Drawing from self-categorization theory (SCT), this study aims to explore how individuals’ place-belonging needs, tied to social identity constructs such as local identity, attachment to tradition, and connectedness with nature, drive local food consumer behavior.
This study uses a sequential mixed methods design. To test the hypotheses, the authors first conducted a survey-based quantitative study using regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) with a sample of Italian residents (n = 495). This was followed by a qualitative study (n = 31), based on semi-structured depth interviews, which explored regional Italian consumers’ real-world experience of local food purchase and addressed the intention–behavior gap.
The quantitative analysis reveals that local identity, attachment to tradition, and connectedness with nature positively shape local food attitudes and drive purchase intention, with urban/rural residency significantly moderating the effects of attachment to tradition and connectedness with nature. The qualitative findings show that purchase intention translates into behavior when marketing cues emphasize these social identity, place-belonging needs.
The findings are generalizable to Global North regions with (post-)industrial trajectories similar to Italy’s but offer a basis for experimental studies examining the role of place in different local food purchase settings.
This research offers detailed strategic marketing insights to support the promotion of local food consumption in both the private and public sectors, countering global competition and enhancing consumer engagement in their local food system.
This research integrates the marketing and food geography literatures through a social psychology lens (SCT), quantitatively testing for the first time the role of place-belonging needs as drivers of local food purchase intention. Complementary fsQCA results provide critical nuance on the moderating role of consumers’ place of residence, while the qualitative study explains how self-categorization can shape behavioral outcomes in real-world contexts.
1. Introduction
Recent global challenges – such as geopolitical turmoil in Ukraine and the COVID-19 pandemic – have disrupted global food supply chains, prompting increased interest in the relocalization of food systems (EU Commission, 2023; Lever and Sonnino, 2022). This shift has spurred growing efforts from both public and private sectors to promote sustainable, place-based food consumption in North America (FSC, 2024), the UK (Welsh Government, 2024) and the European Union (EU Commission, 2023). As the United Nations recommends policymakers to redirect “finance to local stakeholders, empowering communities to make decisions about their own food systems” (United Nations Development Programme, 2024, p. 5), the rising ‘localist’ trend among consumers amid the cost-of-living crisis (Thomas, 2023) highlights the need for a deeper marketing understanding of how local consumers are driven to support their own food systems. However, while marketing research could offer invaluable insights into supporting local food networks (Memery et al., 2015), it still lags behind food geography in understanding local food consumer behavior, as it often overlooks the role of ‘place’ in shaping food choices at the cognitive level (Banerjee and Quinn, 2022). To address this gap, this paper advances an interdisciplinary research model that not only deepens theoretical understanding of local food consumption by highlighting the influence of context-specific cultural-geographical milieus in shaping local food purchase behavior, but also provides marketing practitioners and policymakers actionable insights for strategically increasing consumer engagement with local food systems at the city-region level (e.g. Lever and Sonnino, 2022).
Explorative consumer research (Banerjee and Quinn, 2022) suggests that consumers’ perception of rurality – a spatial concept conveying preindustrial values linked to an enhanced sense of place (Goszczyński and Wróblewski, 2020; Warnaby and Medway, 2013), which contrasts with urban productivist values (O’Neill, 2024) – is a baseline driver of local food purchase. Scholarship in the field of food geographies has already established the link between local food and place through the ideological construct of rurality (Goszczyński and Wróblewski, 2020). This link is based on the symbolic power of rural space to endow food products with localness status (Graciotti and McEachern, 2024), which satisfies consumers’ place-belonging needs (Palladino, 2020; Rodriguez, 2020) – a social identity construction process grounded in an individual’s search for an intimate need of feeling ‘at home’ in a place.
Heeding the Banerjee and Quinn (2022)’s call in the European Journal of Marketing for exploring “consumer constructions of their relationship with rurality” and “how this transmits into purchasing intention” (p. 1288), we aim to advance our understanding of local food purchase decisions by embedding local food consumer behavior in place. Particularly, we argue that if local food is inextricably linked with place (Kneafsey et al., 2021), and rurality signals place-belonging needs concerning local food consumers’ ‘local identity,’ ‘attachment to tradition,’ and ‘connectedness with nature’ (e.g. Goszczyński and Wróblewski, 2020; Graciotti and McEachern, 2024; Rodriguez, 2020), then such place-based social identity constructs will positively affect local food purchase. Therefore, this research goes beyond extant theories indicating that local food consumer behavior involves supporting local food producers (McEachern et al., 2010; Skallerud and Wien, 2019), thereby accommodating an individual’s egoistic and altruistic motives (Megicks et al., 2012), ultimately increasing willingness-to-pay a premium price for quality food (Feldmann and Hamm, 2015).
To achieve this aim, we draw from self-categorization theory (SCT) (Turner et al., 1987) to develop a research model of local food consumer behavior based on the contextual role of place-belongingness in forming individuals’ social identities (León, 2023). ‘Self-categorization’ refers to a social identity construction process whereby individuals (self-)define themselves as abstract group members depending on locally situated sociocultural and geographical contexts, ranging from narrower groups (e.g. ‘we, rural vs urban residents’ – Megicks et al., 2012) to broader ones (e.g. ‘we, members of cultural heritage’ or ‘natural community’ – Autio et al., 2013; Rodriguez, 2020). SCT posits that self-categorization shapes attitudes and intentions at the individual cognitive level, which translate into behavioral outcomes whenever social identity is salient (Hogg and Reid, 2006; Reynolds and Subasic, 2016). Therefore, we advance the following research questions:
What is the impact of consumers’ local identity, attachment to tradition, and connectedness with nature on their attitudes toward local food and purchase intention from an SCT perspective, considering the contingent role of urban vs rural place of residence?
What combinations of sociodemographic characteristics and place-based social identity constructs shape favorable attitudes toward local food among rural and urban consumers?
How does self-categorization translate consumers’ purchase intention into behavior based on their real-world experiences with local food purchase?
Using a sequential (QUAN→qual) mixed methods approach (e.g. Harrison and Reilly, 2011), this research makes three key contributions to the study of local food consumer behavior. First, it applies SCT to present the first interdisciplinary model that quantitatively examines the influence of place-based social identity constructs – local identity, attachment to tradition, and connectedness with nature – on consumers’ attitudes and purchase intention (Study 1), while also showing how these translate into real-world behavior through consumers’ lived experiences of local food choice (Study 2), thereby addressing the intention–behavior gap (Carrington et al., 2014). Second, it advances a novel understanding of local food purchase as a socio-cognitive process shaped by social identity cues, particularly when marketing aligns with consumers’ place-belonging needs across specific cultural-geographical contexts – thus challenging prevailing perspectives on local food consumer behavior in the field of marketing (e.g. Feldmann and Hamm, 2015). Third, it reveals how urban vs rural residency moderates these dynamics, identifying context-specific configurations that offer nuanced insights into the roles of place-based social identity cues in different urban/rural marketing contexts.
2. Literature review and hypotheses development
2.1 SCT and place-belongingness in the context of local food consumer behavior
SCT posits that self-identity develops not only through personal beliefs but also through membership in abstract social categories (Turner et al., 1987). It examines how shifts in self-perception (‘I’ to ‘we’) shape cognitive and behavioral processes and outcomes (Turner and Reynolds, 2012). Identity needs drive individuals to seek belonging through shared social values, symbols and stereotypes (Bal et al., 2015; León, 2023), creating an expectation to align with the ingroup’s reactions, judgments and behaviors (Turner and Reynolds, 2012). Thus, individuals form attitudes and behaviors based on group membership, guided by sociocultural and geographical cues (Crisp et al., 2022; León, 2023), often overriding personal traits (Turner et al., 1987). This psychological shift leads individuals to act in accordance with the values and beliefs signaled by perceived group membership according to the context at hand (Bal et al., 2015; Hogg and Reid, 2006; Turner and Reynolds, 2012).
