ASSESSMENT OF REGIONAL DIGITAL DIVIDE IN TÜRKIYE

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Introduction
The world is changing rapidly, especially in the last decade.This change has accelerated with the help of new technological developments.Graham (2002) emphasised the two leading forces shaping the current era: urbanisation and digital information and communication technologies (ICTs).As of January 2021, 59.5% of the global population (4.66 billion active Internet users) are online (Statista 2022).Likewise, the urban population reached 55% of the world's population (4.2 billion inhabitants) in 2020.By 2050, it is estimated that approximately seven out of 10 individuals will live in cities (The World Bank 2020).Given the information, these two topics have become crucial for sustainable development policies.Not surprisingly, the United Nations (2015) pointed out their significance in the Sustainable Development Goals via many targets.
Despite these rapid developments, inequalities still exist.In 2019, a global breakpoint showed how vulnerable our world and cities are.ICTs have become even more critical of the influence of the lockdown period due to the unexpected COVID-19 pandemic.Improved digital infrastructure and society with digital abilities increased the potential to cope with several emergencies from COVID-19.Quite the reverse, the challenges worsened in countries with fewer digital opportunities.According to the OECD report (2021), the percentage of teleworking  ).Urbanisation can also be a determinant.The OECD Regions and Cities at a Glance Report (2020) states that "in 26 OECD countries, 1 in 3 households in rural areas do not have access to high-speed broadband on average" (OECD 2020a,b: 52).The COVID-19 pandemic proves that the digital divide still exists in different scopes of everyday life.
In the light of all information mentioned above, it is evident that digital inequalities can affect our lives; consequently, it becomes a vital theme for countries to monitor digital progress to have inclusive policies.Thus, this research will focus mainly on the literature on digital divide.Various studies are being conducted to discover the reasons behind digital inequalities.Primarily, researchers concentrated on having an Internet connection or not (the first-level digital divide); after that, the research focus shifted to ICT skills and usage (the second-level digital divide); lately, the research focus has turned to the outcomes of ICT use or tangible benefits (the third-level digital divide).Because of the complex nature of the digital divide, indexes deal with various aspects.The most recent indexes are the ICT Development Index (IDI) (ITU 2017), Digital Economy and Society Index (DESI) (EU 2018), andGoing Digital Toolkit (OECD 2021a,b,c).Despite the fact that all the existing monitoring tools are examining digital inequalities on an 1 https://www.meb.gov.tr/turkiye-uzaktan-egitim-istatistikleriyle-dijital-dunyanin-listelerini-zorladi/haber/21158/trSource: Ministry of National Education (MEB), 2020.international level, digital divide could differ between regions within the same country (Vicente, Lopez 2011).Besides, new research indicates that regional instruments support national measures to mitigate the digital divide (Szeles 2018).There are a few studies to reveal regional disparities in Türkiye in terms of the digital divide (Guz 2019;Koramaz et al. 2019;Ozcan Alp, Baycan 2024).yet, no tool has been developed to monitor digital disparities between Türkiye's regions.As an emerging economy, Türkiye needs to overcome the digital divide to maximise tangible benefits and boost innovation.This study aims to formulate a new index for monitoring regional digital divide in Türkiye.To do so, research starts with an inevitable question: What are the digital divide indicators in the case of Türkiye?Then goes further to reveal the digital divide between regions in Türkiye by using these indicators.Thus, the research involves three steps: finding digital divide indicators, formulating an index, and applying it for Türkiye.
The research is structured in five sections.The following section focuses on the literature on digital divide and the evolution of the term since the beginning.The second section also includes investigating recent indexes to understand digital divide indicators for all levels.The third section explores the indicators related to digital disparities in Türkiye and develops a new regional monitoring index.This allows us in the fourth section to use the new tool for revealing regional disparities in Türkiye.The final part provides brief conclusions and future research topics.

