Urban Maturity Performance Measurement System Through Smart City Actions

Abstract

The uncontrolled urbanization of Brazilian cities accentuates the imbalance between population demands and urban space planning. The integrated management of human and technological resources constitutes a fundamental governance strategy for the proposition of sustainable and effective responses to the challenges faced by cities. To generate references to public management, the objective of this research was to develop a management tool to verify the maturity level of Brazilian cities for smart city actions. A performance measurement system (PMS) organized smart city actions into 11 thematic areas, quantitatively measuring smart city actions in a down–top structure since the indicators and metrics are described in a standardized scale to obtain the general maturity index (GMI). The PMS was implemented in the city of Santa Maria/Brazil, where its GMI equal to 43.72% indicated a currently intermediate maturity level of smart city actions, mainly related to the low performance in the thematic areas of mobility, coexistence and reciprocity, and security and protection. To improve the current performance, five incremental actions were proposed, contemplating the key performance indicators “Public roads”, “Multipurpose lanes”, “Public accessibility”, “Accessibility signage”, and “Monitoring”, projecting a GMI equal to 49.75% and 55.78%, respectively, for an intermediate and an advanced maturity level scenario.

1. Introduction

According to the World Cities Report 2022, published by the United Nations Human Settlements Program (UN-Habitat), 68% of the world’s population will live in urban areas by 2050 [1], mainly due to the different opportunities provided by cities. However, agglomerations with an intense flow of people, goods, and vehicles, in addition to different types of social conflicts, cannot be correctly absorbed by the natural environment and appropriately managed by public management [2]. Thus, actions to support correct service provision in urban environments with information technology infrastructure are fundamental to improving people’s quality of life [3,4,5].

The term smart city [6] highlights the contribution of innovative actions to the development of sustainable public and private practices, reducing pollutant emissions, optimizing energy consumption, and improving urban mobility to contribute to people’s quality of life [7]. Therefore, monitoring smart city actions requires appropriate technological tools derived from research experiences and knowledge obtained over the years for systemic and integrated human and material resource management in urban spaces, contemplating aspects to successfully operate the environmental, social, and economic domains simultaneously [3,8,9,10]. Also, the development of management and technological tools related to smart city actions contributes to communication between different public and private entities, promoting the construction of collaborative and innovative solutions [11,12,13,14].

It is highlighted in [15] the growing interest in research, with investments to implement technological tools focused on smart city actions, involving researchers and managers from the public and private sectors. Since [14] shows the importance of smart and sustainable actions through the development of advanced decision-making methods. According to [9], smart city actions must be implemented and monitored to prospect promising future scenarios. Therefore, monitoring urbanization increases and resource management represent constant challenges for public sector managers. Already [16] highlights that smart cities focus on replicability and scalability actions through insights into the urban context and adaptive strategies to address the challenges faced by public management.

To mainly generate references to public management sectors, the maturity level of smart city actions must be measured over time [17,18], guiding the rational use of human and non-human resources in planning strategies and developing technologies [19,20,21,22]. In this context, the uncontrolled growth of the urban population density in Brazilian cities is a challenge for improving people’s quality of life, triggering special problems related to transportation, sanitation, energy, education, housing, and environmental impacts [2].

Thus, the objective of this research was to develop a management tool to verify the maturity level of Brazilian cities for smart city actions. Its main contributions are related to the following: (i) organizing different smart city actions in thematic areas by similarity, which acts as the basis for the performance measurement system (PMS) development; (ii) quantitatively measuring smart city actions in a down–top structure since indicators and metrics are described in a standardized scale for the thematic areas to obtain a general maturity level index value of a Brazilian city; and (iii) providing a PMS capable of being transformed into a management tool used by public managers to monitor the maturity level related to smart city actions.

This article is structured in six sections: Section 1 presents the thematic context; Section 2 covers the literature review; Section 3 discusses the methodology implemented; Section 4 shows the results; Section 5 presents the discussion; and Section 6 describes the research conclusions.

2. Literature Review

2.1. Epistemological Contextualization in Urban Studies and Sustainability Research

At the dawn of the 21st century, society faces complex interconnected global challenges including climate change, geopolitical instability, socioeconomic inequality, large-scale migration, water scarcity, and biodiversity loss, which differ in nature but are interrelated and often mutually reinforcing, generating risks that challenge traditional paradigms of management, governance, and urban planning. A coordinated and collaborative response involving governments, the private sector, communities, institutions, and individuals is thus necessary. In this context, science is decisive in developing integrated solutions for urban governance [23].

It is conceptualized in [24] urban governance as a dynamic and multiscale process, constituted by networks continuously reconfigured in response to global challenges. This understanding is grounded in contemporary research across the philosophy of science and the natural, social, and human sciences, which converge in recognizing the city as a field shaped by flows and interactions operating at local, regional, and global scales.

In the context of the challenges facing humanity and the search for solutions in a rapidly changing and complex modern world, one of the dominant social and scientific narratives rooted in modernist thought is increasingly confronted by complexity. In response, the metamodern approach engages with the intricacies and ambivalence of contemporary reality by integrating science and aesthetics, critical analysis, and constructive hope. This perspective advocates for a science ethically committed to sustainability and socio-ecological justice [25].

A shift away from linear and sectoral approaches toward an epistemological transition within the applied sciences represents a challenge, particularly in urban studies and sustainability research, in better understanding the relation between society and space. Within this framework, the meta-modernist epistemology in human geography emerges as a relevant perspective, characterized by pluralism and an interdisciplinary outlook, which are central metamodern paradigm features [23].

2.2. Smart City and Performance Measurement

This literature review establishes perspectives related to smart cities actions in urban space management. Population growth and urbanization intensify the demand for the development of smart city actions, such as innovative communication technologies (e.g., internet of things), to reconcile citizens’ lifestyles with the environment and city governance, transforming traditional uncontrolled urbanization into smarter and more comfortable spaces for citizens [5,26]. The importance of smart city actions in advancing sustainability is presented in [14]. Sustainable smart urbanism involves the development of actions for the improvement in urban space decision support against increased energy consumption, pollutant emissions, solid and liquid waste disposal, the inefficient management of urban infrastructure, social inequalities, and socioeconomic disparities. Actions are identified with partnerships within the scope of public management, ref. [4] shows actions to develop infrastructures for the production of private technologies to provide basic public services, as new interactive technologies based on the IoT facilitate access to open data on public services already available, as verified in Manchester, England.

In [27], smart city actions are associated with urban intelligence to detect, transmit, integrate, and analyze information to enable harmonious coexistence in society and reciprocity, oriented towards maintaining social ties and management focused on an integrative environment with equal-opportunity principles. The search for an innovative environment between the government, society, companies, and educational institutions is fundamental, as verified in [28], as well as the influence relations for urban space plan structuring.