This transition from individual to group identity fosters an increased sensitivity to the “shared, social, group-located properties of human beings” (Turner and Reynolds, 2012, p. 400). It enables individuals to behave in agreement with locally situated and embedded sociocultural values and beliefs (e.g. Åkestam et al., 2017; Crisp et al., 2022), which underpin the process of identity construction influencing consumer behavior (Thompson and Loveland, 2015). Therefore, SCT does not conceive of someone’s identity as static, but context-dependent and fluid, thus helping empirically mitigate the limitations of applying context-independent self-identity theories from other disciplines to consumer research due to its theoretical assumption concerning the alignment between attitudes developed from an individual’s ‘social identity needs’ (Banerjee and Quinn, 2022) and behavioral outcomes observed in decision-making contexts (Hogg and Reid, 2006).
SCT’s situated worldview has allowed scholars to associate the theory with the concept of ‘place-belongingness,’ which describes a feeling of membership to a geographically situated social system, its culture and environment (León, 2023). Consistent with SCT’s theoretical assumption that self-identity is multilayered and fluid, research shows that individuals can simultaneously identify with different place-based abstractions, such as “their neighborhood, city, region, country or continent,” depending on context (Belanche et al., 2021, p. 242). This conceptual synergy between SCT and place-belongingness becomes particularly relevant in the context of consumer research. Indeed, consumer perceptions of food localness are closely tied to the fulfillment of place-belonging needs from a marketing perspective (Rodriguez, 2020). Prior research identifies these needs in the self-construction of a local identity (Banerjee and Quinn, 2022; Memery et al., 2015), the desire to revive traditions (Autio et al., 2013; Balzano and Vianelli, 2022; Palladino, 2020) and the yearning to reconnect with an idyllic natural environment through rural imagery (Rodriguez, 2020; Tellström et al., 2006).
As local food consumer behavior unfolds as a decision-making process influenced by place-belonging needs, which are social identity aspirations leading to purchase (Banerjee and Quinn, 2022; Rodriguez, 2020), local food purchase allows individuals to express both personal and group identities simultaneously (Memery et al., 2015). From this perspective, SCT can help predict if consumers’ self-categorization into place-based social abstractions influences local food purchase in terms of a search for place-belongingness (e.g. Graciotti and McEachern, 2024; Palladino, 2020; Rodriguez, 2020), influencing attitudes, which in turn impact purchase intention, and actual behavior (Feldmann and Hamm, 2015; Hogg and Reid, 2006).
2.2 Local identity
‘Local identity’ represents a specific instance of self-categorization into a place-based (or locational, Memery et al., 2015) social group abstraction that is semantically connected to the values and beliefs regarding a territory as shared by a community – i.e. a local social system (Banerjee and Quinn, 2022; Memery et al., 2015; Rodriguez, 2020). In the context of local food purchase, consumers who identify with a specific locale develop a shared local food orthodoxy (a set of socially shared values and beliefs regarding what constitutes local vs nonlocal food based on their self-identity construction as residents belonging to an established social system – Graciotti and McEachern, 2024). In fact, food localness “has a specific meaning that defines [consumers’] identity” (Banerjee and Quinn, 2022, p. 1286), which refers to “belonging to a group of like-minded individuals” (Memery et al., 2015, p. 1214). This orthodoxy satisfies an individual’s socially constructed need to belong to place (Rodriguez, 2020), using the distinctive group properties historically characterizing a community’s local area – e.g. its symbols and cultural-geographical landmarks (Warnaby and Medway, 2013) – to develop “someone’s self-identity” (Memery et al., 2015, p. 1214). Thus, based on SCT, and recognizing that one’s local identity can shape attitudes based on group values and beliefs determining consumer behavior, we advance the following hypothesis:
High local identity positively influences attitudes toward local food.
2.3 Attachment to tradition
Drawing on the foundational principles of SCT, individuals do not perceive themselves solely as isolated entities (Turner et al., 1987; Turner and Reynolds, 2012). Rather, they position themselves within a broader milieu of shared characteristics and common beliefs within a given socio-cultural and geographical context (Crisp et al., 2022; León, 2023). Research shows that local food consumers feel attached to the cultural heritage of a place, including its gastronomic traditions (Balzano and Vianelli, 2022; Banerjee and Quinn, 2022; Palladino, 2020; Rodriguez, 2020). As proposed by Sharma (2010, p. 792), ‘attachment to tradition’ is a construct reflecting “a personal cultural orientation representing respect for traditional values, including hard work, non-materialism, benevolence, social consciousness, morality and respect for one’s heritage,” thus encompassing not only care for one’s cultural heritage, but also for the traditional methods of food production and distribution/retailing that are often perceived as less productivist than modern, industrial, conventional ones (Goszczyński and Wróblewski, 2020; Kneafsey et al., 2021; McEachern et al., 2010; Skallerud and Wien, 2019).
Hence, local food consumer behavior extends beyond material, individualistic experiences driven by the willingness to pay a premium price or egoistic (vs altruistic) motives, including health benefits (Feldmann and Hamm, 2015). In fact, it is imbued with symbolism, resonating with ‘agrarian,’ preindustrial traditions that local food products embody (Autio et al., 2013; Graciotti and McEachern, 2024). Given local food consumers’ social embeddedness in the cultural fabric of place (Kneafsey et al., 2021), and their attachment to a bygone food heritage (Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020), it is posited that attachment to tradition entails self-categorization into a (local) group’s shared set of traditions, thus positively influencing consumers’ attitudes toward local food. Therefore, we advance the following hypothesis:
A strong attachment to tradition positively influences attitudes toward local food.
2.4 Connectedness with nature
‘Connectedness with nature’, as described by Hartmann et al. (2016), represents the depth of an individual’s cognitive and emotional affinity with natural environments, particularly the value and joy derived from engaging with them. Research shows that local food consumers have a heightened inclination toward self-identifying with a preindustrial, agrarian consumer society that is more ‘connected’ with nature (Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020; Rodriguez, 2020). Graciotti and McEachern (2024) further emphasize this perspective by suggesting that local food consumers associate local food with a natural landscape imbued with preindustrial, rural (as opposed to industrial, urban) values and beliefs. This reflects a socioenvironmental desire to protect local natural produce and its gatekeepers, namely local farmers and small food producers (e.g. Rodriguez, 2020; Schmitt et al., 2017).
From an SCT perspective, feelings of connectedness with nature represent a key factor in an individual’s self-categorization with a more-than-human natural group/community (Mayer and Frantz, 2004). Therefore, we argue that, within the context of local food consumption, individuals can self-categorize as belonging to a social abstraction representing a society embedded in a “broader natural community,” who “feel a sense of kinship with it; view themselves as belonging to the natural world as much as it belongs to them; and view their welfare as related to the welfare of the natural world” (Mayer and Frantz, 2004, p. 505). Indeed, from a social psychology perspective, connectedness with nature indicates “the degree to which nature is included in one’s cognitive representation of self” (Samus et al., 2022, p. 2). Thus, connectedness with nature goes beyond an individual’s local identity construction as a member of a local group’s shared social value/belief system regarding the distinctive characteristics of their locale (Memery et al., 2015; Warnaby and Medway, 2013), but concerns the extent to which nature shapes an individual’s self-identity as a member of the natural community (Mayer and Frantz, 2004; Hartmann et al., 2016; Samus et al., 2022). Therefore, we advance the following hypothesis:
A strong sense of connectedness with nature positively influences attitudes toward local food.
2.5 The moderating role of consumers’ rural (vs urban) residency
Considering our reliance on SCT, consumers’ perceived urban-rural differences in terms of belonging should not be considered epistemologically obsolete a priori (Graciotti and McEachern, 2024), as they are place-based social abstractions that influence the concept of rurality, and, in turn, local food consumer behavior (e.g. Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020; Megicks et al., 2012; Tellström et al., 2006). Thus, going “beyond the existing, widely used socio-demographic variables of gender, age and education” (Banerjee and Quinn, 2022, p. 1287), we investigate the contingent role of urban/rural place of residence in influencing consumers’ attitudes toward local food.
