María Verónica Alderete

A smart city approach places citizens at the center of decision-making. However, only a small proportion of citizens actually engage in participatory initiatives. Although citizen participation has been extensively studied, limited empirical evidence exists on how citizens’ awareness of participatory initiatives relates to both their participation and their perception of municipal efforts to promote participation. This paper analyses these relationships using a Propensity Score Matching (PSM) approach based on survey data from a medium-sized city in Argentina. Since the factors associated with participation and perceptions of municipal promotion may also shape citizens’ awareness of government programs, PSM is used to improve comparability between aware and non-aware citizens and to examine the association between awareness of participatory initiatives and participation outcomes. The results show statistically significant differences in both participation propensity and perceptions of municipal promotion between citizens who are aware of these initiatives and those who are not. Awareness is positively associated with prior civic engagement, visiting the municipal website and age, and negatively associated with being a woman. Policy implications highlight the importance of disseminating successful participatory experiences and strengthening communication strategies to encourage broader citizen engagement.

[Purpose] The objective is to analyze the differences among Latin American countries in the adoption and implementation of Artificial Intelligence (AI) and to relate this AI gap to the existing digital divide in Internet access. [Methodology/approach/design] A k-means cluster analysis is conducted to classify and differentiate the countries in the region based on several dimensions of the Latin American Artificial Intelligence Index (ILIA), together with international data on connectivity, Information and Communication Technologies, and cybersecurity. [Findings] Three country clusters are identified: AI-Advanced, AI-Emerging, and AI-Lagging. Brazil, Chile, and Uruguay form the advanced group, characterized by high levels of Internet connectivity (narrow Internet digital divides), robust AI infrastructure, strong AI governance, and abundant talent. The emerging countries differ from the advanced ones mainly in AI governance and e-commerce (wider Internet appropriation gap). The largest group consists of AI-lagging countries, which show lower levels across all variables. The clusters also reflect significant differences in innovation and human development, though not in GDP. Countries with high AI infrastructure have higher GDP than those with low AI infrastructure. [Practical implications] The country classification serves as a tool for political and strategic decision-making. It enables more efficient policies to promote AI and its implementation. AI-lagging countries can strengthen their digital foundations and actively foster AI adoption through collective policies and strategies tailored to their profile. In these countries, AI amplifies the pre-existing Internet digital divide. Transitioning from emerging to advanced status requires institutional changes and investment in talent. [Originality/value] This study recognizes the existence of an AI gap among Latin American countries by identifying, on one hand, the AI-leading nations and, on the other, the emerging and lagging ones. Furthermore, it links this AI inequality or gap to the Internet digital divide. AI tends to generate new inequalities due to its dependence on advanced infrastructure, specialized knowledge, and control over data.

This study examines cross-country differences in Artificial Intelligence (AI) development, emphasizing the role of the digital divide. First, countries are classified into advanced, emerging, and lagging groups using cluster analysis. Then, a probabilistic model assesses how socio-economic factors such as GDP, Human Development Index (HDI), business density, and skilled labor unemployment, influence the likelihood of countries belonging to the AI emerging/advanced cluster. Results show that higher GDP per capita, skilled labor unemployment and HDI increase the likelihood of belonging to the AI emerging/advanced group. AI tends to deepen the pre-existing digital or connectivity divide. The findings underscore the need for policies and coordinated strategies that promote AI adoption and address ICT appropriation disparities, addressing structural socio-economic constraints. Advancing from lagging to an emerging/advanced position requires deep transformations in digital infrastructure, human capital and access to quality data.

Este estudio propone un indicador de adopción de comercio electrónico multicanal (ACEM) que busca capturar de manera más comprehensiva la presencia y uso de diversos canales digitales por parte de las empresas, incluyendo sitios web, redes sociales y plataformas de comercio electrónico de terceros (e-marketplaces). A diferencia de los enfoques tradicionales, que se centraban principalmente en la presencia y funcionalidades del sitio web, el indicador ACEM incorpora la utilización de estos otros canales digitales clave. La construcción del indicador incluyó la definición de cuatro niveles de adopción, que van desde la presencia digital básica hasta la integración avanzada de múltiples canales. Para la aplicación empírica, se realizó una encuesta a una muestra de 116 micro, pequeñas y medianas empresas (mipymes) de la provincia de Córdoba, Argentina. Los resultados muestran que, al utilizar el indicador ACEM, una mayor proporción de empresas son clasificadas en niveles más avanzados de adopción de comercio electrónico, en comparación con la aplicación del indicador tradicional. Un hallazgo relevante es el predominio del uso del sitio web institucional como canal digital principal, seguido por las redes sociales y, en menor medida, los e-marketplaces. Además, se identificaron diferencias en el uso de estos canales según el tamaño de las empresas, sugiriendo estrategias de comercio electrónico multicanal diferenciadas. El trabajo enfatiza la importancia de considerar un enfoque multicanal para evaluar la adopción de comercio electrónico en las empresas, especialmente en el contexto actual de acelerada digitalización. El indicador ACEM propuesto parece ser una herramienta más precisa y comprehensiva para capturar la complejidad de las estrategias de comercio electrónico que están implementando las organizaciones.

