Cities 144 (2024) 104630
Available online 11 November 2023
0264-2751/© 2023 Elsevier Ltd. All rights reserved.
Fundamental power of the city – A proposition of a new paradigm and index for city development
Anna Wojewnik-Filipkowska
a,*, Anna Gierusz-Matkowska
b, Patrycja Krauze-Ma ´ slankowska
caDepartment of Investment and Real Estate, Faculty of Management, University of Gdansk, Poland
bDepartment of Statistics, Faculty of Management, University of Gdansk, Poland
cDepartment of Business Informatics, Faculty of Management, University of Gdansk, Poland
A R T I C L E I N F O Keywords:
Sustainable Smart Resilient Urban City Development Management
A B S T R A C T
Managing a dynamic and complex urban system according to the single concept of city development is insuf- ficient. The study’s aim is to present the main concepts of cities development, formulate a new hybrid concept of city, and propose a related index to support strategy implementation and monitoring. The research methods include literature scoping, literature content analysis, and linear ordering as a multivariate method of analysis.
The research conclusion identifies a new hybrid concept of a “resilient smart sustainable city” and explains a distinction between weak and strong perception of the concept. The practical part of the research develops synthetic measure “Fundamental Power of the City Index” which allows to select variables representing indi- vidual cities’ priorities and apply them in every city analysis, development strategy building, and monitoring.
The Index is tested for 18 voivodship cities in Poland for the period 2014–2020. The results of this study can support city stakeholders in their efforts in developing “resilient smart sustainable city”.
1. Introduction
Cities are areas with a high concentration of population and eco- nomic activity, social, technical, administrative, and political affairs.
They are therefore an interesting but difficult area of research and management. The literature on the subject describes numerous concepts of city development. Among others, the following city labels are dis- cussed in the literature: competitive, creative, attractive, vulnerable, wired, knowledge, entrepreneurial, vital, viable, and digital (de Jong, Joss, Schraven, Zhan, & Weijnen, 2015). Moreover, these concepts are not mutually exclusive. This is confirmed by research on hybrid con- cepts, e.g. smart slow city (Farelnik & Stanowicka, 2016), smart sus- tainable city (Wojewnik-Filipkowska, 2017), or innovative eco-city (Łobejko, 2015). Concepts also infiltrate one another, e.g. a smart city uses the idea of a creative city in which the functioning of the urban infrastructure system is improved in order to balance economic growth and improve the quality of life of its inhabitants. The concept of city development can be therefore built on the basis of selected models separately or jointly, e.g. the synergy of the concept of a creative, sus- tainable, and resilient city can be used to create a human sustainable city (Girard, 2011), or the smart city and resilient city models can be applied
simultaneously, but to a different extent, to strengthen the city’s intel- ligence or resilience (Baron, 2012). The so-called hybridization of development is a process of joining elements of various concepts rooted in sustainable development in order to achieve a higher quality of life in the city (Drobniak, 2019). We claim that there is a need for new development concepts and that the search requires analyzes and studies as well as verification of theoretical assumptions so that the adopted model is aimed at city advancement and takes into account civilization trends, new technologies, local, regional, and international conditions, experiences and, above all, the interests of the city’s community with the respect to principles of sustainable development.
The results of city development can be presented by development indicators. Such indicators can be a tool for city strategic diagnosis, monitoring, and thus support decision making referring planning of investment aimed at improving city dimension characterized by low- value indicators. This paper takes into consideration complementary dimensions of the city development, i.e., the social, economic, and spatial-environmental dimensions. These dimensions of the city can be analyzed and described using the different concepts of city development and can be presented using appropriate indicators.
Based on the above, there are three main research questions which
* Corresponding author at: University of Gdansk, Faculty of Management, Armii Krajowej 101, 81-824 Sopot, Poland.
E-mail addresses: [email protected] (A. Wojewnik-Filipkowska), [email protected] (A. Gierusz-Matkowska), patrycja.krauze- [email protected] (P. Krauze-Ma´slankowska).
Contents lists available at ScienceDirect
Cities
journal homepage: www.elsevier.com/locate/cities
https://doi.org/10.1016/j.cities.2023.104630
Received 22 July 2022; Received in revised form 28 July 2023; Accepted 17 October 2023
refer to the layer of knowledge and the layer of practice:
(1) What are the fundamental concepts of the city development?
(2) Are “single” concepts “sufficient” for the construction of a city development strategy?
(3) How can the level of development of a city be assessed?
Therefore, the study aims are:
(1) To identify the main concepts of city development and find out the fundamental ones.
(2) To formulate a new hybrid concept of city development based on the fundamental city development concepts.
(3) To propose and test a new index of city development based on the hybrid concept of city development to support strategic diag- nosis, strategy implementation, and monitoring.
The reference to the term “fundamental” is deliberate and it is intended to refer to the idea of fundamental analysis on the capital market. Fundamental analysis is based on “fundamentals”, i.e. the condition of the economy and the condition of the company. The better the financial condition of the company, the higher the value of its shares and the more attractive it is to investors. The analysis is not used to assess the value of an investment in the short term but is used for in- vestments with a long-time horizon (Luca, 2018). A similar approach is proposed in this research in reference to cities. The research looks for city “fundamentals” (fundaments) and analyzes its components to identify city potential for development in the long term. The difference between fundamental analysis for companies and for cities refers to the scope of the analysis and criteria of assessment. As fundamental analysis for companies and their valuation is based on cash flow analysis and value for shareholders, the city perspective encounters much more broader determinants (variables) and looks for creation of public value.
These variables will be incorporated into index of “Fundamental Power of the City”.
Taking into consideration the above, the study is based on three assumptions referring respectively to study questions and aims, being also a scientific hypothesis:
(1) Sustainable, smart, and resilient city are the three main concepts of city development.
(2) A “resilient smart sustainable city” (no commas between con- cepts) is a new hybrid concept of city development that de- termines its fundaments for development.
(3) A new index of “resilient smart sustainable city” is a tool to support strategic diagnosis, strategy implementation, and monitoring.
The justification for the conducted research is twofold – based on the importance of the subject of the analysis but also the statistical method applied. The subject of research are cities where about 60 % of people live. Cities are also expected to host most of the future population in- crease (Abu-Rayash & Dincer, 2021; United Nations, 2019; Wendling et al., 2018). Although cities occupy less than 5 % of the earth’s land area, they consume more than 75 % of the natural resources and emit 60–80 % of the global greenhouse gases. The high urbanization urges cities to address social, economic, and environmental challenges (Moustaka, Maitis, Vakali, & Anthopoulos, 2021). On the other hand, the research justification is related to the chosen method of analysis, i.e.
multivariate analysis and its application in city management. The spe- cific method-related motivation includes the need to reduce the large amount of information in order to enable easier communication, con- clusions drawing, diagnosis support, decision-making, and strategic management monitoring (Anderson, 2020; Bibri, 2019; Wendling et al., 2018). Also, a demand for empirical testing of conceptual frameworks inspired the research (Zhao, Fashola, Olarewaju, & Onwumere, 2021).