The marketing and food geographies literatures present mixed views on whether urban and rural consumers have different attitudes toward local food depending on the perception of the values conveyed by rurality (e.g. Tellström et al., 2006). Research shows that, on the one hand, globalization has significantly reduced differences between urban and rural consumers, and that differences in residency type do not affect attitudes toward local food (Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020; McEachern and Warnaby, 2006). On the other hand, some researchers show that:
urban (vs rural) food consumers are less interested in local food consumption due to lower levels of community cohesion or kinship (Bianchi, 2017; Megicks et al., 2012);
rural (vs urban) food consumers are more inclined to develop an attachment to traditional values and beliefs (Carolan, 2022); and
urban (vs rural) food consumers are less affected by the natural landscapes where food production sites are typically located due to geographical proximity reasons (Rodriguez, 2020).
Therefore, we advance the following hypotheses:
The positive relationship between local identity and attitudes toward local food is weaker for consumers in urban areas compared to those in rural areas.
The positive relationship between attachment to tradition and attitudes toward local food is stronger for consumers in rural areas compared to those in urban areas.
The positive relationship between connectedness with nature and attitudes toward local food is weaker for consumers in urban areas compared to those in rural areas.
2.6 Purchase intention
The link between local food consumers’ place-belonging needs and purchase intention needs further development (Banerjee and Quinn, 2022; Rodriguez, 2020). SCT posits that before shaping behavior, self-categorization defines an individual’s attitudes in agreement with a group’s expectations or values as signaled by a geographical and sociocultural context (Crisp et al., 2022; León, 2023). Therefore, SCT assumes that the emergence of self-categorization at broader levels of social abstraction can lead to changes in attitudes and intentions, thus shaping behavioral outcomes (Reynolds and Subasic, 2016). As SCT argues that attitudes and behaviors will be highly consistent provided that social identity is salient (Hogg and Reid, 2006), we advance the following hypothesis:
Strong attitudes toward local food formed by social identity variables, such as local identity, attachment to tradition, and connectedness with nature positively affects purchase intention.
Figure 1 shows a graphical representation of our research model.
The diagram presents a conceptual model outlining the influence of personal and cultural factors on attitudes and intentions related to local food consumption. It features three primary predictors: local identity, attachment to tradition, and connectedness with nature. Each of these factors is connected by directional arrows to a central node representing attitudes toward eating local food. In turn, this attitudinal factor links to purchase intention. The model includes hypothesis labels from H1 to H7 along each path to indicate specific theoretical predictions, with both positive and negative influences illustrated. Arrows from some predictors also directly link to purchase intention, bypassing attitudes, suggesting both mediated and direct effects.Research model
Source: Authors’ own work
The diagram presents a conceptual model outlining the influence of personal and cultural factors on attitudes and intentions related to local food consumption. It features three primary predictors: local identity, attachment to tradition, and connectedness with nature. Each of these factors is connected by directional arrows to a central node representing attitudes toward eating local food. In turn, this attitudinal factor links to purchase intention. The model includes hypothesis labels from H1 to H7 along each path to indicate specific theoretical predictions, with both positive and negative influences illustrated. Arrows from some predictors also directly link to purchase intention, bypassing attitudes, suggesting both mediated and direct effects.Research model
Source: Authors’ own work
3. Methodology
A single-study methodology relying solely on intention measures may yield results that do not accurately reflect actual consumer behavior in real-world contexts (Carrington et al., 2014). To address the intention–behavior gap and gain deeper insights into how place-based social identity constructs influence local food purchase in alignment with SCT, we used a mixed methods design, drawing on quantitative and qualitative data sets addressing research questions (RQ1–RQ3) as part of the same research project, conducted between 2021 and 2024 (Creswell and Plano Clark, 2006; Guest, 2012; Harrison and Reilly, 2011).
We follow an ‘unequal-weight’ sequential design (Creswell and Plano Clark, 2006), where the ‘timing of integration’ of data sets (Guest, 2012) – which refers “more to when the data are analyzed and interpreted than to when the data are collected” (Creswell and Plano Clark, 2006, p. 81) – is central to their ‘purpose of integration’ (Guest, 2012), which is to “explain or expand on quantitative results” through qualitative data interpretation (Harrison and Reilly, 2011, p. 17). Specifically, we build on a survey-based quantitative study that carries more weight than the subsequent qualitative phase, which consists of semi-structured depth interviews investigating local food purchase behavior (Carrington et al., 2014).
This approach “seeks to provide a better understanding of the quantitative results” by enhancing their reliability (Harrison and Reilly, 2011, p. 16), thereby strengthening the paper’s theoretical contributions and practical implications (Creswell and Plano Clark, 2006; Cuesta‐Valiño et al., 2024). In the next sections, we will describe the quantitative (Study 1) and qualitative (Study 2) methods used in detail.
3.1 Study 1: a survey-based quantitative approach
3.1.1 Setting and sample.
Study 1 examines attitudes and purchase intention related to local food products and brands among Italian residents. Italy provides a unique context for investigating the influence of local identity, attachment to tradition, and connectedness with nature on local food consumer behavior for two key reasons. First, Italy’s strong culinary heritage positions food as central to cultural identity and social life (Graciotti and McEachern, 2024; Palladino, 2020). A nationwide appreciation for quality ingredients, seasonal produce and traditional preparation methods reflects a shared food culture that persists despite regional variation (Balzano and Vianelli, 2022). Second, Italy presents a distinctive interplay between globalization and localisms (O’Neill, 2024). While integrated into global cultural and economic systems, including international food trends and markets, Italian consumers continue to value locally sourced goods as expressions of identity and seasonal continuity. This duality makes Italy an appropriate context for exploring how individuals navigate tensions between globalizing influences and place-belongingness in local food consumption.
To gather data from Italian residents, we developed a tailored survey. Before its launch, the survey was informally piloted to ensure clarity and ease of completion. The average completion time during this phase was below ten minutes. Respondents were informed that their data would be used solely in an aggregated form to ensure confidentiality. Moreover, the survey was designed with an emphasis on preserving respondent anonymity. To minimize the risk of common method bias, respondents were not provided with any cues regarding the study’s specific objectives prior to or during the survey. Data collection was conducted using a multi-stage sampling strategy designed to balance feasibility with diversity in the sample, combining convenience sampling, targeting readily accessible networks such as online communities, with snowball sampling techniques, allowing consumer associations to share the survey within their networks. To further ensure data quality and reliability, the survey items were randomized in order, and select items were reverse-coded to mitigate response biases such as acquiescence or straight-lining (Groves et al., 2011).
A total of 503 responses were collected. Responses were considered valid if they met three inclusion criteria: Italian residency, complete data on latent construct indicators, as the specified estimation approach (using listwise deletion) requires casewise completeness for valid latent variable estimation (Kline, 2016), and consistent answers to embedded attention checks. As the survey targeted only Italian residents, all respondents met the residency criterion. Of the eight excluded cases, six failed the attention checks and two showed missing data across latent constructs. No systematic patterns of item nonresponse or subgroup concentration were observed, and exclusions were treated as random.
In Table 1, we report the sociodemographic characteristics of the 495 respondents included in this study. The sample exhibits representativeness in terms of urban-rural distribution, with 71.92% of respondents residing in urban areas and 28.08% in rural areas, closely aligning with Italy’s population structure as of 2024, where 71.5% of residents live in urban areas (Worldometer, 2024).
Sample characteristics
| Respondents’ characteristics | % | |
|---|---|---|
| Age | ||
| 18–24 | 79 | 15.96 |
| 25–34 | 202 | 40.81 |
| 35–44 | 69 | 13.94 |
| 45–54 | 63 | 12.73 |
| ≥ 55 | 80 | 16.16 |
| Prefer not to say | 1 | 0.20 |
| Missing values | 1 | 0.20 |
| Place of residence | ||
| Urban | 356 | 71.92 |
| Rural | 139 | 28.08 |
| Education | ||
| Less than primary school/prefer not to say | 9 | 1.82 |
| High school diploma | 205 | 41.41 |
| BSc | 77 | 15.56 |
| MSc | 130 | 26.26 |
| Master | 39 | 7.88 |
| PhD | 35 | 7.07 |
| Gender | ||
| Male | 215 | 43.43 |
| Female | 277 | 55.96 |
| Other/prefer not to say | 3 | 0.61 |
| Household income | ||
| ≤ 10,000 € | 61 | 12.32 |
| 10,000 € < income ≤ 20,000 € | 122 | 24.65 |
| 20,000 € < income ≤ 30,000 € | 104 | 21.01 |
| 30,000 €< income ≤ 40,000 € | 70 | 14.14 |
| 40,000 € < income ≤ 50,000 € | 52 | 10.51 |
| 50,000 € < income ≤ 60,000 € | 25 | 5.05 |
| ≥ 60,000 € | 43 | 8.69 |
| Missing values | 18 | 3.64 |
| Total 495 | ||
3.1.2 Measures.
The survey measured dependent and main independent variables using latent constructs. Table 2 reports the item list (seven-point Likert scale: 1 = strongly disagree, 7 = strongly agree), along with factor loadings, composite reliability (CR) and average variance extracted (AVE). Discriminant validity was supported through two complementary procedures. First, the square roots of the AVE for each construct exceeded the corresponding interconstruct correlations, in line with the Fornell–Larcker criterion (Fornell and Larcker, 1981). Second, all heterotrait–monotrait (HTMT) ratios of correlations fell below the recommended threshold of 0.85 (Henseler et al., 2014).
