Journal article · 2024
Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics
International Journal of Services and Standards, 14(1), pp. 51–64 · Published
Summary
What question does this paper answer?
Do small and medium-sized enterprises (SMEs) in Albania that pilot data analytics perceive benefits in operational efficiency, process optimisation, profitability and market growth?
What did the study find?
In a survey of 41 Albanian SMEs, about 80% (33) had implemented data analytics, and data-analytics use was significantly and positively correlated with all four performance measures (r = 0.540 with operational efficiency up to r = 0.769 with process optimisation). A MANOVA showed a significant data-analytics effect (F(1, 38) = 20.029, Pillai trace = 0.696, p < 0.001), and a random forest model best explained the outcomes (R² = 0.661).
Why does it matter?
The authors conclude that the strong positive associations between data analytics and key performance indicators show SMEs should integrate data-driven mechanisms into their business strategies. For SMEs and policymakers, the study sets a baseline for further research and calls for attention to data analytics within business strategy.
Key findings
- The study surveyed 41 small and medium-sized enterprises (SMEs) in Albania, of which approximately 80% (33) reported having implemented data analytics, leaving the remaining 20% as a quasi-control group.
- Most respondents in the Albanian SME sample (23 of 41, or 56%) were female, which the authors note contrasts with the male-dominated samples in much of the empirical literature.
- Mean ratings for operational efficiency, process optimisation, profitability and market growth among the Albanian SMEs ranged from 3.1 to 3.7 on a 1–5 scale, with standard deviations of 1.2 to 1.3.
- Data-analytics use at the Albanian SMEs correlated positively with operational efficiency (r = 0.540, p < 0.05), process optimisation (r = 0.769, p < 0.001), profitability (r = 0.756, p < 0.001) and market growth (r = 0.707, p < 0.01), supporting H1.
- A MANOVA found a significant effect of data analytics on the four performance outcomes of the Albanian SMEs (approximate F(1, 38) = 20.029, Pillai trace = 0.696, p < 0.001), supporting hypotheses H2a–H2d.
- Among four machine learning models applied to the SME data, random forest performed best (MSE = 0.508, RMSE = 0.713, R² = 0.661), followed by SVM (R² = 0.619) and linear regression (R² = 0.404), while the neural network was faulty (R² = –2.914).
- A generalised linear model testing perceived benefits of data analytics was significant (p < 0.001) but had a small deviance versus a null model (Χ² = 55.452, DF = 16) and no significant individual coefficients, so further tests were needed.
Source: Vajjhala & Strang (2024), International Journal of Services and Standards, 14(1), pp. 51–64. DOI: 10.1504/IJSS.2024.140078
Study at a glance
| Research question | Did SME participants realise benefits from piloting data analytics: operational efficiency, improved operations, profitability and market expansion? |
|---|---|
| Design | Quantitative, post-positivist survey study with two hypotheses (H1 association; H2a–H2d perceived increases). |
| Sample | 41 SMEs in Albania across a range of industries and sizes; 23 of 41 (56%) respondents were female. |
| Methods | Descriptive statistics, Pearson and Spearman correlations, a generalised linear model, MANOVA, and four machine learning models (random forest, SVM, linear regression, neural network). |
| Main result | About 80% of SMEs had adopted data analytics, which was significantly and positively related to all four performance measures; MANOVA data-analytics effect F(1, 38) = 20.029, p < 0.001. |
| Implication | SMEs should integrate data-driven mechanisms into their business strategies; the study offers a baseline for SMEs and policymakers. |
| Citation | Vajjhala & Strang (2024) · DOI 10.1504/IJSS.2024.140078 |
Abstract
The study examines the impact of data analytics on the performance of small- and medium-sized enterprises (SMEs) in Albania. This post-positivist study adopts a quantitative-based approach drawing from both parametric statistics and machine learning models to analyse data collected from 41 SMEs in Albania. The research study was guided by two main hypotheses: the first hypothesis states that data analytics is related to operational efficiency, optimised operations, profitability, and market growth in SMEs; the second hypothesis states that the use of data analytics by the SME was perceived by the participants to significantly increase production. The results of the analysis showed that 80% of SMEs have accepted data analytics, which was positively associated with all key performance indicators. The outcomes reveal a strong association between data analytics and improved operating efficiency, efficient operations, profitability, and market expansion.
Abstract as published in International Journal of Services and Standards.
Keywords: data analytics; SME performance; operational efficiency; market growth; profitability; process optimisation; quantitative analysis; machine learning models; post-positivist approach; female entrepreneurs; statistical correlation; business strategy; innovation in SMEs; data-driven decision making; competitive advantage
Key terms
- Data analytics
- The use of data and analytical tools to inform business decisions, for example to predict sales, control inventory, understand customers and streamline operations.
- SME
- A small or medium-sized enterprise; in this study, participating firms ranged from fewer than 50 to 250–499 employees.
- Random forest
- A machine learning method that combines many decision trees to predict an outcome; here it best explained SME performance (R² = 0.661).
Limitations
- The sample size (41 SMEs) and the potential for response bias mean the findings are indicative rather than conclusive.
- The study was restricted to Albania, so applicability to regions with different economic and cultural contexts may be limited.
- The predominance of female entrepreneurs in the sample might present a skewed perspective on data analytics adoption and impact.
How to cite
Vajjhala, N. R., & Strang, K. D. (2024). Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics. International Journal of Services and Standards, 14(1), 51–64. https://doi.org/10.1504/IJSS.2024.140078
BibTeX
@article{vajjhala2024data,
title = {Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics},
author = {Vajjhala, Narasimha Rao and Strang, Kenneth David},
journal = {International Journal of Services and Standards},
volume = {14},
number = {1},
pages = {51--64},
year = {2024},
publisher = {Inderscience Enterprises Ltd.},
doi = {10.1504/IJSS.2024.140078},
url = {https://doi.org/10.1504/IJSS.2024.140078}
}Related research