Assessing urban land cover and land use from an equitable infrastructure distribution and access to green spaces perspective promotes collective well-being and socio-spatial justice. Systematic spatial monitoring enables the identification of socio-spatial segregation patterns and supports public policies for equitable urban resource access. Equity in urban infrastructure is seen as a guiding principle for sustainable urban planning. This approach reflects one of urban maturity’s key indicators, defined as the capacity of cities to transition toward more intelligent and inclusive development models, where physical and functional urban growth is aligned with social cohesion and environmental conservation [29].

In approaches to evaluating and monitoring cities, urban research has historically highlighted the performance indicators used according to heuristic and diagnostic aspects, such as what is proposed by [30], where urban indicators contribute to the elaboration of diagnoses and evaluations of spatial structures and processes, as well as the verification of new ways of interpreting the city and projecting future scenarios. In [31], the interaction between people in urban environments is cited, evaluating urban policies based on measurable results with the proposal of economic, social, and environmental indicators. The approaches in [30,31] converge in their understanding of the use of indicators as a fundamental condition for urban standard evaluation and the elaboration of planning policies in contemporary cities. It is recommended in [32] caution when applying public management indicators, where indicators should be used as management tools in smart governance initiatives. However, the evaluation must be developed under a democratic vision and must be dedicated to social change. From this perspective, the indicators favor an evaluation process focused on social learning through the implementation of clear public policies that are attentive to the population reality in urban environments.

Recent trends in smart cities show synergistic decision-making between different city departments, requiring integration between planning and management. They are listed in [33,34] actions by thematic areas for mapping implemented solutions using technologies for energy efficiency, urban mobility, environmental management, and public safety, contributing to sustainable management to advance and improve urban spaces. In this alignment, as discussed in [35] that smart city actions can be developed by reaching six fundamental smart pillars: life; economy; governance; environment; energy and communication; and transportability.

Therefore, for sustainable, intelligent, and innovative urban space management, understanding the thematic areas belonging to smart city actions is useful for structuring planning strategies with the interactions between the government, society, companies, and educational institutions [28].

In Brazil, examples of smart city actions are verified. In Curitiba/Brazil, the integration of the innovation ecosystem, such as the “Cidade das Startups” program, has enabled the development of 604 startups, the availability of nine entrepreneurial spaces to serve 210 thousand individual microentrepreneurs, and free training focused on information technology. Other highlights include the integration of the multimodal transportation system (buses, bicycles, scooters, taxis, and transportation) with an app, the requalification of 100 km of public roads to provide accessibility for people with disabilities, and the provision of 400 km of cycle paths [36]. In Croatá/Brazil, an initiative based on social inclusion, urban planning, environment, and technology pillars was the development of the “Smart City Laguna” program, supported by the concept of a compact city, where all the services necessary for the population could be found in a reduced space, reducing travel by vehicles and encouraging movement as pedestrians or cyclists. In addition, smart meters, smart poles, free internet signal, in addition to security systems, and an innovation hub were made available in partnership with private companies [37].

In the smart city context, technological innovation is relevant to develop solutions addressed to key urbanization challenges, enhancing city management and social interaction. According to [11], technological resource integration aids the collaboration and communication between stakeholders, promoting innovation and the co-creation of collaborative and creative solutions across sectors such as education, health care, energy, industry, environment, and public safety.

3. Materials and Methods

This methodological proposal was structured based on the Design Science Research (DSR) method, aiming to solve a problem in a specific context through a construct and generate new scientific knowledge [38]. For research operationalization, the DSR diagram was structured in three cycles, namely relevance, rigor, and design (Figure 1), based on [39].

The relevance cycle enabled the identification of the requirements and needs to reach the research objective, as well as the acceptance criteria for evaluating the results in the applied context. The rigor cycle provided the outline of scientific knowledge and processes in the research area, as well as the generation of the main contributions. In the central cycle, the design contributed to the proposed PMS conceptual systemic integration to measure the performance of urban maturity by thematic area, applied in the city of Santa Maria/Brazil for demonstration and evaluation purposes.

The PMS was developed based on [40,41,42,43,44,45,46,47], stratifying the research objective into a hierarchical decision-making structure in a top–down orientation formed by thematic areas, key performance indicators and metrics, metric scale normalization, and a general maturity index.

Initially, 11 thematic areas related to smart city actions considering social, economic, and environmental aspects in urban space planning were identified in [48], namely technology and innovation; living environment and infrastructure; governance and engagement; education and training; mobility; energy; economy and sustainable consumption; security and protection; coexistence and reciprocity; entrepreneurship; and health and assistance. A brief description of the 11 thematic areas ($u_i$) is shown, where the index $i$ was adopted to identify each thematic area.

Technology and innovation ($u_1$) includes the application of information and communication technology to improve processes, urban planning, and the development of applied solutions to provide quality of life in urban spaces. The living environment and infrastructure ($u_2$) includes the essential conditions and interactions for harmonious survival in society in an ecologically balanced environment to improve quality of life and sustainability.

Governance and engagement ($u_3$) encompasses the development of management strategies through assistive technologies in customer service, the provision of electronic services, response time for services, and population involvement to regularize the developed activities. Education and training ($u_4$) is based on adequate educational institutions and technological infrastructure for basic and higher-education students.

Mobility ($u_5$) represents sustainable and efficient urban mobility to minimize travel time, congestion, and pollution emissions. Energy ($u_6$) encompasses energy resource rationalization, local energy matrix diversification, and the development of alternative energy source strategies. Economy and sustainable consumption ($u_7$) involves reducing social and environmental implications by reducing human and material resource demand. Security and protection ($u_8$) promotes monitoring through the integration of security systems and remote management processes, as well as the improvement in public road lighting control.

Coexistence and reciprocity ($u_9$) values access, circulation, and support to public environments and spaces, with appropriate signage and assistive conditions for citizens. Entrepreneurship ($u_{10}$) measures the number of companies’ evolution, the creative economy, and the development of technology parks. Health and assistance ($u_{11}$) integrates the development of innovative public policy solutions for diagnosing and mapping the populations’ health conditions, as well as action through procedures and diagnosis automation.

Next, 38 key performance indicators ($v_k$) were hierarchically established for the 11 thematic areas using the Function Analysis System Technique (FAST) method, based on [49,50,51], organizing the key performance indicators into the thematic areas through the answers obtained with the basic questions “how?” (from the objective level to the key performance indicators) and “why?” (from the key performance indicators to the objective level). The $k$ index was adopted to identify each key performance indicator.

The key performance indicators were defined using as a reference the technical standard of the International Organization for Standardization—ISO 37122 [52] and the Connected Smart Cities (CSC) multidimensional platform [53]. In order to enable numerical smart city action measurements to verify the maturity level of a city, metrics were developed for each key performance indicator.