Items and reliability of latent variables
| Factor loadings | CR | AVE | |
|---|---|---|---|
| Please respond to the following questions considering your ‘local area’ as an area ranging within a 20–100 km radius from your place of residencePurchase intention (Bruner, 2009; Rodgers, 2004) Considering local food as a product that is produced, processed/transformed and distributed/retailed in your ‘local area,’ please rate the following statements on a scale from 1–7, where 1 indicates complete agreement with the statement on the left, and 7 indicates complete agreement with the statement on the right | 0.80 | 0.58 | |
| I’m likely to purchase local food (1) – I’m unlikely to purchase local food (7) | 0.76 | ||
| I would like to have more information about local food (1) – I would not like to have more information about local food (7) | 0.66 | ||
| I’m interested in local food (1) – I’m not interested in local food (7) | 0.85 | ||
| Attitude toward eating local food (Skallerud and Wien, 2019) | |||
| Considering local food as a product that is produced, processed/transformed and distributed/retailed in your ‘local area,’ please indicate how much you agree or disagree with the following statements | 0.72 | 0.87 | 0.63 |
| It is wise to eat local food | 0.93 | 0.92 | 0.80 |
| I feel very satisfied when I eat local food | 0.83 | ||
| Local food gives me a pleasant feeling | 0.66 | ||
| Local food tastes good | |||
| Local identity (Memery et al., 2015) | 0.92 | 0.80 | |
| Please indicate how much you agree or disagree with these statements | 0.83 | ||
| I identify strongly with this local area | 0.93 | ||
| I am very attached to this local area | 0.91 | ||
| This local area means a lot to me | |||
| Attachment to tradition (Bruner, 2019a;Sharma, 2010) | 0.90 | 0.65 | |
| Please indicate how much you agree or disagree with these statements | 0.66 | ||
| I am proud of my culture | 0.92 | ||
| Respect for tradition is important to me | 0.83 | ||
| I value a strong link to my past | 0.90 | ||
| Traditional values are important to me | 0.70 | ||
| I care a lot about my family history | |||
| Connectedness with nature (Bruner, 2019b;Hartmann et al., 2016) | 0.89 | 0.68 | |
| Please indicate how much you agree or disagree with these statements | 0.86 | ||
| When I am in natural environments, I feel connected with nature | 0.75 | ||
| It makes me sad to see natural environments destroyed | 0.95 | ||
| Spending time in nature makes me feel happy | 0.72 | ||
| I usually spend some of my time being in nature |
n = 495
Considering that there is no shared, unambiguous definition of local food in the literature (e.g. Banerjee and Quinn, 2022), a broad definition of ‘local food’ that is usually used in the European context was used, namely:
a possible definition is given in the Joint Research Centre (JRC) 2013 scientific and policy report on short food supply chains and local food systems: “a food system in which foods are produced, processed and retailed within a defined geographical area” (depending on the sources, within a 20 to 100 km radius approximately) (Augère-Granier, 2016, p. 3).
Therefore, respondents were asked to consider the local food of their local area as that which is produced, processed and retailed/distributed within a 20–100 km radius. The dependent variables in this study are attitudes toward eating local food and purchase intention. ‘Attitudes toward eating local food’ was measured using a four-item scale adapted from Skallerud and Wien (2019). This construct covers “general positive feeling statements that are often used to assess attitudes toward food objects and/or food behavior” (Skallerud and Wien, 2019, p. 83). ‘Purchase intention’ was measured using a three-item semantic differential scale adopted from Bruner (2009) and Rodgers (2004). The intention items captured respondents’ likelihood of purchasing, interest in obtaining more information, and overall interest in purchasing local food products and brands.
The key independent variables of this study are local identity, attachment to tradition, and connectedness with nature. ‘Local identity’ was measured using a three-item scale adapted from Memery et al. (2015). ‘Attachment to tradition’ was measured using a five-item scale borrowed from Sharma (2010) via Bruner (2019a). ‘Connectedness with nature’ was measured using a four-item scale borrowed from Hartmann et al. (2016) via Bruner (2019b).
The moderating variable of this study is place of residence, which was measured by asking respondents to self-classify themselves into either the urban or rural category. This operationalization follows the approach used by Megicks et al. (2012). In the analysis, rural respondents were assigned the value of 0, while urban ones were assigned the value of 1.
Moreover, the study included several control variables to account for individual characteristics that might influence the dependent variables. Age was controlled because consumer preferences often vary across different life stages. Gender was included as a control variable to account for potential differences in decision-making, consumption preferences, and engagement with food-related orientations. In the analysis, female respondents were assigned the value 0, male ones were assigned the value 1, and respondents identifying as other or ‘prefer not to say’ were assigned the value 2. Education was controlled to consider how varying levels of knowledge and critical thinking skills might shape awareness, evaluation, and perceptions of local food systems. Income was included to account for economic factors that may influence the affordability and prioritization of local food purchases. Individuals with higher income levels may have greater purchasing flexibility, while lower-income groups might prioritize price considerations.
3.1.3 Analytical technique.
As illustrated in Table 2, the latent constructs used in this study exhibited acceptable levels of reliability and validity, with factor loadings, CR and AVE exceeding recommended thresholds. Latent constructs were estimated using the statistical principles of congeneric approaches via the CLC Estimator software (Marzi et al., 2023).
To test the hypotheses, multiple regression analysis (Aiken et al., 1991) was conducted using STATA/MP 18.0. All variables were standardized prior to analysis to facilitate interpretation and comparison of coefficients across models. Also, robust standard errors were applied to address potential heteroskedasticity.
Building on prior research approaches (e.g. Ho et al., 2016; Kyrdoda et al., 2023), a fuzzy-set qualitative comparative analysis (fsQCA) was implemented to complement regression analysis. The fsQCA was executed in R version 4.4.2 (2024–10 - 31) using the ‘QCA’ package (Dusa, 2019). FsQCA integrates the depth of qualitative case study methods with the broader applicability of quantitative approaches (Pappas and Woodside, 2021). The analysis focused on the intermediate solution, with peripheral and core conditions identified following the guidelines of Pappas and Woodside (2021). A consistency threshold of 0.85 was applied, balancing the tradeoffs between inclusiveness and stringency – 0.80 allowing for more flexibility and 0.90 being more restrictive. This threshold was deemed optimal for identifying meaningful configurations. The fuzzy-set calibration was performed using the following anchors: the lower bound was set at the 5th percentile of the variable distribution, the crossover point was at the median and the upper bound was set at the 95th percentile.
3.2 Study 2: Qualitative interviews with local food consumers
Using qualitative methods in consumer research is deemed appropriate for addressing the intention-behavior gap in specific purchase contexts (Carrington et al., 2014), as it helps researchers gain a more complete picture of the behavior under investigation (Goulding, 2005; Thompson et al., 1990). Moreover, using phenomenology for the analysis of individuals’ discourses and practices about real-world experiences of local food purchase shaped by social identity needs is ontoepistemologically coherent with the theoretical lens we use in this paper (SCT), given its assumptions concerning the locally situated and socially embedded nature of self-categorization into context-dependent social abstractions that are signaled through place-based experiential cues (León, 2023; Turner et al., 1987). In this regard, SCT helps us to override the limits of empirical studies investigating how purchase intention translates into purchase behavior (Carrington et al., 2014), by focusing on how individual identities are ‘reshaped’ when they interact with place-belonging needs (León, 2023).
