A new urban digitization index calculation model proposal based on multi-criteria decision-making techniques: Turkey application

The integration of new mobile and digital technologies has started to integrate with digital sensors to enable cities to digitally transform and become Smart Cities. Therefore, "Developing a new Computational Model to measure the Urban Digitization Index and evaluating different Digital Transformation rankings of cities with the help of this model" was determined as the aim of the research. For this purpose, the dimensions, Critical Success Factors (CSF), and indicators affecting Digital Transformation (Digitalization) and Smartening of Cities have been determined through literature review, information forms, and interviews. Indicator data affecting the Digitalization of Cities were collected from city institutions such as the municipality, TSO, Türk Telekom, Police Department, SGK, MEB, district governorship, and national statistical institutions (TUIK, BTK, TİM, TOBB, etc.). Different Urban Digitization Maps (UDM) were derived from the collected data based on CSFs. The weighted and unweighted Urban Digitization Indices (UDI) were determined by the "Satyam" technique with the areas on these maps. The cities are ranked among themselves with these determined UDI values. Then, these determined different city rankings were brought into a single integrated ranking with the TOPSIS technique. In the calculation of the weighted UDIs, the "Categorical Value Selection" was used in the calculation of indicator weight, "SWARA" was used in the calculation of CSF weight percentages, and "AHP" was used in the calculation of dimension weight percentages. At the end of the research, the Digital Transformation rankings of eight districts of Zonguldak province and 81 province centers of Turkey were determined separately. It has been observed that each province and district have different weighted and unweighted UDIs in the resulting ranking table. It has been seen in the UDI rankings that the SC applications used in the cities and the university and internet-related indicators significantly affect the UDI rankings. UDI rankings and UDMs can show the status of the city's Digital Transformation level to the city managers. This way managers can make appropriate decisions in determining the necessary strategies, policies, and plans for Digital Transformation and smartening of cities. In this way, urban resources can be used more effectively, sustainably, and productively. The most important result of the research can be expressed as the presentation of a new Urban Digitization Index calculation model to the literature by using Multi-Criteria Decision-Making techniques such as SWARA, AHP, TOPSIS, Categorical Value Selection, and Satyam UDI Calculation Techniques in an integrated way.