Measuring what matters for socio-economic development is a challenge, but as Stiglitz, Fitoussi and Durand point out, new measures are still
needed to help protect people from possible shocks, restore security and confidence in anti-crisis policies. They state however that indicators alone are not enough – it is necessary to change the way we think about the components of prosperity (Stiglitz, Fitoussi, & Durand, 2019). This research is supposed to respond to above mentioned demands.
The methods used in the paper result from the stated aims, research questions, and hypothesis. Scoping literature review, a simplified version of systematic literature review (SLR) is conducted along a recognized procedure (Siddaway, Wood, & Hedges, 2019). SLR is generally considered to be superior in terms of transparency as other researchers can more easily verify the findings of the study by repli- cating the research frame (Aarseth, Ahola, Aaltonen, Økland, &
Andersen, 2017). The aim of the review is to provide a snapshot of the research field (Xiao & Watson, 2017) but it is not the aim of the paper itself as in typical SLR papers providing an initial evidence backdrop for future research and policy development, e.g. (Chen, Jiang, Liu, Lin, &
Yang, 2023; Shevelkova, Mattocks, & Lafortune, 2023). In particular, SLR is used to answer the first question about fundamental concepts of city development but it also creates grounds and justification to answer the second question about new hybrid concept of city development. So, this paper includes SLR but also SLR-results based further research. As scoping literature review enables to select the main concepts in urban development management, the content analysis is used to characterize these main concepts and determines the content of the introduction. On this basis, a new hybrid concept of city development is proposed.
The fundamental power of a city is a variable that is not directly measurable but generated by so-called diagnostic variables. Therefore, using the design method, an original composite index is constructed.
Composite indicators advantages but also disadvantages, data selection requirements, and guiding principles to construction of a composite indicator (Cash et al., 2002; OECD, 2008) are taken under consideration while the selection of the method for the index construction is linear ordering. When creating the methodology, the classification of di- mensions (subsystems) of the city is used in accordance with the con- clusions of earlier stages of research. Using the experiment method, the above-mentioned synthetic index is tested in a comparative analysis of selected cities. The index is tested for 18 voivodship cities in Poland;
analysis period is 2014–2020. This paper develops research published by authors in 2021 (Wojewnik-Filipkowska, Gierusz, & Krauze- Ma´slankowska, 2021) by adding systematic literature review and extending period of analysis.
The novelty of this research paper refers to development of a new conceptual model of “resilient smart sustainable city” and its oper- ationalization in the index of Fundamental Power of the City which represents integrated approach and is applicable to different cities to determine their sustainability, smartness, and resilience. The main sci- entific focus is on the idea of hybrid city development concept and its Index based on easily accessible, available, not expensive data so that the concept of the Index could be easily used for cities of different size and budget, and in different countries. Therefore, from the scientific point of view, the selection of cities is of secondary importance, as Fundamental Power of the City Index allows to be modified (in terms of variables available, as one-size-fits-all may not apply) on the condition that all dimensions of sustainable, smart, and resilient city are repre- sented by variables in the Index.
The remainder of this paper is organized as follows. The following Section 2 provides a literature overview. The section includes scoping literature review followed by literature analysis relating main concepts of city development, data and the data ecosystems, and overview of selected indices. Section 3 introduces materials and methods. The sec- tion includes the theoretical foundation related to linear ordering, description of phenomenon to be measured which is Fundamental Power of the City, and practical framework applied for cities evaluation including detailed practical questions, description of steps of applying the framework, variables and their requirements, and information about sources of data (variables). In Section 4, results are presented and
discussed. The final Section 5 offers the study’s conclusions, presents study limitations, and possibilities for further research. The document includes appendices as indicated in text.
2. Literature review 2.1. Scoping literature overview
Adopted research methodology for the systematic literature review follows the recognized and practiced procedures (Hajek, Youssef, &
Hajkova, 2022) and can be summarized as follows:
(1) research preparation (identification of key words and the primary string formulation),
(2) data collection (Scopus bibliographic database file was used), (3) data cleaning (verification of the subject area and document
type),
(4) selecting words and phrases from title and abstract field, (5) creation of term co-occurrence map based on text data from
cleaned dataset,
(6) identification of research hotspots and trends (visualization tool VOSviewer version 1.6.18 was applied).
A comprehensive search of the Scopus Collection database was conducted. Firstly, following terms were searched in title and abstracts:
city, sustainable, smart, resilient. These terms constituted the unit of analysis. Subject area and document type limitations enabled to identify 211 articles. After verification of abstracts, additional key words were added: management, performance. As a result, 87 articles were pro- vided. The research queries (advanced search) are presented below in Table 1.
The selected details of research results within the formulated queries and their limitations relating type of document and subject area of the two strings are provided in Table 2. The time scope of the search is not limited. The oldest (or the first research) in the database is published in 2012 (query 1) or 2014 (query 2). The table also provides the same details for the abstract based selected articles for the content analysis performed afterwards.
To provide a snapshot, a content analysis is performed to identify thematic clusters based on the co-occurrence of terms and to visualize the most important terms for the research topic. In order to visualize the
structure and dynamics of the research in formulated area, science maps are created. It helps to present existing knowledge by clustering an underlying research in terms of textual content (terms). VOSviewer tool uses association strengths based on the number of co-occurrences of items (Eck & Waltman, 2017). The term-based science map for the query 2 of 87 articles is presented in Fig. 1.
The conducted scoping literature review shows two clusters. Left side of the map presents city development related cluster where “smart city”
and “sustainable city” are identified. Right side of the map shows management related cluster where “system approach”, “resilience” and
“sustainability” cluster connected with “decision making” is presented.
This justifies the conclusion that research relating simultaneous analysis of sustainable, smart, and resilient cities is multidimensional as these concepts spread between two clusters. From the scientific point of view, the cluster identification is justified by the fact that that city develop- ment concepts are grounded in economic theories of development and growth (Zhang et al., 2023), while planning and decision making – in management (Baynes, 2009).
