1 Introduction

Long before urban planners began to understand the quality of urban life (QoUL) in the twentieth century, the quality of life (QoL) in ancient Greece was of interest to philosophers (McConachie et al., 2018). Gradually, with the formation of cities and the expansion of migration from rural to urban areas, and consequently, the increasing importance of cities, attention to QoUL increased among city planners and authorities (Mason et al., 2018). Many studies have been conducted so far on the mutual impact of QoUL and the issue of urban planning (see Rezvani et al., 2013; Lotfi & Koohsari, 2009; Marans, 2015; and Arifwidodo, 2012). In fact, the identification of the negative consequences of physical development without considering the environmental and social consequences called for a more comprehensive framework, and new components were added to the notion of development (Turkoglu, 2015). Initially, economic growth was the only indicator of development, while more studies confirmed that the consequences of such a one-dimensional approach are threatening to QoL (Ma et al., 2020). As a result, other dimensions such as environmental consideration and social impacts were desired too (Allen, 2016). Studies on the concept of QoUL show that this concept is formed of three main dimensions: objective, subjective, and behavioral (Marans & Stimson, 2011; Marans & Kweon, 2011). The prevailing hypothesis is that the community members, while observing the high level of physical qualities within the community (objective level), realize that they live in a good environment (subjective) and then consider a set of behavioral responsibilities towards the environment (behavioral level). However, the role of interpersonal differences as an intervening variable is also mentioned. Here it seems that there is a causal relationship between the above three dimensions. Thus, the existence of each is the generator of the other. According to Turkoglu (2015), a high level of quality of life leads to an improvement in the level of social capital (SC) and a high quality of urban life. A high-quality neighborhood at the objective level enhances social bonds among residents by facilitating access to health services (García-Sánchez & Güereca, 2019), increasing local security through nightlife activities and indirect supervision (Blekking et al., 2020; Mason et al., 2018).

"The high level of social capital is also a function of residents' subjective perception of their place of residence (Alvarez & Müller-Eie, 2017). The satisfaction resulting from the high level of social capital in urban areas is usually a product of satisfaction with construction quality (Ma et al., 2020), a well-laid road network (Murgaš & Klobučník, 2018), perceived local security (Wadi & Furlan, 2017), visual beauty of the neighborhood (McConachie et al., 2018; Mouratidis, 2018).

Residents of a neighborhood with decent urban per capita income (Wey, 2019), easy access to public transportation (Uysal & Sirgy, 2019), easy access to city services (Tsekoura et al., 2017), clean air (Kautonen et al., 2017), pedestrian-friendly green spaces (Węziak-Białowolska, 2016), and local parks share common interests (Marans & Stimson, 2011; Marans & Kweon, 2011; Marans, 2015). As a result, it is expected that this perception of common interests will lead to the promotion of social capital among the residents of these neighborhoods.

In this research, we sought to prove/decline the above-mentioned equation through field research in Tehran. For this purpose, we examined the 22nd district of Tehran. Consequently, this study seeks to answer the following questions:

Does a high level of quality of life necessarily lead to a high level of social capital among the residents of an urban area?

This article is organized into seven sections. After the first part (introduction), the sections proceed from the literature review to the results, discussion, and conclusion, respectively."

2 Literature Review

2.1 Quality of Urban Life

According to Cicerchia (1996), the expansion of urban life and the resulting issues led to the formation of a more comprehensive concept for the category of quality, which is the QoUL. Since scholars have proposed different QoUL indicators, reaching a unanimous framework is impossible (Marans, 2015). In other words, despite various studies on QoUL conceptualization, there is no unanimous framework for measuring the QoUL that is accepted by all researchers so far (Ma et al., 2020). One explanation for such disagreement lies in the fact that QoUL measures might vary in different communities and at different times and situations (Murgaš & Klobučník, 2018).

According to Brown and Dapa (2020), QoUL is more concerned with the physical qualities of space, while Pazhuhan et al. (2020) confirm the importance of economic components. Alvarez and Müller-Eie (2017) believe that the most important element of the QoUL depends on social issues. It is important to note that despite the lack of consensus on a global conceptual model of QoUL, there appears to be consensus in the literature that the three principal dimensions of QoUL include economic, social, and physical components (Ma et al., 2020; McConachie et al., 2018; Wadi & Furlan, 2017).

