Sustainable Cities in the Light of ISO 37120 and 37101 Standards: A Systematic Review and the Contribution of a Theoretical Framework

Abstract

This paper outlines a significant research gap on sustainable cities: the need for more comprehensive and strategic frameworks for managing sustainable cities, particularly those integrating interdisciplinary elements, dimensions, and global trends. The proposed framework delineates sustainable cities’ elements, dimensions, and trends based on ISO 37120, incorporating pillars linked to the triple bottom line and the Sustainable Development Goals 30 (SDGs). This study suggests specific research agendas, emphasizing theoretical and practical implementation within urban contexts. The methodological approach involved both bibliometric and content analysis techniques, using IRA-MUTEQ software 0.8 Alpha 7. This enabled the identification of key analytical categories and leading authors, with categories derived from lexical forms, similarity analysis, correspondence factor analysis (CFA), and descending hierarchical classification (DHC). Notably, the terms ‘ISO’ and ‘37120’ did not emerge as prominent lexical forms in the IRAMUTEQ results, despite their frequent mentions in the analyzed studies.

1. Introduction

Contemporary cities are recognized as complex systems composed of a vast network of interconnected citizens, businesses, transportation modalities, communication infrastructures, services, and utilities [1,2]. Due to its complexity, the city can be understood as a living ecosystem. These systems are not limited to structural elements but also encompass dynamic interactions that occur across social, economic, and technological domains.

In its broadest sense, a city is an environmental unit composed of interrelated and interdependent elements and processes; that is, changes in any component will impact all the other components [3,4]. Furthermore, it is important to emphasize that cities are not merely the sum of their components, but rather systems par excellence, merging from a variety of individual and collective decisions from both bottom-up and top-down processes [5]. This interpretation is consistent with the perspective of cities as a “system of systems,” which highlights their multilayered and interdependent nature [6].

These conceptual frameworks highlight the inherently contextual character of urban systems, shaped by an interplay of diverse factors that evolve over time and space [2]. This understanding of cities is essential for formulating effective urban policies and sustainability strategies.

Within this context, the analysis of urban metabolism has gained prominence as a methodological approach to understanding the flow of resources within cities. In simplified terms, urban metabolism considers the input of goods, products, and services that support urban life, alongside the output of waste generated by both human consumption and the functioning of urban systems [5].

One of the foremost challenges for contemporary urban governance is to shift cities toward more sustainable patterns of resource consumption. Beyond technological innovation, achieving this goal demands institutional change, behavioral adaptation, and integrated planning approaches that align with the broader principles of systemic sustainability.

Contemporary cities are characterized by increasing complexity and multifaceted challenges. Growing social and territorial inequalities coexist with issues such as urban congestion and public health concerns. Effective urban management requires the adoption of comprehensive and innovative public policies capable of reconciling the diverse interests of social actors and fostering sustainable urban development.

In this intricate context, ISO (International Organization for Standardization) 37120 [7] emerges as a crucial tool. This international standard provides a comprehensive set of indicators for evaluating urban performance. It is a valuable resource for municipal planning and formulating strategies aimed at enhancing residents’ quality of life. By offering a robust framework for measuring urban performance, ISO 37120 plays a pivotal role in addressing the complex challenges faced by cities today.

Urban sustainability has emerged as a topic of global significance and has been incorporated into the United Nations Sustainable Development Goals (SDGs) under the designation “Sustainable Cities and Communities.” As defined by the UN (2015) [8], the ten targets outlined in Goal 11 (Sustainable Cities and Communities) address critical aspects such as access to adequate housing, provision of safe and reliable transportation systems, and the development of urban environments that are both inclusive and sustainable. These targets aim to reduce mortality and the number of individuals affected by disasters, mitigate environmental impacts, and ensure universal access to safe, inclusive, and accessible public spaces.

Sustainable cities represent an urban paradigm that seeks to balance economic development, environmental preservation, and improvement of human well-being. In this context, ISO 37120 has become a significant benchmark, providing a holistic set of indicators for assessing urban performance and sustainability. Its adoption enables municipalities to evaluate their public policies, identify areas for improvement, and formulate strategies to cultivate a more sustainable future. This transformative potential of ISO 37120 and ISO 37101 extends beyond environmental considerations, inspiring profound changes in urban life, social relations, and municipal governance across all facets.

Beyond the performance indicators provided by ISO 37120, the ISO 37101:2016 [9] standard serves as a methodological reference for developing standardized approaches to urban sustainability assessment. This standard defines the requirements for a sustainable development management system applicable to communities—including cities—employing a holistic approach designed to align with the sustainable development of community policies.

