent Agent Technology in Food Supply Chain Management, IGI Global’s Online Bookstore Extended,pp258-279.
17- Nami, Mohammad Reza, Kamali Dehghan, Maleeha, Abbasi, Mehsa, Farsi, Elham. (2009). The role of intelligent agents in improving electronic government activities, Majlisi Electrical Engineering, Winter, Volume 2, Number 4, Page 37-42.
18- Nandy,S. Adhikari,M. Chakraborty,S. Alkhayyat,A. Kumar,N. (2022).Intelligent Agent-based Internet of Medical Things framework for detecting brain response from Electroencephalography signal using Bag-of-Neural Network, Future Generation Computer Systems, Volume 130, May 2022, PP 241-252.
19- Pengcheng,L. Burkay,A. Xu,Z. Xinqiao,J. Zhimin,D. (2022).Across working conditions fault diagnosis for chillers based on IoT intelligent agent with deep learning model, Energy and Buildings, Volume 268,PP12-32.
20- Sargazi Moghadam, Hossein, Shahesvari, Maryam. (2015). An overview of the role of intelligent software agents in supply chain management, Supply Chain Management, Azar, Volume 18, Number 53, Pages 14-26.
21- Phasinam,KH. Kassanuk,TH. Shabaz,M. (2022). Applicability of Internet of Things in Smart Farming, Journal of Food Quality,PP44-61.
22- Vinnarasi,F.Jesline,D. (2022).Intelligent agent and optimization-based deep residual network to secure communication in UAV network, International jouranal of intelligent sestems, Volume37, Issue9, PP 5508-5529.
23- Yang,Y. Yue, L. Xingyang,L. Jin, A. Yifan,L (2023).Anthropomorphism and customers’ willingness to use artificial intelligence service agents, Journal of Hospitality Marketing & Management, Volume 31,PP12-35.