Brief evolution of the digital divide
The digital divide has emerged as an umbrella term for various aspects of digital disparities between individuals.The term entered common usage by the beginning of the 20th century and has been studied by several scholars.The digital divide was initially used in an official report Falling Through the Net by the US Department of Commerce's National Telecommunications and Information Administration (NTIA 1995), in which the term is not used as 'digital divide' but instead referred to those who have access to the Internet and who have not (the first-level digital divide).Conversely, the 1999 report Falling Through the Net did refer to the digital divide by counting all new technologies (NTIA 1999).After much research on material access, the term adjusted and comprehended additional aspects.According to Scopus, there were over 1,000 publications on this phenomenon since 2005 (Scopus 2022).In Table 1, three different phases of the digital divide are shown.
Initially, the term referred to material access (having Internet or not) (NTIA 1999), transformed into a more social issue, and included not only material access but also skills to use the Internet or computer (DiMaggio, Hargittai 2001).As a final step, the scope is broadened by outcomes of ICT use or tangible benefits (Warschauer 2011;van Deursen, Helsper 2015).
In the 2000s, some scholars claimed that the digital divide was shrinking because of the rapid penetration of the mobile Internet (Stump et al. 2008).However, in 2019, a global pandemic has shown that the digital divide still exists; as van Dijk explained, "The digital divide cannot be closed completely.When the whole world population would reach access to the digital media such as the Internet, inequalities of digital skills, usage and outcomes or benefits remain and even tend to grow" (van Dijk 2020: 1).Thus, the digital divide is needed to be considered for comprehensive development policies.
These theoretical digital divide considerations have affected the indexes that track countries' digital progress.Because of its complex nature, the indexes have many indicators related to all three levels.Table 2  DESI is more comprehensive than IDI and more complex as well.Not only material access but also usage, skills, and outcomes are targeted in DESI.However, it boosts the number of indicators (there are 33 indicators).
As the last index, OECD identifies seven policy dimensions in the Going Digital Toolkit (OECD 2021a,b,c) to shape digital transformation.The Going Digital Toolkit tackles various areas, such as embracing education, innovation, trade, and socio-economic outcomes.The index aims to assist governments with a complete governmental approach to the digital economy strategy.Unlike the previous two indexes, the Going Digital Toolkit recognises trust issues in digital technology.It uses some indexes as an indicator, such as OECD Digital Services Trade Restrictiveness Index and OECD Foreign Direct Investment Regulatory Restrictiveness Index, which are calculated on a country scale.In Appendix A, all indicators are listed in detail for each index.In the next section, indicators related to three levels of the digital divide will be discovered with the help of the indexes aforementioned and several scholars.

The first-level digital divide: Material access
The World Wide Web was invented in 1989 by the British computer scientist Tim Berners-Lee and started a revolution in the world (Bory et al. 2016).Parallel to computer and telecommunication technology evolution, in 2001, a life-changing association occurred via a smartphone connection with an existing 3G network (Jackson 2018).Since then, global Internet access has been growing each year.Statista (2021) states that the worldwide Internet penetration rate is 63%, increasing yearly.Thus, a common opinion among policy-makers is that the digital divide problem will be solved after universal access (van Deursen, van Dijk 2018).Conversely, the current situation is far from universal access.The Internet penetration rate differs in some parts of the world; for example, in developed and developing countries, the proportion of people using the Internet reaches 90% and 57%, respectively (Statista 2021).This disparity worsens in the least developed countries, where Internet access is estimated at 27% (Statista 2021).It is evident that economic development is one of the digital divide reasons.Thus, the prominent inequality occurred via the first stage: access to the Internet.
In addition to Internet access, another essential material access is ICT devices.Thanks to technological improvement, smartphones have become more widely available.In the least developed regions, there is a massive increase in people going online.However, some scholars suggest material inequality still requires attention (van Dijk 2005; Gonzales 2016).Van Deursen and van Dijk claimed that "material access includes the means required to maintain the use of the Internet over time, such as computer devices (e.g., desktops, tablets, Smart TVs), software (subscriptions), and peripheral equipment (e.g., printers, additional hard drives)" (2018: 355).The same study defines the 'mobile underclass' as people generally using smartphones and tablets for leisure purposes (gaming and social networking).They also mentioned device opportunity stating that "some combinations of devices are less likely to be beneficial than others in providing a wider variety of Internet uses and outcomes" (van Deursen, van Dijk 2018: 357).
Furthermore, new material divides appear simply because not all of the materials provide the same online opportunities; new material divisions emerge because of rapidly changing technology (van Deursen, van Dijk 2018).On the other hand, maintenance expenses are essential to sustain subscriptions and devices (Gonzales 2016).In 2018, van Deursen and van Dijk's study revealed that the first-level digital divide remained a problem in terms of "diversity in access to devices and peripherals, device-related opportunities, and the ongoing expenses required to maintain the hardware, software, and subscriptions affect existing inequalities related to Internet skills, uses, and outcomes" (p.354).It is reasonably surprising that the Netherlands, one of the most technologically advanced countries worldwide, where 98% of the population has home Internet access, still has first-level digital inequalities (van Deursen, van Dijk 2018).
There are many indicators related to the first-level digital divide in the indexes mentioned before, such as fixed or mobile broadband subscriptions, Internet speed, computer ownership, 4G/5G coverage, and broadband price.In the Digital Tool Kit, there are specific indicators like machine-to-machine (M2M) SIM cards per 100 inhabitants, the share of businesses with a broadband contracted speed of 30 Mbps or more, and the disparity in broadband uptake between urban and rural households.All indicators are listed in Appendix B.

