The term “placeness” carries a complex meaning and frequently overlaps with other place-related concepts. In this paper, we narrow down the definition of “placeness.” We define it simply as a place that is not only in terms of its physical uniqueness or characteristics but also embodies the relationship between humans and place, considering the placeness as a whole. This definition aligns with Relph’s (2015) conceptualization of placeness as a “conveniently broad term that allows [one] to consider everything to do with the diverse qualities, interpretations, uses, and experiences of place, from place cells in the hippocampus to a global sense of place.”

The impact of place on behavioral intention has been widely studied in urban studies. On one hand, towns or places created solely with a focus on economic factors—such as rapid development, modernization of buildings, and mass infrastructure—may result in cities lacking variety (Jacobs, 1961). This can lead residents to experience a sense of unlivability and placelessness. For instance, Relph’s (1976) work on “Place and Placelessness” highlights how post-industrial urban development diminishes the sense of placeness in cities. He argues that mass production and standardization in urban planning have led to a homogenization of cities, fostering a sense of placelessness (Relph, 1976). This argument is also supported in urban history. Consequently, urbanists and architects have proposed a new planning and design agenda focused on people. They believe that the design of public spaces can significantly impact individual behavior, affecting social interaction (Jacobs, 1961; Whyte, 1980; Gehl, 2013). One influential work in this area is Whyte’s (1980), which identifies several key characteristics of successful public spaces, such as ample seating, natural sunlight, and opportunities for social interaction. In his work “Cities for People,” Gehl (2013) emphasized that cities should be designed to promote social interaction, pedestrian activity, and public space, focusing on the importance of creating physical environments that suit the human scale for optional and social activities. This highlights how physical environments are crucial in shaping human behavior.

On the other hand, despite the mass of buildings and poor environmental conditions, residents who live in these areas still feel attached to their place and revisit them. Why does such behavior persist? This question motivates our study. Many studies have attempted to describe this phenomenon, suggesting that attachment may be due to personal experiences, memories, and social interactions within the place (Livingston et al., 2010; Scannell and Gifford, 2017), indicating a tight correlation to the places, or past experiences which serve as mediators between the physical environment and behavior. In other words, the influence is not only direct but also indirect. Several empirical studies in heritage and cultural sites have confirmed that place influences the behavioral intention of residents and visitors through both direct and indirect effects (Im et al., 2013; Zhang and Li, 2021; Zhang et al., 2021). In environmental psychology and built environment behavior studies, a more complex mechanism of how place influences behavioral intention is proposed. For example, Ajzen (1991) defines behavioral intention as an individual’s readiness to perform a given behavior, influenced by their attitude toward the behavior, subjective norm Ajzens, and perceived behavioral control.

In this sense, physical environment attributes may not fully explain the influences on behavior, suggesting that a more comprehensive structure is needed. Therefore, to understand the effect of placeness on behavior, it’s necessary to look beyond the direct effects and consider a comprehensive structure that includes both direct and indirect effects. Based on the literature, we consider two factors as mediators between placeness and behavioral intention: personal perception factors in the form of ‘place attachment’, which focuses on individual preferences, past experiences, and attitudes; and public perception factors, embodied in the ‘public image’ of the physical environment and social norms. The subsequent section will discuss personal place attachment and public place image in more detail.

The relationship between individuals and their environments, particularly “Place Attachment,” has been widely studied in environmental psychology (Altman and Low, 1992; Hidalgo and Hernández, 2001; Scannell and Gifford, 2010; Lewicka, 2011). Many researchers have delved into the process of an individual’s cognitive relationship with a place through theoretical frameworks. For instance, the tripartite organizing framework of Scannell and Gifford (2010) illustrates the relationship between the person, processes, and place. Additionally, Gustafson (2001) suggests a framework that views a place’s meaning through the lens of self, environment, and other aspects. Therefore, place attachment can be viewed as an individual’s perception formed by the interaction of a person’s feelings, the function of place, cognition, experience, and beliefs after experiencing the essence of a place.

