1 Introduction

This bibliometric paper intends to decipher the world research scenario concerning the shift in approach towards incorporating cultural dynamics into the contemporary urban planning process. This study is conducted against the backdrop of the burgeoning concept of ‘cultural planning’, which is perceived as a way to build ‘creative cities’ (Landry, 2012) by leveraging the creative capital of cities (Florida & Adler, 2020) to strengthen the local economy.

The paper is structured as follows: The first section deals with the primary literature on ‘cultural dynamics’, culture, and ‘Urban Cultural Dynamics’. The brief methodology explains the data collection, screening and the software used. The following section comprises data analysis through text-mining analytical tools yielding hot topics, core papers, top journals, influential countries, and institutions, culminating in identifying the hot spots and trends. The conclusion section discusses the significance and shift in the approach towards cultural dynamics in urban planning.

The term ‘Cultural Dynamics’ is often used in the domain of Anthropology, Psychology, Archaeology, and Sociology (Beugelsdijk & Welzel, 2018; Euler et al., 1979; Flache & Macy, 2011; Kashima et al., 2019). The cultural dynamics is concerned with the formation, maintenance and transformation of culture over time (Kashima, 2016). Culture is considered a set of available information that is transmitted non-genetically among a group of people (Kashima et al., 2018). Cultural information has many dimensions; it includes ideas, customs, rituals, and social behavioural norms, etc. Culture is dynamic as it varies from place to place and transforms over time in different social settings. This dynamic nature of culture has an impact on the socio-economic and physical functions of cities, which significantly influences the development and function of a city.

The domain of knowledge about the culture of cities is well known, and urban planning scholars have often discussed the culture; Lewis Mumford argued that the “City is the maximum concentration of power and culture of a community” (Mumford, 1939). The contemporary discourse about the inclusion of cultural dynamics in urban planning can be attributed to several factors, such as globalization, ever-increasing urbanization, and changes in urban demography due to migration (Hansen et al., 2001; Kiruthiga & Thirumaran, 2019; Viki & Al-Harithy, 2019; Zhong et al., 2013), changing patterns of cultural consumption (Rodriguez-Puello & Iturra, 2022), the influence of culture on the local economy (Gibson, 2012; Lazzeretti et al., 2017; Scott, 1997), and so forth. People with different ethnicities, languages, religions, races, beliefs, and values are moving to cities away from their native places. These exogenous factors would bring new cultural transactions (Ayame Hiraide, 2022), causing urban hybrid cultures.

In the previous century, urban planning was led by capitalistic development (Dantzler et al., 2022; Grubbauer & Camprag, 2019; Havel, 2022; Jiang & Waley, 2022; Manevitz, 2022; Scott, 2007; Speake, 2017). In recent decades, globalisation and migration have driven urban growth, altering the demographic composition of cities (Hansen et al., 2001; Neumann, 2018; Speelman et al., 2021; Zhong et al., 2013). According to the UN ‘World Urbanization Prospects’ 2018, 55% of the world's population live in urban areas. The world's urban population surpassed rural regions in 2007 (United Nations, 2018), indicating the increased migration from rural to urban areas in recent decades. The influx of migrants to cities would bring various socio-cultural challenges (Borén & Young, 2013; Krifors, 2022) along with opportunities. New research topics on cultural dynamics have emerged in response to this cultural convergence and transformation.

Urban planning scholars have proposed a few concepts and strategies that consider culture as one of the driving factors of the urban economy, emphasizing culture’s economic dividends. Among these concepts, local consumption theory (Lin, 2018; Rodriguez-Puello & Iturra, 2022) argues that the local culture influences the characteristics of intra-urban economic activity, concomitantly; economic activity becomes an element of urban cultural dynamics (Scott, 1997), bringing the convergence of economy and culture. Some studies refer to the cultural economy as creative economy (Grodach, 2013; Pratt & Hutton, 2013; Vanolo, 2013), diverging from mere consumption theory to the idea of creative capital as a significant cultural asset contributing to the development of a city. Florida (Florida, 2002) discussed the influence of creative people's choices on the local economy. Charles Landry’s creative city theories highlight cultural significance (Landry, 2008) in fostering creative cities by putting culture at the centre of urban development policies. Other theories, such as city branding (Cudny et al., 2020; Dinardi, 2017; Dinnie, 2011; Vanolo, 2008), bank on selling a city's cultural and creative uniqueness by attracting investment, business, and tourists. This paper descriptively investigates the latest research scenario about incorporating various cultural components into urban planning.

Culture is a multidimensional subject. Culture refers to distinctive ideas, customs, social behaviour, products, or a way of life of a particular nation, society, or people (Culture, n, Oxford English Dictionary, 1860), with values and beliefs (Culture, n, Merriam-Webster, 2024). The cultural elements of an urban area can be multiple, spanning diverse sectors of urban development. The cultural identity of a place is determined by factors such as values (Huang & van Weesep, 2021), beliefs, traditions, social sense (H. Chen & Tao, 2017), art (Andron, 2018; Symons, 2018), gastronomy (Leng & Badarulzaman, 2014; Vogel et al., 2022), history (Buckley & Graves, 2016), heritage (Coombes & Viles, 2021; Mubaideen & Al Kurdi, 2017), recreation spaces (Marušić et al., 2019), geography and natural environment (Ferretti & Comino, 2015; Rodwell, 2018b) such as green spaces (Danilina et al., 2021; Guenat et al., 2021; Kabisch & Haase, 2014), water resources (Kostopoulou, 2013; Levin-Keitel, 2014), socio-economic status (Gonzalez-Garcia et al., 2018; Sepe, 2014), politics (Grodach, 2012; Røe, 2014), diversity (Koster, 2020) among the population etc. These elements encapsulate the essence of culture via distinctiveness, activities, and cognitive experiences (Jang & Kim, 2019), establishing a city's unique identity.

