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
Vajjhala and Strang (2024) surveyed 41 small and medium-sized enterprises (SMEs) in Albania to test whether those piloting data analytics perceive benefits in operational efficiency, process optimisation, profitability and market growth. Data-analytics use correlated positively with all four performance measures (r = 0.540 to 0.769), with a significant multivariate effect (MANOVA F(1, 38) = 20.029, p < 0.001), and a random forest model explained the outcomes best (R² = 0.661). Given the sample size and the potential for response bias, the findings are indicative rather than conclusive.
Practical implication. SMEs should integrate data-driven mechanisms into their business strategies, the authors conclude from the strong positive associations between data analytics and key performance indicators among 41 Albanian SMEs.
- The Problem
- Small and medium-sized enterprises in transition economies such as Albania are adopting data analytics, but evidence on whether it improves their performance is scarce.
- The Methodology
- Quantitative post-positivist survey of 41 Albanian SMEs: descriptive statistics, Pearson and Spearman correlation, generalised linear model, MANOVA, and random forest, SVM, linear regression and neural network models.
- The Core Finding
- Among 41 Albanian SMEs, data-analytics use correlated positively with operational efficiency, process optimisation, profitability and market growth (r = 0.540 to 0.769), with a significant multivariate effect (MANOVA F(1, 38) = 20.029, p < 0.001); a random forest model explained the outcomes best (R² = 0.661).
- The Citation
- 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
The summary, key findings, methods, implications and relevance notes on this page are this website’s own description of the paper, written from the published abstract and text. The official abstract and citation details are given further down.
Key findings
- Finding 1. 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.
- Finding 2. 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.
- Finding 3. 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.
- Finding 4. 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.
- Finding 5. 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.
- Finding 6. 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).
- Finding 7. 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
The study in detail
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 detail?
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.
Methods and data
| 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 |
Definitions and 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. — as used in Vajjhala & Strang (2024)
- SME
- A small or medium-sized enterprise; in this study, participating firms ranged from fewer than 50 to 250–499 employees. — as used in Vajjhala & Strang (2024)
- Random forest
- A machine learning method that combines many decision trees to predict an outcome; here it best explained SME performance (R² = 0.661). — as used in Vajjhala & Strang (2024)
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
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.
Practical implications
- The authors conclude that SMEs should integrate data-driven mechanisms into their business strategies, because data-analytics use was positively associated with operational efficiency, process optimisation, profitability and market growth.
- Policymakers and SMEs can use the study as a baseline for further research, and it calls for attention to data analytics within business strategy.
- For SMEs and policymakers, the findings are indicative rather than conclusive, given the sample size (41 SMEs) and the potential for response bias.
- The findings may be less applicable to SMEs and policymakers in regions with different economic and cultural contexts, because the study was restricted to Albania.
Drawn from Vajjhala & Strang (2024), International Journal of Services and Standards, 14(1), pp. 51–64.
When this research may be relevant
This article may be relevant to literature on data analytics adoption and business performance in small and medium enterprises, digital transformation in Albania, the Western Balkans and other emerging markets, and studies combining classical inferential statistics with machine learning on small survey samples.
Research topics addressed: data analytics; SMEs; Albania; emerging markets; business performance; profitability; operational efficiency; market growth; machine learning; random forest; support vector machine; MANOVA; Pearson correlation; female entrepreneurs
How to cite
- APA 7
- 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
- MLA 9
- Vajjhala, Narasimha Rao, and Kenneth David Strang. “Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics.” International Journal of Services and Standards, vol. 14, no. 1, 2024, pp. 51–64. https://doi.org/10.1504/IJSS.2024.140078.
- IEEE
- N. R. Vajjhala and K. D. Strang, “Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics,” International Journal of Services and Standards, vol. 14, no. 1, pp. 51–64, 2024, doi: 10.1504/IJSS.2024.140078.
BibTeX
@article{vajjhala2024dataanalytics,
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}
}RIS
TY - JOUR TI - Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics AU - Vajjhala, Narasimha Rao AU - Strang, Kenneth David JO - International Journal of Services and Standards PY - 2024 DA - 2024 VL - 14 IS - 1 SP - 51 EP - 64 PB - Inderscience Enterprises Ltd. DO - 10.1504/IJSS.2024.140078 UR - https://www.narasimharao.net/research/data-analytics-sme-performance-albania/ LA - en ER -
Links and files
- DOI: https://doi.org/10.1504/IJSS.2024.140078
- This page as text: https://www.narasimharao.net/research/data-analytics-sme-performance-albania/paper.md
- Permanent address of this page: https://www.narasimharao.net/research/data-analytics-sme-performance-albania/
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