An MCDA-based Framework for Prioritizing Digital Transformation Projects in Small and Medium-sized Enterprises

Authors

  • Juan Antonio Álvarez Gaona Faculty of Marketing, Autonomous University of Coahuila, Saltillo, Mexico,
  • Juan Antonio Granados Montelongo Department of Renewable Natural Resources, Antonio Narro Autonomous Agrarian University, Saltillo, Mexico,
  • José Daniel Corona Flores Academic Language Unit, Antonio Narro Autonomous Agrarian University, Saltillo, Mexico,
  • Magaly Martinez Galvan Department of Research, American University of the Northeast, Saltillo, Mexico,
  • Ramón Herrera Torreón Technological Institute, National Technological Institute of Mexico, Mexico,
  • Francisco Magallanes Torreón Technological Institute, National Technological Institute of Mexico, Mexico,
  • Abril Flores Faculty of Accounting and Administration, Autonomous University of Coahuila, Saltillo, Mexico.

Keywords:

Multicriteria Decision-Aiding, Digital Transformation, Project Prioritization, Decision Support Systems

Abstract

There is increasing pressure on Small and medium-sized enterprises (SMEs) to force digital technologies to maintain their competitiveness, viability, and agility amid dynamic market conditions. Yet, there are difficulties associated with selecting priorities among potential digital transformation projects due to constraints like budget restrictions, technological uncertainty, organizational limitations, and numerous strategic and operational considerations that have to be weighed against each other. In this regard, this research seeks to provide an MCDA approach that can be leveraged by SMEs in evaluating and prioritizing digital transformation efforts. The MCDA framework suggested by this paper involves structured criteria related to strategic alignment, project cost, anticipated impact on operations, technological feasibility, cybersecurity risk, organizational readiness, and speed of deployment. The MCDA model provided in this study offers a structured means of making informed decisions, combining criteria weighting and alternative ranking. This methodology seeks to improve the subjectivity of the selection process, align digital investments more closely with business objectives, and improve decision-making when constraints are involved. The research is useful in terms of contributing to existing methodologies, but what makes it more important is the contribution it offers to SMEs from various industries through a helpful tool that will allow them to develop plans related to their digital initiatives. This model helps increase the convergence between multiple criteria aiding decision-making, digital transformation, and intelligent management systems.

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Published

2025-12-02

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Section

Articles