Decision-Making and Financial Performance in E-Commerce SMEs: Perceptions on Data Analytics and Artificial Intelligence

Laura Vasilescu (), Mirela Sichigea, Valeriu Brabete, Daniel Goagara and Dorel Berceanu
Additional contact information
Laura Vasilescu: University of Craiova, Craiova, Romania
Mirela Sichigea: University of Craiova, Craiova, Romania
Valeriu Brabete: University of Craiova, Craiova, Romania
Daniel Goagara: University of Craiova, Craiova, Romania
Dorel Berceanu: University of Craiova, Craiova, Romania

The AMFITEATRU ECONOMIC journal, 2026, vol. 28, issue 72, 650

Abstract: The study explored and interpreted the perceptions of managers of Romanian small and medium-sized enterprises (SMEs) in the e-commerce sector regarding the effects of adopting data analytics and artificial intelligence technologies on decision-making processes and financial performance. The research was conducted using a qualitative approach based on 25 semi-structured interviews with managers and business owners. The data were processed through manual coding, supported by thematic analysis using QDA Miner Lite. The following dimensions were examined: the level of adoption of digital technologies, the factors that drove their implementation, the perceived influence on the decision-making process, and the effects on financial performance. The results revealed an intermediate level of digital maturity, dominated by the use of descriptive analytics, while AI applications were only partially implemented. The main barriers identified were the deficit of digital competencies and financial constraints, with variations across firm size categories. As these barriers are overcome, the adoption of data analytics and artificial intelligence technologies contributed to a more rigorous grounding of decision-making and to improved financial performance through sales optimisation, cost reduction, and inventory management efficiency. The study provided a contextualised understanding of the adoption of advanced technologies by Romanian SMEs, capturing specific features and nuances of managerial experiences that are difficult to quantify through quantitative approaches, thus contributing to the expansion of empirical knowledge in the field of e-commerce.

Keywords: decision-making; artificial intelligence; data analytics; financial performance; SMEs; e-commerce. (search for similar items in EconPapers)
JEL-codes: D83 L81 M10 M15 O33 (search for similar items in EconPapers)
Date: 2026
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.amfiteatrueconomic.ro/temp/Article_3542.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aes:amfeco:v:28:y:2026:i:72:p:650

Access Statistics for this article

More articles in The AMFITEATRU ECONOMIC journal from Academy of Economic Studies - Bucharest, Romania Contact information at EDIRC.
Bibliographic data for series maintained by Valentin Dumitru ().