Table 1. Key performance indicator definitions.

Thematic Area (${\mathit{u}}_{\mathit{i}}$)	Key Performance Indicator (${\mathit{v}}_{\mathit{k}}$)	Metric	Scale	Lower Limit	Upper Limit
Technology and innovation ($u_1$)	Coverage ($v_1$)	Coverage of 5G mobile networks	Percentage	0.00	100.00
	Connectivity ($v_2$)	Average download connection speed	Megabytes	0.00	-
	Fixed broadband ($v_3$)	Proportion of population with broadband access	Percentage	0.00	100.00
	Free internet ($v_4$)	Proportion of area covered by free Internet connectivity	Percentage	0.00	100.00
Living environment and infrastructure ($u_2$)	Risk areas ($v_5$)	Provision of risk areas monitoring	Binary	No	Yes
	Investment in urbanism ($v_6$)	Amount invested in urban planning per inhabitant	USD/inhabitant	0.00	-
	Sanitation ($v_7$)	Proportion of sewage treatment in urban areas	Percentage	0.00	100.00
	Waste collection ($v_8$)	Proportion of population with quantitatively monitored waste collection	Percentage	0.00	100.00
Governance and engagement ($u_3$)	Citizen service ($v_9$)	Provision of service via apps and websites	Binary	No	Yes
	Digital inclusion ($v_{10}$)	Availability of accessibility to service portals	Binary	No	Yes
	Socioeconomic development ($v_{11}$)	Municipal development index	Absolute	0.00	1.00
Education and training ($u_4$)	Quality of education ($v_{12}$)	Basic education development index (IDEB) for elementary education (initial and final years)	Absolute	0.00	10
	Higher education training ($v_{13}$)	Proportion of students enrolled in undergraduate courses	Percentage	0.00	100.00
	Investment in education ($v_{14}$)	Value of investment in education per inhabitant	USD/inhabitant	0.00	-
Mobility ($u_5$)	Public roads ($v_{15}$)	Availability of public roads mapped in real time	Binary	No	Yes
	Multipurpose lane ($v_{16}$)	Proportion of multipurpose lanes in urban spaces	Percentage	0.00	100.00
	Urbanization ($v_{17}$)	Urbanization proportion of public roads	Percentage	0.00	100.00
	Public transport ($v_{18}$)	Proportion of use of urban public transport	Percentage	0.00	100.00
Energy ($u_6$)	Energy meter ($v_{19}$)	Availability of households with smart energy meters	Binary	No	Yes
	Public lighting ($v_{20}$)	Availability of public lighting managed by remote management systems	Binary	No	Yes
	Electric vehicles ($v_{21}$)	Availability of electric vehicle charging stations	Binary	No	Yes
	Decentralized energy ($v_{22}$)	Availability of independent distributed energy generation	Binary	No	Yes
Economy and sustainable consumption ($u_7$)	Interaction spaces ($v_{23}$)	Availability of area covered by online supplier mapping system	Binary	No	Yes
	Wealth generated ($v_{24}$)	Gross domestic product concerning number of inhabitants	Percentage	0.00	100.00
	Development ($v_{25}$)	Municipal human development index (IDHM)	Absolute	0.00	10
Security and protection ($u_8$)	Control and operations center ($v_{26}$)	Availability of control and operations center	Binary	No	Yes
	Monitoring ($v_{27}$)	Proportion of area covered by digital surveillance systems	Percentage	0.00	100.00
	Public safety ($v_{28}$)	Investment in public safety per inhabitant	USD/inhabitant	0.00	-
Coexistence and reciprocity ($u_9$)	Public accessibility ($v_{29}$)	Proportion of public buildings with accessibility to residents	Percentage	0.00	100.00
	Accessibility in public transportation ($v_{30}$)	Proportion of public transport lines equipped with accessibility systems for residents	Percentage	0.00	100.00
	Accessibility signage ($v_{31}$)	Proportion of pedestrian crossings equipped with accessibility signage	Percentage	0.00	100.00
Entrepreneurship ($u_{10}$)	Companies ($v_{32}$)	Proportion of growth in number of companies in the last 24 months	Percentage	0.00	-
	Creative economy ($v_{33}$)	Proportion of growth in number of creative economy companies in the last 24 months	Percentage	0.00	-
	Technological parks ($v_{34}$)	Existence of a technology park	Binary	No	Yes
Health and assistance ($u_{11}$)	Family health ($v_{35}$)	Proportion of family health teams concerning number of inhabitants	Percentage	0.00	100.00
	Availability of doctors ($v_{36}$)	Number of doctors per 100 inhabitants	Absolute	0.00	-
	Infant mortality ($v_{37}$)	Number of child deaths per 1000 live births	Absolute	0.00	-
	Investment in health ($v_{38}$)	Value of investment in health per inhabitant	USD/inhabitant	0.00	-

shows the key performance indicators organized by their thematic areas and indicators, as well as the metrics with their scales, lower limits, and upper limits. A crescent trend was verified in all metrics.

The metric scale normalization protocol standardizes the values obtained with the metrics’ original scales to a common scale, measured in absolute values from a lower limit of 0.0 to an upper limit of 10.

To convert for the normalized scale, the metrics’ original scales were divided into levels, using the original scale’s lower and upper limits as a reference. For example, the “Coverage of 5G mobile networks” from Coverage ($v_1$) is measured in percentages with a lower limit equal to 0.00% and an upper limit equal to 100.00%, is divided into five levels, 0.00% to 20.00%, 20.01% to 40.00%, 40.01% to 60.00%, 60.01% to 80.00%, and 80.01% to 100%, and is, respectively, converted to the normalized scales as 0, 2.5, 5.0, 7.5, and 10. This conversion logic divided into five levels was replicated for all metrics with original scales in percentage or absolute values, as verified for the “Basic education development index (IDEB)”, with an original scale measured from an initial level of 0 to 2.0 up to an advanced level of 8.1 to 10, and for the “Municipal development index” ($v_{11}$), with an initial level of 0 to 0.20 up to an advanced level of 0.81 to 1.00. The conversion tables from the original scales to the normalized scales used for all metrics are available in Appendix A.

For metrics where the upper limit of the original absolute scale is open (“-”), a value must be defined to be a reference according to the conditions of the city (or cities) adopted to verify the smart city maturity. The remaining four levels are divided into proportional intervals using the lower limit and the defined reference value for the upper limit. The same original scale conversion logic is used for USD/inhabitant ($v_6$, $v_{14}$, $v_{28}$, and $v_{38}$) and the megabyte ($v_2$) metrics. Finally, for the binary metrics ($v_5$, $v_9$, $v_{10}$, $v_{15}$, $v_{19}$, $v_{20}$, $v_{21}$, $v_{22}$, $v_{23}$, $v_{26}$, and $v_{34}$), the answer “No” is equivalent to 0, while the answer “Yes” is equivalent to 10 on the normalized scale.