The aforementioned cultural elements have been the major driving factors in a city’s attraction and development. For example, in Rome, Italy, tourism is driven by its well-restored and well-marketed heritage monuments (Capuano, 2022). Rome thrives on its ancient glory. Barcelona, in Spain, is a different success story of urban cultural regeneration. Since the 1980s, Barcelona City Council has adopted a distinctive urban planning policy in which culture has played a strategic role (Rius-Ulldemolins & Klein, 2020). In the Asia region, Shenzhen, Singapore, and a few others are listed in the UNESCO Creative Cities Network in the design category. Shenzhen was an ordinary town till 1980; after that, it was selected as the first Special Economic Zone in China, transforming Shenzhen into a giant design city. In the year 2015, Shenzhen had 6000 design firms, with an output of 1.5 billion USD, which has been a beacon of China’s economic success (UNESCO, 2024). In Hanover, Germany, the music industry is a prominent part of the city’s vibrant culture. Hanover is where the world’s first music cassette was produced, and the first music Compact Disc (CD) was pressed. Likewise, ‘Cannes’ city name is synonymous with the Film industry. Milan, Edinburgh, and Dublin are associated with literature, and San Antonio and Alba are associated with the culture of gastronomy. York City in the UK, Lyon in France, and Gwangju in China are identified with the media industry (UNESCO, 2024).

1.1 Urban system

A system functions with the interaction of several subsystems. All the subsystems of the system are interlinked and interdependent to each other, forming a system. Even if one subsystem is defunct or partly functions or functions with a higher degree (taking a lead role), its effects can be visualised in the entire system over time. Sometimes, the system may not function at all, while in some cases, the system may function, but with many disturbances, the smooth functioning of the system may be paralysed. This ‘system concept’ is employed for developing an urban system, where the urban area is considered a system (Devadas & Kumar, 2007) and is presented in Fig.1a.

Fig.1a
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(Source: Authors). Social subsystem (Source: Authors)

Urban System and Social Subsystem. Fig 1b. ‘Culture’ as a subsystem of Urban

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Culture is the function of the population, and cultural attributes such as faith, beliefs, customs, rituals, religion, behaviour, tradition, aspirations, attitude, food, fashion, public realm, and art forms function together within the urban system. The functions of culture are similar to the functions of an urban system. The cultural attributes mentioned above form a cultural subsystem and function as a whole, as presented in Fig.1b. Here, the culture is a subsystem of the social subsystem of the urban system, and it is a dynamic system; hence, the cultural subsystem is an integral part of the dynamic urban system.

Culture is a dynamic entity; as it is said, it evolves and transforms over time. Similarly, in an urban system, urban culture is purely a dynamic entity that transforms over time. Most cultures, when they come in contact with other cultures, tend to exchange ideas, knowledge, and practices, thus adapting to different living environments. Globalisation, liberalisation of the economy, migration patterns, and power politics also impact the culture of a city due to mass movements leading to cultural transactions and the assimilation of new cultures. Thus, cultural dynamics impact the social life of the urban system over a period, and urban culture becomes a dynamic entity, hence the term “Urban Cultural Dynamics”.

Recently, researchers have attempted to establish the significance of cultural dynamic factors in urban development through different cross-disciplinary topics, such as tourism, ecotourism, cultural tourism, and heritage tourism (Arnaiz-Schmitz et al., 2021; Bhowmik, 2021; Haigh, 2020), cultural economy, the creative economy and education (Comunian et al., 2015; Gibson, 2012; Lin, 2018), ethnography (Koster, 2020), migration dynamics (Borén & Young, 2013), heritage in spatial planning (Janssen et al., 2014; Swensen, 2020), intangible heritage (Ross, 2017), cultural and creative city policies (Adams, 2005; Anttiroiko, 2014; Bodirsky, 2012; Boren & Young, 2021; Henderson et al., 2020; Ortegel, 2017; Trip & Romein, 2014), and city branding (Rabbiosi, 2015; Zhao, 2015).

In continuation to the aforementioned topics, scholars have investigated urban culture with a focus on sustainable urban development, environmental sustainability (Betlej & Kačerauskas, 2021; Blejer & Moya, 2010), ecology, urban landscape, urban forestry, green spaces (Charli-Joseph et al., 2018; J. Chen et al., 2021; Jaligot et al., 2019), cultural ecosystem services (La Rosa et al., 2016; Vejre et al., 2010), urban redevelopment and revitalization (Darchen, 2013; Hashim et al., 2017; Wang & Aoki, 2019), protection of natural and cultural heritage (Ferretti & Comino, 2015; Pena-Alonso et al., 2018; Skrede & Berg, 2019), sustainable tourism (Grah et al., 2020; Xie et al., 2021), the community participation in planning (Cahantimur & Ozturk, 2021; Della Spina, 2019; Prajnawrdhi et al., 2015).

In this bibliometric investigation, the different cultural components and topics mentioned are clubbed together under the umbrella of Urban Cultural Dynamics (UCD), and these various cultural components have been analysed through an urban planning lens since the existing literature lacks a comprehensive analysis of the research scenario on Cultural Dynamics in urban planning. In this study, the published peer-reviewed journal articles touching upon the various cultural components are selected through a double screening process for further analysis. The methodology for the selection of articles is discussed further.