For the content analysis, the set of 87 documents is analyzed and 25 articles are chosen to present the selected concepts in city management and selected city development indicators. The 25 documents are listed in the Appendix. The term-based science map for 25 selected articles for the content analysis is presented in Fig. 2.
The analysis of the term-based map of selected documents shows three clusters. Starting from the left, there are terms grouped around the main keyword of “smart city”, accompanied by “sustainable city” and
“resilient city”. Although the three concepts are in one cluster, the term
“smart-city” represents greater strength which is confirmed by the terms of “technology”, “climate change” and “energy” associated with the concept. There is no “performance” or “indicator” in this cluster. The central cluster concentrates around term “city”. It focuses on city development in the context of sustainable development and refers to
“data”. The right-side cluster concentrates around phase “framework” Table 1
Advanced research queries.
No. String Result (no of
articles) (1) TITLE-ABS-KEY (city AND sustainable AND smart AND
resilient) AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE, “cp”) OR LIMIT-TO (DOCTYPE, “ch”) OR LIMIT-TO (DOCTYPE, “re”) OR LIMIT-TO (DOCTYPE,
“cr”) OR LIMIT-TO (DOCTYPE, “bk”)) AND (EXCLUDE (SUBJAREA, “PHYS”) OR EXCLUDE (SUBJAREA, “MEDI”) OR EXCLUDE (SUBJAREA, “CENG”) OR EXCLUDE (SUBJAREA, “BIOC”) OR EXCLUDE (SUBJAREA,
“NURS”)) AND (EXCLUDE (SUBJAREA, “AGRI”)) AND (EXCLUDE (SUBJAREA, “PSYC”)) AND (EXCLUDE (DOCTYPE, “re”) OR EXCLUDE (DOCTYPE, “cr”))
211
(2) (TITLE-ABS-KEY (city AND sustainable AND smart AND resilient)) AND (management) AND (performance) AND (LIMIT-TO (DOCTYPE, “ar”) OR LIMIT-TO (DOCTYPE,
“cp”) OR LIMIT-TO (DOCTYPE, “ch”) OR LIMIT-TO (DOCTYPE, “re”) OR LIMIT-TO (DOCTYPE, “cr”) OR LIMIT-TO (DOCTYPE, “bk”) OR EXCLUDE (DOCTYPE,
“re”) OR EXCLUDE (DOCTYPE, “cr”)) AND (EXCLUDE (SUBJAREA, “PHYS”) OR EXCLUDE (SUBJAREA, “MEDI”) OR EXCLUDE (SUBJAREA, “CENG”) OR EXCLUDE (SUBJAREA, “BIOC”) OR EXCLUDE (SUBJAREA, “NURS”) OR EXCLUDE (SUBJAREA, “AGRI”) OR EXCLUDE (SUBJAREA, “PSYC”))
87
Table 2
Results of advanced research queries.
Criteria No. of articles in brackets
String 1
(211) String 2
(87) Content analysis (25) Document
type Article 96 55 20
Conference paper 74 26 4
Book chapter 37 6 1
Book 4 0 0
Year 2022 25 18 8
2021 36 12 5
2020 50 24 5
2019 38 13 2
2018 17 8 2
2017 22 7 2
2016 9 1 0
2015 8 3 1
2014 1 1 0
2013 4 0 0
2012 1 0 0
Subject area Social Sciences 107 47 13
Engineering 103 46 14
Computer Science 62 28 4
Environmental Science 50 21 6
Energy 44 25 9
Business, Management
and Accounting 24 10 6
Decision Sciences 16 13 3
Mathematics 14 7 2
Earth and Planetary
Sciences 10 1 1
Economics, Econometrics and Finance
8 2 0
Materials Science 8 5 1
Arts and Humanities 5 0 0
Fig. 1.Term-based science map. A full counting of terms extracted from title and abstract fields was used with a minimum number of occurrences of the keyword of 10 (query 2, 87 documents).
Fig. 2. Term-based science map. A full counting of terms extracted from title and abstract fields was used with a minimum number of occurrences of the keyword of 5 (25 documents).
and presents terms such as “indicator”, “indicator set”, “assessment scheme” which are related to the assessment, but the cluster in- corporates concept of sustainable development and resilience, ignoring smart city. At this stage of research, based on literature analysis, it can be concluded that literature gap refers to performance analysis using a framework, metrics, or indices for joined concept of sustainable, smart, and resilient city. The content analysis of selected documents provides opportunity to draw more detailed conclusions.
2.2. Main concepts of city development
Various city concepts have been considered as responses to chal- lenges of urbanization (Bruzzone, Dameri, & Demartini, 2021; de Jong et al., 2015; Hatuka, Rosen-Zvi, Birnhack, Toch, & Zur, 2018). The growing use of city labels, their conceptual dimensions, mutual in- terdependencies, and future trajectories demonstrate diversification of city labels beyond “smart” and “sustainable”, and constant concerns about achieving synergies of different approaches to support urban transformation (Schravena, Jossb, & Jongcd, 2021).
The “sustainable city” is the best-known concept. Sustainable development, which emerged in the 1980s (WCED, 1987), shaped thinking about urban development and gave it high-level policy recog- nition both worldwide and locally. It continues to be influential today.
The “triple bottom line” shows the interrelationship between and co- dependence of social, economic, and environmental dimensions, and it has become a mainstream in research, policy, and practice (de Jong et al., 2015). A milestone in sustainable development is the 2030 Agenda and a set of 17 Sustainable Development Goals (SDGs) covering “triple bottom line”. Based on the discussion of substitutability between natural and human-made capital, distinction between week and strong sus- tainability has been acknowledged (Wu, 2013). The 2030 Agenda is also linked to New Green Deal and European Green Deal, the global and European action plan for sustainable economy, focusing on climate neutrality, and modern, resource-efficient and competitive economy.
The goal of being a sustainable city should drive the decisions for city interventions (Quijano et al., 2022). So sustainability is crucial in the urban transformation strategy to reach more resource, efficient, resil- ient, and smarter cities. Simultaneously, sustainable development concept has been under critique (Molamohamadi & Ismail, 2014). It is often used imprecisely, which makes it difficult to implement; actions taken in the name of sustainability are insufficient or ineffective. There is often a lack of concrete policies and actions to achieve sustainable development, short-term and shallow solutions dominate. Sustainable development is criticized also because it focuses on economic and environmental aspects while ignoring social issues. There is also too much faith in technology and innovation which can push away other aspects such as reducing consumption, increasing social justice and equality.
