Digitalization and the Information Society in Algeria: Digital Transformation Actors and Key Variables

the Information


Introduction
The economy has undergone a profound transformation in recent years, marked by the emergence of information and communication technologies (ICT) as a determining engine of economic growth. ICT have radically changed the state of play in developed countries, which are now information societies, and have generated a strong interest in developing countries, which seek to leverage them to accelerate their development. This digital revolution has led to the emergence of a computer culture that has transformed practices and social relations in society. In contemporary economies, technology is the main driver of improving the quality of life for people in developing countries, but it is also a lever for economic growth in industrialised, developed, and emerging countries (Mattelart, 2009).
Moreover, ICT occupy a crucial and even central place in our economies, as the transfer of knowledge and information (usually done through interpersonal contacts) has undergone a transformation . The concept of the new economy refers to the increase in growth generated from the late 1990s by new information and communication technologies (NICT). While this change was initially seen as a new industrial revolution, this new economy permeates all layers of our society, and it now seems to animate and inspire all sectors of economic activity, productivity and innovation. Gradually, it is fueling discussions about the emergence of the new economy, characterised by a significant presence of ICT that are viewed as instruments of economic and technical progress" (Accart, 2004).
Today, it is generally recognised that the shift towards an information society is not a matter of choice, but a necessity. Information and communication technologies (ICTs) have become an indispensable tool for decision-making and achieving sustainable development goals. In this context, many countries, such as the United States, have understood the vital importance of this new economy, both for wealth creation and social progress, and are promoting its development by investing in high-speed transmission infrastructure programs, also known as "information highways" (Chevalier, 1997).
However, so far this technological transformation has been marked by extreme disparities in access to this new culture between developing and developed countries.
While the provision of infrastructure is a necessary condition, it is not sufficient to address these diffusion inequalities. Indeed, there are gaps not only in access to ICTs and their use between industrialised nations and developing countries, but also between the rich and poor within a single country, as well as between different regions within a single country (Gollac & Afriat, 2003).
To analyse the technological revolution in its entirety and in a practical manner, it could be useful to study the experiences of global and regional leaders recognised for their remarkable contributions to economic performance through ICTs (Aísa et al., 2011). However, this should not prevent from paying closer attention to other developing countries, such as Algeria, for their advanced positioning in the fields of the information society. Although the information society has become a new culture and way of life for citizens in developed countries, its presence in third-world countries remains thin and limited to certain sectors such as higher education, scientific research, airlines, and financial companies, which have a strong capacity for using ICTs (Nwamen, 2006).
The objective of this article is twofold. First, the authors analysed the situation of Algeria and its position in relation to other countries regarding the information society. Next, they examined the factors that influence the development of the information society in Algeria, trying to identify the most important ones. Finally, a development strategy in this area was proposed. The research thesis was formulated as follows: What are the key variables that have an impact on the development of digitalization and the information society in Algeria? To provide answers to the questions raised above, the authors relied on the following two hypotheses: • H1: Investment in emerging technologies has an impact on the development of digitalization and the information society in Algeria. • H2: The low impact of investment in emerging technologies on the development of digitalization and the information society is explained by cultural and legal factors.
To explain the measurement variables of the information society and their grouping into homogeneous sub-groups, the study used a multidimensional analysis method to identify classes of countries and observe Algeria's position among the countries of the world. The authors also determined the characteristics of the leaders' class in order to conduct a comparative analysis between the class in which Algeria is positioned, and the reference class where the most advanced countries are located. Next, the study examined the available data and used advanced statistical tools to process the data and study the characteristics of Algeria's group. This allowed to identify the most influential variables and propose strategies to help Algeria move from one group to another in terms of the development of the information society and digitalization. In summary, the study aimed to understand the different dimensions of the information society and propose solutions to help Algeria improve its position in this field (NRI, 2020).