Due to the social nature of individuals, community members need to gain social standards in space (Mouratidis, 2018). These standards include healthy and purposeful interaction with other neighbours, a sense of security and well-being, a sense of belongings and unity towards the living environment, as well as the development of social skills through the urban environment (García-Sánchez & Güereca, 2019). Additionally, since one of the motivations for rapid urbanization has been the higher employment opportunities and income within cities, economic growth, higher access to jobs, and greater profitability of economic activities are other expectations that individuals have of their living environment (Blekking et al., 2020). Herein, Pazhuhan et al. (2020) have confirmed that physical qualities such as architectural attractions and visual qualities have a direct impact on an individual's level of satisfaction with their living environment. Consequently, QoL is created by an ongoing interaction between community, environmental, and socioeconomic qualities (Mouratidis, 2018).

A high-quality urban place provides social support networks enabling citizens to communicate and participate with each other (Mason et al., 2018). The physical environment creates a healthy liveable space in which the community enjoys a sense of fairness and justice (Wey, 2019). The SQoUL encompasses one's perception of their living condition quality (Turkoglu, 2015), while the OQoUL proposes the existence of a set of physical infrastructures within the space (Blekking et al., 2020), and BQoUL represents a set of responsible actions that are managed to improve the quality of the environment (Marans, 2015). The objective indicators mostly represent the physical quality of urban spaces, while subjective indicators usually explain mental and emotional aspects of satisfaction such as happiness and wellness, and behavioural factors iterate collaboration and cooperation of residents in fostering the quality of the area (Marans & Stimson, 2011). According to Marans and Kweon (2011), a causal relationship functions among the three dimensions of QoUL, since each is a generator of the other."

2.2 Social Capital

Communities with higher levels of social capital are more sustainable, resilient, and in short, happier (Calcagnini & Perugini, 2019). It accounts for knowledge transfers in each community (Chitsaz et al., 2019), encourages innovation, and triggers more efficient performance in all social institutions within a community (Moore & Kawachi, 2017). This concept is considered a unifying informal term that facilitates cooperation among individuals in society (Akhavan & Mahdi Hosseini, 2016). It is a powerful mechanism that ensures the connection between social institutions. It is the consequence of the potential and actual assets of a society in peaceful coexistence which are embedded within, accessible through, and obtained from the informal relations functioned by an individual, community, or institution (Rodgers et al., 2019).

In another definition, social capital stands for the correlation among members and institutions that foster cooperation for creating values and includes structural, cognitive, and relational aspects (Zhang et al., 2019). However, for some other researchers, social capital is categorized into internality and externality (see Cai et al., 2019; Acedo et al., 2017), while in some studies, it is associated with three main types: bonding, bridging, and linking (see: Koutsogeorgou et al., 2020; Fraser, 2021; Moore & Carpiano, 2020). Structural social capital includes a sense of community, group membership, a sense of responsibility, awareness, calls to action, and communication with local authorities or government organizations on related issues (Lu, 2019). The cognitive aspect includes trust, social harmony, a sense of belonging, and a sense of fairness, while the relational level encompasses trust, reliability, commitment, social networks, social cohesion, and congruence (Bayat et al., 2022, Mazumdar et al., 2018).

The subject of this research is the effect of quality of life on social capital. In this research, quality of life is the independent variable, and social capital is the dependent variable. Identifying the factors of social capital expansion is one of the most important goals of all urban managers, because without social capital, the implementation of urban projects faces many difficulties.

In general, there is general acceptance in the literature related to the quality of life that the improvement of the level of social capital can ultimately lead to an increase in the quality of life and expected well-being. However, the question still arises whether this relationship is bidirectional and whether increasing the level of urban qualities necessarily leads to an increase in social capital or not. Accordingly, Fig. 1 shows the conceptual model of this study, which is based on the relationship between our variables and the three levels of each indicator. This model will be investigated through a field study as follows.