Considering the alignment between SCT and the situated, context-dependent nature of phenomenological qualitative consumer research (Thompson et al., 1990), local food purchase behavior needs to be understood as the result of discourses and practices embedded in a culturally and geographically specific ‘local’ social system to collect relevant experiential data about the phenomenon (e.g. Warnaby and Medway, 2013). Therefore, this study (Study 2) empirically locates participants within a specific socio-cultural and geographical context, i.e. the Italian region of Marche – a region with a unique food identity (Graciotti and McEachern, 2024). This area, part of central-eastern Italy, has historically lacked focus in the marketing and food geographies literatures (e.g. O’Neill, 2024), albeit its unique rural landscape, which intertwines with urban areas and industrial districts, presenting an interesting hybrid socioeconomic context, where the modern forces of globalization have impacted a long history of preindustrial agrarian economy (Goszczyński and Wróblewski, 2020). The agricultural and farming heritage of Marche significantly characterizes local production and consumption discourses and practices influencing locals’ conceptualization of food localness (Graciotti and McEachern, 2024), similar to other postpeasant societies impacted by late globalization processes in the latter decades of the 20th century (e.g. Goszczyński and Wróblewski, 2020).
In particular, Study 2 draws on qualitative data that help explain the quantitative results from Study 1 (Creswell and Plano Clark, 2006; Guest, 2012; Harrison and Reilly, 2011). To understand how purchase intention translates into real-world purchase behavior from an SCT perspective, we recruited a sample of regular patrons of various ‘alternative’ marketing channels (e.g. local farmers’ markets, direct purchase from producers, community-supported agriculture – Goszczyński and Wróblewski, 2020; McEachern and Warnaby, 2006; McEachern et al., 2010; O’Neill, 2024) in the Italian region of Marche. These individuals are local Marche residents and acted as gatekeepers in a snowball sampling process (Carrington et al., 2014), enabling us to reach other local participants from Marche who actively engage in their local food system by purchasing local food products at least once a week. This sampling strategy allowed us to collect data from individuals for whom local food products and brands hold particular value in their grocery shopping, thereby capturing the uniquely situated, culturally and geographically embedded decision-making processes surrounding place-based, local food purchase behavior (e.g. Carrington et al., 2014; Thompson et al., 1990). We conducted 40–80-min semi-structured depth interviews online over a ten-month period (e.g. Carrington et al., 2014), reaching saturation with 31 participants (anonymized in Table 3) once information became redundant (Goulding, 2005). Transcripts were deductively coded using NVivo 1.7.2, identifying the place-based social identity constructs from Study 1 – ‘local identity,’ ‘attachment to tradition,’ and ‘connectedness with nature’ – as they emerged from participants’ comments regarding their real-world local food purchase experiences (Fife and Gossner, 2024).
Characteristics of interview participants
| Participants | Gender | Age | Job | Residence |
|---|---|---|---|---|
| P1 | F | 31 | Entrepreneur | Rural |
| P2 | M | 29 | Entrepreneur | Urban |
| P3 | M | 58 | Manager | Urban |
| P4 | F | 39 | Entrepreneur | Rural |
| P5 | M | 46 | Manager | Urban |
| P6 | F | 34 | Entrepreneur | Urban |
| P7 | M | 42 | Entrepreneur | Urban |
| P8 | M | 39 | Employee | Urban |
| P9 | M | 54 | Manager | Urban |
| P10 | M | 36 | Entrepreneur | Rural |
| P11 | M | 44 | Manager | Urban |
| P12 | F | 40 | Employee | Urban |
| P13 | F | 54 | Employee | Urban |
| P14 | M | 76 | Retired | Rural |
| P15 | F | 55 | Freelancer | Urban |
| P16 | M | 63 | Retired | Rural |
| P17 | M | 50 | Employee | Rural |
| P18 | F | 60 | Retired | Urban |
| P19 | M | 25 | Employee | Rural |
| P20 | F | 54 | Unemployed | Rural |
| P21 | F | 34 | Unemployed | Urban |
| P22 | M | 30 | Employee | Rural |
| P23 | F | 41 | Unemployed | Urban |
| P24 | F | 41 | Employee | Rural |
| P25 | M | 37 | Freelancer | Urban |
| P26 | M | 50 | Entrepreneur | Urban |
| P27 | F | 31 | Freelancer | Urban |
| P28 | F | 26 | Employee | Rural |
| P29 | F | 42 | Freelancer | Urban |
| P30 | F | 42 | Employee | Urban |
| P31 | M | 28 | Manager | Urban |
4. Results
4.1 Quantitative survey
4.1.1 Hypotheses test.
Table 4 presents the descriptive statistics of the variables, showing that none of the independent variables had correlations with coefficients exceeding 0.5. In addition, no significant multicollinearity issues were identified, as all variance inflation factor (VIF) scores were well below the recommended threshold of 10 (Gujarati, 2003). Moreover, the Harman’s one-factor test revealed that a single factor explained 20.14% of the total variance, indicating that common method bias is unlikely to have a substantial impact on the results.
Descriptive statistics
| Mean | SD | Min. | Max. | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (1) Attitudes toward local food | 5.943 | 1.053 | 1.000 | 7.000 | 1.000 | |||||||||
| (2) Purchase intention | 4.467 | 1.122 | 1.000 | 7.000 | 0.303*** | 1.000 | ||||||||
| (3) Local identity | 4.671 | 1.672 | 1.000 | 7.000 | 0.229*** | −0.085+ | 1.000 | |||||||
| (4) Attachment to tradition | 5.039 | 1.457 | 1.000 | 7.000 | 0.276*** | 0.149*** | 0.278*** | 1.000 | ||||||
| (5) Connectedness with nature | 6.032 | 1.257 | 1.000 | 7.000 | 0.209*** | 0.021 | 0.305*** | 0.078+ | 1.000 | |||||
| (6) Age | 2.737 | 1.344 | 1.000 | 7.000 | −0.035 | 0.014 | 0.028 | 0.139** | 0.050 | 1.000 | ||||
| (7) Place of residence (urban vs rural) | 0.719 | 0.450 | 0.000 | 1.000 | −0.075+ | −0.037 | −0.172*** | 0.036 | −0.167*** | 0.072 | 1.000 | |||
| (8) Gender | 0.446 | 0.510 | 0.000 | 2.000 | −0.170*** | −0.101* | −0.043 | −0.166*** | −0.070 | −0.018 | 0.071 | 1.000 | ||
| (9) Education | 3.182 | 1.293 | 1.000 | 6.000 | 0.009 | 0.083+ | −0.115* | −0.132** | −0.020 | −0.003 | 0.015 | −0.044 | 1.000 | |
| (10) Income | 3.374 | 1.740 | 1.000 | 7.000 | 0.012 | 0.010 | −0.032 | 0.102* | 0.026 | 0.232*** | 0.008 | 0.069 | 0.231*** | 1.000 |
+p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001, n = 495
Table 5 summarizes the estimated coefficients from the multiple regression models. For attitudes toward local food, the results are presented incrementally, from Model 1 (control variables only) to Model 8 (full model). Notably, the results remain consistent across all models in terms of both statistical significance and direction of effects. For local food purchase intention, Model 9 includes only attitudes toward local food as independent variable, while Model 10 also introduces control variables.