Studies of place attachment have shifted toward more empirical work and are widely conducted in many fields. Particularly, the testing relationship between place attachment and behaviors such as willingness to pay, loyalty, risk-coping behavior, tourism management, civic engagement, pro-environmental behaviors, and pro-tourism behavior (Vaske and Kobrin, 2001; George and George, 2004; Gross and Brown, 2008; Halpenny, 2010; Lewicka, 2011; Ramkissoon et al., 2012, 2013; Silva et al., 2013; Su and Hsu, 2019; Dang and Weiss, 2021; Wan et al., 2022). Some of these studies confirmed that place attachment has a positive and direct effect on behavior, forming a bond between an individual and a specific place (e.g., memories, emotions, identity). For example, a study on pro-environmental behavior highlighted place attachment as a personal factor positively influencing pro-environmental behavior, (Halpenny, 2010; Ramkissoon et al., 2013). Halpenny (2010) researched visitors to Point Pelee National Park in Canada and discovered a strong correlation between the intensity of place attachment and the prediction of place-related pro-environmental intentions. The study also highlighted the predictive power of place attachment to pro-environmental behavioral intentions in everyday life. Additionally, people who have developed a strong attachment to a place are more likely to protect the environment of a park in Australia (Ramkissoon et al., 2012). In other fields such as tourism management, studies have found that place attachment positively influences behavior intention in terms of word of mouth, revisiting, and active involvement in activities (Su and Hsu, 2019; Soonsan and Sukahbot, 2020). Research in the field of urban studies has found similar results. For instance, in urban areas in South Korea, it was shown that people who have developed an attachment to a place tend to have positive word of mouth, recommend the place to others, and revisit the place in the future (Kim and Choi, 2011; Seong et al., 2016; Son et al., 2023).

Not only does personal place attachment influence behavioral intention, but public place image perception is also a crucial factor. Place image, which focuses on the image of a place, particularly regarding its common and well-known characteristics, also has a relationship with behavioral intention. Place image is shaped by social factors and the meaning attributed to the place by the community (Kang and Choi, 2012; Im et al., 2013). Additionally, Relph (1976) emphasizes that the meaning people give to a place is important in understanding their perception and experience of it. This relationship between place image and behavioral intention has been studied extensively in the tourism sectors using the terminology “Destination Image.” Previous studies have shown mixed results regarding the relationship between place image and behavior. The research on overall destination image, event, and festival image has demonstrated that it influences behavioral intentions to choose a destination, with both direct and indirect effects (Chen and Tsai, 2007; Chi and Hailin, 2008). Papadimitriou et al. (2015) found that cognitive and affective place image components positively influenced residents’ word-of-mouth intentions toward tourists in the urban area of Athens, Greece. Moreover, a study by Chi and Hailin (2008) found evidence of an indirect relationship between destination image and destination loyalty in the context of the state of Arkansas—Eureka Springs. In aspects of urban planning and design, the public perception of a place is not only organically bound by itself. It is also affected by urban planner-designer work that attempts to create an image of the place that refers to a mental map of the city, to make the place easy to memorize as seen in detail in The Image of City (Lynch, 1964).

The studies mentioned above recognize concepts such as place attachment, place image, and behavioral intention for their intrinsic value and contribution to city development. However, to genuinely unlock the potential of urban development and foster more comprehensive improvements in our cities, it is imperative to integrate these concepts.

This study aims to address the gaps in prior research by proposing a comprehensive structural pathway. We seek to integrate concepts such as placeness, place attachment, and place image to understand their influence on behavioral intention. Notably, we incorporate place attachment and place image as mediators, bridging the connection between placeness and behavioral intention. To delineate this comprehensive pathway from placeness to behavioral intentions, we have pinpointed five direct pathways. Among them, three pathways directly map the transition from placeness, place attachment and place image, to behavioral intention. The remaining two pathways explicitly connect placeness with place attachment and place image, respectively. Furthermore, we have identified two indirect pathways linking placeness to behavioral intention via place attachment and place image.