Fig. 1
figure 1

Conceptual model of the study

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Earlier mentioned that our main question is:

Despite the low level of SC, is the causal relationship between the three dimensions of the QoUL still significant?

As a result, our hypotheses are:

  1. 1.

    SC is positively associated with OQoUL.

  2. 2.

    SC is positively associated with SQoUL.

  3. 3.

    SC is positively associate d with BQoUL.

  4. 4.

    High OQoUL will cause high SQoUL.

  5. 5.

    High SQoUL will cause high BQoUL.

3 Research Background

There has not been much research on the relationship between social capital (SC) and quality of urban life (QoUL) in urban scholarship and assessing the relationship between these two variables began at the beginning of the twenty-first century.

Rogers et al. (2011) studied the role of walkability and SC as influencers of QoL at the municipal and neighbourhood scales. Living in pedestrian and walkable neighborhoods fosters the level of SC among residents through promoting social interactions and consequently increases the QoL.

Karimzadeh et al. (2013) studied the impact of SC on QoL in India. The results of this study also confirm the relationship between these two variables. Moreover, multiple regression analysis suggests that except for social participation, all indicators of SC are accepted as predictors of QoL in India.

Hamdan et al. (2014) researched the association of SC with QoL in urban neighborhoods with high-density housing. This investigation affirms that the practice of SC is influenced by the length of neighborhoods formation, the population diversity of residents, and the physical extent of the area. Additionally, SC in these areas upgrades positive social qualities towards a decent living that contributes to QoL.

Rimaz et al. (2014) investigated the health and psychological dimensions of SC and QoL. This study researched the association between SC and QoL in multiple sclerosis patients. The findings of this study confirm the positive role of SC in improving the QoL among patients. However, the scope of studies on the impact of SC on patients' QoL does not end here, and Hu et al. (2015) studied the association between SC and QoL among type 2 diabetes patients in China. This study confirms that cognitive SC was positively associated with the physical and mental aspects of patients. However, the associations between structural SC and the physical component summary were not statistically significant.

In a recent study, Lane et al. (2020) studied the way neighbourhood SC interacts with QoL in older Singaporeans. The findings reveal that social cohesion (β = 1.39, p < 0.01) and associational membership (β = 19.16, p < 0.01) were key in higher QoL, along with individual socio-demographics, social networks, functional limitations, global cognitive status, and medical conditions.

Finally, Zhao et al. (2020) investigated the effects of physical activity and stress on the relationship between SC and QoL among breast cancer survivors. The serial multiple mediations of physical activity and perceived stress were found significant in the relationship of QoL with all five dimensions of individual SC.

A review of research in the field of SC and QoL reveals two facts. First, in these studies, QoUL has been neglected, and attention has generally been paid to QoL, with most studies focusing on specific groups such as the elderly and patients. The second point is that most of the present research, without adopting a critical and challenging approach, have aimed to measure the positive relationship between SC and QoL. As a result, their findings, despite the differences in method, scale, and case studies, are similar in general. We believe that the literature in this field requires a challenging and critical approach to the intervening role of SC in QoUL. The significance of this study is that we aimed to discover how SC in each area can influence the causal relationship among the three dimensions of QoUL: objective, subjective, and behavioural QoUL. As follows, we tested this equation.

4 Case Study

"District 22 of Tehran Municipality is the westernmost urban district of Tehran, situated in the northwest of the city. District 22 is the largest geographical part of Tehran. Prior to the Islamic Revolution in 1979, this area belonged to the Farmanfarmayan and Firoozgar families, two wealthy families. However, after the Islamic Revolution, these lands were declared national property, and some of them were handed over to the Urban Land Organization (Ashraf, 1993).

The imbalance between existing lands and the needs of residents prompted authorities to transform this vast empty land into the twenty-second district of Tehran, meticulously designed and planned in accordance with the principles of new urbanism (Barati et al., 2010). A comprehensive plan was prepared for the area in 1991, followed by a detailed plan in 1994. Finally, after years of research and development, District 22 of Tehran was officially established in 2000 (Madanipour, 2006). Notably, this district stands as the only area in Tehran that has been entirely designed by urban planners and designers, whereas other districts have evolved through gradual organic development (Arbab & Azizi, 2016).