Multiple regression analysis
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | Model 9 | Model 10 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Hypothesis | Attitudes | Attitudes | Attitudes | Attitudes | Attitudes | Attitudes | Attitudes | Attitudes | Intention | Intention | |
| Constant | −0.000 (0.044) | −0.000 (0.042) | −0.000 (0.042) | −0.004 (0.043) | −0.032 (0.044) | −0.000 (0.042) | −0.042 (0.042) | −0.045 (0.042) | 0.000 (0.043) | 0.000 (0.043) | |
| Local identity | H1 | 0.119* (0.050) | 0.223*** (0.049) | 0.117* (0.051) | 0.135** (0.047) | 0.147** (0.045) | |||||
| Attachment to tradition | H2 | 0.231*** (0.048) | 0.283*** (0.047) | 0.231*** (0.046) | 0.234*** (0.044) | 0.228*** (0.045) | |||||
| Connectedness with nature | H3 | 0.148* (0.068) | 0.248*** (0.064) | 0.156* (0.066) | 0.198** (0.061) | 0.201** (0.062) | |||||
| Local identity × place of residence | H4 | −0.000 (0.046) | −0.018 (0.046) | −0.023 (0.045) | |||||||
| Attachment to tradition × place of residence | H5 | 0.115** (0.037) | 0.148*** (0.037) | 0.152*** (0.036) | |||||||
| Connectedness with nature × place of residence | H6 | −0.192** (0.070) | −0.199** (0.072) | −0.211** (0.076) | |||||||
| Attitudes toward local food | H7 | 0.303*** (0.044) | 0.295*** (0.046) | ||||||||
| Age | −0.042 (0.053) | −0.079 (0.050) | −0.052 (0.051) | −0.065 (0.050) | −0.074 (0.053) | −0.096+ (0.049) | 0.028 (0.043) | ||||
| Place of residence | −0.060 (0.043) | −0.025 (0.041) | −0.022 (0.041) | −0.068 (0.042) | 0.013 (0.045) | 0.033 (0.043) | −0.015 (0.043) | ||||
| Gender | −0.169*** (0.043) | −0.113** (0.043) | −0.161*** (0.042) | −0.121** (0.043) | −0.149*** (0.043) | −0.110** (0.042) | −0.045 (0.044) | ||||
| Education | −0.005 (0.045) | 0.051 (0.043) | 0.019 (0.044) | 0.042 (0.044) | −0.003 (0.044) | 0.049 (0.042) | 0.082+ (0.044) | ||||
| Income | 0.035 (0.047) | 0.003 (0.043) | 0.038 (0.046) | 0.006 (0.043) | 0.045 (0.045) | 0.029 (0.043) | −0.016 (0.041) | ||||
| n | 495 | 495 | 495 | 495 | 495 | 495 | 495 | 495 | 495 | 495 | |
| Adjusted R2 | 0.035 | 0.146 | 0.083 | 0.118 | 0.095 | 0.123 | 0.168 | 0.192 | 0.092 | 0.102 | |
| AIC | 1398.114 | 1343.498 | 1377.101 | 1357.583 | 1370.207 | 1346.674 | 1326.499 | 1322.340 | 1359.989 | 1364.691 | |
| BIC | 1423.341 | 1381.339 | 1410.738 | 1391.220 | 1403.843 | 1363.492 | 1355.931 | 1372.795 | 1368.398 | 1394.123 | |
Robust standard errors in parentheses +p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001
H1 posits that a strong local identity positively influences attitudes toward local food, while a weak local identity negatively affects them. In the full model for attitudes (Model 8), the coefficient for local identity is positive and statistically significant (β = 0.147, p < 0.01), supporting H1. H2 suggests that a strong attachment to tradition positively influences attitudes toward local food, with a weak attachment having a negative effect. In Model 8, the coefficient for attachment to tradition is positive and highly significant (β = 0.228, p < 0.001), providing strong support for H2. H3 predicts that a strong sense of connectedness with nature positively influences attitudes toward local food, while a weaker connection negatively affects them. Model 8 shows a positive and significant coefficient for connectedness with nature (β = 0.201, p < 0.01), supporting H3. H4 proposes that the positive relationship between local identity and attitudes toward local food is weaker for urban consumers compared to rural ones. In Model 8, the interaction term for local identity and place of residence is not significant (β = −0.023, p > 0.10), thus not supporting H4. H5 posits that the positive relationship between attachment to tradition and attitudes toward local food is stronger for rural consumers compared to urban ones. The interaction term for attachment to tradition and place of residence in Model 8 is positive and significant (β = 0.152, p < 0.001), supporting H5. H6 predicts that the positive relationship between connectedness with nature and attitudes toward local food is weaker for urban consumers than rural ones. In Model 8, the interaction term for connectedness with nature and place of residence is negative and significant (β = −0.211, p < 0.01), supporting H6. H7 states that attitudes toward local food positively influence intentions to purchase local food. In the full model for purchase intention (Model 10), the coefficient for attitudes is positive and highly significant (β = 0.295, p < 0.001), providing strong support for H7.
Model 8 was the optimal specification for attitudes toward local food, with an adjusted R2 of 0.192, the lowest AIC (1322.340) and a competitive BIC (1372.795), indicating strong explanatory performance relative to its complexity. For purchase intention, Model 10 performed best, with an adjusted R2 of 0.102 and the lowest AIC (1364.691), despite a marginally higher BIC compared to Model 9.
Figure 2 illustrates the interaction effect related to H5. As the figure shows, attachment to tradition predicts more favorable attitudes toward local food, with a stronger effect in urban settings. Attitudes improve with attachment to tradition in both groups, but more markedly among urban respondents. Moreover, Figure 3 (related to H6) shows a significant moderation by place of residence (Model 5, interaction = −0.192, p = 0.007), with connectedness with nature more strongly associated with positive attitudes toward local food in rural areas. While attitudes improve in both contexts as connectedness increases, the slope is steeper in rural settings.
The graph illustrates the relationship between attachment to tradition and attitudes toward eating local food, with values ranging from negative 1 to positive 1 on the vertical axis. The horizontal axis represents levels of attachment to tradition, marked from low to high. Two lines represent different population groups: a dashed line for rural participants and a solid line for urban participants. Both lines trend upward, showing that greater attachment to tradition is associated with more positive attitudes toward eating local food. The lines differ in slope, with the rural group's line appearing steeper, indicating a stronger relationship. A key is provided for distinguishing the lines.The moderation effect between attachment to tradition and place of residence (urban vs rural)
Source: Authors’ own work
The graph illustrates the relationship between attachment to tradition and attitudes toward eating local food, with values ranging from negative 1 to positive 1 on the vertical axis. The horizontal axis represents levels of attachment to tradition, marked from low to high. Two lines represent different population groups: a dashed line for rural participants and a solid line for urban participants. Both lines trend upward, showing that greater attachment to tradition is associated with more positive attitudes toward eating local food. The lines differ in slope, with the rural group's line appearing steeper, indicating a stronger relationship. A key is provided for distinguishing the lines.The moderation effect between attachment to tradition and place of residence (urban vs rural)
Source: Authors’ own work
The line graph plots attitudes toward eating local food against connectedness with nature on a two-axis grid. The vertical axis ranges from negative 1 to positive 1 and represents attitudes toward eating local food. The horizontal axis shows connectedness with nature, progressing from low to high. Two distinct lines represent the two population groups: a dashed line for rural populations and a solid line for urban populations. The rural line displays a gentle upward trend, while the urban line rises more steeply, indicating that urban individuals show stronger positive shifts in attitude as connectedness with nature increases. The graph compares how nature connection relates differently to food attitudes in rural and urban contexts. A title at the top reinforces the graph’s focus on these relationships.The moderation effect between connectedness with nature and place of residence (urban vs rural)
Source: Authors’ own work
The line graph plots attitudes toward eating local food against connectedness with nature on a two-axis grid. The vertical axis ranges from negative 1 to positive 1 and represents attitudes toward eating local food. The horizontal axis shows connectedness with nature, progressing from low to high. Two distinct lines represent the two population groups: a dashed line for rural populations and a solid line for urban populations. The rural line displays a gentle upward trend, while the urban line rises more steeply, indicating that urban individuals show stronger positive shifts in attitude as connectedness with nature increases. The graph compares how nature connection relates differently to food attitudes in rural and urban contexts. A title at the top reinforces the graph’s focus on these relationships.The moderation effect between connectedness with nature and place of residence (urban vs rural)
Source: Authors’ own work
4.1.2 Robustness test.
To inspect the robustness of the findings, additional analyses were conducted. Multiple regressions were performed both with and without control variables to evaluate the stability of the observed relationships (Aiken et al., 1991). These robustness checks yielded consistent results, as observed in Models 6, 7 and 9 of Table 5, confirming the stability and validity of the initial findings. In addition, to enhance the accuracy of the results, latent constructs were re-estimated using parallel measurement models instead of congeneric approaches. The recomputed models retained the same directionality and statistical significance of coefficients, further substantiating the robustness of the findings. Finally, Jackknife Resampling techniques (Miller, 1974) were applied to evaluate the influence of a small group of observations on the results. By excluding few observations at a time and reestimating the models, we inspected that the coefficients remained stable across iterations, supporting robustness to data perturbation.