The bibliometric analysis attempts to answer the following questions related to UCD topics. 1) which are the major countries and institutes involved in the primary research? 2) Which are the core papers and most influential journals? 3) What are the research topics and hot spots? 4) What is the scope for global research cooperation on this topic?

2 Methodology

Bibliometrics is a method used to analyse the evolution, trends, hotspots and future directions of one or more research fields (Godin, 2006) through the examination of available published literature. In this investigation, the data used for bibliometric analysis is obtained from Web of Science core collection. The analytical tools such as VOS viewer, Biblioshiny, KNIME data analyser, WordStat and Web of Science analytics (WoS) are used to identify and analyse the hotspots, hot topics, hot keywords, core papers, influential journal sources and authors, top countries, and influential institutions in this research field based on different metrics, such as number of publications, total citations, average citations, average publication year, total link strength, and journal influence score as listed in Fig. 2.

Fig. 2
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Methodology for the bibliometric analysis

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2.1 Collection of data

The data was collected from the Web of Science (WoS) database through institutional access. The period for collecting data was set from 1965 to 2022 in the WoS. The search uses keywords, Boolean operators, parenthesis, and a set of queries, and the keywords were searched for in the title, abstract, author keywords, and Keywords Plus in WoS. As discussed previously, urban culture is a dynamic entity since it evolves and transforms over a period in different dimensions. In this subject, a good number of researchers have published peer-reviewed articles; having this knowledge in mind, the authors attempted to pursue an investigation. Initially, the authors collected some papers in this particular field of learning and reviewed them. During this review, it was observed that most of the papers were focused on heritage, urban culture and other dynamic elements of culture. Observing these frequently co-occurring keywords, the following keywords, such as Urban, Planning, Dynamics, Heritage, Culture and Urban Cultural Dynamics, were used to search the articles. Further, these five search keywords have associations and are interlinked, thus forming the skeleton of “Urban Cultural Dynamics”. The functions of these search keywords in ‘urban cultural dynamics’ are symbolically represented in Fig. 3.

Fig. 3
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(Source: Authors)

Symbolic interrelation between the major search keywords

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In the present investigation, a total of 2678 research articles were observed in the WoS database search. These papers are segregated into six segments based on the different combinations of search strings such as cultur*, perspectiv*, urban, plan*, heritag*, "cultural planning", heritage, dynamics, “urban cultural dynamics” and “cultural dynamics”, this search resulted in 387, 465, 6, 465, 829, 0, 526 numbers of papers respectively and are presented in the Table 1. These 2678 papers have been analyzed thoroughly to exclude the duplicates and unrelated papers to the field of Urban Cultural Dynamics (UCD) in Planning. Further, the most important papers in this particular field of learning were identified, and 191 papers were found to be closely associated with the UCD research. Therefore, these 191 papers have been used further for the detailed bibliometric analysis. The search was limited to English-language and peer-reviewed published articles from the WoS core collection. (Supplementary data-https://doi.org/10.17632/fy774w7wsf.1).

Table 1 Search strings used in WoS with their results
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2.2 Software tools used

1) VOSviewer: It is an open-source software tool for data analysis. It is used to analyse sources, authors, and research cooperation of countries and institutions based on number of citations, co-citation, bibliographic coupling, and co-authorship (van Eck & Waltman, 2014). VOS viewer provides network and overlay visualisations through data mining. 2) Bibliometrix Biblioshiny: It is an open-source tool programmed in R to facilitate integration with other statistical and graphical packages (Aria & Cuccurullo, 2017). Biblioshiny is used to obtain citation networks and analysis of influential authors, countries, and affiliations. 3) KNIME: This open-source software is used for data mining that runs across words, images, simple numbers, and networks to analyse the topics (Andisa & Kilian, 2017). KNIME interface is convenient for non-coders to use for text mining through drag and drop operation using the elbow method. The KNIME has topic extraction function, which enables data import in text, MS Excel, or image format. The imported data is pre-processed, tagged, and filtered through the topic-extractor node to get topic clusters. 4) WordStat (trial version 9.0.6): It is a text mining and content analysis software. It provides content and sentiment analysis through data mining from various databases, including websites and social media (Davi et al., 2005). 5)Web of Science: Data is collected from WoS core collection. WoS analytics is used for primary data segregation and citation analysis.

3 Data analysis

The selected data set covers the years from 2002 to 2022, comprising 89 sources, 528 authors, and 39 single-authored docs, with an average of 2.92 coauthors per document and an international co-authorship rate of 24.08%. The Annual growth rate of publications is 7.19%. The average age of the papers is 4.02. Total citations are 10300. The average citation per document is 11.29. The results showed an exponential growth in the number of publications and citations from 2015 to 2021 (Fig. 4). The highest number of publications is from Italy (42), and the lowest is one from 18 other countries, as shown in Table 2. The remaining countries have publications ranging from 2 to 26.

Fig. 4
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Citations versus publications from 2002 to 2021 (Obtained in WoS analytics)

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Table 2 Country’s TP, TC and TLS (Obtained in VOS viewer)
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3.1 Country and research areas analysis

He research areas are categorised into different labels in the WoS core collection. The top ten countries are obtained for interpretation based on the number of publications in the different research areas. Italy has 32 publications, followed by the People's Republic of China (26), Spain (18), United Kingdom (16), Turkey (13), the USA (10), Poland (9), Germany, and Norway (7 each), Austria (6). India and Serbia have six articles each. In Fig. 5, It is observed that Italy is spearheading the research on UCD topics.