Following the Islamic Revolution and driven by large-scale urban planning policies, this area experienced substantial construction activity. Consequently, due to the physical expansion of the area and the increase in population, challenges emerged in the management of urban and environmental services in this region (Dehghani et al., 2018).

Predominantly inhabited by immigrants and newcomers, this district has been designated as the green lung of the city and an area intended for tourism and green spaces within the master plan of Tehran (Heidarian et al., 2016). In stark contrast to other districts of Tehran, which have evolved through gradual organic growth, this region is relatively planned (Tehrani et al., 2020).

Despite its relatively well-planned physical development, recent studies reveal that District 22 of Tehran faces challenges in terms of the social dimensions of quality of life (Shadi et al., 2018 and Mohammadi et al., 2019).

According to the 2016 census, the population of this district is 175,398 people (54,857 households), comprising 89,146 men and 86,252 women. This district has the lowest population density in Tehran and the highest ethnic diversity. As per Rezvani et al. (2015), this area serves as the primary destination for immigrants settling in Tehran, with the shortest length of residence among city districts and ranking third in development among city districts based on physical-spatial factors. Studies conducted in this region indicate that due to the extent of ethnic diversity, short residence time, lack of historical background, and low activity and population density, the level of social capital in this region is relatively lower than the city average (Shadi et al., 2018; Shaini et al., 2017; Mohammadi et al., 2019). Figure 2 shows the location of District 22 in Tehran.

Fig. 2
figure 2

District 22 of Tehran (Ghodrati et al., 2013)

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5 Method

As discussed in the introduction, the aim of this study is to investigate the relationship between the three dimensions of Quality of Urban Life (QoUL) while considering the role of social capital (SC). The prevailing theory, accounting for individual differences, posits that a high level of Objective QoUL (OQoUL) contributes to a high level of Subjective QoUL (SQoUL), and a high level of SQoUL leads to a high Behavioural QoUL (BQoUL) level (Marans and Stimson, 2011; Marans, 2015). To challenge this claim, a questionnaire containing the structures identified in the literature review was distributed among the residents of District 22. The questionnaire was designed using a 5-point Likert scale, where options ranged from strongly agree (5) to strongly disagree (1). Participants filled out the surveys in streets, parks, and public spaces of the region.

To ensure representation from all neighborhoods and demographic groups within the region, a combination of stratified sampling and quota sampling methods was employed. The sample size was calculated using Cochran's formula, resulting in the distribution of 384 questionnaires among participants. The questionnaires were distributed and collected between 2018 and 2019. The collected questionnaire data were analysed using SPSS 21 and Smart PLS 3 with a structural equation modelling (SEM) approach.

Structural equation modelling (SEM) combines path models (representing structural relationships) and confirmatory factor models (representing measurement relationships). In path models, the researcher represents phenomena through a collection of unidirectional and bidirectional (mutual) relationships when observing variable types are under study. A comprehensive SEM is a fusion of path models and confirmatory factor analysis. Essentially, SEM is a comprehensive statistical approach to testing hypotheses regarding the connections among observed or latent variables, sometimes referred to as covariance structural analysis or causal modelling (Hesari et al., 2019).

5.1 Demographic Description

All participants had a minimum of 10 years of residence in the area. The youngest participant was a 21-year-old woman, while the oldest participant was a 67-year-old man. Among the study group, 60.4% (232 people) were male, and 39.6% (152 people) were female. In terms of age distribution, 4.7% of the respondents were under 25 years old, 25.8% were between 25 and 30 years old, 37.8% fell within the 30–40 years age range, and 31.8% of our sample were over 40 years old. Regarding educational attainment, 34.1% held a bachelor's degree, 48.7% had a master’s degree, and 17.2% possessed a doctorate.”

6 Results

Before delving into our result, we tested the reliability and validity of our variables. AVE value for all our constructs is between 0.6671 and 0.8266 which confirms acceptable validity of the constructs (Chan & Lay, 2018). The result of validity and reliability are presented in Table 1.