The input data for the metrics on the original scales is collected using a diagnosis with 14 questions (for indicators $v_4$, $v_9$, $v_{13}$, $v_{15},$ $v_{16}$, $v_{18},$ $v_{20}$, $v_{21}$, $v_{23}, v_{27}$, $v_{29}$, $v_{30}$, $v_{31},$ and $v_{34}$) collected through semi-structured interviews with public city managers (mayor and/or technical administrative staff); 12 questions ($v_1$, $v_6$, $v_{14}$, $v_{19}$, $v_{24}$, $v_{26}$, $v_{28}$, $v_{32}$, $v_{33}$, $v_{35}$, $v_{36}$, and $v_{38}$) provided by national agencies and entities; 5 questions ($v_7$, $v_{12}$, $v_{17}$, $v_{25},$ and $v_{37}$) obtained from statistical institutes; 5 questions ($v_2$, $v_3$, $v_8$, $v_{11}$, and $v_{22}$) collected using specific websites related to telecommunications regulatory agencies, industry federations, and the national energy regulatory agency; and 2 questions ($v_5$ and $v_{10}$) obtained from websites related to city management authorities.

The thematic areas’ ($u_i$) quantitative maturity level performance for smart city actions is calculated based on the arithmetic mean of the key performance indicators’ normalized values ($v_k$), as shown in Equation (1), where $m$ is the number of $k$ key performance indicators contained in each $i$ thematic area. For example, the thematic area of Technology and innovation ($u_1$) is composed of four key performance indicators ($u_1$, $u_2$, $u_3$, and $u_4$), where $m=4$.

$$u_i=\left[\left(\sum _{k=1}^{38}{v}_k\right)\times 10\right]/m;\forall k\subset i;k=\left\{1,\dots ,38\right\}$$

(1)

The general maturity index (GMI), shown in Equation (2), is calculated from thematic areas’ ($u_i$) maturity level performance for smart city actions in proportion to the scores, also named “weights” ($w_i$) (in percentages), of the thematic area rankings found in [54], obtained using the multi-criteria method Decision-Making Trial and Evaluation Laboratory (DEMATEL), proposed in [55], useful in this research to allow interdependent relations between the smart cities thematic areas based on expert opinion to obtain the influence level between thematic areas with a relation matrix and vector calculation, as well as the direction and intensity of the relations, structured using the cause-and-effect relation diagram [56]. In this research, the proportionality score $w_i$ values are presented in Section 4.2.12.

$$GMI=\sum _{i=1}^{11}{u}_i{w}_i; i=\left\{1,\dots ,11\right\}$$

(2)

The general city’s maturity level calculated with the GMI is situational, serving as support for directing strategies in urban planning through the implementation of or improvement in smart city actions to promote improvements in quality of life and urban service efficiency. The GMI is expressed by the “smart city maturity scale”, measured as a percentage from a lower limit of 0.00% to an upper limit of 100.00%, divided into five sequential levels, proportionally distributed from an initial level (0.00% to 20.00%) to an advanced level (80.01% to 100%), as shown in Figure 2.

A level considered initial (from 0.00% to 20.00%) reflects the non-execution of strategic smart city actions in urban planning. At level 2, in evolution (20.01% to 40.00%), the city develops basic strategic smart city actions. Level 3, intermediate (40.01% to 60.00%), contemplates partial smart city action implementation, with an initial identification of technologies used in urban environments. Level 4, in improvement (60.01% to 80.00%), is the technological development stage, where mature smart city action implementations are verified. Level 5, advanced (80.01% to 100.00%), includes almost the completeness of smart city actions implemented over the years.

The smart city maturity scale is also useful to qualitatively measure the performance of each thematic area ($u_i$) individually. The proposed PMS application is useful to represent a situational urban maturity demonstration, aiming to understand the current context to support future urban planning decisions and policies.

4. Results

Section 4.1 shows the characteristics of Santa Maria/Brazil, the selected city to apply the proposed PMS, as well as information about the input data collected. Next, in Section 4.2, the results are stratified to show the maturity level concerning the 11 thematic areas, ending with the GMI analysis of Santa Maria/Brazil.

4.1. Scenario

The city of Santa Maria is located in the southern region of Brazil, with approximately 280 thousand inhabitants and a population density of 152.64 inhabitants per square kilometer, being considered a medium-sized city in the Brazilian context, as well as a regional road and rail junction between cities located in the center of the Rio Grande do Sul state [57].

Urban governance in Santa Maria/Brazil alternates between periods of participatory planning and discontinued public policies. The city is a signatory to the 2030 Agenda, aligning its planning with sustainable development. Despite significant advances, such as the Council for Urban Development, its incorporation of urban planning instruments is technically and financially limited. Urban planning is based on the Master Plan, the land use and occupation law, and sectorial plans focused on mobility, habitability, and sanitation. In the last five years, public management has been incorporating sustainable concepts with actions towards green infrastructure, digitalizing public services, and efficient public transport. However, challenges such as land regularization, integrated urban mobility, and territorial planning are verified [58].

Santa Maria/Brazil has an urban structure with a concentration of services, commerce, and infrastructure in the central zone and urban expansion in the north and west zones. From its founding period until 1930, there was a compact and gradual expansion, with urbanization focused on activities related to the railway. The decades from 1940 to 1970 were marked by moderate urban development and the installation of public management departments, being recognized as a Brazilian educational and military hub. From 1980 to 2000, a peripheral expansion of socio-spatial segregation was observed, characterized by the excessive centralization of services in the central zone and disorderly peripheral growth, mainly with the implementation of popular housing developments and irregular occupations. This phase characterizes the main infrastructure limitations in the current urbanized zones. From the year 2000 onwards, horizontal growth was highlighted, together with accelerated urbanization in nearby rural zones, commuting expansion, and road system expansion. According to [59], Santa Maria/Brazil follows a typical Latin American city pattern, driven by departmental policies and reactive planning to solve already established urban problems.

The public management structure of Santa Maria is decentralized through 17 departments (e.g., governance, environment, economic development and innovation, education, and social development), integrated into the municipal mayor’s office, the attorney general’s office, and the auditor’s office. Each department has a head manager and a team with a superintendent, coordinators, and employees working on the execution of projects and activities related to the activities covered by each department.

