Assessing the ICT development in Iranian cities: The strategy to accelerate digital advancement

• Published in: Technological forecasting & social change 2023-12, Vol.197, p.122904, Article 122904
• Main Authors: Amiri, Elham, Sangar, Amin Babazadeh
• Format: Article
• Language: English
• Subjects: CCR model; Clustering; DEA; Efficiency measurement; ICT development; ICT development index (IDI); Reciprocal efficiency
• ISSN: 0040-1625; 1873-5509
• DOI: 10.1016/j.techfore.2023.122904

Iran is one of the Middle East's developing countries, with a per capita GDP that ranks among the upper middle countries, according to international reports. On the other hand, according to research, the development of e-government in a country is directly tied to that country's economic status. Despite its economic strength, Iran is not well-positioned in the sphere of information and communication technology (ICT), with undesirable development of e-government and ICT infrastructure. The performance of Iranian provinces in the field of ICT development is analyzed in this study utilizing the DEA-CCR model, the Malmquist productivity index (MPI), reciprocal efficiency technique and k-means clustering. The main contribution of this study is that it aids policymakers and top managers by identifying poorly performing provinces, to make thorough preparations to strengthen them, and implement suitable policies and strategies. Indeed, by supporting and developing the weak provinces in the field of ICT, the overall ICT status of the country will improve. •In order to assess the digital divide in Iran, the state of ICT development in Iran's provinces during a nine-year period was investigated by the DEA-CCR model, the Malmquist productivity index (MPI), the reciprocal efficiency technique and k-means clustering.•The efficient and inefficient provinces in the development of IDI index were identified based on the provincial population and budget through DEA-CCR model and Malmquist Index.•For each province, the level of inefficiency in each sub-index of IDI was determined through DEA-CCR model and reciprocal efficiency technique.•The budget of each province was analyzed by k-means clustering.