Justifying the search for ISO 37120 in conjunction with ISO 37101, as this standard offers a framework to guide the creation of indicator methodologies, such as ISOs 37120, 37122, 37123, and 37125, promoting a systematic and consistent evaluation of urban sustainability efforts, which ultimately contributes to the standardization of urban management practices.

Beyond ISO 37120, various other indicators can be employed to measure a city’s performance across different dimensions, including environmental, social, and economic aspects. By providing concrete data on local realities, these indicators enable city managers to identify strengths and weaknesses, establish clear objectives, and monitor progress over time. Thus, municipal indicators are essential for assessing sustainability and guiding urban management initiatives. Quality of life, urban mobility, waste management, and energy efficiency are also particularly pertinent indicators for guiding public policies and promoting more sustainable and equitable urban development.

Several authors [10,11] underscore the importance of analyzing ISO 37120 within the urban context, with studies encompassing cities in Brazil and Portugal. Given the relevance of this topic, identifying prominent authors and their respective approaches is an emerging need in global research.

Therefore, the guiding research questions for this study are as follows: (i) Who are the primary authors in this field and what are their interrelationships? (ii) Which analytical categories have been identified? (iii) What are the main contributions of the existing literature? To address these questions, this study conducts a content analysis of ISO 37120—Sustainable Cities—and proposes a framework comprising elements, dimensions, and trends for the research agenda. The primary objective was to propose a comprehensive framework encompassing elements, dimensions, and trends for future research agendas on sustainable cities.

This paper is structured as follows: Section 1 provides the introduction. Section 2 presents the theoretical framework, focusing on Sustainable Cities and Communities and ISO 37120. Section 3 details the methodological procedures. Section 4 discusses the results. Section 4.2.4 proposes the framework. Finally, Section 5 offers conclusions and outlines a research agenda.

2. Theoretical Framework

Sustainable Cities and Communities and ISO 37120

Due to the growing role of cities in human development, smart city initiatives focused on improving the conditions and quality of urban life are attracting interest. In this context, life expectancy emerges as a key indicator of population well-being, intrinsically linked to interconnected socioeconomic, environmental, and health factors, as widely documented in the literature. This study is contextualized within the principles of Sustainable Cities and Communities and the ISO 37120 standard, exploring how the implementation of smart city practices can positively impact life expectancy and contribute to achieving urban sustainability goals [12].

The pursuit of more sustainable and resilient cities has driven the development of ISO 37120, an international standard that offers a robust framework for measuring urban performance. Launched in 2014 by the World Council on City Data, ISO 37120 has been widely adopted by cities worldwide, demonstrating its relevance as a global standard for comparing and evaluating public policies [13]. The global adoption of ISO 37120 demonstrates its universal applicability and importance in the context of sustainable city research.

This standard is an essential tool for managing and planning sustainable cities. It comprises a set of 104 key performance indicators (KPIs) organized into 19 themes, ranging from urban infrastructure to citizens’ quality of life. These indicators are selected based on city priorities and enable a multidimensional assessment of municipal performance to guide decision-making. The structure of ISO 37120, with its core, supporting, and profile indicators, offers a holistic view of urban management and facilitate the identification of areas for improvement [14].

The adoption of ISO 37120 enables cities to optimize resource allocation, enhance transparency, promote citizen participation, and strengthen their presence on the global stage. ISO 37120 recognizes a city’s commitment to sustainability and contributes to attracting investments and strengthening its international reputation [14].

In 2021, ISO 37120 underwent a substantial update. The new edition, ABNT NBR ISO 37120:2021, coordinated by ABNT Special Study Commission 268, introduces an expanded set of indicators, covering 19 themes and 128 key performance indicators, rendering it even more comprehensive [15,16].

This update reflects the international community’s commitment to promoting urban sustainability and equipping cities with the necessary tools to measure and improve their performance. By adopting ISO 37120:2021, cities gain access to a set of guidelines and indicators to steer decision-making and foster citizen engagement towards improved quality of life and community development.

As illustrated in Figure 1, the themes outlined in ISO 37120 offer a comprehensive framework for assessing quality of life and sustainable urban development. Its 19 themes, which range from water and energy management to culture and sport promotion, enable cities to accurately diagnose their current situation. Indicators such as access to education, air quality, transport efficiency, and public safety highlight the challenges and opportunities for building a more just and equitable future. This tool is essential for monitoring municipal progress toward the UN’s SDGs, especially SDG 11, which aims to make cities more inclusive, safe, resilient, and sustainable.

