Mitigating Entrepreneurship Policy Challenges in Developing Countries’ Startup Ecosystems Through Machine Learning Analysis

Entrepreneurship plays a significant role in the economic development of emerging economies, particularly by addressing persistent issues such as youth unemployment and growth challenges. Developing nations perceive their startup ecosystems as critical engines of economic progress. Policymakers in these countries strive to reduce uncertainties and mitigate risks that could impede the growth of this essential sector. However, they face a significant obstacle: the lack of accurate and reliable data necessary to comprehend the challenges and requirements of the startup ecosystem. To effectively navigate these challenges, policymakers must utilize advanced analytical tools and technologies, including big data analytics, artificial intelligence, and machine learning. These technologies are crucial for the comprehensive collection and analysis of data from diverse sources. This research aims to identify current trends and challenges within the startup ecosystem in developing countries through the meticulous collection and analysis of news data on the topic. To achieve this objective, we developed a detailed plan to collect news data on Iran’s startup ecosystem spanning from 2017 to 2022. By employing advanced natural language processing techniques, we intended to conduct a thorough analysis of the collected data. Our goal is to extract significant insights that will inform and shape effective policymaking.

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Publication Details

Journal
Economies
Published
2025-10-11
DOI
https://doi.org/10.3390/economies13100295
Citations
1
Primary Topic
Economic Growth and Development
Type
article
Field-Weighted Citation Impact
3.25
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article

Mitigating Entrepreneurship Policy Challenges in Developing Countries’ Startup Ecosystems Through Machine Learning Analysis

Mohammad Jahanbakht, Mohammad Hossein Rohban, Sayed Mohammad Mahdi Mirahmadi
1 citations
Economies
Economic Growth and Development
3.25
article

Mitigating Entrepreneurship Policy Challenges in Developing Countries’ Startup Ecosystems Through Machine Learning Analysis

Mohammad Jahanbakht, Mohammad Hossein Rohban, Sayed Mohammad Mahdi Mirahmadi
article en
1 citations

Abstract

Entrepreneurship plays a significant role in the economic development of emerging economies, particularly by addressing persistent issues such as youth unemployment and growth challenges. Developing nations perceive their startup ecosystems as critical engines of economic progress. Policymakers in these countries strive to reduce uncertainties and mitigate risks that could impede the growth of this essential sector. However, they face a significant obstacle: the lack of accurate and reliable data necessary to comprehend the challenges and requirements of the startup ecosystem. To effectively navigate these challenges, policymakers must utilize advanced analytical tools and technologies, including big data analytics, artificial intelligence, and machine learning. These technologies are crucial for the comprehensive collection and analysis of data from diverse sources. This research aims to identify current trends and challenges within the startup ecosystem in developing countries through the meticulous collection and analysis of news data on the topic. To achieve this objective, we developed a detailed plan to collect news data on Iran’s startup ecosystem spanning from 2017 to 2022. By employing advanced natural language processing techniques, we intended to conduct a thorough analysis of the collected data. Our goal is to extract significant insights that will inform and shape effective policymaking.

EconomiesVol. 13(10)
Sharif University of Technology (IR), The University of Texas at Arlington (US)
Openalex Percentile: Top 6%
Economic Growth and Development
3.25
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