Fig. 5
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Country production over time (Obtained in Biblioshiny)

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Quantity and quality of research depict the influence of a particular country in a research field. The number of citations of a paper adds weightage to authors, their institutions and countries. Italy has the highest total of 398 citations from 32 papers, followed by Germany with 227 citations, and the People’s Republic of China has 159 citations from 26 publications. The following countries scored above 100 citations: Austria (101), Chile (107), United Kingdom (108), Poland (112), Spain (123). Notably, Germany has 227 citations from only seven publications, indicating the higher impact of the papers. The remaining countries are divided into two groups based on the number of citations, as ‘<50’ and ‘<100>50’, irrespective of the number of publications, as the number of publications ranged between 1 and 13. Forty-two countries have less than fifty citations, with Turkey having 42 citations from 13 publications. Meanwhile, India has 76 citations from six publications. There are five countries, Bosnia, Brazil, Scotland, Singapore, and South Korea, with zero citations.

The publications of each country are categorised under multiple research areas, as per WoS core collection (Table 3), which depicts the interdisciplinary nature of research in UCD topics. The research area analysis shows that, China (17), Italy (16), the United Kingdom (10), and Poland (9) have emphasised the research on Environmental Sciences and Ecology topics of UCD. Spain and the Republic of China have at least one publication in all areas. Italy and the United Kingdom do not have publications on Arts-humanities and Architecture topics related to UCD. Poland has focused on Environmental Sciences, Ecology, Science and Technologies, whereas Austria has covered urban studies topics in addition to Poland’s topic. It can be stated that scholars from these countries have investigated the culture from the perspective of Environment and Ecology for the sustainable development of urban areas.

Table 3 Research area distribution of papers from the top ten countries. (WoS classification)
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3.2 Country network and cooperation analysis

In the VOSviewer country network visualization, countries with more publications are represented by proportionately larger circles, and each cluster has a different colour, as in Fig. 6. The overlay visualization presents the country research cooperation network based on the number of publications in collaboration overlaid with the average citation weightage. The country cooperation network is based on the number of co-authored papers. In the VOSviewer cooperation network map (Fig. 7), the relative size of the circle changes with the TLS, the thicker connecting line depicts higher collaboration, and the colour gradient scale shows average citations.

Fig. 6
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Network visualisation of the country’s total publications, and links

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Fig. 7
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Overlay visualisation of the country’s total link strength and average citations

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The overlay of TLS and AC of countries provided 58 countries in 19 clusters with 114 links and a link strength of 124. The United Kingdom, having a TLS of 23, is the leading link partner with 20 countries, followed by Italy (18), Estonia (13), Germany (13), Slovakia (13), the People’s Republic of China (12), Spain (12) have led the cooperation in this research area. It is observed that the United Kingdom's major research cooperation is with European countries such as Italy, Germany, Spain, and Estonia. In recent years (2018-2020), Italy has partnered with Poland, New Zealand, Cyprus, Austria, and Portugal. Germany, having the second-highest number of citations (227) with a total link strength of 13, is majorly linked with Poland, Slovakia, Hungary, the United Kingdom, Spain, and Italy. China is linked with Italy, New Zealand, France, Malaysia, and Belgium.

Major research cooperation is observed among European countries. A total of 35 countries are in the cooperation network, while 13 countries had no research linkage with others. In the VOSviewer cooperation network map, Italy is placed at the centre of the map, linking different continents. It can be said that based on the TP, AC and TLS metrics, The United Kingdom, Italy, China, Spain, Germany, and Austria are the top influential countries in UCD research.

3.3 Institutions and cooperation analysis

The Institutions with significant influence are obtained based on the number of publications and citations. Among the 289 institutions in the data set, 253 have only one publication, 27 have two, and Four institutes have three publications each. The Polytechnic University of Milan, The Norwegian Institute for Cultural Heritage Research, and Southeast University have the highest of five publications each. VOSviewer co-authorship network visualization generated the clusters of linked institutions, revealing 70 institutes with individual papers on UCD topics without linkage with other organizations.

In the co-authorship network, top three clusters consist of ten institutions each and are represented by red, green, and blue circles, respectively (Fig.8). The first cluster has the Estonian University of Life Sciences, the Forest Policy Research Network of European Forest Institute, Istanbul Technical University, the Latvia University of Life Sciences and Technologies, the Slovak University of Technology Bratislava, the University of Aegean, the University of Algarve, University of Belgrade, University of Natural Resources and Applied Life Sciences Vienna, Vytautas Magnus University. The Estonian University of Life Sciences, with the highest TLS, has collaborations with 16 institutions.

Fig.8
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Co-authorship network of institutions

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The University of Basilicata leads the second cluster with six links, consisting of ENEL-SpA Italy, ENEA Italy, the Italian National Research Council, National Authority for Remote Sensing and Space Sciences-NARSS of Egypt, National Research Council Italy-CNR-IMAA, Qatar University, Technologies for Earth Observation and Natural Risks TeRN Consortium at the University of Basilicata, Sapienza University Rome.

The third cluster consists of the Bu-Ali Sina University of Iran, J Selye University of Slovakia, Obuda University of Hungary, Opole University of Technology, Oxford Brookes University, Technical University of Dresden, Thuringian Institute of Sustainability and Climate Protection Germany, Autonomous University of Chile, University of Catania, Polytechnic University of Madrid. The University of Dresden is prominent in the cooperation network with nine links. The fourth and fifth clusters consist of nine institutions, each represented by green and purple circles, respectively, with the University of Barcelona in the centre and the Southeast University of China having eight links. The sixth cluster comprises eight institutions, with the Chinese Academy of Sciences and the University of Hong Kong having six cooperation linkages.