The diversity of the 19 themes in ISO37120 reflects the complexity of the challenges faced by cities in the 21st century. The standard encourages an integrated and multidisciplinary approach to urban planning when addressing issues such as housing, health, education, environment, and economy. By implementing ISO 37120 recommendations, cities can optimize the resource allocation, reduce environmental impacts, improve population’s quality of life, and strengthen their competitiveness on the global stage. In addition, this standard contributes to building more resilient cities capable of facing future challenges, such as climate change and accelerated urbanization.

3. Methodological Procedures

Bradford’s laws of dispersion and Lotka’s laws of scientific productivity are considered milestones in bibliometrics, as bibliometric research began in the late 1960s. Beginning in the 1990s, bibliometrics became a standard tool in science policy. This research considers both laws of bibliometrics. The methodological approach adopted in this study consisted of a systematic search in international bibliographic databases.

For this study, the keywords “ISO 37120 OR ISO 37101” were used in the search query, focusing on the current state of the art within the specified period. Boolean search, grounded in Boolean logic, is a powerful tool for retrieving information from databases. A well-defined search strategy also allows researchers to easily revisit and refine their approach as needed [17].

Data were collected from three databases: Web of Science, Scopus, and ScienceDirect. The selection of these three databases was determined by discussions among the authors, prioritizing sources containing peer-reviewed scientific literature. Data collection took place in July 2024. The results of this systematic search are presented in

Table 1. Systematic literature search.

Base	ISO 37120 OR ISO 37101	Period Last 10 Years
Web Of Science	48	48
Scopus	40	40
Science Direct	148	131
Overall	236	219

Source: Research (2025).

.

From the 219 studies initially identified, 188 were available. A 10-year timeframe was adopted to align with the latest updates to the ISO standards. Studies unrelated to ISO 37120 and 37101, or those with highly specific objectives (e.g., city noise analysis, water pollution analysis), were excluded. After screening the titles and abstracts, 98 studies were selected for full-text reading. Ultimately, 69 articles were retained for qualitative analysis.

The bibliometric review began with the application of Zipf’s Law, recognized as one of the three fundamental laws of bibliometrics. This principle served as a basis for analyzing the distribution of terms within the corpus of scientific publications. The use of Zipf’s Law is justified by its capacity to reveal language and term usage patterns, contributing to a deeper understanding of the structure and evolution of scientific knowledge in the field [18].

Zipf’s Law, named after the linguist George Kingsley Zipf, establishes an empirical relationship between the frequency of a term and its position in a list ordered by frequency. Although originally formulated in the context of linguistics, this law has been widely applied in diverse areas of knowledge, including information science, librarianship, and sociology. By mapping the frequency distribution of terms in a text corpus, Zipf’s Law enables the identification of lexical patterns and hierarchies, contributing to the quantitative analysis of texts and to a deeper understanding of the structure of knowledge [18].

In qualitative research, statistical data can complement qualitative information. In fact, the integration of quantitative and qualitative data through technological tools enhances the analytical depth of qualitative studies [19]. According to the authors, the use of specialized software facilitates integrated analyses, fostering a more comprehensive understanding of the research object and its implications.

The data analysis in this study followed Bardin’s content analysis [20], which comprises three phases: (1) pre-analysis, (2) material exploration, and (3) treatment, inference, and interpretation. The pre-analysis involved organizing and verifying the studies identified in the systematic review. Material exploration consisted of an in-depth reading of the selected documents. In the treatment phase, the content was coded and systematized using a data analysis tool. Finally, inference and interpretation were conducted based on the results, particularly the generated analytical categories.

IRAMUTEQ software (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires) was employed for text analysis. The selected studies were compiled into a single text file (txt) to form the textual corpus. Following Salviati [21], the textual corpus was constructed using the titles, keywords, and abstracts of the 69 selected studies.

The integration with the R and Python software platform—a prerequisite for the operation of IRAMUTEQ 0.8 Alpha 7—facilitated the execution of multivariate data analyses, including word frequency analysis, correspondence factor analysis (CFA), descending hierarchical classification (DHC), similarity analysis, and word cloud generation. This approach enabled a qualitative analysis of the studies, underpinned by a quantitative examination of lexical forms.

4. Discussion

4.1. Descriptive Analysis

The data collected for this study was analyzed using a variety of analytical methods to thoroughly explore the nuances of the topics of sustainable cities and ISO 37120 in conjunction with ISO 37101. Each method was carefully selected based on the specific characteristics of the data and the research objectives. The qualitative analysis allowed a comprehensive understanding of the phenomena investigated, making it possible to identify patterns and trends.

