Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms
This study investigates the impact of business environment obstacles on the performance of Cottage, Micro, Small, and Medium Enterprises (CMSMEs) in Bangladesh, utilizing data from 998 firms in the 2022 World Bank Enterprise Survey. A recursive feature elimination algorithm identified ten key busine...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844025004724 |
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| author | Chandan Kumar Roy |
| author_facet | Chandan Kumar Roy |
| author_sort | Chandan Kumar Roy |
| collection | DOAJ |
| description | This study investigates the impact of business environment obstacles on the performance of Cottage, Micro, Small, and Medium Enterprises (CMSMEs) in Bangladesh, utilizing data from 998 firms in the 2022 World Bank Enterprise Survey. A recursive feature elimination algorithm identified ten key business factors and obstacles from an initial set of twenty-eight that significantly influence CMSME performance. Analysis using ordinary least squares (OLS) and generalized least squares (GLS) regression models reveals that investments in electricity infrastructure, access to financial services, and obtaining quality certifications positively impact CMSME performance. In contrast, challenges such as power outages, delays in licensing, uncompetitive practices, and stringent tax and labor regulations hinder performance. Additionally, the predictive accuracy of the OLS model was compared with several machine learning algorithms, including decision tree, random forest, support vector, and gradient boosting, using a 75-25 training-testing split and k-fold cross-validation. The findings provide data driven actionable insights for policymakers to address specific obstacles, thereby enhancing the business environment for CMSMEs in Bangladesh. |
| format | Article |
| id | doaj-art-ba5c7aa8836b4cd5a2a25d24642cebf6 |
| institution | Kabale University |
| issn | 2405-8440 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj-art-ba5c7aa8836b4cd5a2a25d24642cebf62025-02-02T05:28:58ZengElsevierHeliyon2405-84402025-01-01112e42092Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithmsChandan Kumar Roy0Credit Guarantee Department, Bangladesh Bank (Central Bank of Bangladesh), Head Office, Dhaka, 1000, BangladeshThis study investigates the impact of business environment obstacles on the performance of Cottage, Micro, Small, and Medium Enterprises (CMSMEs) in Bangladesh, utilizing data from 998 firms in the 2022 World Bank Enterprise Survey. A recursive feature elimination algorithm identified ten key business factors and obstacles from an initial set of twenty-eight that significantly influence CMSME performance. Analysis using ordinary least squares (OLS) and generalized least squares (GLS) regression models reveals that investments in electricity infrastructure, access to financial services, and obtaining quality certifications positively impact CMSME performance. In contrast, challenges such as power outages, delays in licensing, uncompetitive practices, and stringent tax and labor regulations hinder performance. Additionally, the predictive accuracy of the OLS model was compared with several machine learning algorithms, including decision tree, random forest, support vector, and gradient boosting, using a 75-25 training-testing split and k-fold cross-validation. The findings provide data driven actionable insights for policymakers to address specific obstacles, thereby enhancing the business environment for CMSMEs in Bangladesh.http://www.sciencedirect.com/science/article/pii/S2405844025004724Business environmentFirm performanceCMSMEsMachine learning algorithmsFeature selection |
| spellingShingle | Chandan Kumar Roy Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms Heliyon Business environment Firm performance CMSMEs Machine learning algorithms Feature selection |
| title | Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms |
| title_full | Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms |
| title_fullStr | Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms |
| title_full_unstemmed | Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms |
| title_short | Dynamics between the obstacles of business environment and firm performance in Bangladesh: Survey-based empirical insights using ML algorithms |
| title_sort | dynamics between the obstacles of business environment and firm performance in bangladesh survey based empirical insights using ml algorithms |
| topic | Business environment Firm performance CMSMEs Machine learning algorithms Feature selection |
| url | http://www.sciencedirect.com/science/article/pii/S2405844025004724 |
| work_keys_str_mv | AT chandankumarroy dynamicsbetweentheobstaclesofbusinessenvironmentandfirmperformanceinbangladeshsurveybasedempiricalinsightsusingmlalgorithms |