The overlay of total citation and average citation of institutions provides the citation strength in the institutional network (Fig. 9). The colour gradient scale depicts an institute's average citations, and the circle's size varies with the total citations. The top five universities with high total citations in the previous five years are the Technical University of Dresden (103 citations) and the Technical University of Munich (101 citations) from two publications. The remaining three universities, Opole University of Technology, the Autonomous University of Chile, and the University of Catania, have 97 citations, each from a single publication. These institutes with high-impact research on UCD topics can be termed top institutes in UCD research.

Fig. 9
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Overlay of total citation and average citation of Institutions

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3.4 High-impact journals and core papers

3.4.1 Journal analysis

Journal analysis helps in finding out the high-impact source and their influence on a particular research area. There is a total of 89 journals in the data set. The highest number of papers are from Journal Sustainability (42), followed by the Journal of Cultural Heritage (9), Historic Environment: Policy and Practice (8), Cities and Land Use Policy (7 each), Urban Forestry and Urban Greening Journal (5) and European Planning Studies, Frontiers of Architectural Research, Landscape and Urban Planning, Tourism Geographies (4 each). In the order of highest total citations, the journal Sustainability stands first with 226 citations, followed by the Journal of Cultural Heritage (163), Cities (89), Landscape and Urban Planning (81), Tourism Geographies (56), Historic Environment Policy and Practice (53), Land Use Policy (24), ‘Urban Forestry and Urban Greening’ (18) (Table 4).

Table 4 Key journals with most articles on CUD topics
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The average citations (AC) and the average publication year (APY) help determine the impact factor and influence of journals. The Journal Landscape and Urban Planning has the highest AC (20.25) of 4 publications, with the APY 2011.75 indicating the journal had a high impact but lacks recent publications on UCD topics. In contrast, the Journal Sustainability has the highest number of documents (42) and total citations (226) with APY 2019.16 and the AC of 5.38, positioning the journal at a lower position of influence due to lower AC than other journals. The Journal Cultural Heritage has the second highest number of papers (9) with a total citation of 163 and a higher AC of 18.11, but the APY is 2016.55, indicating fewer publications in the past four years. Journal Tourism Geographies has the third-highest AC (14) with an APY of 2018.25. If the average citation index (AC) alone is considered, the journals; ‘Landscape and Urban Planning’, ‘Journal of Cultural Heritage’, and ‘Tourism Geographies' would be the top influential journals.

The method of identifying the most influential journals in a particular research area based on average citation index (AC) and journal impact factor is contested by various scholars (Falagas et al., 2008; Haupt, 2005; Larivière & Sugimoto, 2019; Yu et al., 2010). Some journals with higher AC have APY falling back to more than five years in the data set. In this context, it was deemed necessary to consider the average publication year (APY) to assess the consistently influential journals in UCD research. The Analytical Hierarchy Method (AHP) advocated by Saaty (Saaty, 1987) was employed to find the most influential journals in recent years based on three parameters: number of publications, APY and AC. The steps involved in assessing the most influential journals through the AHP method are discussed in the following paragraphs.

Three parameters, Number of Documents, APY, and AC, each with a weightage of 3, 5, and 7, respectively, were considered in the decision pairwise comparison matrix to assess the most influential journals. The least weightage is assigned to the parameter, ‘the number of documents’ of a journal. The decision matrix is obtained through pairwise comparison as represented below:

$$\mathbf{A}=\left|\begin{array}{ccc}1& {a}_{12}& {a}_{1n}\\ 1/{a}_{12}& 1 & {a}_{2n}\\ {1/a}_{1n}& 1/{a}_{2n}& 1\end{array}\right|$$

Each parameter/criterion i is compared to each parameter/criterion j, where the upper triangular matrix and lower triangular matrix are reciprocals of each other. In the next step, the normalized matrix is obtained by the formula 1,

\({X}_{ij}={a}_{ij}/{\sum }_{i=1}^{n}{a}_{ij}[i,j=\text{1,2},3\dots ..n]\)----------- (1)

After getting the normalized matrix, parameter weightage is obtained by calculating the quotient between the sum of scores of all the parameters and the number of parameters, as represented below:

\({w}_{ij}={\sum }_{j=1}^{n} {X}_{ij}/n [i,j=\text{1,2},3\dots ..n]\)-----------(2)

Where n = number of parameters

The consistency of the pairwise comparison is checked to assess the reliability of the judgments. The consistency ratio (CR) indicates the reliability of judgments. CR is a quotient between the consistency index (CI) and random index (RI), as represented in equation (3). Random Index (RI) varies with the number of parameters (Saaty, 1987). If CR is less than 0.1, the judgments are perceived as reliable and consistent.

\(\text{CR }=\text{ CI}/\text{RI}\) -------------- (3)

Where,

\(CI=\frac{\lambda max-n}{n-1}\) ---------------(4)

(n = the number of parameters used.)

A weighted sum vector is obtained by multiplying a pairwise matrix with vector weights. Then, it is divided by criterion weight to get the consistency vector. The average of the consistency vector is the principal eigenvector value \({\uplambda }_{\text{max}}\) (Table 5).