The input data collection for the metrics on the original scales was developed between November and December 2023, starting with interviews with the employees and managers of the Santa Maria Planning Institute (IPLAN) and the Urban Mobility, Environment, and Health departments. Next, in the months January and February 2024, data collection was developed through document verification on the city’s official website (https://www.santamaria.rs.gov.br), the Santa Maria Planning Institute (https://iplan.santamaria.rs.gov.br), the Cidades@ system from the Brazilian Institute of Geography and Statistics—IBGE (https://cidades.ibge.gov.br/), the National Telecommunications Agency—ANATEL (https://www.gov.br/anatel), the National Electric Energy Agency—ANEEL (https://www.gov.br/aneel), the Federation of Industries—FIRJAN (www.firjan.com.br), and the Connected Smart Cities website (https://connectedsmartcities.com.br).

4.2. Thematic Area Maturity Level

The data were collected and systematized using the proposed PMS, which enabled a structured and quantitative assessment of the smart city actions in urban environments. Figure 3 shows the maturity level performance verified for Santa Maria/Brazil based on the 11 thematic areas ($u_i$) related to smart city actions.

In the next sections, the specific results analysis for the Santa Maria/Brazil context is described individually by thematic area, ordered by maturity level starting with the thematic area with the best performance, living environment and infrastructure, until the worst performance, verified for mobility.

4.2.1. Living Environment and Infrastructure

The living environment and infrastructure includes spaces where the compatibility and functionalities of different technologies are perceived, adding intelligent practices in the human, economic, and social spheres [60]. In this context, the living environment and infrastructure area ($u_2=68.75\%$) presents a maturity in improvement (level 4), highlighted by the management and monitoring of “Risk Areas” ($v_5=100.00\%$), where the municipal risk reduction plan presents a risk area hierarchy, as well as the necessary structural measures and the type of intervention demanded to control identified risks. According to [61], the Santa Maria/Brazil risk reduction plan lists the main areas associated with geomorphological risks to public managers to define and formulate feasible measures to be executed in short, medium, and long periods. The “Waste collection” ($v_8=98.88\%$) coverage is close to the Brazilian urban areas average (98.80%) according to the [62]. However, “Sanitation” ($v_7=82.80\%$) requires the implementation of public actions to manage sanitation services, following [63], contemplated by improvements and constant updates, through governance instruments applied according to the local reality. In 2015, the basic sanitation policy was established in Santa Maria/Brazil, ensuring the population’s health in urban and rural areas, in addition to the regulation of basic sanitation actions [64].

Currently, the biggest living environment and infrastructure challenge for Santa Maria/Brazil is the sanitation system expansion in peripheral and rural zones, as the implementation of decentralized treatment is a feasible option compared to the traditional centralized model, which is economically unsustainable. Public–private partnerships, such as the sanitized city program of the metropolitan region of Recife/Brazil [65], which began in 2013, can also contribute to the operation, maintenance, recovery, and expansion of sanitation services in peripheral and rural areas.

4.2.2. Governance and Engagement

According to [66], governance and engagement require practices related to holistic and collaborative management through transparency in resource application to serve the population. Thus, in governance and engagement ($u_3=59.70\%$), an evolving maturity level was verified (level 3), with emphasis on “Digital inclusion” ($v_{10}=100\%$), where an accessibility menu with a responsive design and features adapted to access devices is available on the municipal digital information portal. In “Socioeconomic development” ($v_{11}=79.11\%$), Santa Maria/Brazil has a moderate development, occupying position 536 among 5471 Brazilian cities evaluated [67]. Regarding “Citizen service” ($v_9=0.00\%$), interactive online services via application or website were not verified.

One of the main governance and engagement challenges found was a lack of interactive online service channels for citizens, such as mobile applications, chatbots, and virtual assistants. This is a representative smart city action to promote transparency and communication with public management, adding agility and efficiency in real-time interactions. One example is the SP156 application, implemented in São Paulo/Brazil, which has more than 560 digital services, and also brings citizens and the government closer through the design of co-constructed services [68].

4.2.3. Entrepreneurship

Entrepreneurship ($u_{10}=58.33\%$) was evaluated with intermediate maturity (level 3), especially by “Companies” ($v_{32}=50.00\%$), which indicates the proportional growth in 2023 of 13.35% in the number of private companies [69], being part of the 37,131 active private companies of Santa Maria/Brazil [70]. Regarding creative economy enterprises, the city is in an early development stage ($v_{33}=25.00\%$), with an 8.19% increase in the number of such businesses within the municipality. As for “Technological park” ($v_{34}=100\%$) availability, the city has the “Santa Maria Tecnoparque”, a reference in technology and innovation in the southern region of Brazil, adding 30 resident companies and six institutions involved in the development of new technologies for innovative solutions [71]. It is shown in [72] that entrepreneurship actions are relevant in the emergence of smarter and sustainable technological solutions to influence companies and entrepreneurs to develop and grow cities.

A relevant challenge for Santa Maria/Brazil is the financial investment improvement and the expansion of private companies mainly in strategic sectors such as the industrial and creative economy, requiring the continuous long-term integration of public policies, infrastructure, entrepreneurial education, and investment incentives. An example of a smart entrepreneurship stimulus is structured technology parks enabled to promote innovation and integration between science, the government, and the productive sector.

4.2.4. Health and Assistance

Health and assistance ($u_{11}=57.50\%$) was evaluated with intermediate maturity (level 3), highlighting “Family health” ($v_{35}=55.00\%$), which indicates the population coverage by Family Health Strategy (FHS) teams for monitoring and guidance the population on health service access. Considering the “Availability of doctors” ($v_{36}=50.00\%$), 3.88 doctors for every 1000 inhabitants are available, whereas the national average register in 2022 was 2.69 doctors per 1000 inhabitants [57]. In Santa Maria/Brazil, the Brazilian Unified Health System (SUS) is supported by the University Hospital of Santa Maria (HUSM), linked to the Federal University of Santa Maria, serving multiple specialties in a region with more than one million inhabitants [73].

The main challenge is to expand the family health coverage strategy through geographic mapping using information systems, enabling habitants’ access to primary health care services. Current digital technologies allow the development of mobile applications to constantly update household records, as well as online health service scheduling based on geolocation and risk classifications, promoting equitable and effective access to primary health care.

4.2.5. Education and Training

Education and training ($u_4=50.67\%$) presents intermediate maturity (level 3), where the “Quality of education” ($v_{12}=52.00\%$) of primary students follows the national average level of development according to the Basic Education Development Index (IDEB) [74], calculated from data on school approval and average students’ performance in the public school system. The indicator “Higher education training” ($v_{13}=50.00\%$) indicates that 10.25% of citizens are enrolled in undergraduate courses, exceeding the Brazilian national enrollment average by 112.83%. According to [75], formal education is relevant to improving quality of life aspects, directly contributing to the generation of qualified jobs and income, in addition to contributing to the city’s technological development. In this context, higher education institutions are strategic for the execution of innovative projects for smart city actions related to solving social, environmental, and economic public demands.