A bibliometric analysis of the data was fundamental to identify the most prominent and influential authors in the study areas. By mapping scientific production and citations, it was possible to identify researchers who have made significant contributions to the advancement of knowledge on the subject. This information provides a solid theoretical framework for identifying possible collaborators in future research. Bibliometrics also made it possible to visualize the evolution of research over time and identify trends and gaps in the literature, which contributes to outlining new research perspectives.

Bibliographic production, recognized as a crucial indicator of scientific activity, has been explored by many researchers, but its systematic application to a homogeneous corpus represents a unique opportunity to deepen our understanding of Lotka’s Law and the dynamics of scientific research in general. The proposal to analyze bibliographic production based on Lotka’s Law has excellent potential for generating new knowledge about the dynamics of scientific research in this area [22].

Table 2. Authors with publications.

Most Cited Authors
n = 7	Sławomira Hajduk
n = 5	Mark S. Fox
n = 3	Iliana Papamichael	Maria-Lluïsa Marsal-Llacuna
	Fernando A.F. Ferreira	James Merricks White
	Antonis A. Zorpas
Authors with 2 citations
Aapo Huovila	Giuliano Dall’O’	Matthew Jull
Adam Przybylowski	Gumersindo Feijoo	Miimu Airaksinen
Adeeb A. Kutty	H C Melo	Murat Kucukvar
Agnieszka Kałaska	H S Dantas	Nuri C. Onat
Angela Panza	Irene Voukkali	Pantelitsa Loizia
Antonios Maitis	John R. Vacca	Piotr Przybyłowski
Athena Vakali	Jose M. Diaz-Sarachaga	Rob Kitchin
Benjamin DiNapoli	Kannan Govindan	Sara González-García
Daniel Jato-Espino	Leandro F. Pereira	Suane De Atayde Moschen
Dongping Fang	Leonidas G. Anthopoulos	Suélen Bebber
Elisa Bruni	Luca Sarto	Tan Yigitcanlar
Fazel Khayatian	Manuel Rama	Vaia Moustaka
Galal M. Abdella	Marcelo B. Corrêa da Silva	Zeyu Zhao
Georgios Pappas	Maria Teresa Moreira

Source: Research (2025).

shows the main authors who have published in the databases searched. Slawomira Hajduk, an associate professor at the Faculty of Engineering and Management at the Bialystok University of Technology, Białystok (Poland), has the highest number of publications, with seven articles. Her keywords are urban intelligence measurement, urban resilience assessment, civil participation in smart cities, public management, statistical methods, territorial management, spatial management, and multi-criteria methods.

Mark S. Fox, a professor of industrial engineering at the University of Toronto, is a globally recognized authority on smart city systems, with an emphasis on his research into ISO 37120. His extensive academic output positions him as one of the leading names in the development of methodologies and tools for assessing and improving the quality of urban life. Fox is recognized for his pioneering contributions to the development of Constraint Programming and its application in various domains, such as manufacturing, logistics, and smart cities. His research, focused on topics such as artificial intelligence, ontologies, and intelligent agents, has been fundamental in advancing the research and application of ISO 37120 in different urban contexts.

Zipf’s Law was observed in the keyword distribution. The first keyword has more than twice as many citations as the second, as well as twice as many citations as the third word. Zipf’s law was developed around the 1950s and has contributed to the quantitative analysis of texts and standards for publications in the field. The keywords contribute to objective search forms, serving as both complements and indicators of the relationship among the terms to be searched.

Table 3. Absolute and percentage frequency of terms.

Keywords	n	%
Smart Cit *	64	7.2%
ISO 37120 OR ISO 37101	27	3.0%
Sustainable development	17	1.9%
Indicators	13	1.5%
Urban planning	10	1.1%
Sustainability	10	1.1%
Other words	745	84.1%

Source: Research (2025). * Includes in search terms Smart City and Smart Cities.

shows Zipf’s Law, as the first grouping of words, Smart Cit* (n = 64), appeared more than twice as often as the second word, ISO 37120 OR ISO 37101 (n = 27), and almost twice as often as the third word, Sustainable development (n = 17).

The keywords searched were “ISO 37120 OR ISO 37101”, in addition to the following words: indicators, urban planning, and sustainable, as the main words. Another 595 different words were found with a frequency of 745 presentations. The top six words with the most repetitions accounted for 15.9% of the keywords.