Table 5 Pairwise Comparison Matrix (Compiled by Author)
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The Journal Influence Score (JIS) of all the top journals are listed in Table 6. Here, JIS is the sum of weighted averages of normalised APY, AC and TP values. The Journal Landscape and Urban Planning has a JIS of 0.934, closely followed by the Journal of Cultural Heritage with a JIS of 0.874, Tourism Geographies is in third position with a JIS of 0.734, Cities Journal got a score of 0.698, and Habitat International has JIS of 0.679. It can be inferred that these are the top five journals that have consistently influenced UCD research. Most of the journals in the data set are open-access (OA) type, reflecting the author’s preference for journals, possibly due to time factors and the convenience of the OA type. It is essential to mention that despite some concessions, top OA journals' high article processing charge (APC) may not be affordable for researchers from developing countries.

Table 6 Journal Influence Score in UCD research. (Compiled by Authors)
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3.4.2 Core papers and citation networks

The citation network analysis provides insight into the evolution of a research field and the knowledge inheritance over a period. It also helps identify core papers with a high impact on a research area. Bibliometrix Biblioshiny is used for citation analysis. This analytical tool builds a citation network through historiography based on Local Citations (LC). Historiography lays out the knowledge inheritance through linked cited references and are represented by the corresponding author's name along with the year of publication (Fig. 10). For Example, In this data set, the initial year of a local citation for the paper by Tavemor (Tavemor, 2007) is 2007, which is cited in 2020 by Grah (Grah b, et al., 2020). Considering these two papers, ‘Grah et al, 2020’ is related to sustainable urban tourism development, and ‘Tavemor 2007’ is about visual and cultural aesthetics. It is evident that the approach towards culture and heritage in urban planning shifted from heritage conservation and tourism-related research in 2007 to sustainable urban development in 2020. The spectrograph revealed the oldest reference in the data set, which dates back to 1779 (Fig. 11).

Fig. 10
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(Source:Biblioshiny)

Historiograph

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Fig. 11
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(Source: Biblioshiny)

Spectrograph of references

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The influential core papers are identified based on the number of citations and listed in Table 7. Among these, Papers No.1, 2 and 4 discuss the ‘cultural ecosystem services’ topics in urban planning, emphasising sustainable development of cities. Papers No. 6, 9 and 10 focus on urban green spaces. Papers No. 6, 9, and 10 have an APY of 2014.1, whereas papers No. 1, 2 and 4 have an APY of 2015.5; Through these papers, it could be inferred that the idea of ‘cultural ecosystem services’ research is a result of the previous studies on ‘urban green spaces’ and ‘urban landscapes’. Paper. No. 6, published in the year 2008, is referred by Paper No. 3, published in the year 2020; paper No. 6 discusses cultural heritage management in a suburban context, whereas Paper No.3 discusses circular economy strategies and reducing environmental impact. The shift of the study from management to environmental impact hance sustainability angle is evident in these two papers. The Paper. No.5. discusses the application of multicriteria decision-making methods in the study of built heritage. Similarly, papers number 2 and 7 deal with the application of the latest technology, such as GIS and mobile LiDAR systems, in the study of cultural heritage. Paper No.8. argues that the Geo-sites in Rome are a part of cultural heritage, and tourists are referred to as Geo-tourists. Seven out of the top ten papers have focused on the sustainability aspects of UCD, exploring the direct or indirect relationship of urban culture with green spaces, water bodies, natural ecosystems, urban landscapes, natural heritage and the standard of living. The other two papers, No. 5 and No.7, discuss urban regeneration policy mechanisms and technologies. The citation network analysis revealed the multidisciplinary nature of research papers, reflecting the broader dimension of UCD topics.

Table 7 Core papers in the citation network
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3.5 Hot topics

3.5.1 Keyword analysis

Keywords indicate the focus of a particular paper. Keyword analysis is done to find hot keywords, trending subjects and hot spots. The co-occurrence network provides interconnected keyword clusters highlighting the cross-disciplinary research areas and emerging hotspots. Each keyword cluster has a different colour (Fig. 12).

Fig. 12
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Co-occurrence network of hot keywords

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The VOSviewer generated 60 highly co-occurred keywords in four clusters out of 1230, with a threshold set at 4 (Table 8). The first cluster consists of 21 keywords: adaptive, reuse, Architecture, built heritage, cities, city, community, cultural-heritage, entrepreneurialism, gentrification, governance, heritage conservation, historic preservation, policy, politics, redevelopment, regeneration, tourism, urban, urban heritage, urban renewal, urbanization. The second cluster consists of 18 keywords: Biodiversity, China, conservation, conservation planning, cultural landscape, culture, diversity, heritage, heritage management, heritage values, historic urban landscape, landscapes, management, perception, place, protection, urban regeneration, and values.

Table 8 Hot topic analysis based on keywords
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The third cluster has 11 keywords: benefits, cultural ecosystem services, framework, health Impact, indicators, landscape, participation, perceptions, recreation, and valuation. The smallest fourth cluster has ten keywords: area, cultural heritage, design, environment, model, quality, sustainability, sustainable development, urban landscape, and urban planning. The research on these closely interconnected keywords in each cluster forms the hotspots. The first cluster represents the hot spot related to policy research on the redevelopment and renewal of old cities through cultural heritage preservation and adaptive reuse of built heritage, emphasising community participation. The second and third clusters represent the research hotspots depicting the connection between urban diversity, culture, heritage, cultural landscape, biodiversity, cultural ecosystem services, health impact, and allied topics. The fourth cluster, with a combined APY of 2018.63, represents a trending research hotspot on the role of culture in sustainable urban planning and development.