Literature review
The development of the information society in a country or group of countries is closely linked to their level of economic and social development, as evidenced by statistics. Indeed, the classification of countries into three categories (advanced, developing, and least developed) is based on quantifiable scientific indicators that evaluate the degree of development of the information society in a country or region, based on the mastery of information and communication technologies (ICT). ICT play an important role in promoting other socio-economic and industrial sectors and also constitute a separate sector of activity, contributing to the increase of GDP and job creation (Dańska-Borsiak, 2022). The economic and performance indicators such as GDP, generated revenue and profits, the number of jobs created each year, and the budget allocated to research and development in these sectors, allow for an assessment of the level of development of the information society (Bojnec & Ferto, 2012). The penetration rate of ICT in different layers of society is also a key element for evaluating this development. Among these indicators, the number of stationary telephone lines and personal computers per 100 inhabitants constitute the basic data necessary for any evaluation (Bensiam & Marquaire, 2018).
According to the ITU, the United States, Japan, and the countries of the European Union are the leaders in the field of information society, thanks to their policies and actions promoting ICT. The importance given by public authorities to this sector is reflected in several indicators. National-level actions and cooperation efforts among EU countries show a common vision of the information society, based on principles such as promoting dynamic competition, encouraging private investment, establishing a flexible regulatory framework, guaranteeing open access to networks, providing universal services, promoting equal opportunities for all citizens, promoting diversity of content, and developing international cooperation in this field (CNUCED, 2019).
In France, the ICT sector represents just over 8% of the value added by businesses, which is similar to the European level. By comparison, in the United States, this figure is 11.1% and 9.6% in Japan. However, in some small European countries specialising in telecommunications (such as Finland) or in the assembly and reexportation of computer hardware (such as Ireland), the weight of ICT in value added exceeds 15%. In contrast, in Germany and the Netherlands, the percentage is around 6% (Philip et al., 2010).
The global production of ICT is marked by three major trends. Firstly, the United States confirms its leadership by producing 30% of ICT goods in the world, surpassing Western Europe (21%) and Japan (19%). The US is competitive in all segments except for consumer electronics. They were the first to benefit from the industrial fallout of the new economy. Secondly, new players are emerging in the ICT sector, particularly Korea which is increasingly present in all ICT industrial sectors, as well as Taiwan in components, along with Chinese companies. Finally, Ireland has become one of the most important platforms for assembly and re-exports in the computer field, thanks to the inflow of foreign investments. European performance is mainly due to the Scandinavian model, particularly that of Finland, which specialises in the mobile phone industry. However, the French model is distinguished by the importance given to services, which represent 62% of the sector's production (UIT, 2018).
In 2022, the information society continued to develop, with widespread diffusion of ICT around the world. Key points to note include (UIT, 2022): • Since 2005, fixed-line telephony has continued to decline, particularly in developed countries, where the number of mobile phones exceeds that of fixed lines. • According to the latest available statistics, the penetration rate of mobile phones in developed countries continues to be at high levels, often exceeding 100%. According to 2021 data, some countries such as the UK, Germany, and the United States have penetration rates of over 120%. This means that there are more mobile phones than people in these countries. Due to this saturation, the growth of the mobile phone market in developed countries is limited.
In 2022, the growth rate was only 6%, according to Statistic data. In contrast, the mobile phone market in developing countries remains very dynamic, with a growth rate of 4.4% in 2022. This growth rate is mainly driven by increasing demand for affordable smartphones and the expansion of mobile connectivity in these regions. • The analysis shows that universal and meaningful connectivity -the possibility for everyone to enjoy a safe, satisfying, enriching, productive and affordable online experience -remains a distant prospect for LDCs. For example, only 36% of the population in LDCs used the Internet in 2022, compared with 66% globally. As many as 17% of the population in LDCs did not even have access to a fixed or mobile broadband network, the so-called access gap. The remaining 47% offline population, representing the usage gap, were facing other barriers, such as the affordability of ICT services. Accessing the Internet in LDCs is more costly than anywhere else. The price of a benchmark mobile broadband basket with a 2 GB monthly allowance in a typical LDC amounts to almost 6% of the average income -around four times the typical world price of 1.5%. Only two LDCs met the UN Broadband Commission's affordability 2% target. • The number of internet users doubled in the last five years, with over 3.9 billion internet users worldwide. Growth is driven by large countries such as Brazil, China, India, Nigeria, and Russia. • 65.6% of the entire world's population has Internet access. There are 4.28 billion unique mobile internet users worldwide, which makes up 54.6% of the global population. Internet users spend an average of 6 hours and 56 minutes online every day. Overall, the trend is towards greater adoption of ICT globally, with developing countries showing significant growth potential in the mobile and broadband sectors.
Like many other countries, Algeria has chosen digital technology as a solution to diversify and boost its economy. The foundations for a digital economy in Algeria were laid in the early 2000s with the adoption of Law No. 2000-03 on 5 August 2000, which sets out the general rules for postal and telecommunications services with the main objective of introducing competition in the telecommunications sector. The strategies for developing ICTs in Algeria are integrated and cover several fundamental aspects, including the revision of institutional and regulatory frameworks, reorganisation of operational structures, and improvement of the telecommunications infrastructure. The primary objective of the public authorities is to adopt and appropriate ICT to modernise operations and produce competitive goods. In 2001, revenues from the ICT sector represented around 0.9% of GDP, which equates to an average annual consumption of approximately $16 US per inhabitant (Toumache et al., 2014).