In smart cities, basic education quality is a priority and should be measured not only by learning outcomes but also by integration with urban policies. For example, Curitiba/Brazil built spaces called “lighthouses of knowledge and innovation” integrated with public schools, providing modern educational technologies, maker environments, and cultural and innovative activities for basic education students outside of school hours to promote creative learning and innovative thinking [76].

4.2.6. Energy

Energy ($u_6=50.00\%$) is performed at intermediate maturity (level 3), highlighting the availability of charging stations for “Electric vehicles” ($v_{21}=100.00\%$), according to the global demand to reduce greenhouse gas emissions through alternative energy sources, mainly in urban environments [77], in addition to “Decentralized energy” ($v_{22}=100.00\%$), indicating the existence of renewable energy generation sources by independent consumers with an emphasis on photovoltaic energy. According to the National Electric Energy Agency, Santa Maria/Brazil has an installed capacity of 68,548.55 kilowatts in residential, commercial, and rural units, representing 2.15% of the installed capacity in the extreme south of Brazil [78]. However, in the “Energy meter” ($v_{19}=0.00\%$), residential smart meters are not used, and “Public lighting” ($v_{20}=0.00\%$) is not managed by remote management systems. This lack of smart meters and management in public lighting represents an opportunity for the development of smart city actions focused on energy efficiency, in line with [79], where smart city actions are necessary for the optimal use of energy, resource management, and energy optimization, given the challenges faced by public management in the search for sustainable cities.

Energy efficiency must be improved with the installation of smart energy meters and the implementation of a public light remote management system, integrating technologies as verified in the Netherlands through smart grids with distributed generation, conscious consumption, and the use of real-time data [80].

4.2.7. Technology and Innovation

Technology and innovation ($u_1=43.75\%$) presents intermediate maturity (level 3), obtained mainly by its performance in “Coverage” ($v_1=95.64\%$), higher than the Brazilian national average coverage of 62.70% verified in [81], and in “Connectivity” ($v_2=72.18\%$), indicating a good connectivity stage compared to the average of Brazilian cities, but still below the connectivity stage compared to the average of the southern region of Brazil’s cities. In addition, the density of “Fixed broadband” ($v_3=37.50\%$) and the unavailability of areas covered by “Free internet” $(v_4=0.00\%$) limit real-time access to communication technologies that depend on internet connection availability and stability. According to [26], in smart cities, information technology and connectivity contribute to improving the responsiveness, interactivity, and effectiveness of public services provided through technological ecosystems, service applications, and data centers, contributing to the construction of a more holistic vision in the development of solutions for the challenges present in urban areas and public management policy proposals. According to [12], the use of smart technologies in cities contributes to the universalization of and improvement in direct service to the population, the provision of transportation services, and the maintenance of safe public urban spaces to expand social inclusion, contributing to increasing the city’s resilience.

One limitation identified is the lack of free Internet connection. Smart cities use technology for daily routines, and Internet access is a key infrastructure for digital tool usability, especially in transport terminals, public offices, squares, parks, and tourist areas. As an example, a wide-reaching initiative in Europe is WiFi4EU, led by the European Commission to promote free access to Wi-Fi connectivity in public spaces, with more than 93,000 Wi-Fi hotspots installed in different European cities [82].

4.2.8. Economy and Sustainable Consumption

In economy and sustainable consumption ($u_7=42.80\%$), intermediate maturity was verified (level 3) through its performance in “Wealth generated” ($v_{24}=50.00\%$), which shows a growth in the gross domestic product (GDP) per capita of 8.90% in 2022, higher than the Brazilian GDP growth of 4.80% in the same period [57]. However, for “Interaction spaces” ($v_{23}=0.00\%$), there is no online system for mapping the suppliers’ operations, though this has already been successfully implemented in some cities in search of local and regional economic development. In this sense, ref. [83] indicates that the economy is constantly changing as a result of technological innovations and digital transformation, which require the effective monitoring of strategic actions aimed at boosting the local economy. In Barcelona/Spain, actions are structured with a focus on projects, whose interconnection is developed through an information portal with data sharing, as verified in the “Open Data”, which contributes to the creation of products and services, impacting the local economy and society [84].

The sectoral mapping of services and products with location and interaction can be a differentiation strategy for economic development in urban spaces, contributing to boosting innovation, entrepreneurship, and local economic activities. However, sectoral mapping requires the use of digital technologies and real-time data transmission on interactive business platforms (e.g., apps).

4.2.9. Security and Protection

In security and protection, are highlighted in [85,86] the implementation of new surveillance technologies as a key component in smart city building, people, and information protection, preventing crimes and providing a sense of security for the citizens. In the security and protection assessment ($u_8=41.67\%$), intermediate maturity (level 3) was obtained mainly by its performance in the “Control and operations center” ($v_{26}$ = 100.00%) through the implementation in 2018 of the integrated public security operations center, including a public security intelligence center with the participation of the municipal guard, military police, and civil police, aggregating telephone, radio communication, electronic fencing, traffic light control, and vehicle location services. In “Monitoring” ($v_{27}=0.00\%$), security cameras were installed in different locations, both on roads and in public buildings. However, the digital surveillance system coverage area was not available.

The main challenge is mapping the digital monitoring system in urban spaces, connected devices, cameras, and digital platforms capable of collecting real-time data for public safety, allowing the identification of areas with higher crime rates.

4.2.10. Coexistence and Reciprocity

Coexistence and reciprocity ($u_9=29.47\%$) showed evolving maturity (level 2), mainly through “Accessibility in public transportation” ($v_{30}=88.42\%$). Of the 190 public urban transport vehicles (buses), 168 are equipped with an accessibility system. However, limitations were found regarding the quantitative coverage measurement and “Accessibility of public buildings” structure mapping ($v_{29}=0.00\%$) given the lack of formal registrations of public buildings with accessibility conditions, as well as the absence of “Accessibility signage” ($v_{31}=0.00\%$) on pedestrian crossings, which compromise the circulation conditions of people with disabilities, restricting mobility in urban spaces. Thus, coexistence and reciprocity require the implementation of actions by public management regarding the mapping of public facilities with accessibility conditions, as well as the implementation of accessibility signage on public roads. Such actions ensure accessibility conditions on public roads, furniture, urban equipment, buildings, and transport with safety and autonomy, and without segregation or discrimination [87].

Even with technological advances, public building accessibility in Santa Maria/Brazil is one of its main challenges, particularly public road accessibility signs. Technology, in addition to providing opportunities for improving urban systems, should promote inclusion, equity, and accessibility in public spaces.