The most frequent keywords and trending are obtained through the overlay visualisation in VOSviewer, as shown in Fig. 13. Here, a colour gradient scale indicates the APY of keywords; a circle's size is directly proportional to the frequency. The words within the red-to-green gradient are the recently trending keywords. The top keywords based on high occurrence and TLS are heritage, cultural heritage, city, sustainability, cultural heritage, sustainable development, conservation, management, urban planning, tourism, urban, cities, and landscape. These 13 keywords have an APY ranging from 2016.58 to 2019.46. The Cultural Heritage (Cultural-heritage) is the top keyword with a combined occurrence of 50 and a TLS of 127. Heritage word has 35 occurrence, 121 TLS and APY 2018.45. The third word is City, which has 22 occurrence and 73 TLS, followed by keyword sustainability with 19 occurrence and a TLS of 57.

Fig. 13
figure 13

Network visualisation of keyword frequency overlaid with APY

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Further, the keywords were examined using the WordStat tool to validate the VOSviewer results. WordStat generated a dendrogram of the keyword’s agglomeration order (Fig. 14) based on the association strength and frequency. The top frequent keywords in agglomeration order are Urban (60), Cultural (59), and Heritage (50), followed by city, local, development, and sustainable, signifying the research related to cultural heritage in urban development with emphasis on ‘local’ factors.

Fig. 14
figure 14

Dendrogram of keyword agglomeration (Obtained in WordStat)

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3.5.2 Topic analysis

Topic analysis helps understand the cross-disciplinary evolution of a research area, hot topics and the scope for future research. The topic analysis is done in KNIME and WordStat. The title, abstract and keywords were fed into KNIME; the ‘Topic Extraction’ function of the KNIME can extract the frequently occurring topic words and hot topics from the data provided. The optimal number of topics was obtained using the elbow method in the KNIME tool, as depicted in Fig. 15. The topic analysis resulted in four major cluster topics in UCD research with a weightage assigned to each ‘topic word’ and is presented in Table 9.

Fig. 15
figure 15

KNIME workflow for topic extraction. (Obtained in KNIME)

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Table 9 Research topics and topic words obtained in KNIME.
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The first cluster of research topics contains topic words such as Tourism, topping the list with a weightage of 104, followed by conservation(84), policy(60), regeneration(58), community(55), and sustainability(50). It indicates that tourism and conservation are the frequent topic words. Further, based on the obtained topic words, the first research topic is cultural and heritage tourism (Haigh, 2020; Hristic et al., 2020; Jha-Thakur et al., 2021; Shoval, 2018). The second topic in this category would be heritage conservation and regeneration in the urban context (Coombes & Viles, 2021; Mubaideen & Al Kurdi, 2017; Pietrostefani & Holman, 2021). The third topic is policy research related to UCD topics (Haigh, 2020; Ripp & Rodwell, 2016; Vita, 2022; Zhao et al., 2020). The fourth topic is Community participation in UCD research (Daldanise, 2020; Rodwell, 2018a; Wang & Aoki, 2019). The fifth topic is research on sustainable urban development (Y. Chen & Yang, 2018; Ozcan, 2008; Rostami et al., 2015).

The second cluster consists of the words Landscape with a frequency of 189 and management(67) and conservation(37) as frequent words. Here, the topic would be cultural and historic urban landscape conservation and management (De Rosa & Di Palma, 2013; Kirmizi & Karaman, 2021; Rodwell, 2018b; Swensen & Jerpasen, 2008). The next topic is research on the value of landscape in an urban context (Ferretti & Comino, 2015; Garcia-Esparza & Altaba Tena, 2020; Ginzarly et al., 2019; Zwierzchowska et al., 2018).

Third cluster has topic words; service(55), space(39), ecosystem(31), resident(28) quality(28), tree(26) community(26), garden(25), park(23). These words represent research on urban ecosystems involving green spaces, parks, gardens, community spaces, and their access to residents(Caneva et al., 2020; Jaligot et al., 2019; Rall et al., 2017; Unnikrishnan & Nagendra, 2015; Vejre et al., 2010; Zwierzchowska et al., 2018). The Topic words from the last cluster are; space(67), change(39), facility(37) design(34), environment(32), and integration(29). The topic here would be environmental integration in designing urban cultural spaces and facilities (Lopez Sanchez et al., 2020; Rinalduzzi et al., 2017). Further, the topic analysis is done using WordStat software.

In WordStat, the topic extraction tool generates the topic phrases based on the cumulative frequency of co-occurred keywords, providing the hot ‘topic phrase’ of research (Table 10). The first topic phrase obtained is Cultural heritage, with a cumulative frequency of 846, indicating the research on cultural heritage planning, management, and conservation; the second topic phrase of research is sustainable urban development, with a cumulative frequency of 626, and the third topic of research is the historic urban landscape (424). The ‘cultural heritage’ and ‘sustainable urban development’ are trending topics in UCD research. The keyword and topic analysis from both the software indicates the emerging significance of cultural components in sustainable urban planning discourse.