According to Baran, Kłos, Chodorek, and Marchlewska-Patyk (2022), the smart city concept has recently turned out to be a top sustainable city management idea. Therefore, it can be assumed that smart city concept is not a stand-alone idea but it is developed on the basis of sustainable development. The authors prove that there are many concepts of smart cities as cities and their development level differ and therefore they must find their own priorities (Baran et al., 2022; Myeong, Kim, & Ahn, 2021). According to Quijano et al. (2022), multiple pillars of a smart and sustainable city include environment, energy, mobility, ICT, citizens, economy, governance. According to Abu-Rayash and Dincer (2021) smart city comprises eight main domains including economy, environ- ment, society, governance, energy, infrastructure, transportation, and pandemic resiliency. Smart cities are also expected to improve the ef- ficiency and effectiveness of urban management - ultimately enabling cities to be sustainable and resilient (Zhang, Pee, Pan, & Cui, 2022). In this sense, smart city is a key tool in making cities sustainable and also resilient among others by policy integration in smart city development such as horizontal integration across sectors and disciplines, vertical
integration across different governmental levels and linkages between national and local development, and a whole-of-society approach engaging private sector and civil society (Zheng, Kwok, Aquaro, & Qi, 2019).
In particular, a smart city as a tool in the struggle against climate change was claimed by Fern´andez and Peek (2020). They formulated a concept of a “smart sustainable city” however the synergy of the con- cepts is not new and earlier research shows that synergy (Wojewnik- Filipkowska, 2017). According to Fern´andez and Peek (2020), the climate change made the environment the core of smart sustainable development and results from their research suggest possibility of the interaction of technology and nature.
According to the Zheng et al. (2019) smart city is a “guide” also for livable cities. It evolves, and it may be tailored to support the empow- erment of individuals, groups, and society where high-tech expensive infrastructure does not play a key role (Myeong et al., 2021). So not only digital, wired, information city are conceptual relatives of smart city.
Also creative, learning and human city are conceptual cousins of smart city (Nam & Pardo, 2011). Cities (by their social and human capital) must act smarter in their sustainable development.
Although smart city can be perceived as an “up-date” version of sustainable city, it is not free of challenges. Zhao et al. (2021) highlight that smart city research is often fragmented and technology-driven;
studies concentrate on benefits but avoid shortcomings of technologies and unsuccessful projects; there is a need to build new theories for smart city research; and there is a lack of empirical testing of the conceptual frameworks. Therefore, smart city strategies should be considered in a holistic way when building vibrant, sustainable, and resilient cities.
Other concepts, such as already mentioned resilient city, are increasingly recognized and must be aligned to the smart and sustain- able city concepts (Sharifi & Allam, 2021). Resilience related to the urban infrastructures is rooted in the concept of industrial resilience (Timashev, 2017). The resilient city is also called an evolutionary concept and a new city development paradigm anchored in consolidated visions of above-mentioned concept of “smart sustainable city” (Bruz- zone et al., 2021). Timashev claims (Timashev, 2017), that city becomes resilient when it becomes smart. This is confirmed also by Zheng et al.
(2019), as stated above, they claim that smart city is a guide for resilient city. These examples show that concept of city resilience is discussed in connection with sustainable development and smart cities, being an up- dated version of smart sustainable city.
Energy and resource optimization, climate-neutral digital economy, digital citizen engagement, and intelligent governance are essential for resilient urbanization (Pee & Pan, 2022). The components of urban resilience refer to preventing any potential threat; withstanding any impact; reacting to the crises derived from the impact; recovering the city’s functionalities; and learning from the experience (Timashev, 2017). Pee and Pan (2022) underline that resilient urbanization refers to climate shocks as well as energy shocks that cities may encounter.
Moreover, different shocks can be connected - for instance the COVID-19 pandemic has been perceived in terms of social large-scale risk and shock has serious economic and also environmental consequences.
Therefore, the four main components of urban resilience are: industrial disaster and climate resilience, economic resilience, social resilience, and urban resilience.
As the concept of resilience assumes that communities and systems can survive and adapt to change, it does not take into account differ- ences in resources, social and economic capital, and access to public services, which is a reason for critique of the concept. This shortcoming can further exacerbate inequalities and make it more difficult to rebuild and protect the most vulnerable groups in society. Another problem of the concept of resilience is that it is often understood as adaptation to change, rather than seeking to prevent and mitigate the negative effects of those changes, and the lack of consistency in the approach to resil- ience at different scales, from the individual to the community, the re- gion or the global system.
What connects all three concepts is knowledge. Sustainability, smart city and resilience refer to knowledge – and knowledge requires data.
According to Rani, Jabar, Abdullah, and Jusoh (2020), knowledge resilience should bring numerous benefits to smart cities as it influences knowledge network in smart cities. The authors identified eight factors which influence knowledge resilience in smart cities and their knowl- edge can contribute to potential development and successful expansions of smart and sustainable city. These factors include energy, social cap- ital, human capital, economic, environmental capital, IT-enabled pro- cesses, smart institution, and smart project portfolio. The connection between technology and data related smart city and resilience under- stood as a city’s capacity to learn and adapt are discussed by Anderson (2020). Anderson presents a human-approach to smart city. The author claims that development and change adaptation involves a capacity for imaginative problem identification and solving as much as it involves technical know-how. The author introduces four critical operating principles supporting development of smart city. Firstly, operating principle refers to incomplete data, uncertain information, and needed action. Secondly, lack of the decision, even if the indeterminacy of in- formation is observed, is a threat to the resilience of an urban ecology.
Thirdly, the ethics of the system must be driven by communal wellbeing.
Finally, design “with” the city, not “for” the city must be done. In this context, community, civility, communication, connection, and commitment are five keystone practices which can create smart, sus- tainable, and compassionate city (Anderson, 2020).
Referring to dependence between concepts, contrary to Zheng et al.
(2019) stating that smart city is a guide for sustainable and resilient city (Zheng et al., 2019), Chui, Pablos, Lytras, and Vasant (2022) claims different relation. The resilience, and sustainable development are crucial elements to achieve the global smart city vision (Chui et al., 2022). In other words, resilience and sustainability are determinants for smart city. These two viewpoints are not so much mutually exclusive but rather confirm that the three concepts are co-related. For instance, sustainable urban development connection with urban resilience to climate change via intergenerational equity is proved by Wendling et al.
(2018).