4.2. Content Analysis

Following the bibliometric review of the portfolio comprising 69 studies, a content analysis was conducted using IRAMUTEQ Data Analysis Software, following Bardin’s methodological framework [20]. The selection of IRAMUTEQ was driven by our research group’s institutional license, established expertise in textual analysis, and this study’s core emphasis on content and lexicometric analysis of the textual corpus, as detailed in Section 3.

The initial phase of this analysis involved the construction of a semantic word cloud, which was generated as part of the review process using IRAMUTEQ. The word cloud graphically displays the most frequently used terms, providing a visual representation that facilitates the identification of key concepts within the analyzed texts. In this display, the larger and more centrally positioned a word appears, the higher its frequency in the textual corpus, as illustrated in Figure 2.

The results indicate that the most prominent lexical forms include “city,” “intelligent,” “urban,” “indicator,” “development,” “sustainability,” “sustainable,” “data,” and “framework.” This initial output was compared with subsequent analytical results to aid in the identification of thematic categories related to sustainable cities and their association with ISO 37101 and ISO 37120 standards. Notably, the terms “ISO” and “37120” did not appear prominently in this first stage of analysis.

Figure 2 presents the results of the similarity analysis. As described by Salviati [21], this technique generates a chart that visually represents the connections between words within the textual corpus. Through this approach, it is possible to discern the underlying structure of the text and identify themes of relative importance based on their co-occurrence.

It is important to highlight that the similarity analysis was performed using the 43 most frequently occurring words. This number was determined by calculating the square root of the total number of distinct words analyzed (1870) across the 69 studies processed in IRAMUTEQ software, following the Reinert method. According to this method, the units of analysis (i.e., words) should exhibit semantic homogeneity and comparable size, meaning that each statistical unit is assigned an identical weight [21].

Figure 3 presents the similarity analysis of the lexical forms revealed strong and homogeneous associations between the terms “city,” “smart,” “sustainability,” “sustainable,” “data,” and “framework.” In contrast, the term “urban” exhibited a distinct connection, forming a separate cluster from the primary group. This indicates that “urban” is conceptually connected in a in a different manner compared to the other lexical forms evaluated.

Identifying the theoretical relationships between the word cloud and the similarity analysis revealed that both homogeneous lexical clusters and uniquely connected terms (such as “urban” and “system”) correspond to keywords highlighted in the word cloud. This congruence reinforces the consistency of the analytical approach and underscores the relevance of these terms to the central topics addressed in the literature.

The third analytical result produced by IRAMUTEQ is the correspondence factor analysis (CFA). The CFA outputs both a dendrogram—illustrating the hierarchical clustering of words—and a graphical model, displaying word groupings in a two-dimensional space. As a multivariate statistical technique, CFA increases the robustness of categorical data analysis [23].

The use of these categorical data enables a deeper examination of the textual content in the analyzed studies. Figure 4 presents the CFA, depicting the theoretical associations among subjects, as determined by IRAMUTEQ. The correlations between terms are calculated using the chi-square method, with terms of higher frequencies and greater chi-square values emphasized in each class. The most prominent terms are displayed in larger fonts, while less frequent terms appear in smaller fonts. Notably, no outliers were detected in the analyzed sample. The interpretation of the CFA results, combined with DHC, enabled the identification and naming of the primary thematic categories that emerged from the corpus.

The CFA uses the same color scheme for lexical forms as the categories defined by the DHC. The textual content segmented and analyzed by DHC is represented in the form of a dendrogram, which stratifies the textual elements into three distinct classes. Within each class, the terms with the highest frequency and significance (p < 0.05) are highlighted.

Figure 5 presents the DHC dendrogram produced results consistent with those obtained in other IRAMUTEQ analyses, such as the word cloud generation, similarity analysis, and CFA. Collectively, these results supported the categorization of elements and emerging trends within the theme of sustainable cities, based on the framework established by the ISO standards. It is noteworthy, however, that the terms “ISO” and “37120”—despite being central to the systematic literature search—did not appear prominently in any of the identified classes.

Class 2, which accounted for 41.6% of the lexical forms, encompassed the most frequent and statistically significant terms, serving as the basis for the “Metrics and Performance” category. Class 1, representing 40% of the lexical forms, supported the identification of the “Open Data, Knowledge, and Infrastructure” category. Meanwhile, Class 3, comprising 16.4% of the forms, was associated with the “Sustainability and Sustainable Development Goals (SDG)” category.

As suggested by Bibri [24], it is essential to highlight the value of synergistic interactions among theoretical perspectives, discursive trends, and foundational frameworks that support the development of sustainable cities. Therefore, the following section conducts an in-depth interdisciplinary discussion, reinforcing the importance of integrating diverse analytical dimensions to advance the study and implementation of sustainable cities.