Placeness is the initiative of the awareness of the people who perceive the place. and it considers in many inspects those visitors and residents perceived environment surrounding in a single element. Therefore, the relationship started from the perceived placeness that has directly affected the personal place attachment, public place image, and behavioral intention. Therefore, we assumed the hypotheses below:

Additionally, place attachment and place image itself we also assumed that it is have positive and direct effects on behavioral intention. as studies on place attachment in psychology studies being used to represent the connection between place and behavior through psychological processes. This process is often linked to individual cognition and past experiences and can influence future behaviors (Halpenny, 2010; Ramkissoon et al., 2013; Dang and Weiss, 2021). In tourism studies the public image is used to describe people’s perceptions of a place collectively and much research also shows the connection between the place image and the future behavior of both residents and visitors. For more details see (Chi and Hailin, 2008; Elliot et al., 2011; Papadimitriou et al., 2015; Stylidis et al., 2016). Therefore, we assumed that two place attachments and place image directly influenced the behavioral intention as the hypotheses below:

Nonetheless, this study employs an empirical approach and utilizes hypothesis testing to analyze the relationship between placeness and behavioral intentions. Based on previous literature reviews, it is hypothesized that placeness also has an indirect relationship with behavioral intentions through place attachment and place image. To investigate and confirm these relationships, this study proposes hypotheses 6a and 6b as the hypotheses below, and the overall structure framework is present in Figure 1.

A review of previous studies is required to develop the measurement of our proposed theorize framework. The measurement consisted of questions developed to capture how the respondents perceived the place and their behavior, see Table 1. For instance, the studies of placeness aim to uncover the definition and measurement of placeness from the perspective of urban residents and visitors. Which is not only focused on the uniqueness of the place, but it considers as a whole the characteristics of the areas. In the placeness construct see more details from Kang and Choi (2012) and Im et al. (2013) who widely studies measurement placeness. Additionally, place attachment has been widely studied in psychological environments that measure on the individual level through the place. For example, Williams and Roggenbuck (1989) and Kyle et al. (2005) have discussed and tested both place identity and place dependence to capture the function of place and personal perceptions of place. Place images are widely studied in tourism studies such as Echtner and Brent Ritchie (1993) and Kang and Choi (2012) and we focus on measurements of the social or public perception of places. Lastly, measuring behavioral intention is more common than studying universal behavioral intentions. Particularly, this approach is beneficial for scholars focusing on future behaviors related to places and tourism, as well as for organizers evaluating future behaviors after individuals have experienced certain events or visited certain places.

Given the diverse nature of metropolitan regions, the selection of a specific area to represent an entire city can be quite varied. In this study, we selected distinct locales within three major Japanese cities – Tokyo, Kyoto, and Osaka – to validate the concept of placeness.

In Tokyo, our focus was on Shibuya, a vibrant retail and entertainment district renowned for its iconic “scramble” crossing and towering digital billboards. In Osaka, we concentrated on Dotonbori, a favorite tourist hotspot recognized for its bustling ambiance along the Dotonbori Canal in the Namba district. Meanwhile, in Kyoto, our attention was on Gion, a quintessential district celebrated for its rich historical culture, most notably the presence of Geisha and traditional Japanese eateries and boutiques lining Hanamikoji Street.

In conducting this study, we adhered to the general principles of ethical research, which are appropriate for studies classified as minimal risk. Our study involved distributing questionnaires and did not collect identifiable personal information from participants, thereby posing minimal or no risk to them. Consistent with ethical research practices, we ensured informed consent, maintained participant anonymity, and protected data privacy throughout the research process. Data collection took place from June to July 2013. Interviews were conducted between 6 p.m. and 10 p.m. Each questionnaire required approximately 5–8 min to complete. To accommodate our target audience, the questionnaire was translated into Japanese. It was divided into three sections. Part 1 emphasized respondents’ demographic and mobility traits, such as gender, age, occupation, and time spent on transportation. Part 2 touched upon the perceived reason for visiting, the facilities used, and the motivation behind their visit. Part 3 homed in on four primary factors: perceived placeness of the location (PL01-PL07), place attachment (PA01-PA04), place image (PIM01-PIM04), and behavioral intention (BI01-BI04). Both Parts 2 and 3 utilized a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree).