Obviously, the three concept of sustainable, smart, and resilient city are interconnected and needed. A lot of efforts have been committed to the study of the uniqueness of the different concepts in theory, but ac- cording to Hatuka et al. (2018), in practice many cities tend to ignore differences and view the concepts just as a set of tools or prescriptive ideas for city management. The concepts of sustainable city, smart city, and resilient city does not operate independently, but they all constitute and contribute to the urbanization. Also, their meaning may change over time (Hatuka et al., 2018). Different city labels and their combination seek to capture and conceptualize key aspects of ongoing urban sus- tainability efforts but sustainable development remains the basic and primary concept. Closer examination reveals also that policy makers, planners and developers often use different terms interchangeably (de Jong et al., 2015). Based on the literature review we also conclude that the concepts are incomparable as to compare ideas, the same “denom- inator” is needed. These concepts are different, focusing on different issues, therefore, is it the main reason for this research recommendation and the justification supporting the concept of the concepts’ integration in the phenomenon of the Fundamental Power of the City.
2.3. Data and the data ecosystem
Data and data ecosystems are necessary to build sustainable, resil- ient, and smart cities which are transparent and citizen centered (Lne- nicka et al., 2022). Also Eicker, Weiler, Schumacher, and Braun (2020) claim that an integrated urban platform is the necessary software infrastructure for smart, sustainable, and resilient city planning, oper- ation and maintenance. Handling and analyzing large and heteroge- neous urban data sets from very different domains requires a special system (Eicker et al., 2020). The sciences of smart sustainable urbanism
are big data and technology sciences. Bibri (2019) stated that this data- intensive science supported by sustainability and urban sustainability can make cities more sustainable, resilient, efficient, and livable by making them more measurable, knowable, and tractable in terms of their operational functioning, management, planning, design, and development. Major streams of information research for creation of digitally enabled and climate-intelligent cities range from information systems and IT governance to Fintech applications.
Chui et al. (2022) claim that 2.5 quintillion bytes of data are generated every day and resilient Internet of Things forms the founda- tion of data collection, provides ground truth of information, and as a result, determines sustainable city. The incredible growth of primary data volumes and diversity have been playing a crucial role in man- agement and decision making. But according to authors, the successful technology has not yet been fully integrated into resilient and sustain- able development. Big data have been identified as a key enabler in the development of smart sustainable cities but understanding of different data sources management and application is limited (Zhang et al., 2022).
According to Ng, Xu, Yang, and Lu (2017), interoperable and reliable different infrastructure systems are required to realize the smart infra- structure concept for efficient smart city planning and to develop appropriate resilience and sustainable programs. To unlock the value of big infrastructure data for sustainable, smart, and resilient city planning, data management solution must be developed (Ng et al., 2017). Each system needs input data – variables, transformed into indicators and information for the decision making. However, all the concepts of sus- tainability, smartness, and resilience can be difficult to apply in practice due to its abstractness and lack of accepted measurement methodology – besides sustainable development measured by Sustainable Development Goals (SDGs). Determining how many changes a community or system can survive in relation to resilience, what the criteria for assessing city smartness and resilience will be very often subjective and difficult to define, also as problem of measurable and unmeasurable data.
2.4. Selected composite indices
Current trends and challenges relating urban sustainability assess- ment have proven that measuring and interpreting quality of life re- quires a complex analysis as not always what is measurable is important, and what is important – can be measured. Quality of life might be operationalized by public value which represents results and issues important for inhabitants (Alford & O’Flynn, 2009). But this might be a huge challenge as inhabitants are diversified stakeholders in terms of their interest, needs, power, legitimacy and therefore conflicts may arise. In this light, the idea of public and common value as a strategic city development aim might be unrealistic and even utopic (Osborne, 2010). Although thinking along metrics (indicators) has been indicated as a trap already over 80 years ago by a philosopher (Heidegger, 1962), economists try to measure development and look for a new metrics to help decision-making but above all, they try to change thinking about the components of quality of life as multidimensional phenomenon. In particular, Agenda 2030 with a set of 17 Sustainable Development Goals (SDGs) comprising 169 objectives has been operationalized by in- dicators to measure sustainable development. A standardized set of variables has been also developed by international standardization or- ganizations: International Organization for Standardization (ISO), and International Telecommunication Union (ITU). Standardized indicators may not take into account the specificities of individual entities, how- ever they allow consistent and objective measurement, and comparison of the analyzed categories. The standardization also contributes to building cooperation and exchange of information on the results ach- ieved with the obvious limitation that one-size-fits-all approach does not exist. The international standards for sustainable and smart cities include (Moustaka et al., 2021) norms: ISO 37120, ISO 37122, ISO 37123, ETSI TS 103463, ITU-T Y.4901/L.1601, ITU-T Y.4902/L.1602,
ITU-T Y.4903/L.1603. These norms are based on different sets from 30 to 104 variables (Huovila, Bosch, & Airaksinen, 2019). These interna- tional standards were developed as an indication of the action which should be taken for creating sustainable and smart city, however, cities often do not have adequate organizational and financial resources to implement standardization. Furthermore, neither SDG indicators, nor ISO or ITU norms provide synthetic information. They are informative but they are sets of single-variable indicators and describe single aspects of the development.
Many city assessment frameworks, indicators, indices have been developed in the last two decades. These studies have improved un- derstanding of the thematic focus of the concepts and enabled to oper- ationalize them (Quijano et al., 2022) but only composite indices (also named taxonomic or synthetic measures) provide multidimensional in- formation in one value. A properly constructed composite index is easy to interpret and refers to a specific phenomenon, creating an attractive tool for shaping economic policy in accordance with the postulate of creating simple information and diagnostic tools used in the process of implementation and monitoring city development strategies. Multidi- mensional approach is demanded and fulfilled by the composite index.
For instance, resilient city inherits the interweaving of different di- mensions of smart city and sustainable city. The lack of ability to insert the resilience strategy in rooted connections with sustainable and smart city and its transformation into one ecosystem that crosscuts different sectoral urban processes has been indicated as the greatest problem (Bruzzone et al., 2021).
Przybylowski, Kałaska, and Przybyłowski (2022) proposed sustain- able development indicators based on the above-mentioned ISO 37120 standard. They converted the standard into partial and total utility value, then grouped within social, economic, and environmental di- mensions to measure the level of urban quality of life. According to authors, this approach could support decision making towards safe, resilient, prosperous, inclusive, smart, and sustainable city – neverthe- less authors confirm challenge that refers to the objective and quanti- tatively accurate measurement of quality of life (Przybylowski et al., 2022).