4.2.1. Analysis Category 1 (Class 2)—Metrics and Performance

Metrics and performance encompass the array of methods, indicators, systems, indices, assessments, practices, and tools implemented within sustainable cities, as well as those employed in the context of smart governance. The focus on energy and water highlights the prevailing trends in monitoring and evaluating these essential urban resources.

Smart and sustainable cities can be conceptualized as complex social fabrics, constituted by intricate relationship networks among multiple synergistic clusters of urban entities. From a holistic perspective, these networks facilitate the integration and deployment of smart technologies, supporting the creation, dissemination, and popularization of innovative solutions and advanced methods. This approach cultivates a favorable environment for sustainability through strategic measurement and continuous improvement of contributions to UN’s SDGs [25].

The literature also indicates that the complexity of urban systems is increasingly amplified by the technologies employed to monitor, interpret, and analyze the physical structure, spatial and temporal scales, operational functions, and planning and management processes of cities. These technological tools are designed to enhance urban sustainability performance and strengthen cities’ capacity to mitigate the multidimensional effects of urbanization.

Indeed, the application of advanced technologies is essential for addressing the challenges posed by sustainability and urbanization. However, as observed in previous studies, there is a dynamic tension between scientific, environmental, social, institutional, and political practices and the evolution and performance of urban systems and technological applications.

Regarding metrics, the literature [26] emphasizes that, when combined, indicators can be aggregated into indices or other composite measures, such as ecological or carbon footprints and material flow analyses. This generally requires converting different measurements into common units and assigning relative weights to each measurement according to their significance. The use of indicators is also prominent in certification and classification schemes, including ISO 37120.

Given the inherent complexity of urban development and the large number of stakeholders involved in the application of indicators, effective performance management, and the development of metrics require the collaboration of multidisciplinary teams and the active participation of subject-matter experts to ensure the selection of appropriate variables.

Furthermore, since the set of indicators must remain appropriate, manageable, and feasible, the responsibilities of these experts goo beyond mere technical selection. They must collaborate closely with professionals from various fields to prioritize indicators and assess the relative importance of incorporating metrics from different areas of expertise. Additionally, these experts play a key role in articulating the logic behind prioritization and in communicating the significance of the selected indicators to non-specialists. This process ensures that the development of indicators is grounded in interdisciplinary dialogue and aligned with practical realities, rather than being conceived in abstract isolation [25].

4.2.2. Analysis Category 2 (Class 1)—Open Data, Knowledge and Infrastructure

The lexical form “datum,” as identified by IRAMUTEQ software, reflects the various mentions and contexts in which this term appears across the analyzed studies. “Knowledge” encompasses the diverse and interconnected intangible elements that characterize sustainable cities, while “infrastructure” refers to the array of information and communication technologies, as well as other physical, technological, and spatial artifacts that permeate urban environments.

Recent European Union initiatives for Smart Cities have increasingly prioritized support for information and communication infrastructures to foster development across multiple dimensions, including economic growth, transportation, environmental sustainability, social well-being, quality of life, and more effective urban management [26].

From this perspective, the primary objective of smart city initiatives is to transform ordinary urban environments into technically advanced ecosystems. The essential concern is delivering enhanced services and improved quality of life for citizens [27]. However, the demand–supply balance between infrastructure and public services is ultimately crucial in determining the global success of a city [28]. Therefore, the development of smart cities should be conceptualized as a continuous process of harmonization between physical and virtual realities, encompassing all subsystems of the urban fabric. This approach emphasizes the provision of comprehensive services and socioeconomic development, moving beyond the notion of smart cities as merely technological responses to isolated challenges. The literature also recommends that, while a global perspective is important, the conceptualization and implementation of smart cities must remain grounded in local realities and needs.

Beyond infrastructure considerations, open data policies have also been subject to significant criticism [29]. Authors highlight the concern that current dynamics are moving toward a surveillance society, characterized by limited oversight or regulation (a political challenge) and variable data quality (a technical challenge). Autonomous vehicles—whether aerial, terrestrial, or subterranean—illustrate systems with complex challenges related to human control, community acceptance, privacy, security, and information protection.

Equity remains a core concern in the implementation of smart city strategies [30]. Fundamental questions arise as to who ultimately benefits from smart city investments: do local citizens have more substantial gains than economic and political actors? Critics suggest that excessive reliance on technology and corporate interests may risk marginalizing broader public interests.

