Barriers and Strategies for Digitalisation of Economy in Developing Countries : Pakistan, a Case in Point

Mahrose Nadeem, Yousaf Ali*, Obaid ur Rehman, Lauri Tapani Saarinen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)


Digital economy refers to the economic model where manual financial transactions, interactions, and activities are replaced or facilitated by digital tools. Incorporating digital tools has become an absolute necessity for economic development in the modern era. However, the digitalisation of economies faces several hindrances, especially in the underdeveloped and developing world. This study has two objectives. First, it aims to identify and analyse the barriers to digitalising the economy in Pakistan, a developing country. Second, it identifies and examines the strategies that can aid in overcoming these barriers and lead towards the digitalisation of the economy. It has employed Interpretive Structural Modelling (ISM) to analyse the obstacles and Fuzzy Quality Function Deployment (QFD) to examine the proposed solutions. Results indicate that the lack of adequate ICT infrastructure, lack of awareness of the business opportunities and benefits, and market challenges are the most significant barriers to the digitalisation of the economy. Furthermore, the introduction of artificial intelligence (AI), machine learning, advanced analytics, research and development, and standardisation of digital processes were recommended as the most effective measures. The study contributes to the research methods literature by proposing a hybrid methodology comprising ISM and Fuzzy QFD. In addition, the results of this study can be replicated across developing economies.

Original languageEnglish
JournalJournal of the Knowledge Economy
Publication statusE-pub ahead of print - 2023
MoE publication typeA1 Journal article-refereed


  • Barriers
  • Digital economy
  • Fuzzy Quality Function Deployment
  • Interpretive Structural Modelling


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