Based on our literature review on the recognition of placeness, we identified both place attachment and place image as mediators. These serve as the connecting links between placeness and behavioral intention. This study employs PLS-SEM to explore the relationships among these four constructs. We chose PLS-SEM because it sheds light on the connections among multiple variables, examining the structure of interrelationships articulated through a series of equations, which are well-known for handling small sample sizes. Moreover, our decision to use the PLS-SEM approach was influenced by the fact that the constructs encompassed both formative and reflective measurements (Hair et al., 2020; Sarstedt et al., 2020). Within these constructs, placeness (PL) and place image (PIM) are categorized as formative, while place attachment (PA) and behavioral intention (BI) are classified as reflective.

Consequently, we adopted a two-step PLS-SEM modeling approach. First, in the measurement model, our focus was on the quality of indicators. For formative constructs, we examined the variance inflation factor (VIF), outer weight, and outer loading (Sarstedt et al., 2020; Hair et al., 2021). For reflective constructs, evaluation metrics such as Cronbach’s alpha, the average variance extracted (AVE), composite reliability (CR), and the heterotrait-monotrait ratio of correlations (HTMT) were utilized (Chin, 2010). Second, delved into the structural model, analyzing collegiality through the VIF, the R-squared value, the Q-squared value, and the path coefficient (Sarstedt et al., 2020).

Out of the 130 survey responses we received, 117 were fully validated, yielding an effective response rate of 90%. The characteristics of the respondents are detailed in Table 2. The respondents from these three areas were predominantly female, representing 58.12% of the total, with an average age of 26.88. The largest occupational groups were service sector workers and students, making up 30.77 and 25.6% of respondents, respectively. Notably, 68.38% of individuals spent less than an hour traveling to participate in the survey, which is consistent with the urban nature of the areas, located in the heart of urban environments and easily accessible via transportation.

As for the nature and context of the commercial areas we surveyed, respondents reported visiting these areas due to the commercial facilities, which align with convenient transportation options and a pleasant atmosphere. The purpose of respondents visiting these areas is to utilize facilities that are well-provided, such as restaurants and coffee shops. They use these facilities primarily for eating, drinking, and shopping. These reasons for visiting were influenced by individual experiences. However, it is interesting to note that these areas are also visited because they are famous places, known for their social or public image.

These demographics and reasons for visiting these areas provide the fundamental context of the visit. Although other areas also offer these basic facilities, the reasons why visitors choose these areas and are willing to revisit, recommend them to others, and even return multiple times are the main interests of this study. The next section will show how the ‘placeness’ impacts behavioral intentions from an urban planning and design perspective, through the psychological perception of place.

Our theoretical framework incorporates two types of constructs: reflective and formative. To assess these constructs requires different methodologies (Hair et al., 2020, 2021; Sarstedt et al., 2020) detailed in Table 3. For the reflective constructs, such as place attachment and behavioral intention, we begin by evaluating the loading and significance (p-value) of each indicator. Place attachment is measured using four indicators: PA01, PA03, and PA04 each show an outer loading exceeding the 0.70 threshold, while PA02 (“I will miss this area if it changes”) has a loading of 0.645. Despite being below the typical cutoff, its significance at p < 0.05 justifies its retention in our model. Similarly, all indicators of behavioral intention surpass the threshold of 0.707, affirming their adequacy (Sarstedt et al., 2020).

Next, we assess the reliability of these constructs using Cronbach’s alpha and Composite Reliability (CR), with both metrics requiring values above 0.70. Our findings indicate strong reliability for both constructs: place attachment (Cronbach’s alpha = 0.817, CR = 0.878) and behavioral intention (Cronbach’s alpha = 0.743, CR = 0.852), suggesting internal consistency within the measurement model (Hair et al., 2021). We then evaluate convergent validity through the Average Variance Extracted (AVE), with an acceptable threshold set at 0.5. The AVE values for place attachment (0.645) and behavioral intention (0.659) both exceed this benchmark, confirming adequate convergent validity. Discriminant validity is assessed using the Heterotrait-Monotrait ratio (HTMT). Our model meets these criteria as demonstrated in Table 3, with place attachment and behavioral intention showing an HTMT value under of 0.90, which supports their distinctiveness (Hair et al., 2017, 2021).