Methodology
The importance of measuring the information transformation within societies lies in identifying the extent of what they have accomplished on the path to their transformation into an information society (Kaczmarczyk, 2021). The measurement process enabled to define the following objectives: providing the basis of information and data to guide decision-makers and contribute to the formulation of macro--level technology policies to address partial imbalances, and measuring the level of information maturity, which allows for the comparative process between different countries and international groups, examined at the level of the digital divide between countries as such. This enables to formulate a global map of the information society and understand the level of development of each country in order to rank them according to a specific indicator. The study then proceeded with the analysis of the position and characteristics of Algeria.

Definition of the NRI indicator
NRI stands for Networked Readiness Index, a composite indicator that measures the ability of a country to leverage information and communication technologies (ICT) for increased competitiveness and development. The NRI is calculated by the World Economic Forum and is based on a combination of data from publicly available sources and a survey of business executives in the country being assessed. In its latest 2020 version, the NRI report maps the landscape of state readiness based on a network of 134 economies according to their performance in four different pillars: Technology, People, Governance, and Impact. Each of these is composed of three sub-pillars that are powered by a total of 60 variables (NRI, 2020).

Pillar (Technology)
Technology is at the heart of the networked economy. This pillar therefore aims to assess the level of technology that is an essential condition for a country's participation in the global economy. This pillar brings together 16 variables out of 60 that make up the NRI global index, divided into three sub-pillars as follows: a) Access (7 variables): represents the fundamental level of ICT in countries, including communication infrastructure and affordability issues. b) Content (4 variables): the type of digital technology produced in countries and the content/applications that can be deployed locally. c) Future Technologies (5 variables): measures the extent to which countries are prepared for the future of the networked economy and new technological trends such as artificial intelligence (AI) and the Internet of Things (IoT).

Pillar (People)
The availability and level of technology in a country are only of interest to the extent that its population and organizations have the access, resources, and skills necessary to use it productively. This pillar contains 16 variables mainly concerning the application of ICT by people at three levels of analysis: individuals, businesses, and governments. a) Individuals (6 variables): how individuals use technology and how they use their skills to participate in the networked economy. b) Businesses (6 variables): how businesses use ICT and participate in the networked economy. c) Governments (4 variables): how governments use and invest in ICT for the benefit of the population at large.

Pillar (Governance)
This pillar contains 14 variables and includes the following three levels of analysis: a) Trust (4 variables): the security of individuals and businesses in the context of the networked economy. This concerns not only actual crime and security, but also perceptions of privacy security. b) Regulation (5 variables): measures the extent to which the government encourages participation in the networked economy through regulation. c) Inclusion (5 variables): digital divides within countries where governance can address issues such as gender, disability, and socio-economic status inequalities.