The second-level digital divide: Skills and usage
According to recent statistics, there are 4.66 billion active Internet users worldwide, that is, 59.5% of the global population (Statista 2021).The percentage of active Internet users that accessed the Internet via mobile devices is 92.6 (Statista 2021).This statistic demonstrates the significance of affordable tools.However, some scholars discovered that people who only access the Internet through mobiles tend to have lower skills and conduct less diverse online activities than those who can use a computer (Correa et al. 2020).Thus, being online does not mean having equal benefits from the Internet.As Warschauer explained, "What is at stake is not access to information technology in the narrow sense (of having a computer on the promises) but in a much wider sense of being able to make use of information technology for productive ends" (2011: 2).In that case, the second-level digital divide becomes a hot topic on the literature on digital divide.Primarily, Kling (2000) pointed to the importance of inequality in users' possession of "know-how, a mix of professional knowledge economic resources, and technical skills, to use technologies in ways that enhance professional practices and social life" (Kling 2000: 256).After that, a study on the level of digital skills exposed the fact that "differences in digital proficiencies create new inequalities" (DiMaggio, Hargittai 2001).According to the study, "'Internet' itself is not a fixed object, but rather a protean family of technologies and services that is being rapidly reshaped through the interacting efforts of profit-seeking corporations, government agencies, and nongovernmental organizations.Patterns of inequality will reflect not just differences in individual resources, but also the way in which economic and political factors make such differences matter" (DiMaggio, Hargittai 2001: 4).The paramount need is to know how to use ICT to benefit from it.As a result, the scope of ICT usage becomes vital; social media usage, e-government usage, health data sharing intensity, cloud, and AI usage are indicators in DESI (EU 2018).Similarly, the Going Digital Toolkit offers indicators relevant to the scope of usage, such as the share of individuals using the Internet to interact with public authorities and the percentage of Internet users who have purchased online.
The second-level digital divide has many aspects, such as scope and diversity of use, types of skills, and education (DiMaggio, Hargittai 2001;Warschauer 2003;van Deursen, van Dijk 2018).Furthermore, second-level digital divide indicators deal with ICT usage among individuals and public and private sectors.Especially digitalisation of SMEs is a hot topic (OECD 2021a,b,c).The percentage of individuals using the Internet, SMEs with at least a basic level of digital intensity, SMEs selling online cross-border, the share of small businesses making e-commerce sales, the percentage of companies with a web presence, and the share of businesses purchasing cloud services are some indicators associated to SMEs digitalisation.
As a final comment for the three indexes, most indicators are intensely connected to the second-level digital divide.It is because the scope of the second-level digital divide is extensive.Here are distinctive indicators: basic digital skills, basic software skills, social media usage, big data usage, e-government users, and share of businesses purchasing cloud services.All indicators are listed in Appendix B.