Este trabajo tiene como objetivo analizar los factores que explican el desarrollo digital de las ciudades en América Latina. Se parte de la hipótesis de que en los últimos años hubo cambios significativos en el desarrollo digital de las ciudades, y que tales cambios se explican por variaciones en las características de las propias ciudades, así como de los países a los que pertenecen. Se propone estimar un modelo multinivel con tres niveles: tiempo, ciudad y país. Se analizan los efectos aleatorios como alternativa para evaluar la evolución de tal desarrollo digital en el tiempo. Con este fin, se utilizan datos en el período 2020-2023 de 27 ciudades pertenecientes a 16 países de la región de América Latina. Los resultados indican que existe una variación significativa en el desarrollo digital entre ciudades y entre países en los últimos años. Por otro lado, esta evolución en el desarrollo digital se explica principalmente por la brecha digital de nivel país y por las políticas urbanas que implementan las ciudades.

El estudio analiza el compromiso de las MiPyMEs argentinas con la estrategia de digitalización en un contexto de transformación tecnológica acelerada. Con datos del Observatorio Iberoamericano de la MiPyME (2022), se construye un indicador que mide dicho compromiso y su relación con la madurez digital, el sector y el tamaño empresarial. Los resultados evidencian brechas estructurales y diferencias sectoriales, así como la influencia del liderazgo y la planificación estratégica en la adopción tecnológica. Se aportan evidencias útiles para el diseño de políticas y programas que fortalezcan las capacidades digitales y la competitividad sostenible del sector MiPyME.

This article examines the association between primary students’ academic performance andhousehold access to computers with internet connectivity in Argentina, extending the empirical literaturein the context of the COVID-19 pandemic. We investigate whether information and communicationtechnologies (ICTs) affect educational outcomes and whether their impact differs before and after thepandemic. We estimate propensity score matching models using Aprender 2021 data for students in thefinal year of primary school, disaggregated by geographical regions. The results indicate that householdaccess to computers with internet connectivity is associated with higher language arts and mathematics testscores. The estimated effect varies across regions. In addition, the performance gap between students withand without ICT access is, on average, 2.33% larger than the estimated pre-pandemic gap, suggestingthat ICT access became more salient during school closures. Overall, this study contributes to the evidenceon ICT-related educational inequalities at the primary level during the pandemic.

Este artículo estudia los factores sociodemográficos que explican el nivel de adopción del gobierno electrónico (AGE) por parte de los ciudadanos. La AGE es de naturaleza ordinal e incluye diferentes plataformas digitales, desde sitios web oficiales hasta redes sociales. Se utilizan los datos de una encuesta online realizada entre octubre y noviembre del 2020 a un grupo de ciudadanos de Bahía Blanca, Argentina. Se plantea una metodología de regresión de tipo logística y ordinal (modelo de chances proporcionales parcial). Entre los principales resultados, se destaca que, cuanto mayor es el nivel educativo y mayor es la edad, la propensión a adoptar niveles más altos de gobierno electrónico aumenta. El uso de Internet en el trabajo también explica los mayores niveles de adopción. Asimismo, el género femenino explica positivamente la propensión a realizar un gobierno electrónico frente a la opción de no hacerlo, mientras que la opción “Otro género” genera una menor probabilidad en todos los niveles de AGE.

The digital economy and the sharing economy have changed the role citizens may acquire in society. Citizens can perform at least two roles from the open government perspective: on the one hand, they can be passive users/demanders of information and, on the other hand, they can provide or produce the information in an active manner. The objective of this paper is to offer a theoretical model to explain citizens’ incentives to participate in open government projects. Which is the opportunity cost of participation for the citizen? Which are the drivers of the preferences for the social good? This model is based on the utility function and consumption theory. We complement the theoretical framework with an exploratory–descriptive analysis based on a case study’s primary data about citizen participation. In democracy projects where citizens actively collaborate and could earn monetary gains or become entrepreneurs, the opportunity cost of participation is lower than in a passive type and the amount of the social good depends on the preferences. Preferences for social goods are related to community experiences and e-government and they also affect the decision to participate. Very few studies in the field of open government have pretended to explain citizens’ participation by using microeconomic foundations.