Pillar (Impact)
Ultimately, readiness in the networked economy is a means of improving society and economic growth and well-being. This pillar therefore aims to assess the economic, social, and human impact of participation in the networked economy -14 variables describe this pillar. a) Economy (5 variables): the economic impact of participation in the networked economy.
b) Quality of Life (4 variables): the social impact of participation in the networked economy.
c) Contribution to the SDGs (5 variables): the impact of participation in the networked economy in the context of the SDGs -the goals agreed by the UN for a better and more sustainable future for all. The focus is on goals in which ICT has an important role to play, including indicators such as health, education, and the environment. The original data comes from various sources, including statements and reports from reputable media companies.

Variable definitions
• Tertiary Enrollment (V22): refers to the ratio of the total number of students enrolled in tertiary education, regardless of age, to the population of the age group that officially corresponds to the level of higher education. Higher education, whether or not it is an advanced research qualification, normally requires the successful completion of secondary education as a minimum admission requirement. The tertiary level is based on the International Standard Classification of Education (ISCED) levels 5 to 8. evaluates the quality of online service delivery by a government on a scale of 0 to 1 (best). The evaluation is conducted by researchers who assess "national data from each country, website in the native language, including the national portal, online service portal, and online participation portal, as well as the websites of relevant ministries of education, labor, social services, health, finance, and environment." to 1 (best), the quality, relevance, and usefulness of government websites in providing online information and participatory tools and services to their citizens.

• Socioeconomic Gap in Use of Digital Payments (V44): the difference between
rich and poor income groups that made or received digital payments in the past year (% age 15+).

• Availability of Local Online Content (V45): the average response to the question:
To what extent in your country are internet content and services adapted to local populations (e.g., in the local language)? (1 = Not at all; 7 = To a large extent).

• Gender Gap in Internet Use (V46): the difference between the female and male
population in the Internet use.

• Rural Gap in Use of Digital Payments (V47):
the difference between the rural population and the total population who have made or received digital payments in the last year (% age 15+). • Medium and High-Tech Industry (V48): refers to the percentage of value added by the medium and high-tech industry as a share of total value added of production. • High-Tech Exports (V49): refers to manufactured high-tech products (electronics and electrical and others), as a share of total manufactured exports.

• PCT Patent Applications (V50): refers to the total number of Patent Cooperation
Treaty (PCT) applications filed, by filing date and nationality of the inventor. • Labour Productivity per Employee (V51): the basis for GDP growth and levels that take into account the rapid decline in ICT prices.

• Prevalence of Gig Economy (V52): a survey (EOS) conducted on an annual
basis to gather information from business owners on subjects for which data sources are rare or nonexistent.

Data preparation and coding
The selection was based on the availability of the majority of statistical data, total of (60) variables with 134 countries according to the Network Readiness Index (NRI) indicator. To prepare a variable value matrix for the case study, 59 columns were created to represent the proposed variables for measuring the phenomenon of the information society. One variable was eliminated due to a lack of information (Sustainable Cities and Communities (V60)). The 134 rows represent the case study countries, which have been identified and coded according to internationally recognized codes.

Estimation of missing values
The final result of the data includes some missing data, which amounts to 8.58% of the required data size, as shown in Table 1. In this case, missing values were replaced with estimated values in order to proceed with the statistical analysis. The XLSTAT software was used for the analysis of data and statistics, these values were calculated using the NIPLAS algorithm. It is important to note that there are various methods for replacing missing values, such as mean, median, mode, linear regression, multiple imputation, etc. (Alvarez et. al., 2015). The selection of the replacement method depends on the type of missing data and the distribution of existing data. The choice of method also depends on the objective of the analysis and the nature of the data . However, it is important to exercise caution when replacing missing values as it can have an impact on the results of the statistical analysis. Therefore, it is recommended to verify the results after replacing the missing values.