The third-level digital divide: Outcomes or tangible benefits of ICT
The third-level digital divide is a relatively new topic in digital divide studies.The focus shift from skills and use of ICT to the beneficial outcomes of using ICT has been labelled the 'third-level digital divide' (Wei et al. 2011).Warschauer defined it as "social stratification due to unequal ability to access, adapt, and create knowledge via use of information and communication technologies (ICT)" (Warschauer 2011: 5).In other words, there are disparities in the ability to use online resources to have offline outcomes (van Deursen, Helsper 2015).An important question emerged: What are ICT outcomes or offline turnouts?There are various outcomes of ICT, both positive and negative.
Economic consequences include increased employment earnings, teleworking opportunities, and new job creation.Another influential outcome is educational opportunities via online education.Moreover, e-services help inhabitants to get in touch with public authorities and provide a base for public participation and social interaction.Finally, ICT can create a base for innovation, which can be counted as one of the most significant benefits of ICT.In this study, economic outcomes are accepted as the primary outcome.
DiMaggio and Bonikowski ( 2008) already revealed that employment earnings are triggered by more intensive Internet usage.Likewise, teleworking opportunities helped people to work from home during the pandemic.Technological circumstances transform not only companies but also individuals and make them more global.Van Deursen and Helsper suggest a dual relation: "Individuals who consistently convert their internet use into high offline returns such as earnings may benefit from a feedback effect where greater economic resources enable them to further develop their internet skills" (2015: 32).This dual relation is also valid for countries.Dewan and Kraemer (2000) discovered that ICT investment correlates with the level of development and relates to higher output in developed countries.The information economy is growing with new ICT task-intensive job opportunities.Additionally, Singer's (1970) theory of 'technological dualism' indicates the imbalanced progress in science and technology between rich and developing countries.This theory is coherent with "the outcomes of the dynamics of IT development that, so far, have resulted in 96% of total world IT research and development being located in rich countries" (Holley 2005: 200).In Türkiye's case, it is vital to use technology as a booster of innovation to maximise the ICTs' outcomes and to overcome technological dualism.
Van Deursen and Helsper show that "when information and services are offered online (or replaced by online counterparts), the number of potential outcomes the internet has to offer increases" (2015: 47).Additionally, OECD claims that "digital technologies have the potential to boost more inclusive and sustainable growth by spurring innovation, generating efficiencies and improving services" (OECD, 2020c).Not surprisingly, in the Going Digital Toolkit, there are several indicators in innovation theme, such as business R&D expenditure in information industries as a percentage of GDP, the share of startup companies in the business population, the top 10% most-cited documents in computer science as a percentage of the top 10% ranked documents, and patents in ICT-related technologies as a percentage of total IP5 patent families (OECD 2021a,b,c).In addition, researchers emphasise how digitalisation goes beyond the classic, technical understanding and encompasses shaping social, economic, and specialised structures: "Transformations in mobile media, internet development and digital publications are striking examples of digitalization currently taking place.
In these examples, digital innovations take place not only in innovations themselves but are also a result of the broader, socio-technical transformations of markets and industries" (Shakina et al. 2021: 3).
In the indexes mentioned in the second section, there are fewer indicators related to the third-level digital divide than at other levels.For example, in the IDI, no variable is associated with the third-level digital divide.DESI has four variables.Here are some variables: a share of startup companies (up to 2 years old) in the business population, ICT task-intensive jobs as a percentage of total employment, digital public services for citizens and businesses, and open data usage.Two of them are associated with adverse outcomes of new technologies: e-waste generated kilogrammes per inhabitant and percentage of Internet users experiencing abuse of personal information or privacy violations.All indicators are listed in Appendix B.