4.1.3 Results of the fsQCAs.
Tables 6 and 7 present the fsQCA results for rural and urban residents, respectively, focusing on attitudes toward local food. For rural residents, the eight configurations reveal a stronger and more consistent emphasis on environmental and sociocultural rootedness. Connectedness with nature and attachment to tradition often function as positive core conditions, signaling that proximity to and engagement with the natural environment remain salient in shaping favorable attitudes toward local food. Low income also appear regularly, but its influence is often amplified when combined with other demographic variables (such as age, gender and education), which show less persistent effects.
Results of fsQCA analysis for rural residents
| Solutions | ||||||||
|---|---|---|---|---|---|---|---|---|
| Configurations | Path 1 | Path 2 | Path 3 | Path 4 | Path 5 | Path 6 | Path 7 | Path 8 |
| Local identity | ● | ● | ● | |||||
| Attachment to tradition | ● | ● | ||||||
| Connectedness with nature | ● | ● | ||||||
| Age | ⊗ | ● | ⊗ | ⊗ | ||||
| Gender | ● | ⊗ | ⊗ | |||||
| Education | ● | ⊗ | ⊗ | |||||
| Income | ⊗ | ⊗ | ⊗ | ⊗ | ||||
| Consistency | 0.849 | 0.719 | 0.792 | 0.787 | 0.852 | 0.853 | 0.762 | 0.884 |
| Raw coverage | 0.481 | 0.461 | 0.489 | 0.556 | 0.278 | 0.368 | 0.343 | 0.352 |
| Unique coverage | 0.028 | 0.040 | 0.036 | 0.078 | 0.006 | 0.001 | 0.002 | 0.003 |
| Overall solution consistency | 0.700 | |||||||
| Overall solution coverage | 0.880 | |||||||
Black circles (●) indicate the presence of a condition, and circles with (⊗) indicate its absence. Large circle: core condition; small circle: peripheral condition; blank space: 'do not care' condition
Results of fsQCA analysis for urban residents
| Solutions | |||||||
|---|---|---|---|---|---|---|---|
| Configurations | Path 1 | Path 2 | Path 3 | Path 4 | Path 5 | Path 6 | Path 7 |
| Local identity | ● | ● | ● | ||||
| Attachment to tradition | ● | ● | ● | ● | |||
| Connectedness with nature | ⊗ | ● | |||||
| Age | ⊗ | ⊗ | ⊗ | ||||
| Gender | ⊗ | ⊗ | ⊗ | ⊗ | |||
| Education | ⊗ | ⊗ | ⊗ | ||||
| Income | ⊗ | ⊗ | ⊗ | ⊗ | |||
| Consistency | 0.727 | 0.800 | 0.822 | 0.856 | 0.849 | 0.845 | 0.869 |
| Raw coverage | 0.325 | 0.299 | 0.365 | 0.367 | 0.303 | 0.365 | 0.302 |
| Unique coverage | 0.073 | 0.011 | 0.027 | 0.046 | 0.015 | 0.031 | 0.021 |
| Overall solution consistency | 0.748 | ||||||
| Overall solution coverage | 0.681 | ||||||
Black circles (●) indicate the presence of a condition, and circles with (⊗) indicate its absence. Large circle: core condition; small circle: peripheral condition; blank space: 'do not care' condition
Urban configurations present a different structure. Unlike the rural model, where connectedness with nature only contributes positively, in some urban paths it operates as a negative core condition. While sociocultural dimensions – particularly local identity and attachment to tradition – are still influential, their appearance is more often combined by demographic characteristics. Gender (female) frequently acts as a core condition in the urban set, suggesting a more pronounced role of gendered attitudes or behaviors in local food-related preferences in those environments. Moreover, income appears consistently as a negative core condition across several urban configurations, reinforcing the relevance of economic constraints in limiting local food attitudes among urban residents.
In terms of solution quality, both rural and urban models demonstrate acceptable to strong consistency levels across individual paths, with overall consistency reaching 0.700 for rural and 0.748 for urban residents. Coverage statistics are robust, particularly for rural residents (solution coverage = 0.880), though unique coverage remains modest in both contexts. This suggests overlapping explanatory patterns, reinforcing the value of interpreting configurations holistically rather than discretely.
4.2 Qualitative study: real-world experiences of local food purchase
The findings of the follow-up qualitative analysis confirm that participants’ place-belonging needs related to the social identity constructs (i) local identity; (ii) attachment to tradition; and (iii) connectedness with nature play a key role in facilitating the decision-making process leading to local food purchase in real-world scenarios, thus providing valuable insights into how self-categorization translates consumers’ purchase intention into actual behavior.
First, regarding the role of local identity in facilitating local food purchase, our participants show that local food products, brands and producers/retailers should signal shared symbolic territorial values and beliefs for purchase to occur. In particular, participants show that geographical symbols [e.g. “the soil and the hills of our territory” (P19)] help them self-categorize in a meaningful, everyday community environment (Warnaby and Medway, 2013) – a symbolic ‘landscape’ (Graciotti and McEachern, 2024) they share with fellow locals (their ingroup – Turner et al., 1987). These identity cues must convey symbolic information concerning “where food is farmed, the person who farms it, and the place where it is sold” (P1) by highlighting “the social and historical aspects of local food, namely the fact that it is deeply rooted in our territory” (P6) – i.e. the distinctive, situated properties making someone’s sense of place “different” due to the lived experience of a “specific habitat” (P11). Thus, local consumers can “resonate” (P25) with food products and brands’ localness, a feeling of identifying with a place which facilitates local food purchase:
Purchasing local food satisfies me because it is from the territory where the ingredient or product is processed and finished. It is tied to the soil and hills of our territory (P19).
Local food identifies a territory. It’s clear that there’s a difference between buying a jar of spinach and buying a jar of paccasassi [wild sea fennel, a typical product of the Ancona area]. Knowing that it is a different food, you pay more for it compared to others. You seek it out and know it’s worth it. This plant grows in a specific habitat which cannot be reproduced elsewhere (P11).
Second, regarding the role of attachment to tradition in facilitating local food purchase, local consumers are more likely to purchase local food when marketing cues evoke a rural local food heritage which they managed to experience during their upbringing – especially if they have never moved or relocated from their place of residence (Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020). Interestingly, however, we found that an area’s local food heritage can also be ‘acquired’ if individuals relocate from other regions, as in the case of P17, who moved from Northern Italy to Marche and embraced the shared ‘foodways’ of this region’s sociocultural system (Kneafsey et al., 2021). In line with SCT, P17 exemplifies the fluidity and context-dependence of self-identity construction through the satisfaction of place-belonging needs (León, 2023):
A few years ago, when I moved to this town – which in the 90s was still a rural village, I developed a passion for the countryside. I bought a small piece of land and, like many others here, I became a weekend farmer. This brought me closer to local food products. Compared to my childhood home, we absolutely didn’t do this (P17).
When I make a purchase, I always choose food products with a certain history – tradition attracts me. However, that tradition has to be local. Tradition has enabled local farming and breeding (P14).
Third, connectedness with nature is also a key social identity cue that facilitates local food purchase, stemming from participants’ sense of belonging to a local (natural) environment, which they seek to protect by distinguishing between local food producers/retailers who share their eco-conscious place-belonging need and those who do not: “the true value of local food is respect for nature” (P18). In line with SCT, we found that participants self-categorize with producers/retailers within a broader human-nature community (Mayer and Frantz, 2004). In particular, when products/brands convey respect for soil and animal welfare, local food purchase is further facilitated, especially through direct marketing channels that reduce the perceived producer–consumer gap (McEachern et al., 2010; Thomas, 2023) – provided that local food producers are “able to establish the right relationship with the consumer,” as “sometimes, they are unprepared to explain their products and help you understand their true value” (P18):
I love to go to producers. They are welcoming, they talk to you about the countryside and the soil (P13).
