hamed mirashk; Amir Albadvi; mehrdad kargari; Mohammadali Rastegar Sorkhe; mohammad talebi
Volume 27, Issue 4 , January 2024, , Pages 138-168
Abstract
The Design Science Research method (DSR) is an approach to provide practical solutions based on scientific principles in order to produce substantiated and inferred results and products, and at the same time, the results can be scientifically evaluated in the form of primary artifacts and practical use ...
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The Design Science Research method (DSR) is an approach to provide practical solutions based on scientific principles in order to produce substantiated and inferred results and products, and at the same time, the results can be scientifically evaluated in the form of primary artifacts and practical use in four main stages which ultimately results in their practical efficiency and effectiveness in the outside world. By designing and creating an archetype in the prototyping stage, DSR evaluates real scenarios and then examines the solution in practical cases. From this point of view, in this research, it has been tried to use the DSR method to provide an innovative solution for predicting bank liquidity risk and upcoming scenarios. This study uses semtiment analysis and deep learning algorithm such as deep convolutional network in predicting liquidity risk and presents a simple and effective method to identify dynamic qualitative variables from recent news about a domestic bank in the country. Predicted scenarios are available to banking experts in the real world to facilitate decision-making in risk measures. According to the guidelines of the Basel Committee and other European banking regulatory frameworks, comparing these scenarios with the scenarios occurring in the bank indicates a relatively high accuracy of the proposed method. In the scenarios derived from the Basel Committee and derived from the European Banking Authority, the forecasting accuracy is about 91% and 82%, respectively
kazem kayyal; Amir Albadvi
Volume 23, Issue 2 , July 2019, , Pages 200-225
Abstract
The first part of this paper, reviews research on open innovation.There would be four stages in the use of open innovation approach: 1. abtaining; 2. Integrating; 3. Commercializing; 4. The interaction mechanisms. In the second part of the paper, the information is collected by semi-structured interviews.then ...
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The first part of this paper, reviews research on open innovation.There would be four stages in the use of open innovation approach: 1. abtaining; 2. Integrating; 3. Commercializing; 4. The interaction mechanisms. In the second part of the paper, the information is collected by semi-structured interviews.then The information analyzed and investigated using grounded theory method and the four-phase model proposed in the literature. At this stage, the banking and payment industries were selected as the case study; Due to their characteristics according to the study.Finally the main considerations and challenges to implement open innovation approach, is determined. Also an appropriate model to implement open innovation approach is proposed.