Additional divides: Demographic and socio-economic factors
In addition to all these levels of the digital divide, it is accepted by many international institutions that there are many demographic and socio-economic factors related to digital inequalities (ITU 2017, EU 2018, OECD 2021a,b,c).According to the EU, it is stated that factors such as gender, age, education, income, social groups, and geographical location can be determinative (Eurostat 2019).Additionally, many scholars propound demographic elements such as race/ethnicity, population density, urban/rural dimension, country size, employment status, and occupation (DiMaggio, Hargittai 2001; Billon et al. 2009;Scheerder et al. 2017;Grishchenko 2020;Lythreatis et al. 2022).DiMaggio and Hargittai (2001) claimed that enhancing human capital will strongly predict Internet use, improving social capital and political participation.They also estimated that "the Internet will be more strongly associated with positive life outcomes than will forms of Internet use that represent pure consumption activities" (DiMaggio, Hargittai 2001: 13).For positive outcomes of the ICT, education is vital.In all indexes, there are several indicators associated with education.For example, the mean year of schooling, secondary and tertiary gross enrolment ratio is in IDI; ICT graduates, ICT specialists, and female ICT specialists are involved in DESI, and top-performing 15-to 16-year-old students in science, mathematics, and reading are in the Going Digital Toolkit.
In addition to education, many indicators in the three indexes are intensely connected to demographic and socio-economic factors.Here are some indicators: disparity in broadband uptake between urban and rural households, the disparity in Internet use between men and women, and ICT investment as a percentage of GDP.All indicators are listed in Appendix B.

A new digital divide index
In this study, the digital divide is considered in four phases.Even if it seems similar to the existing literature, there are some unique considerations.The first step represents material access and skills together because conscious usage of them is possible with proper strategic, informational, and instrumental digital skills (van Dijk 2005).The second step represents the usage in terms of variety and regularity (DiMaggio, Hargittai 2001;Warschauer 2003;van Deursen, van Dijk 2018).The third phase represents the outcome of Internet usage (van Deursen, Helsper 2015); the consequences can create benefits for individual users or an innovation driver for communities or countries.In Türkiye's case, using technology as a booster of innovation is crucial to overcome the digital divide in terms of Singer's (1970) theory of technological dualism.Thus, here in this study, innovation is considered the primary effect.
As a final comment, to have digital inclusions, all three phases should be equal for all individuals in various socio-demographic and socio-economic conditions (ITU 2017; EU 2018; OECD 2021a,b,c).Thus, the fourth phase represents socio-demographic and socio-economic divides.

Data and methodology
In the previous section, three recent and international indexes, IDI (ITU 2017), DESI (EU 2021), and Going Digital Toolkit (OECD 2021a,b,c), were analysed.According to the proposed conceptual framework, the second step is identifying digital inequality indicators that can be used in Türkiye's case.After identifying appropriate indicators, the data-gathering process starts via various data sources.While TurkStat is the leading data provider, various other public and private authorities, such as the Information Technologies and Communications Authority, Ministry of Industry and Technology, and TurkPatent, were used as statistical data resources for the study.All indicators with data sources and units are listed in Appendix C. Thanks to principal component analysis (PCA), a new index for Türkiye will be constructed.As a final step, QGIS does the spatial analysis of digital inequalities at the regional scale (NUTS1 -12 sub-regions) and provincial scale (NUTS3 -81 provinces).