Turning to formative constructs, we first check for collinearity among indicators using the Variance Inflation Factor (VIF), with all indicators for placeness and place image recording VIF values below three, thus avoiding collinearity issues. The significance and relevance of the formative indicators were evaluated by analyzing their weight and loading using the bootstrap method with 10,000 replications. This method provided a robust and reliable evaluation of the indicators by resampling the data multiple times to account for the uncertainty in estimating weights and loadings (Sarstedt et al., 2020; Hair et al., 2021). The results showed that five formative indicators had insignificant weights and factor loadings below 0.5. However, two of these indicators were significant in terms of factor loading and were retained in the analysis (Sarstedt et al., 2020; Hair et al., 2021). Conversely, three formative indicators (PL02, PL03, and PIM02) were found to be insignificant (p > 0.05) and were removed from the model due to their factor loading values being far below the cutoff point. Therefore, after assessing all factors and constructs, the measurements are ready for evaluating the path and structural elements of our theoretical framework.

We assessed the structural model by examining significant path coefficients, t-values, and explained variance (R² and Q²), employing a two-tailed bootstrapping method with 10,000 samples for hypothesis testing. This robust method addresses the uncertainties in model parameter estimation through repeated data resampling (Sarstedt et al., 2020; Hair et al., 2021). Unlike covariance-based SEM (CB-SEM), PLS-SEM does not utilize model fit indices like CFI or TLI, as it is variance-based and instead relies on R² and Q² values for assessing model fit (Hair et al., 2021).

Our analysis revealed no collinearity issues, with inner VIF values remaining below 3. The Standardized Root Mean Squared Residual (SRMR) was 0.090, indicating an acceptable fit (Hu and Bentler, 1999). The model’s goodness of fit was gaged by the strength of each structural path, showing notable effects on place attachment (R² = 0.246, Q² = 0.142) and place image (R² = 0.251, Q² = 0.161), as well as a collective impact of placeness, place attachment, and place image on behavioral intention (R² = 0.353, Q² = 0.126), as detailed in Table 4.

The primary goal of our study was to examine how placeness influences behavioral intention. The results of hypothesis testing showed that three out of five direct hypotheses had significant relationships. H1, asserting a positive effect of placeness on place attachment, was confirmed with a path coefficient (β = 0.469, p < 0.001). H2 demonstrated that placeness significantly affects place image (β = 0.501, p < 0.001). H4 established that place attachment directly enhances behavioral intention (β = 0.484, p < 0.001). Thus, H1, H2, and H4 were supported, highlighting significant pathways in these relationships, particularly from place attachment to behavioral intention.

Conversely, H3 and H5 were not supported. H3, which assessed whether placeness directly influences behavioral intention, showed a positive but insignificant effect (β = 0.203, p > 0.05), suggesting that placeness alone may not significantly affect future visitor behavior, aligning with findings by Kang and Choi (2012). H5, proposing a positive impact of place image on behavioral intention, showed a negative, insignificant effect (β = −0.033, p > 0.05), indicating that public perception alone might not significantly influence revisitation behavior, suggesting a reevaluation of the influence of initial visit decisions based on place image.

Finally, our study emphasized the mediating roles of place attachment and place image in the relationship between placeness and behavioral intention. The mediation analysis revealed a significant positive indirect effect via place attachment (H6a, β = 0.240, p < 0.001), supporting its role as a mediator. However, the indirect effect via place image (H6b) was negative and not significant (β = −0.016, p > 0.05), raising questions about the effectiveness of urban planning and design in shaping public perception and influencing revisitation behavior (Table 4).