Table 10 Research topic words and topic phrases obtained from WordStat.
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Table 11 The chronological evolution of research topics in UCD.
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4 Discussion and conclusion

The analysis showed an exponential increase in publications starting from 2016, highlighting the radical shift in approach towards Urban Cultural Dynamics (UCD) garnering the attention of urban planning scholars and policymakers worldwide. The keyword and hot topic analysis indicated that in the recent four decades, scholarly works have transitioned from isolated sectoral research to culture-inclusive urban planning research and new terms such as ‘cultural planning’, ‘creative cities’, ‘creative clusters’, ‘creative economy’, ‘creative class’ and ‘brand cities’ have emerged. Notably, no published literature was found with the search string “Urban Cultural Dynamics” (in double quotes) in the Web of Science core collection till the year 2023. The authors cross-checked the ‘Science Direct’ database with the mentioned search string, and only one article was found (O’Connor & Gu, 2014), which is about creative cities. This indicates that the “cultural dynamics in urban planning” research is evolving. The various urban cultural topics were often studied in isolation. Therefore, the articles were carefully selected to cover the maximum possible dimensions of urban culture, such as tourism, cultural economy, employment, city attractiveness, migration, tangible and intangible cultural heritage, native identity, public spaces, green spaces, natural heritage, arts, innovation, city branding, cultural planning, creativity, creative capital, and creative economy, etc., together forming the basis of UCD research.

The topic analysis indicates that the evolution of topics in the field of UCD research could be broadly categorised into four periods, i.e. before 1990 and the subsequent three decades till 2021, demonstrating the chronological transition from isolated research on different cultural elements to an integrated approach as presented thematically in the Table 11. The blurring boundaries between isolated research topics are depicted through symbolic horizontal lines separating the key elements. The horizontal separation gradually vanished in the previous decade, from 2011 to 2021, as individual topics were interlinked into multidimensional research topics. In the period before 1990, the cultural topics in urban planning research were limited to isolated studies on heritage conservation, local arts, festivals, and sightseeing tourism. The period from 1990 to 2000 could be considered a transitory period due to globalisation reaching individuals with the advent of cheap communication networks (Nchofoung & Asongu, 2022), during this period, there seems to be competition among cities to attract investments and businesses by projecting the unique potential of cities. The focus of topics in this period was ‘downtown rejuvenation’, ‘urban redevelopment’, and ‘Heritage walks’ along with the policies for ‘community participation in urban redevelopment’. In the later decade, from 2001 to 2010, new topics, such as cultural planning, creative cities, creative class, cultural heritage tourism, and brand cities, took shape, garnering the attention of scholars across the globe. Then from 2010 to 2022, the exponential growth is seen in number of publications on interdisciplinary topics. For instance, ‘Cultural Heritage’ is studied in conjunction with urban regeneration, tourism, creative city, economy, and property redevelopment. City employment dynamics are analysed in relation to the creative economy and creative capital. ‘Urban art’ is studied in relation to downtown regeneration, tourism, creative city policy and local economy. ‘Urban green spaces’ are analysed in relation to urban culture, tourism and cultural ecosystem services. These topics reflect the blurred boundaries between isolated research of different cultural elements and topics, leading to the evolution of new integrated topics.

The country analysis showed that Italy is a catalyst in connecting the global East and West in UCD research cooperation. Globally, major tourist cities have invested in the research of cultural planning policies (De Frantz, 2018), demonstrating the circuitous economic relationship between cultural dynamics and the tourism industry, generally referred to as ‘Cultural Tourism’ or ‘Cultural Heritage Tourism’. The top tourist countries, such as Italy and Spain, have invested in research on cultural-heritage tourism policies (Campodonico, 2021; Xie et al., 2021). The quantum of research on UCD topics could be correlated with the growth of the tourism economy of Italy (Panzera et al., 2021), as one of the hot destinations for urban cultural tourism along with other European countries, mainly Spain, France, and the United Kingdom. The adverse effects of excessive tourism on the natural environment and society are also a topic of scholarly interest. It is evident through the published literature that the world's top tourist destinations are adopting a change in approach towards UCD in order to promote sustainable urban development rather than limit culture to arts and festivals. These examples can serve as case studies for cities across the globe to adopt plausible cultural policies for sustainable development.

The following conclusions are drawn based on an analysis of the data set from WoS; Italy, China, Spain, and the United Kingdom are considered the hot-spot countries in UCD research. Italy has the highest number of papers in the data set, influencing UCD's research significantly. The United Kingdom has the highest link strength in international institutional cooperation in this area of research, making it one of the influential countries in cultural dynamic relations worldwide. There is less representation observed in the data set from the Global East, Middle East, Asia, Africa, and Latin America, except for the People’s Republic of China and Australia. There seems to be a gap in academic research collaboration between developed world and developing countries in UCD research. Institutional analysis revealed that The Estonian University of Life Sciences plays a major role in cooperation with 16 links among 289 organizations in the data set. The Technical University of Dresden highly influences UCD research with the highest number of citations (103). The Technical University of Munich has 101 citations from only two papers, showing the high-impact research on UCD topics.

Landscape and Urban Planning, Journal of Cultural Heritage, Tourism Geographies, Cities, and Habitat International are high-impact journals. The top ten core papers among the data set have emphasized the environmental, ecological, and sustainable significance of cultural dynamics in urban planning. Keyword analysis showed that ‘Cultural Heritage’ is the top keyword, followed by the word ‘Sustainability’. The hotspot analysis showed that the urban cultural dynamics are investigated through the perspective of sustainable urban development. The results indicate the larger scope for future research on Urban Cultural Dynamics (UCD) for the sustainable development of cities aligning with the UN Sustainable Development Goals 2030(SDGs). This bibliometric analysis provides a meta-analysis of the UCD research. A systematic assessment of core publications is recommended for further research to micro-analyse policy mechanisms related to UCD in different cities worldwide.