A model to assess smart cities has been proposed by Abu-Rayash and Dincer (2021). It uses key parameters that reflect the condition of smart city domains including economy, environment, society, governance, energy, infrastructure, transportation, and pandemic resiliency. Based on its application in 20 cites, the authors claim that enhancing the smart energy index by 25 % results in doubling the smart economy index for all cities. At the same time, they ask about the relation between public participation and government effectiveness which are great indicators, with the economy, and find no answer. There are also indicators based on quantification of demand and energy sources, which according to the authors could contribute to prioritizing actions for CO2 mitigation strategies in urban areas (Eicker et al., 2020).
The framework for city development assessment may adapt compo- nents of the Business Model Canvas (BMC) to become smarter. The Smart City BMC (SC-BMC) proposed by Giourka et al. (2019) provides a practical framework that supports developing and communicating a more holistic and integrated view of a smart city business model. In particular, in the case of the SC-BMC, the analytical cost-benefit analysis can be implemented – although it might be controversial (Mouter, Annema, & van Wee, 2013). Also, the network of beneficiaries maps all the target users for whom value is created and whose needs are addressed through a smart city project. Among others, the beneficiaries include community, nonprofits, and research organizations (Giourka et al., 2019).
According to Quijano et al. (2022) measuring city progress is a key step to reach more resilient and smarter city. The authors state that there are many indicators and assessment procedures available, but the convergence in the definition of terms and application methodologies are missing which make their implementation complex. The evaluation framework which has been proposed within their research covers the
pillars of a smart and sustainable city. It defines the concepts and terms to guide implementation of the framework for any city. The research claims that a definition of measurement boundary must be formulated to prevent subjective interpretations (Quijano et al., 2022).
Referring to 2030 Agenda for Sustainable Development, Zheng et al.
(2019) provide a high-level analysis of global and regional metrics in accessing smart cities. Sharifi and Allam’s (2021) research proves that existing indicators are mainly related to information and communica- tion technologies, economy, and governance; in reference to resilience abilities, indicators focus mainly on planning abilities and less attention is given to recovery and adaptation, and indicators are not well-aligned with other important characteristics such as environmental dimension.
It can be concluded from the research that more efforts should be made to select the most suitable assessment frameworks or indicator sets for promoting resilient, smart, and sustainable communities (Sharifi &
Allam, 2021). Also, a paper by Wendling et al. (2018) provides the investigation of alignment between selected assessment schemes for nature-based solutions enhancing urban resilience in terms of water- energy-climate relationship, and the SDG indicator framework. Partic- ularly, they recommended integration of an ecosystem services with metrics, and inclusion of indicator metadata detailing standardized, scientifically-validated methods of data acquisition and calculation of metrics in order to facilitate widespread use (Wendling et al., 2018).
The strong demand for robust standardization to measure city per- formance and dynamics of cities’ transformation into smart and resilient is stated by Moustaka et al. (2021). In their research, earlier so-called
“cityDNA” framework, which was designed to detect the interrelations between the six smart city dimensions, is revised. In particular, the au- thors update the framework with smart city standard (ISO 37120:2018), along with an adaptive desktop to process urban data and visualize the city’s profile to facilitate decision-making. The outcomes show that cities should intensify formulation and exploitation of proper key per- formance indicators, along with a set of standards for cities, to enable individualization of indicators to reflect individual city’s attributes.
To sum up, a report by commercial company JLL indicates that there are currently more than 150 initiatives related to measuring and comparing the level of urban development (Kitchin, Lauriault, &
McArdle, 2015). Selecting case studies of frameworks is a challenge as a great number of performance measurement systems exist, not only in respect to sustainability assessment systems (Ahvenniemi, Huovila, Pinto-Sepp¨a, & Airaksinen, 2017; Sala, Ciuffo, & Nijkamp, 2015). It is also confirmed by Sojda (2020) claiming that complexity means that there is no transparent assessment system. The common issue is that the systems are hierarchical, facilitate the assessment of the city according to sub-areas, factors and indicators. Therefore, based on the literature review, selection of indices includes the most recognizable and popular indices which are used for creating rankings of cities around the world, but also locally. They include (Baran et al., 2022; Zheng et al., 2019):
IESE Cities in Motion, Global Livability Index, Green City Index, Smart City Index, Global Power City Index (GPCI), and include from 18 to 101 variables from all city’s dimension as Table 3 shows. It is worth to mention ARCADIS - locally developed indicator which has been also applied globally.
The ability to assess and compare the services provided or actions taken to improve the quality of life and well-being using other cities with composite indices improves and facilitates effective management (McCarney, 2015, p. 103). While individualized indicators offer virtu- ally unlimited possibilities for a tailored assessment method, they are of limited use and may require non-standard data. The unsolved challenge also refers to evaluation of non-quantifiable components of sustainable, smart, and resilient city, especially in the context of implementation and capturing qualitative factors.
3. Materials and methods
3.1. Fundamental power of the city - the phenomenon to be measured Different pace of development of different cities can be caused by different and by related factors, such as:
- social and economic potential, environmental conditions – i.e. areas of sustainable development,
- implementation of smart technological solutions and innovative methods of management – a core of the concept of smart city within smart city domains,
- factors improving resilience of city to changes –attributes of resilient city.
These factors are components of fundaments of a city, understood also as fundamental strength or power of the city. Therefore, the com- plex phenomenon which is city development can be defined as Funda- mental Power of the City. It can be operationalized (measured) via synthetic index determined by sustainable, smart, and resilient components.
The hybrid concept of city refers to components of sustainable, smart, and resilient city. A sustainable city develops according to the concept of sustainable development – although initially the concept functioned as a political category, it was soon incorporated into eco- nomic and social practice. Sustainable development means balance in the use, creation, and preservation of the natural, social, and economic resources. However, this resource management should also be smart as all resources are limited. Cities, thanks to social and human capital, can act wisely (smart) in the process of sustainable development. Therefore, smart sustainable development should be interpreted in terms of “inte- grated” ecological, social, and economic order, where decision-makers act “wisely” (smart), and manage limited resources within individual dimensions of the city, using the latest technologies (Wojewnik-Fili- pkowska, 2017). The third key concept which forms the fundamentals of a power of a city is urban resilience. Resilient city maintains and reaches the higher level of development or is able to at least return to the prior path of development, after social, economic or environmental shocks.
The conditions for the development of a resilient city are reached by creativity, which determines the ability to self-organize. Creativity is an intangible asset that enables cities to face economic challenges, envi- ronmental crisis, urban marginalization, poverty, and increased inequality. Ultimately, the power of the city is determined by the po- tential and integration of the resources of the city system – the “internal” integration of individual concepts separately and integration of all concepts together. These are the dimensions of a sustainable city to be integrated: socio-demographic, economic, environmental-spatial; di- mensions of a smart city: economy, people, governance, mobility, environment, and life; dimensions of a resilient city: social, economic, institutional, and infrastructural. The effect of this specific “synthesis” is Fundamental Power of City as presented in Fig. 3.
