[
  {
    "id": "10.1504/IJSS.2024.140078",
    "type": "article-journal",
    "title": "Profitability, effectiveness, operational efficiency, and market growth of SMEs in Albania after piloting data analytics",
    "author": [
      {
        "family": "Vajjhala",
        "given": "Narasimha Rao"
      },
      {
        "family": "Strang",
        "given": "Kenneth David"
      }
    ],
    "container-title": "International Journal of Services and Standards",
    "issued": {
      "date-parts": [
        [
          2024
        ]
      ]
    },
    "volume": "14",
    "issue": "1",
    "page": "51-64",
    "publisher": "Inderscience Enterprises Ltd.",
    "DOI": "10.1504/IJSS.2024.140078",
    "URL": "https://www.narasimharao.net/research/data-analytics-sme-performance-albania/",
    "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.",
    "keyword": "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, SMEs, Albania, emerging markets, business performance, machine learning, random forest, support vector machine, MANOVA, Pearson correlation",
    "language": "en"
  }
]