Table 1 The result of validity and reliability test
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According to Table 3. All values are above 0.6 which confirms the validity of indicators. Now normality/abnormality of data is evaluated through Kolmogorov–Smirnov test, all data are abnormal according to significance level (p < 0.05) (Table 2).

Table 2 Normality/abnormality of data test
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Before testing research hypotheses, it is necessary to make sure that the questions related to research variables are correct, therefore, in this stage, confirmatory factor analysis (CFA) is used.

In the standard estimation mode, the closer the factor load are to 1, the better the observed variable (question) can explain the latent (hidden) variable. If the factor load is less than 0.3, a weak relationship is considered, and that question will be ignored. A factor load between 0.3 and 0.6 is acceptable and if it is more than 0.6 it is very desirable (Tables 3 and 4).

Table 3 R2 test results for dependent variables
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Table 4 Q2 test results for variables
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Factorized loads are of great importance in interpreting the results of factor analysis. These values indicate the correlation between each obvious variable (questions) and its related factors. Depending on how careful the researcher is to remove the questions, the criterion values vary from 0.5 to 0.7, but the minimum declared limit is 0.4. Figure 3 shows CFA for research questions in the significant numbers’ mode. The values in this graph measure the relationship between latent (unobserved) variables in a significant way.

Fig. 3
figure 3

standard values for research test

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According to Fig. 4, if − 1.96 < t value < 1.96 then the relationship between factors is insignificant at the 95% confidence level and if T value > 1.96 or T value < − 1.96 then the relationship among factors is significant at the 95% confidence level (Kim, 2015). T value indicates the accuracy of the relationship between the structures and thus confirms the research hypotheses at the 95% confidence level, based on which all the relationships in the model are significant.

Fig. 4
figure 4

Significant numbers of research questions

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R2 determines the extent to which an exogenous variable affects an endogenous variable. It is important to note that the value of R2 is calculated only for the dependent (endogenous) structures of the model, and in the case of exogenous structures, the value of this criterion is zero. The higher the value of R2 is for the endogenous structures, the more fit the model is. Miles (2014) considers 0.19, 0.33 and 0.67 respectively as weak, medium and strong values of structural fit of the model according to R2 criterion.

Q-squared (Q2) determines the predictive power of the model. Models that have an acceptable structural fit should be able to predict the characteristics of the endogenous structures of the model. Shaffer (2013) considers 0.02, 0.15 and 0.35 respectively as weak, medium and strong predictive power of the structure. It is important to note that this value is calculated only for the endogenous variables of the model whose characteristics are of the reflective type.

The goodness of fit (GOF) describes how well it fits a set of observations. Measures of GOF typically summarize the discrepancy between observed values and the values expected under the model in question. 0.01, 0.25 and 0.36 are respectively regarded as weak, Medium and strong values for this criterion according to Eq. (1) (Maydeu-Olivares & Garcia-Forero, 2010). The GOF for our model is strong.

$$ GOF = \sqrt {\overline{Communality} \times \overline{{R^{2} }} } = \sqrt {0.454 \times 0.720} = 0.571 $$
(1)

Now according to above mentioned analysis, the result of our hypotheses assessment is presented in Table 5.

Table 5 Result of hypotheses assessment
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7 Discussion

In this study, we utilized the concept of social capital (SC) to challenge the assumed causal relationships among the three dimensions of Quality of Urban Life (QoUL). Our findings suggest that in the absence of an acceptable level of SC, even within a comprehensively well-planned urban area boasting suitable urban infrastructure and high levels of objective and subjective qualities, a high level of Subjective QoUL (SQoUL) may not necessarily lead to a high level of Behavioural QoUL (BQoUL). Consequently, the cultivation of responsible behaviours within urban districts appears to be more closely associated with strong social ties between residents rather than the mere presence of diverse physical qualities. This study underscores the importance of the third pillar of sustainable development, namely social sustainability, in modern urban life and highlights how it can potentially alter the objectives of physical development.