Contemporary strategic city management refers to the potential of the city and management that enables an appropriate response to the complex social, economic, and environmental challenges, and at the same time uses modern technology – in fact, it is a prerequisite for the implementation of the assumptions of a “resilient smart sustainable city”.
3.2. Economy based linear ordering
This section provides general presentation of the linear ordering.
First method was proposed by Z. Hellwig (in 1967–1968) and named
“Taxonomic measure of development” (Hellwig, 1967; Hellwig, 1968).
This study introduced the key terms: stimulants and dis-stimulants, pattern of development, and measure of development defined as a dis- tance of an object to the pattern of development. Hellwig’s idea initiated the development of linear ordering methods. These methods are aimed at differentiating the method for the normalization of variables, intro- ducing nominant variables, determining the pattern of development (comparative base) in a different way, applying various constructions of the composite measure, and applying fuzzy sets in the construction of the composite measure. The recent development of linear ordering method includes application of the concepts to interval symbolic data and inclusion of spatial dependencies (Walesiak, 2016). The general framework of linear ordering is presented in Fig. 4. The individual stages are described in detail in subsection that follow.
3.3. Practical framework for the case study
This section provides details of the linear ordering using Hellwig method. It is adopted to assess the Fundamental Power of selected cities along a practical research framework. Hellwig’s measure has a wide range of applications, including construction of synthetic variables in the process of econometric modeling or investigation of regional development. Phenomena such as level of economic development is not directly measurable. These phenomena are aggregates, with their values generated by directly measurable diagnostic variables. Aggregate Table 3
Selected urban indices.
No. Index (reference) No of
variables Dimensions (1) Sustainable development
Index (Barrera-Roldan, & ´ Saldı́var-Vald´es, A., 2002)
21 Economic indicators, social indicators, natural indicators (2) Ranking of Polish
Sustainable Cities ARCADIS (Arcadis, 2021)
45 Society, environment, economy
(3) European Smart Cities Ranking (Giffinger, Fertner, Kramar, Kalasek, & Pichler- Milanovi´c, 2007; Giffinger &
Gudrun, 2010)
64 Economy, people, governance, mobility, environment, living
(4) Smart City Index, (IMD World Competitiveness Center, 2021)
18 Health and safety, mobility, activity, opportunities (study and work), governance (5) Disaster Resilience
Indicators (Cutter, Burton, &
Emrich, 2010)
36 Social, economic, institutional, infrastructure, community capital (6) City Resilience Index (CRI) (
Arup, 2018) 52 Health and well-being,
economy and society, infrastructure and ecosystems, leadership and strategy
(7) Global Liveability Index ( Economist Intelligence Unit;, 2021b)
30 Stability, healthcare, culture and environment, education, infrastructure
(8) Green City Index (Economist
Intelligence Unit, 2021a) 30 CO2 emissions, energy consumption, construction infrastructure, land use, transport, water consumption, waste management, air quality, general approach to environmental policy (9) Global Power City Index
(GPCI) (Institute for Urban Strategies, 2021)
70 Economic, research and development, cultural interaction, quality of life, environmental, city accessibility (10) IESE Cities in Motion (IESE
Business School, 2021) 101 Human capital, social cohesion, economy, governance, environment, mobility and transport, urban planning, international reach, technologies
Source: based on (Wojewnik-Filipkowska, Gierusz, & Krauze-Ma´slankowska, 2021).
functions can have different analytic formulas. Realizations of the syn- thetic variable allow to rank multivariable objects (Bąk, 2016). The synthetic variable, i.e. Fundamental Power of the City Index, is however not just a tool that allows to assess potential of an object in relation to other objects. It also allows for an assessment of whether a given city is characterized by a stability of development, defined as positive change, and conforming to a path of development in the analyzed period. It is also a tool of comparative analysis – in comparison to development of other cities in the investigated group. At the same time, this is a starting point for strategic analysis and a tool for authorities and citizens in the process of decision making and monitoring the level of sustainability, smartness, and resilience of a city – separately and together as the Fundamental Power of the City Index. Results of the analysis form a diagnosis of a given city potential – they allow to indicate which areas are strong or weak, where a development or decline can be observed, and how the given city compares to others.
The practical framework is presented in Fig. 5 together with detailed research questions in Table 4. In this paper the following nomenclature was applied: “variable” refers to the original data based on which three synthetic “indicators” were constructed for the given concepts of
development: synthetic indicator for sustainable city, synthetic indica- tor for smart city, and synthetic indicator for resilient city. “Index” refers to Fundamental Power of City, and aggregates (combines) assessment of a city according to the concept of resilient smart sustainable city.
First, according to Step 1 (see Fig. 4) the complex phenomenon must be defined. It is Fundamental City Power which is determined by sus- tainability, smartness, and resilience of the city. Due to multiperspective analysis it is possible to observe trends and any disproportions in the level of socio-economic development. This allows to indicate cities which are leaders in terms of sustainability, smartness, and resilience but also from the perspective of Fundamental Power of the City.
In step 2 (Fig. 4), objects for the analysis are selected. The territory of Poland is divided into regions (voivodeships), counties and municipal- ities. Choice of objects is determined by the urbanization level, a feature common to all cities with county rights (66 cities). The urbanization level is reflected in the data on population growth, growth of population economically active outside of agriculture, state of infrastructure and individual character of the city. Those cities also form the strongest level of local government in terms of competencies and economy, as they combine two forms of authority: county and municipality. However, due Fig. 3. Components of Fundamental Power of City.
Source: based on (Wojewnik-Filipkowska, Gierusz, & Krauze-Ma´slankowska, 2021).
Fig. 4.The classic linear ordering process
to their influence on regional development and transparency of applied methodology and results presentation, the final choice of cities is limited to 18 voivodeship capital cities.
In step 3 (Fig. 4), choice of variables is made on the basis of avail- ability of data for 66 cities with counties rights. As a result, the meth- odology obtained can be applied to both small and big cities, however the analysis itself is finally conducted for 18 cities as explained above.