The automatic classification method
The automatic classification method is a powerful tool for data analysis allowing to categorise a set of n individuals from Ω into a defined number of classes. To use this method, one first needs a measure of dissimilarity between the individuals. In the case of points located in Euclidean space, one can use distance as a reliable measure of dissimilarity. The measure of distance adapted in this classification is the Euclidean distance, the matrix that represents the Euclidean distances between countries is symmetric and its diagonal elements are all zero. To continue with the clustering process, the next step involves grouping the countries that have the shortest Euclidean distance, using an appropriate aggregation criterion. After the initial grouping, a new matrix is created by merging the two countries with the smallest distance, and then the Ward's aggregation criterion is used to find the two closest countries to merge. This iterative process is continued until a second partition is generated that includes the first one, and so on. One of the most popular classification methods is hierarchical agglomerative clustering. This method is called "ascendant" because it starts with each individual alone in a class, and then gradually groups them into larger classes based on their similarities. With this approach, one can gain valuable insights into the underlying structure of the data and identify meaningful patterns that might otherwise go unnoticed (Krzanowski, 2000).

The three steps of the method
a) Choice of variables representing individuals: when the observed data are the values of p numerical variables on n individuals, one can choose to perform a classification of individuals or a classification of variables. For example, one may choose to retain certain traits of individuals (i.e. certain variables that were used to describe them) and perform the classification on the individuals described by this choice of variables. Note that this is equivalent to, for example: -performing a hierarchical clustering analysis (HCA) of individuals based on p centered and standardised variables; -performing a HCA of individuals based on the p factors obtained using a normalised principal component analysis (PCA) on the preceding variables. However, it may be of interest to perform the HCA based on the first q factors (q < p). This has the effect of eliminating a portion of the variations among individuals, which generally correspond to random fluctuations or 'statistical noise'. b) Choice of a dissimilarity index: many measures of 'distance' between individuals have been proposed. The choice of one (or several) of them depends on the data being studied. This study used the Euclidean distance, which is probably the most commonly used type of distance. It is simply a geometric distance in a multidimensional space.
c) Choice of an aggregation index: the application of the method also requires to choose a 'distance' between clusters. Here again, many solutions exist. It should be noted that all these solutions make it possible to calculate the distance between any two clusters without having to recalculate those that exist between the individuals composing each cluster. This study used the minimum distance or 'single linkage'. This is the one used above: ( , ) min min ( , ) Ward's method is well justified when the distance between individuals is the square of the Euclidean distance. Choosing to group the two closest individuals then amounts to choosing the pair of points whose aggregation results in the minimal decrease of the inertia of the cloud. The calculation of new indices between the grouped pair and the remaining points then amounts to replacing the two points forming the pair with their mean point, weighted by 2 (Johnson, 1967).

Variance decomposition for optimal classification
The variance decomposition for optimal classification involves breaking down the total variance in the data into two components: inter-class variance and intra-class variance (Table 2). Inter-class variance measures the variability between different classes, while intra-class variance measures the variability within each class. For optimal classification, inter-class variance should be maximised, meaning that the different classes should be well separated from each other (Toumache et al., 2013). In contrast, intra-class variance should be minimised, indicating that individuals within each class should be as similar as possible. Using variance decomposition, it is possible to identify the most discriminating variables for classification. These variables are those that contribute the most to inter-class variance and the least to intra-class variance. Overall, variance decomposition for optimal classification is an essential tool for evaluating the quality of a classification model and identifying the most important variables for separating different classes (Fadel et al., 2022).

The distances between the barycenters of the classification classes
Although the study could not present the distances between individual countries, examining the distances between the class centroids can still provide valuable insights. As shown in the table below, the first and second classes exhibit greater heterogeneity with respect to the third class, while the fourth class is more heterogeneous with the second class. These findings can be further explained by analysing each class in greater detail, which will be the next step in the analysis (Chellai, 2022). The Hierarchical Clustering Analysis (HCA) allowed to identify and group countries in the world into four classes, each characterised by distinct socio-economic and demographic profiles. The composition of each class is listed below: The composition of each class was determined based on data from 60 variables.