4.2.11. Mobility

In mobility ($u_5=25.35\%$), evolutionary maturity was found (level 2). “Urbanization” ($v_{17}=49.10\%$) shows that approximately half of the urban public roads are adequate (with paving, curbs, sidewalks, and manholes). Also, “Public transport” ($v_{18}=52.33\%$) represents the main urban transport means, totaling 104,769 passengers transported daily on weekdays [88]. However, “Public roads” ($v_{15}=0.00\%$) are not contemplated with real-time mapping, in addition to a lack of “Multipurpose lanes” ($v_{16}=0.00\%$) in urban spaces. Thus, mobility is the thematic area with the lowest maturity level, requiring special attention from public management.

The main challenge is to implement a road mapping system that enables the real-time monitoring of the urban infrastructure, with a view to implementing future improvements. The use of real-time data can benefit urban planning and technological interoperability. However, it requires significant financial investment, specific technical training, and usability regulation.

4.2.12. Current GMI

Combining each thematic area maturity level ($u_i$) with the proportionality scores ($w_i$) found in [54], the GMI for the current scenario in Santa Maria/Brazil is calculated and shown in

Table 2. Current GMI of Santa Maria/Brazil.

Thematic Area	Main Challenge	Score (${\mathit{w}}_{\mathit{i}}$)	Maturity (${\mathit{u}}_{\mathit{i}}$)	${\mathit{u}}_{\mathit{i}}{\mathit{w}}_{\mathit{i}}$
Living environment and infrastructure	Peripheral zone sanitation	9.71%	68.75%	66.76%
Governance and engagement	Interactive online services	9.61%	59.70%	57.37%
Entrepreneurship	Private company expansion	8.49%	58.33%	49.53%
Education and training	Quality of basic education	9.58%	50.67%	48.54%
Health and assistance	Family health coverage	8.03%	57.50%	46.17%
Energy	Lack of efficiency	8.98%	50.00%	44.90%
Technology and innovation	Free Internet connectivity	10.05%	43.75%	43.97%
Economy and sustainable consumption	Product/service mapping	8.95%	42.80%	38.31%
Security and protection	Digital monitoring system	8.85%	41.67%	36.88%
Coexistence and reciprocity	Public space accessibility	8.62%	29.47%	25.40%
Mobility	Public road real-time mapping	9.13%	25.35%	23.14%
GMI				43.72%

, with the main challenge identified throughout the results’ analysis.

The GMI of 43.72% in Santa Maria/Brazil indicates intermediate maturity (level 3) to smart city actions, positively highlighted mainly by the thematic areas of life and infrastructure ($u_2=68.75\%$), governance and engagement ($u_3=59.70\%$), and entrepreneurship ($u_{10}=58.33\%$), and negatively by mobility ($u_5=25.35\%$), coexistence and reciprocity ($u_9=29.47\%$), and safety and protection ($u_8=41.67\%$).

The main challenges identified are drivers for the improvement in and evolution of the Santa Maria/Brazil urban maturity concerning smart city actions. Identified and resolved in a systemic way, the main challenges can offer relevant subsidies for public policy development and incremental action formulation, aligned with sustainability principles and quality of life to intelligent urban environment planning.

5. Discussion

To improve citizens’ living conditions and the urban services currently provided in Santa Maria/Brazil, five incremental actions are proposed for the three thematic areas with the lowest maturity levels, being a guideline for public management.

Smart city actions use information from communication technologies to obtain real-time data to more effectively manage services interactively. For mobility, the first incremental action focuses on the “Public roads” indicator ($v_{15}$), suggesting the implementation of an interactive real-time mapping system through applications with information on the traffic situation and public spaces level of occupation, as well as public transport and safety service availability. In Santander/Spain, a smart city project called “SmartSantander” was developed with the large-scale implementation of over 12,000 traffic, environmental, and parking sensors, improving the city’s habitability. The “SmartSantander App” has been downloaded by more than 24,000 users, serving to view, in real-time, the location of buses, taxis, and bicycle loan points, as well as traffic information, parking, security points, safety services, and public space use [89,90]. Another solution to improve urban mobility is the “Moovit” application. Launched in 2012, this app facilitates public transport use and enables travel planning with different options of transport modes, and also provides official information from the authorities and transportation operators to indicate the best urban displacement route in real time. With over 1.7 billion users in 45 languages present in 112 countries and over 3500 cities, “Moovit” is the world’s most-used urban mobility application [91,92]. In Brazil, it is being adopted in cities such as Porto Alegre, Curitiba, Belo Horizonte, Campinas, and Salvador.

The second mobility incremental action includes the adoption of “Multipurpose lanes” ($v_{16}$) to promote active mobility alternatives, reducing congestion generated by motorized private transport, aligned with [93]. The multipurpose lanes implemented in Curitiba/Brazil are an example, where currently 300 km of bike lanes and shared lanes contribute to sustainable urban mobility, including the “Curitiba Cycle Plan”, which foresees, by the end of 2025, over 400 km of bike lanes installed in different regions of the city. In addition, in 2023, a system with 500 shared mechanical and electrical bikes with fixed stations was launched [94].

In coexistence and reciprocity, the first incremental action involves adapting public buildings to accessibility based on technical specification preparations to the required adaptations, attempting to improve demand for “Public accessibility” ($v_{29}$). Next, the “Accessibility signage” indicator ($v_{31}$) can be improved with an incremental action related to expanding the movement autonomy of people with disabilities in urban spaces through multi-accessible equipment and tactile flooring, prioritizing hospitals, educational institutions, and supermarket zones, and also adapting traffic lights with audible devices in populated zones. It consists with emphasis on [95] the importance of the appropriate solutions related to accessibility in urban spaces. In Santa Catarina/Brazil, the “Accessible SC” project, developed by the Public Prosecutor’s Office, supports a multidisciplinary group of professionals linked to control authorities, the government, and civil representatives to verify the accessibility conditions in public buildings based on 56 NBR 9050:2015 requirements [87]. As a result, a technical report was prepared and delivered to the public managers, responsible for developing adaptations within defined deadlines and budgets [96].

In security and protection, the incremental action is an effective mapping of the area covered by the current digital surveillance system, as well as a feasibility analysis of integration with commercial facilities’ private cameras with public road capture, expanding the “Monitoring” ($v_{27}$) system area covered. Paraná/Brazil shows an average coverage of 30% in public urban areas, despite their continuous investment in surveillance camera installations. By integrating areas covered by public and private surveillance cameras, the average coverage could reach 80% [97].

From the five incremental actions proposed, two future scenarios are projected and compared using the GMI (

Table 3. Current scenario and projected scenarios for GMI in Santa Maria/Brazil.

