Volume 13, Issue 2 (6-2021)                   itrc 2021, 13(2): 49-58 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Moridi Z, Mousavi S A, Toloie A, Soltani R. A Smart Contract Model in Knowledge-based Companies Based on Grounded Theory by Focusing on the Robotic Process Automation and Process Management Strategies. itrc 2021; 13 (2) :49-58
URL: http://journal.itrc.ac.ir/article-1-484-en.html
1- Department of Information Technology Management, Qeshm Branch, Islamic Azad University, Qeshm, Iran
2- Department of Management, Firoozabad Branch, Islamic Azad University, Firoozabad, Iran , ar.moosavi@iauf.ac.ir
3- Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
4- Department of Industrial Engineering, Faculty of Engineering, Khatam University, Tehran, Iran
Abstract:   (2216 Views)
A smart contract is a computer protocol for creating or improving a contract which makes it possible to create valid transactions without intermediaries. The most important feature is security and speed, because this technology runs on a blockchain platform and its information will remain confidential. Despite these benefits, unfortunately, companies still use paper contracts. Knowledge-based companies can save time and money by implementing smart contracts with their customers in the form of robotic process automation and process management, and by reducing errors and risks in processes. Increase productivity in business. The purpose of this study was to present a smart contract model in knowledge-based companies based on Grounded Theory by Focusing on the robotic process automation strategies and process management using qualitative and quantitative paradigms. The analysis approach in this research is quantitative-qualitative. To collect data in the qualitative part, semi-structured interviews were used. In the quantitative part, the structural equation method was used. The sample size was calculated according to confirmatory factor analysis of 110 experts. Based on the data analysis, due to the abnormality of the data distribution, the partial least squares method was used with the help of Smart PLS software version 2.
Full-Text [PDF 1084 kb]   (765 Downloads)    
Type of Study: Research | Subject: Information Technology

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.