Scenarios to Improve E-Commerce SMEs Activity Based on Their Classification: A Case Study on Romania

Ana Maria Mihaela Iordache (), Alexandru Ionescu, Vlad Gabriel Cârstea, Hanna Chung, Nicoleta Rossela Dumitru and Bogdan Glăvan
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Ana Maria Mihaela Iordache: Department of Informatics, Statistics and Mathematics, Romanian-American University, 012101 Bucharest, Romania
Alexandru Ionescu: Department of Commerce, Economic Integration and Business Administration, Romanian-American University, 012101 Bucharest, Romania
Vlad Gabriel Cârstea: Department of Commerce, Economic Integration and Business Administration, Romanian-American University, 012101 Bucharest, Romania
Hanna Chung: Department of Informatics, Statistics and Mathematics, Romanian-American University, 012101 Bucharest, Romania
Nicoleta Rossela Dumitru: Department of Management—Marketing, Romanian-American University, 012101 Bucharest, Romania
Bogdan Glăvan: Department of Commerce, Economic Integration and Business Administration, Romanian-American University, 012101 Bucharest, Romania

Sustainability, 2023, vol. 15, issue 15, 1-19

Abstract: With the onset of the COVID-19 pandemic, society has increasingly relied on alternative ways to procure goods, leading to an e-commerce boom. This study analyzes the performance of small and medium-sized enterprises (SMEs) that are active in e-commerce in Romania and provides recommendations for entrepreneurs to improve their efficiency. Through unsupervised learning techniques, three classes are identified according to company performance: (1) a class of high-performing companies whose entrepreneurs took the risk of investing in the business, (2) a class of medium-performing companies that maintained their position in the market and (3) a class of financially weak companies whose managers adopted risk-averse, defensive policies. Furthermore, we present scenarios for moving companies from a lower-performing class to a higher-performing class. The research identifies the strategies that managers need to adopt in order to stimulate the activity of e-commerce companies, provides foreign investors a rubric for making investment decisions, and offers a starting point for an entrepreneurship course in academia.

Keywords: classification; data analysis; scenarios; cluster; data mining; neural network; SMEs (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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