Results analysis
The first class is the reference class for evaluating the delays experienced by the third class, of which Algeria is a part. Indeed, the leading class brings together countries that perform well in most dimensions of the information society, with high use of ICT and strong ICT skills. However, they all rank among the top countries in each of the four pillars and achieve equivalent results in at least two-thirds of the twelve sub-pillars (Access, Content, Future Technologies, Individuals, Enterprises, Source: own elaboration. Government, Trust, Regulation, Inclusion, Economy, Quality of Life, and Contribution to SDGs). As expected, the top 23 countries are highly technological economies. Two elements highlight the performance of the top-ranked economies with impressive scores in the field of ICT. The next step was to conduct a comparative analysis between the reference class and the third class, in order to dissect the key factors where the third class lags behind the most. In order to do this, the authors calculated the average of the variables that characterise the leading class in each of the four pillars for each class. The objective was to first evaluate the identified gaps for each factor and each pillar, interpret these results, and provide recommendations to improve the level of digital development and information society in the countries that make up the third class.

Results Pillar (Technology)
Based on the results shown in the table 4, the authors were able to identify the gaps between the leading class and the third class, where Algeria is positioned, which allowed to evaluate the delay experienced by Algeria in this field.
• In this regard, in the "Technology" pillar, the highest gap is related to the variable "GitHub commits," which represents the largest completely free programming platform. In fact, compared to the leading class, which has a score of 81.03, the average for Algeria was 5.101, which is surpassed by the rate of 93.69%. This indicates a very low usage of this platform by individuals, despite the fact that it contributes to the development of skills, leading to a very significant impact on the adoption of ICT. • Regarding the second variable, "Internet access in schools", Algeria has an average of 47.49 and a lower gap of 53.54% compared to the first class. Access to the Internet in schools is crucial as it improves teaching and learning, and also allows students to access a variety of communication services via various devices. • Regarding "Fixed-broadband subscriptions", despite the increase in the number of subscribers to fixed broadband access service in 2020 according to the World Bank, it is still very insufficient compared to the leader class, with a gap of 53.92%. • Regarding the variable "Households with Internet access", it remains low at 42.20%, due to the inaccessibility of the Internet network for residents in rural areas and other disadvantaged groups. To address this issue, it is essential to ensure universal access for everyone so that no one is excluded and can benefit from the advantages of ICT. • In terms of "Wikipedia edits", Algeria's participation is insufficient, with an average of 39.03 while the maximum is 83.75. The study suggests providing adequate access to official public information through various means of communication, particularly the Internet. • Regarding the variable "Mobile tariffs", which measures mobile phone tariffs, the observed gap is low, only at 33.57%. This can be explained by financially affordable tariffs for Algerian citizens. In addition, the development of mobile applications is considered sufficient, with a gap of only 29.40% for the variable "Mobile apps development". • The gaps observed in the variables "Adoption of emerging technologies" and "Investment in emerging technologies" are low compared to other variables, indicating that Algeria has fully participated in the adoption of these emerging technologies, by dedicating significant budgets to acquire them.

Results Pillar (People)
Based on the results shown in Table 5, the authors were able to identify the gaps between the leading class and the third class, where Algeria is positioned.
• The variable "R&D expenditure by businesses" measures the investments made by companies in research and development. This variable shows the highest and most considerable gap. The leading class surpasses Algeria by 93.41%. This unsatisfactory result indicates a lack of a coherent strategy in the research and development field. Source: own elaboration.
• The variable "Publication and use of open data", which refers to the publication and utilisation of open data, has an average score of 27.46 (with the best average being 67.65), resulting in a gap of 59.40%. • The variable "Government online services", which refers to online services provided by the government, has a gap of 43.92% compared to the leading class.
The study shows that this result is unsatisfactory. • Regarding the variable "Tertiary enrollment", which refers to enrollments in higher education, the results are just above average. The gap between the leading class and the third class is 43.59%. • The variable "Active mobile-broadband subscriptions" shows an average of 68.97 for the third class. In contrast, the leading class reached 120.76, which means that mobile broadband subscriptions in leading countries reached saturation point, with penetration rates exceeding 100%. It is worth noting that in Algeria, according to the latest ITU report, more than 38.77 million subscribers were registered in 2020. • The variable "Firms with a website" shows that very few companies have a website, and those who do often suffer from a lack of updates. This observation is supported by the gap in this variable, which is 40.75% compared to the leading class. • The Algerian government is devoting significant investments to promote emerging technologies. • Despite more than 50% of the Algerian population using the Internet, there is still a moderate gap of 34.94% compared to the leading class. • The number of social media users in Algeria is close to that of the leading class, with a gap of 22.25%. Social media usage is significant in Algeria, and one can see that Algerians are increasingly active and engaged on social media. Social media platforms are essential tools for accessing information. • Algeria has the necessary skills to successfully complete major ICT projects, as confirmed by the small gap of 23.46% between the third class and the leading class. These achievements allow to overcome any barriers that arise during the adoption of ICT.