Exploring indicators for Türkiye
All indicators are divided into four categories explained in the conceptual framework.There are 19 indicators associated with the first-level digital divide, 30 indicators are connected to the second-level digital divide, and 17 hands are mainly about the third-level digital divide.Finally, 21  ).Thus, this study accepts techno parks, R&D, and design centres as digital-intensive sectors.The number of businesses making e-commerce, ICT goods, and services as a share of international trade is also used as third-level digital divide indicators.Additionally, demographic and socio-economic factors play a vital role in Türkiye because low purchasing power creates an economic barrier to digital technologies (Ozcan Alp, Baycan 2024).ITU (2017) states that computer ownership in Türkiye is 20% lower than the European average.Additionally, Türkiye's human capital score is nearly half of the average score of the EU member states (EU 2021).Another interesting aspect is gender inequality; the gap in Internet use between men and women in the western part is smaller compared to the eastern part of Türkiye being 6% and 22%, respectively (TurkStat 2021).Demographic and socio-economic factors include disparity in Internet use between men and women, age dependency, mean year of schooling, secondary gross enrolment ratio, percentage of tertiary graduates, poverty ratio, urban and rural households, business R&D expenditure, and GDP.
As a final step, repeated indicators are gathered, such as the percentage of households with Internet access, the share of households with fixed broadband access, and the rate of households with mobile broadband access.Similarly, indicators related to Internet speed are simplified at the length of fibre optic cable since there is no other suitable statistic for Internet speed in Türkiye.
Unluckily, many indicators could not be used because of a lack of precise or equivalent statistical data.No region-or city-scale data are available since many are measured countrywide, such as individuals' basic digital and software skills, enterprises providing ICT training, and electronic information sharing.Furthermore, the study has limited the need for regional statistics such as e-government and e-health usage.Even if the ratio of e-government users is increasing in Türkiye (58.9%), it is still not equal among all regions (TurkStat 2021).Another significant limitation of the study was that there were no data on digital literacy and skills at a regional scale, which is the most problematic issue in Türkiye.In particular, digital skills are missing in Level 1.According to DESI (2020), Türkiye's human capital score (23.0) was almost half the EU member states' average (41.8).The final list of indicators can be seen in Table 3.All indicators with data sources and units are listed in Appendix C (Table 3).
Principal component analysis is used to determine the final indicators.PCA helps to have a relatively simple index by dropping the number of variables.It has been performed for all levels using the Statistical Package for the Social Sciences (SPSS).Before PCA, Pearson correlation is applied to all data, and indicators with a high correlation are eliminated by checking the correlation matrix score (r > 0.80).Six indicators have been removed as the high correlation score are the percentage of households with fixed broadband access, the share of the population covered by at least a 4G mobile network, mean year of schooling, percentage of tertiary graduates, and GDP.Then, PCA is applied to the remaining indicators.Three main steps are as follows: 1.The significance of KMO and Bartlett's test was checked (KMO > 0.6 and Bartlett sig < 0.05).2. Communalities were examined in how each factor affected the total factor, and weak values were eliminated (extraction <500).3.According to the component matrix TBA analysis, those with a low coefficient of explanation (Component Loadings <600) were excluded.
ICT goods and services as a share of international trade and poverty ratio are eliminated because of PCA.After that, for each level, PCA was applied with the final indicators for each level.The results derived from the PCA are shown in Table 4.
Thanks to PCA, final indicators are determined.Then, to have a precise index, the weights are computed with the help of the IDI methodology.Finally, the following three steps are performed: 1.The component loadings were squared and divided by the share of variance explained by the component.2. The results were multiplied by the variance ratio explained by the component and total variance.3. The derived weights were rescaled to sum up to 100 (to increase comparability) (ITU 2009: 81).
The contribution of all four levels to the new index has been determined to be equal.As a final step, the ideal value is calculated by adding two standard deviations to the mean value of the indicator (ITU 2009).After various stages, the last index can be seen in Table 5.

Results and discussion
The new index is applied at regional (NUTS1 -12 sub-regions) and city scales (NUTS3 -81 provinces).The results indicate a digital divide among Türkiye regions.While regions generally converge in terms of access and use of technology (Levels 1 and 2), it is seen that the tangible benefits obtained from technology (Level 3) differ from each other in Türkiye.Levels 1 and 2 score between 0.25-0.18and 0.49-0.28,respectively.However, the score range varies for Level 3, between 1.98 and 0.01.At the same time, it is observed that the socio-economic and demographic factors (Level 4) that are effectual in outcomes differ between regions.The score range varies for Level 4, between 0.15 and 0.07.Since Level 3 represents the outcome of Internet usage (van Deursen, Helsper 2015), to be specific,  The results indicate that fostering the ability to use technology, supporting gender equality, encouraging R&D expenditures, and supporting initiatives, especially ICT initiatives, will assist in reducing digital inequalities in Türkiye.Tables 6  and 7 represent the new index scores on regional and city scales.

