 ERP adoption prediction using machine learning techniques and ERP selection among SMEsAveek Basu and Rohini Jha International Journal of Business Performance Management, 2024, vol. 25, issue 2, 242-270 Abstract: Small and medium scale industries (SMEs) have always been the backbone of a country's economy as they play a vital role in ensuring the goals such as balancing regional development, equality of income, and poverty alleviation by employment generation. However, SMEs are resistant to growth; facing challenges in sustainability in digital era. Others stay small and avoid taxation related problems. SMEs in developing nations are one of the most aggressive adopters of ERP packages. At times they have incurred huge capital expenses which ultimately raises a question mark in their survival on account of incorrect selection. ERP systems can benefit SMEs post COVID era. In this paper, machine learning techniques applied to predict adoption of ERP and multi-criteria decision-making technique (MCDM) applied for vendor and type of ERP selection viz. cloud ERP, on premise, or hybrid ERP will be suitable for SMEs and appropriate vendors. Keywords: enterprise resource planning; ERP; cloud ERP; small and medium enterprise; SME; K-nearest neighbour; decision tree; machine learning algorithms; multi-criteria decision making. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbpma:v:25:y:2024:i:2:p:242-270 Access Statistics for this article More articles in International Journal of Business Performance Management from Inderscience Enterprises Ltd |
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