In the context of sustainable smart cities, it has become crucial to consider urban analytics to address contemporary urban sustainability challenges and to evaluate how these data can enhance sustainability performance across multiple urban domains, beyond merely sectoral applications [24]. Pervasive computing technologies—defined by the integration of digital devices into everyday life—are expected to generate environmental improvements and socioeconomic benefits. This aligns with the urban sustainability agenda, as these technologies offer advanced capabilities to deliver innovative, high-performing applications, services, and products [31].

Therefore, technological innovations should focus on improving production and business processes, strengthening social connections, and transforming the relationships between public authorities and society. These advancements allow cities to become increasingly instrumented, interconnected, and intelligent, providing urban managers with new tools to support a more sustainable urban future and enhance the intelligent management of urban dynamics [28,32].

Finally, considerations of human–computer interaction, emerging paradigms for natural interaction (involving people, machines, and the environment), and the role of information and communication technologies (ICTs) in promoting sustainability are essential for advancing the analysis and understanding of the emergence and impacts of smart cities [24].

4.2.3. Analysis Category 3 (Class 3)—Sustainability and Sustainable Development Goals (SDGs)

Sustainability and the SDGs encompass all aspects of the triple bottom line, including policies for sustainable development, social inclusion, and urban quality of life. In [33], the authors present a diagram of eco-cities’ taxonomy, focused on dynamic systems. For the authors, an eco-city operates through management levels, which are composed of elements such as energy consumption, waste management, greenhouse gas emissions, urban transport, and sustainable urban growth. As a result, quality of life, employment, and services are at the top level. Their study of industrial sectors demonstrates that political interventions aimed at environmental protection are only able to limit the increasing rate of pollution.

Similarly, ref. [34] clarify that the input–output analysis of pollutant emissions enables the examination of intersectoral economic flows in cities and makes it possible to analyze patterns of employment, resource use, and emissions on a sector-by-sector basis. This analysis assists in the identification of key sectors capable of generating above-average side effects.

For application across sectors and for the identification of environmental impacts, ref. [33] suggest a method for minimizing the impacts on urban organisms. The methodology consists of a system of eco-indicators specifically designed to estimate the impacts of cities and communities, while also suggesting strategies for mitigation. Indicators related to energy, water, solid waste, and atmosphere are evaluated.

In this perspective, refs. [35,36] demonstrates a method for assessing sustainability, which includes rural areas. They consider the transparency and availability of data, administrative and demographic representation, and environmental commitment as indicators. The authors consider cities as complex housing structures, characterized by social and economic interrelations, large resource consumption, and substantial greenhouse gas emissions. Thus, cities require thorough evaluation to guide citizens and plan actions and policies that contribute to achieving sustainable growth.

4.2.4. Framework

The bibliometric and content analyses provided qualitative insights into Sustainable Cities and ISO 37120 and 37101 standards. One of the main motivations for conducting these analyses was to provide a useful cognitive map to support decision-makers, policymakers, and investors in actions such as resource allocation in cities, future research projects, innovation in sustainability, etc.

Thus, elements (or dimensions) and trends were highlighted in the analysis categories discussed in this study. In this context, a framework (Figure 6) indicates how different dimensions interact.

The development of sustainable cities, often referred to in the literature as smart cities within the same approach [10,30,37,38], is an exploratory process that requires changes across many levels, including infrastructure, information technology, urban governance, and social interaction [39].

The literature presents elements that align with the proposed framework in terms of infrastructure, open data, and knowledge, as it relates to information technology. Smart urban governance aligns with metrics and performance in order to establish parameters to evaluate the governance process and its results. In addition, social interaction is considered part of the sustainability tripod, with an intrinsic relationship to all SDGs.

It also identifies dimensions of sustainable cities that align with the proposed framework, such as planning and democratic governance (metrics and performance); transportation, energy, and intelligence (open data, knowledge, and infrastructure); and economic, social, environmental, green, and creative (sustainability and SDGs) [34].

Similarly, ref. [27] offers key domains for sustainable cities in terms of governance (metrics and performance); mobility (open data, knowledge, and infrastructure); and economy, environment, people, and life (sustainability and SDGs).

Ref. [25] extensively discuss the importance of developing metrics through interdisciplinary teams and propose indicators aligned with the framework presented in this study: access and mobility (open data, knowledge, and infrastructure); governance (metrics and performance); environment, sanitation, health, and social equity (sustainability and SDGs).

To scientifically explore the unknown territory of cities, governments, and international organizations, academics began to formulate a series of discussions on the concept to establish a clearer research paradigm and a stronger foundation for urban research. The 69 studies analyzed revealed a panorama marked by specificity and content fragmentation or studies focusing on only one city in the context of sustainability. Thus, this framework contributes to determining elements and trends in sustainable cities, considering ISO 37120 and 37101 standards from a systemic, holistic, and globally comprehensive perspective. In addition, it seeks to support sustainable city management by incorporating elements and trends outlined by international standards and validated theoretical models.