Results Pillar (Governance)
Based on the results shown in Table 6, the following can be inferred: • Regarding the "Internet shopping" variable, there is a significant gap of 85.64% compared to the leader. The online buying and selling has not taken off yet; indicating that e-commerce in Algeria represents a relatively small portion of trade. Source: own elaboration.
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• In terms of "Regulatory quality", the quality of regulation is average, with a gap of 44.57% compared to the leader. • As for the "Secure internet servers" and "cybersecurity" variables, the gaps compared to the leader are 43.09% and 44.29%, respectively. This indicates that the security measures are not sufficient. • In terms of "Availability of local online content", the gap between the leading class and the third class is 26.6%. This suggests that the availability of online content is only average. • In regard to "Legal framework's adaptability to emerging technologies", the leading class surpasses Algeria by 37.39%, which is considered a small gap. • As for "E-participation", the leading class surpasses Algeria by 29.64%, which is a satisfactory result. Online participation promotes citizen engagement for participatory governance through ICT.

Results Pillar (Impact)
Based on the results shown in Table 7, the following can be inferred: • Regarding "PCT patent applications", the number of patent applications related to communication technologies, this variable is the weakest link, with an average that is very insignificant, at 0.54. The leader surpasses Algeria by 99.67%. • Regarding "Labour productivity per employee", Algeria's productivity is far behind the leader, with a gap of 69.96%. • As for "Quality education", the quality of education in the leading class has an average of 68.116, while Class 3, to which Algeria belongs, has an average of 30.210, resulting in a gap of 55.64%. • For "Sustainable cities and communities", there is a small gap of 28.07% compared to the leader. • "Happiness" and "Healthy life expectancy at birth" are complementary variables and analysed as a pair of factors, especially since the gaps are less than 25%. • In terms of "Income inequality", the third class significantly surpasses the leading class, with a gap of -28.11%. This suggests that income redistribution is more equitable in the third class, but it does not mean that Algeria should stop pursuing this policy.

Conclusion
Algeria has advantages that enable it to engage in the global development of the information society and knowledge economy. The introduction of ICT in Algeria is well underway and can serve as an example for other sectors of the economy, with a tangible and measurable impact. However, the country is still behind others, and there is still a huge effort to be made, particularly in expanding the infrastructure. This is due to several problems such as inadequate security measures, a low share of e-commerce exchanges, a low budget allocated to research and development by companies, a lack of patent filing in ICT, limited internet access in schools, limited publication and use of open data by the government, insufficient labour productivity per employee, and high costs of access and subscription to Internet and international lines. Additionally, these research results explain that several factors have not favoured the emergence of an information society that matches the country's potential and ambitions. This confirms that the Algerian government has not fully realized the importance of two cultural and legal dimensions. The real challenge is to articulate these two dimensions without sacrificing one at the expense of the other.
In addition to its strategic significance, the ICT sector is characterised by its rapid evolution. Therefore, producing statistics and indicators to measure and monitor the integration of these technologies is of utmost priority and importance. This is why the Algerian government must increasingly focus on statistical data to be able to self-evaluate and improve its services to citizens and, at the same time, it's ranking on the international scale according to various indicators.