Thematic Area	${\mathit{u}}_{\mathit{i}}{\mathit{w}}_{\mathit{i}}$
	Current Scenario	Projected Scenario A	Projected Scenario B
Security and protection	36.88%	51.63%	66.38%
Coexistence and reciprocity	25.40%	54.13%	82.87%
Mobility	23.14%	45.97%	68.79%
Living environment and infrastructure	66.76%	66.76%	66.76%
Governance and engagement	57.37%	57.37%	57.37%
Entrepreneurship	49.53%	49.53%	49.53%
Education and training	48.54%	48.54%	48.54%
Health and assistance	46.17%	46.17%	46.17%
Energy	44.90%	44.90%	44.90%
Technology and innovation	43.97%	43.97%	43.97%
Economy and sustainable consumption	38.31%	38.31%	38.31%
GMI	43.72%	49.75%	55.78%

). For all five indicators related to the incremental actions, in “Projected scenario A”, an intermediate maturity level achievement (50%) is proposed, and in “Projected scenario B”, an advanced maturity level achievement (80%) is considered.

For “Projected scenario A”, an additional value of 13.79% in the GMI was obtained compared to the current scenario, while for the “Projected scenario B”, the increase in the GMI was 27.58%. This GMI evolution shows the incremental actions’ effect in the three thematic areas with the lowest maturity levels, supporting the development of sustainable urban strategies with opportunities for advancements in the economic, environmental, and sociocultural dimensions.

The incremental actions’ implementation requires public governance planning and can be gradually executed since the incremental actions are independent. In the short term (up to 2 years), the implementation of the interactive system for mapping public roads in real time through an application and the effective area-covered mapping via the current digital surveillance system are the two feasible incremental actions to effectively improve urban spaces. A defining aspect of the incremental actions’ implementation is economic viability given the limited financial investment capacity of Santa Maria/Brazil and the prioritization of other public demands. Also, specific technical feasibility must be considered for the implementation of all incremental actions proposed, for example, the implementation of multi-use lanes in urban spaces and public buildings’ adaptation for accessibility. Finally, according to stakeholders involved in public management, all proposed incremental actions have a positive cost–benefit effect, being within the scope of smart city actions and contributing to citizens’ quality of life. However, the proposed incremental actions must be implemented sequentially and independently according to the available financial resources and/or the consolidation of public–private partnerships, a complex bureaucratic process in the Brazilian context that takes time and human resources to be executed.

6. Conclusions

Through smart city actions, technological innovations enable organized and sustainable city development, providing financial resource-saving and environmental preservation. In this context, and in alignment with the research objective of supporting the implementation of strategic actions for urban development, a performance measurement system was developed. This system was designed to provide methodological and managerial support for strategic urban planning, enable the continuous monitoring of municipal performance, and inform the implementation of public policies to enhance quality of life in urban environments.

The PMS is a tool designed to assess the level of development of smart city initiatives within the Brazilian context. It is structured around 11 thematic areas and comprises 38 key performance indicators, enabling a quantitative evaluation of urban maturity by calculating the general maturity index. This index offers a situational analysis that reflects the current stage of urban management practices in cities. By adopting this framework, it becomes possible to enhance successful initiatives, identify critical gaps, and guide the implementation of new actions aimed at optimizing public resource allocation and improving the efficiency of urban services in alignment with the principles of intelligent and sustainable urban development.

Despite being a quantitative approach to result analysis, the proposed PMS was developed with the definition of the 11 thematic areas and the 38 key performance indicators aligned to a qualitative bibliographic nature, contributing to the expansion of comparable data across different contexts, emphasizing cities as contextually inserted governance spaces, according to the world of imperfect and innovative urban point of view highlighted in [98].

According to [99], the implementation of appropriate public policies requires the analysis of specific empirical contexts. However, to produce relevant insights, an appropriate analytical framework must be considered as a reference. The performative dimension of the proposed PMS provides support for the definition of urban priorities by thematic areas. Thus, measuring performance is useful to inform about the development level of a thematic area, offering an analytical reference to interpret the effects on the behavior of stakeholders and the concrete results of the implemented public policies.

For future implementation of smart city actions in Santa Maria/Brazil, where different challenges related to informal occupied areas and land use management are verified, the analysis of behavioral factors can be a relevant aspect. It is highlighted in [100] the relevance of behavioral elements such as trust between stakeholders, cultural norms, and past experiences in decision-making related to land use, emphasizing the subjective dimensions of local reality and the need for an approach related to the cultural, social, and institutional aspects that influence public policy implementation.

To test the proposed PMS, the current scenario in Santa Maria/Brazil was investigated, where a GMI of 43.72% was obtained, indicating an intermediate maturity level. For the thematic areas, the best performance was verified for the living environment and infrastructure ($u_2=68.75\%$), governance and engagement ($u_3=59.70\%$), and entrepreneurship ($u_{10}=58.33\%$). On the other hand, mobility ($u_5=25.35\%$), coexistence and reciprocity ($u_9=29.47\%$), and security and protection ($u_8=41.67\%$) had the worst performance.

Five incremental actions were proposed to improve the public management planning demands of Santa Maria/Brazil, covering the key performance indicators “Public roads”, “Multiuse tracks”, “Public accessibility”, “Accessibility signage”, and “Monitoring”. Possible structural improvement projections obtained with the five incremental action applications were aggregated into two projected future scenarios, which presented a GMI of 49.75% for “Projected Scenario A” and 55.78% for “Projected Scenario B”.

The PMS’s applicability requires available time and planning for execution to obtain all input data provided online by national agencies, statistical institutes, regulatory agencies, and industry federations. Also, the limitations and difficulties in PMS application can be verified to obtain input data collected through semi-structured interviews with public city managers, especially if the city’s data structure and availability are partially decentralized, as verified in Santa Maria/Brazil, which required more than one visit to different departments (e.g., governance, environment, education, social development) to obtain answers about all the input data required.

Based on the PMS application, the result analysis verified in the 11 thematic areas and the GMI reflects a performance bias of the current scenario in Santa Maria/Brazil; the results are not generalizable to other local or regional Brazilian contexts and realities, even for a similarly sized or culturally related city.

As a future research proposition, the proposed PMS can be applied periodically (e.g., annually) to verify the performance of Santa Maria/Brazil regarding smart city actions and measure GMI evolution mainly after applying the five incremental actions proposed, visualizing the indicators on a timeline to provide opportunities for the development of actions by smart city thematic area. Also, the PMS should be applied to verify the situation of smart city actions in other cities, mainly in the southern region of Brazil, allowing the analysis and comparison of the results obtained in this research with other urban contexts.

To verify smart city maturity in a holistic view, citizen surveys and structured stakeholder interviews can be applied to establish comparisons between the analytical results verified with the PMS and the qualitative perception of smart city actions by citizens and stakeholders involved with public management.