The variables selection is based on the relevant literature in reference to the sustainability, smartness, and resilience assessment presented and analyzed in the literature review (section 2.4). In particular, variables measuring sustainability of the city are based on the 17 Sustainable Development Goals; research conducted by Giffinger and Gudrun (2010) and Giffinger et al. (2007) is the main inspiration for smart city vari- ables; the set of variables for resilience of a city required review of several studies (Cutter et al., 2010; Drobniak, 2015; Hill, Wial, &
Wolman, 2008; Jha, Miner, & Santon-Geddes, 2013). Finally, for the purpose of research also the selected urban indexes were analyzed (Table 3). Choice of variables that comprise the synthetic indicators is also determined by formal requirements for quality of synthetic mea- sures. These requirements include (Cash et al., 2002):
- salience – variable must reflect the reality, there must be a direct or indirect relationship between the value of selected variable and the phenomenon observed, variable must be useful, appropriate, and helpful to the user (decision maker), in particular possible to use as a benchmark for formulation of strategic aims,
- credibility – refers to the use of trustworthy and complete statistical data, scientifically justified, appropriately aggregated, and normal- ized, allowing for repeatability of the research, at the same time guaranteeing adequacy of the description of similar phenomena, - legitimacy – refers to perception of the indicator, but also to the
method of construction and competency and independence of the researcher, which strengthens the meaning of projections.
Next, data for chosen criteria is collected from the Central Statistical Office (GUS, 2022) and National Electoral Commission (PKW, 2022).
After the initial collection of variables, variability and correlation be- tween variables is measured. Variables characterized by low variability (variability coefficient below 5 %) or strong correlation with other variables (Pearson’s coefficient above 0.8 or below − 0.8) are removed.
The decision as to which of the correlated variables should be removed is made based on merits. Other studies usually assume values between 0.5 and 0.9 for correlation coefficient threshold and 5 %–10 % for variation coefficient threshold (Gierusz-Matkowska, Wojewnik-Filipkowska, &
Krauze-Ma´slankowska, 2023). The general structure of 100 variables, together with areas and count of variables (after variables of low vari- ability or high correlation are removed) is shown in Fig. 6. Finally, 32 variables are taken under consideration for the purpose of sustainable Fig. 5. Framework of application of the linear ordering using Hellwig method to cities development measurement.
Table 4
Practical detailed research questions.
No. Practical research questions
(1) a) What are the variables that determine the level of sustainability, smartness, and resilience of cities?
b) Which of the variables are characterized by the highest and which by the lowest variability?
(2) Are individual cities on the path of stable development in respect to their sustainability, smartness, and resilience?
(3) a) What are the results of rankings according to synthetic indicators?
b) Which variables are crucial in case of leaders?
c) Is there a correlation between the results of individual cities in individual rankings?
(4) a) What is the result of ranking according to aggregated Index?
b) Which variables are crucial?
c) Are individual cities on the path of stable development with respect to the aggregated Index?
city indicator, 48 variables for smart city indicator, and 20 for resilient city indicator. As it is not suitable to indicate more or less important variables, all are given the same weight in the calculations.
In step 4 (Fig. 3) selected variables are identified as stimulants or dis- stimulants, and they are standardized in the step 5 according to the formula:
xij− xj
sj
where xij is a value of variable j for city i, xj is the mean for variable j and sj is the standard deviation for variable j. The full list of variables used with their descriptive statistics is given in the appendix. The descriptive statistics have been calculated for the last year of the analysis (2020).
Next, two hypothetical objects -the “pattern” and “antipattern” - are created. Pattern is assigned the best possible value for each variable, that is the maximum value in the dataset for stimulants and minimum value in the dataset for dis-stimulants. For antipattern the worst possible values are assigned, so the minimum value in the dataset for stimulants and maximum value in the dataset for dis-stimulants. The Euclidean distance between pattern and antipattern (d0) and Euclidean distance between pattern and each object (di0)is then calculated. Taxonomic measure is then obtained for each city using the formula (Balicki, 2013):
mi=1− di0
d0
This measure takes values between 0 and 1, with 1 meaning the object is the pattern, and 0 is the antipattern.
Aggregation (step 6) and ranking (step 7) are performed twice – as separate indicators and joint index. In other words, firstly, aggregated measure (composite measure) of sustainability, of smartness, and of resilience is calculated for each city (step 6) to enable ranking (step 7).
Secondly, after repetitive 20 variables are removed, the 80 variables representing sustainable, smart, and resilient city are aggregated to form the synthetic value of the Fundamental Power of the City Index (step 6) and cities are finally ranked (step 7).
4. Results and discussion
In reference to the first set of practical research questions (1a, 1b), the detailed values of the variables for sustainable, smart, and resilient city are presented in the Appendix. The summary of the most and the least volatile variables is presented in the Table 5.
Given the range and nature of the variables, it is not possible to indicate less and more significant variables, therefore, in a further study,
equal weights are assumed for all variables as stated above. Analysis in accordance with the framework, allows to determine the rankings for sustainable cities, smart cities, and resilient cities. These refer to the practical research question 2 and 3a and are presented in tables below.
The tables are accompanied by comments over the most crucial vari- ables for the two leaders of last year ranking (2020) which answers the practical research question 3b. Table 6 presents ranking of the sustain- able cities.
Warszawa in its strategy focuses, among others, on strengthening local potential and development of human resources. Such actions are reflected in population, average monthly gross earnings, number of dwellings, and also current expenditure on municipal engineering and environmental protection. It means that Warszawa attracts in economic, social, and environmental terms. The second city in the sustainable cities ranking is Rzesz´ow. It achieves the best results in the following in- dicators: net internal migration, children in kindergartens and pupils in primary schools, pupils in general education high schools, out-patient departments, new residential buildings, length of district and communal unsurfaced roads, total subvention. The results shows that Rzeszow develops society, to a lesser extent economy, but there are no ´ Fig. 6.Summary of variables sets in the study.
Table 5
Variables with the highest and the lowest variability in the study (2020).
Concept The highest variability
(dimension) The lowest variability
(dimension) Sustainable
city - net internal migration per 1000 population (society) - year to year change in sold
production of industry per inhabitant (economy)
- children in kindergartens and pupils in primary schools per 1000 population (society) - dwellings connected to gas
network per number of dwellings (economy) Smart city - emission of air pollutants
(gases) from entities harmful to the environment per 1000 population (t/year) (environment) - visitors of museums and
branches per 10,000 population (life)
- net primary education enrolment rate (%) (people) - proportion of population using
sewage system (%) (life)
Resilient city - year on year change in own revenue derived from a share in revenue from corporate income taxes per population (economy)
- year on year change in population (%) (society)
- net primary education enrolment rate (%) (society) - dwellings per 1000 population
(infrastructure)
Source: own work based on data from (GUS, 2022) and (PKW, 2022).