In addition to the challenges discussed, ref. [33] provides a social perspective on emerging trends. According to the authors, interregional inequalities, cultural differences, the coexistence of non-smart and sustainable cities or quasi-smart and sustainable cities, and small cities represent complex challenges in the current context. Complementing these results, refs. [29,38,40] emphasize the role of people in cities and highlight migration as a significant issue.

From an economic standpoint, ref. [34] analyzes investment management and best practices, while incorporating innovative sustainability strategies and considering environmental issues, such as pollutant emissions, modeled as part of a dynamic system by [33,41].

From a quality-of-life perspective, ref. [40] developed a model for assessing smart cities based on residents’ needs. The authors analyze smart city functions according to the same dimensions as Maslow’s Hierarchy. Health and social issues, such as social security, were considered elements with the greatest demands.

Ref. [42] explore digitalization and associated quality protocols as key performance indicators for a smooth transition toward economic circularity. In this context, technology and investments exposed in the framework can serve as connecting elements between the pillars of sustainable cities and the trends that encompass the circular economy.

The fundamental strength of cities lies in the components of sustainable, smart, and resilient cities [43], as well as the elements and pillars presented in this research. Concerns regarding the models are also shared due to the constant need to achieve synergies among different approaches, to holistically consider strategies, and to address problems of incomplete data and uncertain information.

The themes encompassed by standard norms and the role of sustainable cities extend beyond the scope of this study, which does not aim to exhaust the topic but to contribute to the local management of cities from a global and interdisciplinary perspective. The proposed conceptual model is an effort to capture the complexity inherent in the themes addressed by this study. Elements and trends were not analyzed separately, as each pillar, dimension, and trend can be considered individual research fields.

In addition to the conceptual diagram provided by this framework, a suggested research agenda involves classifying studies according to their research areas. The analysis indicates that the ISO theme spans multiple fields, models, and instruments. Therefore, it is important to identify which areas are receiving greater attention and gaps in less-explored areas.

5. Conclusions

This study aimed to analyze the content of ISO 37120 and 37101 standards through bibliometric and content analysis, in order to propose a framework encompassing elements, dimensions, and trends for a future research agenda.

A qualitative analysis, conducted using IRAMUTEQ software, facilitated the identification of analytical categories that supported the development of an interdisciplinary conceptual framework for sustainable cities, based on ISO 37120. The categories were analyzed by a focus group of PhD experts and are as follows: metrics and performance; open data, knowledge, and infrastructure; and sustainability and the Sustainable Development Goals.

These categories were derived from the most frequently occurring lexical forms identified through the word cloud, similarity analysis, correspondence factor analysis (CFA), and descending hierarchical classification (DHC). Lexical forms found in the literature but lacking statistical significance in the CFA were excluded from final analysis.

Notably, ‘ISO’ and ‘37120’ did not emerge as prominent lexical forms in the IRAMUTEQ results, indicating a lower frequency despite their recurring mention in the analyzed studies. This finding suggests that while this standard is referenced, there remains a significant research gap concerning comprehensive and strategic frameworks for managing sustainable cities, particularly those incorporating interdisciplinary elements, dimensions, and global trends.

Another critical area for future research is the influence of city size, a variable that has been relatively underexplored in the existing literature, despite ISO’s assertion that its indicators are applicable regardless of urban scale or location. In this regard, defining priority areas for implementing sustainable city concepts and programs, as well as effective resource allocation, represents an emerging theoretical and practical challenge.

Simulating long-term scenarios for sustainable cities emerges as a relevant initiative for supporting their implementation and standardized environmental management. For instance, ref. [33] conducted a 30-year simulation of eco-city subsystems, an approach that aligns with the objectives of the present study in assessing urban elements and dimensions.

Smart urban governance aligns with metrics and performance in order to establish parameters to evaluate the governance process and its results. In addition, social interaction is considered part of the sustainability tripod, with an intrinsic relationship to all SDGs.

While acknowledging the inherent limitations of studies relying on bibliometric analysis and text mining, the analyzed studies and the proposed framework suggest paths for future research. These include a deeper exploration of the concept of habitability and its characteristics. Additionally, it is recommended to understand the regulatory structure of the SDGs by developing studies on tax incentives, venture capital, and financing strategies for management issues, aiming to provide realistic recommendations.