Regional scale (NUTS1 -12 sub-regions)
Digital development differences between regions within Türkiye are seen in Figure 2. TR1

City scale (NUTS3 -81 provinces)
TR100 Istanbul significantly differs from all provinces at the city scale, similar to the regional scale.However, the inequalities between provinces are more pronounced than in regions.Some cities stand out with specific indicators, such as TR310 İzmir excessive enterprises, TR510 Ankara with high R&D expenditures, and the number of techno parks, R&D, and design centres.On the other hand, while the number of enterprises is high in TR421 Kocaeli, the rate of ICT enterprises is relatively low.That caused a low overall index value, and TR411 Bursa surpassed TR421 Kocaeli's ICT initiatives.Helsper 2015) and economic outcomes; specifically, innovation is considered the primary outcome (Shakina et al. 2021).As a further divide, all individuals in various socio-demographic and socio-economic conditions (ITU 2017;EU 2018;OECD 2021a,b,c) should be considered equal for digital inclusion.

Conclusion
The indicators encompassing all aspects of the digital divide are analysed for Türkiye.The maps the digital divide at regional level (NUTS1 -12 Sub-Regions) and city level (NUTS3 -81 provinces); however, disparities are more significant at the city scale.While regions in Türkiye generally converge in terms of access and use of technology (the first and second-level digital divide), the tangible benefits of technology (the third-level digital divide) are divergent.The primary findings of the study indicate the reasons, which are uneven digital skills, socio-economic and demographic divides, and R&D expenditure as a percentage of GDP.All of them gain imbalanced scores between the regions.To enhance digital inclusion, Türkiye needs to focus on fostering the ability to use technology, supporting gender equality, encouraging R&D expenditures, and supporting initiatives, especially ICT initiatives.
This study has developed a comprehensive index containing all digital divide aspects.In addition, the results demonstrate how digital inequalities exist in regions within the same country.Similar to the previous studies, the findings show that there are many determinants of outcomes of technology usage.This study's determinants are uneven digital skills, socio-economic and demographic factors, and R&D expenditure.However, the study has some limitations owing to a lack of precise or equivalent statistical data at a regional scale, such as individuals' basic digital and software skills, ICT usage in enterprises, e-government usage, and digital literacy.Despite these study limitations, digital development differences at the regional scale have been revealed.More than that, the regional strengths and weaknesses have been exposed.Future studies can be focused on the physical effects of digitalisation in cities.
economic outcomes are considered the primary outcome in this study; the disparities are conspicuous.It can be related to socio-economic and demographic factors and unequal ability to use ICT(Warschauer 2011) to have offline outcomes(van Deursen, Helsper 2015).Supportively, Türkiye's human capital score is lower than most EU members (EU 2021).Another critical factor is R&D expenditure as a percentage of GDP and the disparity in Internet use between men and women.That indicators show relatively unequal distribution between the regions.Furthermore, two distinctive indicators in Level 3 are ICT companies in the business population and techno parks, R&D, and design centres for the regions in Türkiye.Therefore, these two indicators need to be targeted to boost the outcomes of ICTs and overcome technological dualism.
This article proposes a new digital development monitoring index to understand and observe the digital development differences in Türkiye.With the help of the current literature, a comprehensive monitoring index is presented.The monitoring tool consists of three different levels of digital divide: Level 1 represents material access and skills (van Dijk 2005), Level 2 represents usage in terms of variety and regularity

Table 1 .
Three levels of digital divide (adopted from van Deursen, van Dijk 2018).
of them are primarily corresponding to other divides.All indicators are listed in Appendix B. After the categorisation, the next step is to evaluate them in the case of Türkiye.To do so, three questions help with the identification.They are

Table 4 .
Results of PCA.

Table 5 .
A digital divide index for Türkiye with final indicators.

Table 6 .
Regional digital divide results.