While our results support the association between SC and QoUL as suggested by Marans and Stimson (2011) and Marans (2015), they introduce a novel perspective wherein SC acts as a potent intervening factor in QoUL. In contrast to prevailing theories that posit a direct causal relationship among the three dimensions of QoUL while attributing any deviations solely to interpersonal differences (Marans, 2015), this study demonstrates that SC plays a decisive role with the potential to disrupt the aforementioned-assumed equivalence.

A significant theoretical implication of our study is the recognition that urban issues, particularly those concerning the connections between community members and institutions, are more than outcomes of any single variable; they are products of intricate social components. The inherently social nature of human beings contributes to a persistent weak linkage between individuals and social institutions, regardless of the presence of high-quality physical attributes like a subway network, green spaces, modern buildings, and well-structured road networks.

Consequently, our findings deliver a crucial message to practitioners and professionals in city authorities. While the establishment of identity and the fostering of social bonds represent time-intensive and constructive objectives, employing design and planning measures can enhance SC levels and fortify human connections. In today's urban neighborhoods, what's essential is the creation of spaces conducive to communal activities, pedestrian-friendly pathways, street performances, local shops, robust community centres, and inviting corners that facilitate citizens' interaction opportunities. These spaces serve as platforms for visibility and engagement, allowing urban planners and designers to rejuvenate the sense of community by transforming urban environments into hubs for daily civic interactions. Ultimately, spaces should evolve into arenas for shared experiences and collective action among residents.

This research underscores the need for urban planners and managers to place a dual emphasis on the role of public spaces as catalysts for enriching citizens' social lives. Based on the demographic makeup of the 22nd region, we conclude that cultural and ethnic disparities lead individuals to inaccurate impressions of each other, resulting in a preference for reinforcing personal boundaries over engaging in social interactions.

Continued adherence to this approach leads to a decrease in social capital and consequently undermines the behavioural dimension of our urban life's quality. Our recommendation, therefore, is to prioritize the creation of public spaces, particularly parks and pedestrian areas with diverse activities that primarily foster interpersonal interactions and dismantle invisible social barriers. Promoting public spaces and encouraging participation in collective activities such as morning workouts, local exhibitions, bazaars, group sports, music, and street theatre is a measure aimed at dispelling people's misconceptions about each other. In this context, proper planning can alleviate anthropophobia and pave the way for a sense of community. The allocation of space and the design of activities that replace the paradigm of "tribal membership" with the modern concept of "city citizenship" stand as essential tasks that city managers should address in this domain.

8 Conclusion

The primary aim of this study was to investigate the dynamic interaction between social capital (SC) and the dimensions of Quality of Urban Life (QoUL). A key takeaway from this study is the substantial and influential role that SC plays as an intervening factor in shaping QoUL. In summary, while a positive correlation exists between SC and QoUL, it's crucial to note that when SC within a community is lacking, even in the presence of a high level of Objective QoUL (OQoUL), we may not observe the anticipated elevated behavioural outcomes. This study addresses a gap in existing theories concerning the functioning of QoUL within urban scholarship by challenging established hypotheses. Nonetheless, further investigations are required to ascertain the extent to which SC can elucidate QoUL and the strategies that can be employed to nurture QoUL in communities characterized by low levels of SC.

9 Limitations and Suggestion for Future Studies

Certainly, our study is not exempt from certain limitations. For instance, while we have attributed the reduced Behavioural Quality of Urban Life (BQoUL) to low levels of social capital (SC), it is possible that there are additional factors, not considered in this study, that also impact BQoUL. In other words, while it holds true that a deficit in SC can contribute to a decline in BQoUL, the extent to which this deficit influences BQoUL through SC warrants further investigation.

Furthermore, the case study utilized in this research pertains to a transitional area for the citizens of Tehran. This region's formation spans less than two decades, and its residents encompass diverse ethnicities and cultures from across Iran. This unique context may introduce bias errors into our research findings. It is advisable for future researchers to conduct a comparative study involving two neighborhoods characterized by varying levels of objective quality and SC. This approach would offer insights into the generalizability of our results and facilitate a deeper understanding of the interplay between these factors in different urban contexts.