I feel very at ease with the products that come from here in terms of potential pesticides or chemical products that might be in the soil and could harm the food (P28).
For me, animal welfare is very important. That’s why I joined this local community-supported-agriculture group, because they monitor this farm. It’s a well-known farm, and I know they treat the animals well. Even though, unfortunately, the animals live the lives they do, at least they are well-treated during their lives (P12).
5. Discussion and conclusions
Drawing on SCT, this paper adopts a sequential mixed methods design (quantitative and qualitative) to examine how local food consumer behavior is shaped by social identity needs linked to place-belongingness (Banerjee and Quinn, 2022; León, 2023). It proposes a research model showing that local food purchase behavior is driven by consumers’ construction of self-identity through the satisfaction of place-belonging needs – specifically, local identity, attachment to tradition, and connectedness with nature – via self-categorization across different levels of place-based social abstraction (León, 2023; Rodriguez, 2020). Focusing on Italian consumers, Study 1 shows that these constructs positively influence attitudes toward local food, which in turn drive purchase intention, while also considering the moderating effect of urban/rural place of residence. An fsQCA further explores how place-belonging needs shape favorable attitudes across rural and urban sociodemographic configurations. The follow-up qualitative study (Study 2) deepens these findings by investigating how purchase intention translates into real-world behavior (Carrington et al., 2014), revealing how place-belonging cues in decision-making contexts facilitate local food purchase. Together, Studies 1 and 2 show that attitudes and behaviors align closely when self-categorization with place-based social identity constructs is salient (Hogg and Reid, 2006; Reynolds and Subasic, 2016).
5.1 Theoretical contributions
This paper makes multiple theoretical contributions. First, this research presents the first interdisciplinary study to quantitatively test the influence of different place-based social identity constructs – specifically, local identity, attachment to tradition, and connectedness with nature – on local food consumers’ attitudes and purchase intention within a single research model (Study 1), building on recent exploratory qualitative research in the field (Banerjee and Quinn, 2022; Goszczyński and Wróblewski, 2020; Graciotti and McEachern, 2024; Rodriguez, 2020). In this regard, this research enriches the marketing literature by introducing SCT as a crucial lens for embedding local food consumer behavior in ‘place,’ offering an original and interdisciplinary application of this social psychology framework at the intersection of consumer and food geography research.
Second, by drawing on SCT, this research shows that certain commodities – such as local food products – not only shape and reinforce consumers’ self-identity (e.g. Memery et al., 2015), but also facilitate a shift from individual to social identity construction. This shift is driven by the need to belong to social groups at varying levels of abstraction (Turner et al., 1987; Turner and Reynolds, 2012), including identification with the broader natural community (Mayer and Frantz, 2004). In doing so, the study advances our understanding of local food consumer behavior in marketing as a place-based, sociocognitive phenomenon (e.g. Banerjee and Quinn, 2022). Specifically, the combination of our quantitative and qualitative findings suggests that local food consumer behavior unfolds through a process of self-categorization, driven by individuals’ perception of social identity cues that highlight consumers’ place-belonging needs – needs that are satisfied through the act of purchasing local food, depending on marketing capability to communicate local consumers’ everyday sense of place in alignment with specific cultural-geographical contexts (e.g. Warnaby and Medway, 2013).
In this regard, by challenging traditional local food marketing research focused on individual cognitive barriers and willingness-to-pay (Banerjee and Quinn, 2022; Feldmann and Hamm, 2015), we highlight the importance of social psychological context in local food consumer behavior and offer a fresh perspective through our examination of urban vs rural residency differences, as these can reflect cultural-geographical and social identity variations among local food consumers (Banerjee and Quinn, 2022; Carolan, 2022; O’Neill, 2024). Although no significant difference emerges between urban and rural consumers in how local identity shapes attitudes, fsQCA results reveal that local identity is a key component in several configurations driving favorable attitudes in both groups. This underscores the role of the moderation effect of place of residency on local identity in context-specific local food purchase scenarios (e.g. Banerjee and Quinn, 2022), even if its average effect is not statistically significant. This is further supported by Study 2 findings, where local identity emerges as a key facilitator of local food purchase among a small sample of both urban and rural residents who consistently value food ‘localness’ (Graciotti and McEachern, 2024) in their grocery shopping.
Third, while we expected connectedness with nature to have a stronger moderating effect among rural (vs urban) consumers (Autio et al., 2013; Rodriguez, 2020) – a finding also supported by the fsQCA results, where demographic variables were largely peripheral – we find that attachment to tradition plays a greater (positive) moderating role among urban (vs rural) consumers. This finding marks a shift from its usual association with rural residents in local food consumption contexts (Bianchi, 2017; Carolan, 2022; Megicks et al., 2012). Interpreting this moderating effect of place of residence in light of the fsQCA results, connectedness with nature appears substantially less relevant than attachment to tradition for urban (vs rural) consumers. This inversion may suggest that environmental orientation and self-categorization into a more-than-human natural community (Mayer and Frantz, 2004) in urban contexts may be decoupled from – or even in tension with – the development of local food attitudes. This may reflect more complex relationships with nature among urban residents, shaped by distinct urban lifestyles (e.g. Carolan, 2022; O’Neill, 2024).
5.2 Practical implications
This research provides several recommendations for marketing practitioners and policymakers. In particular, our results offer actionable insights for local food producers and marketing practitioners to develop strategies that align place, people, and product (Palladino, 2020), fostering consumers’ satisfaction of place-belonging needs. The fsQCA findings offer clear segmentation guidance: among rural consumers, favorable attitudes toward local food are shaped by connectedness with nature and, often, low income, reflecting strong reliance on mutual aid (Leipämaa-Leskinen, 2021; Skallerud and Wien, 2019) and an aspiration to support soil and animal welfare (Schmitt et al., 2017). Here, marketing should highlight land stewardship as well as antiproductivist farming and production practices through storytelling and cross-sector community partnerships (Lever and Sonnino, 2022; Schmitt et al., 2017; Welsh Government, 2024). For example, rural producers can invest in making production sites accessible to the public, fostering a sense of shared belonging to the place commonly associated with the origin of local food (Graciotti and McEachern, 2024; Rodriguez, 2020).
In urban contexts, low income remains relevant, but attachment to tradition – especially among respondents who identified their gender as ‘female’ – plays a stronger role than connectedness with nature. Preindustrial food heritage and socially oriented marketing channels should therefore be prioritized, such as farmers’ markets, and urban community farming (McEachern et al., 2010; O’Neill, 2024; Palladino, 2020). In supermarkets, partnerships with rural producers and direct storytelling can highlight the natural connectedness and cultural significance of both local food production sites and products, while retailers can use signage to promote sustainable production values (e.g. Thomas, 2023).
For policymakers aiming to build a more sustainable consumer society through place-based food systems (EU Commission, 2023; FSC, 2024; Welsh Government, 2024), our qualitative study findings suggest the need for strategic communication that integrates local identity, tradition, and environmental consciousness into food systems relocalization agendas. These initiatives, such as urban farming, regional food programs, and urban-rural network development, can enhance consumer engagement and bridge urban-rural divides (Carolan, 2022; Graciotti and McEachern, 2024; Lever and Sonnino, 2022; O’Neill, 2024). The Welsh Government’s Food Matters policy (2024) offers an interesting model, promoting local food systems development to meet sustainability goals and strengthen economic resilience through local community-driven, place-based actions aimed at ‘harnessing’ food localness, including small-producer subsidies, transparent regional labeling, cross-sector partnerships formation and consumer socio-environmental education initiatives. Policies like this provide a strong example of contemporary place-based efforts to address national (and international – e.g. EU Commission, 2023) policy intervention challenges through local stakeholder support, which have often favored globalized food supply chains (Fiala et al., 2024) and lacked focus on making local food consumer choices easier and more competitive (Kneafsey et al., 2021; Loebnitz and Grunert, 2019; Schmitt et al., 2017).
5.3 Limitations and future research recommendations
This research has several limitations. Study 1 relies on a cross-sectional data set using convenience and snowball sampling among Italian residents, which may limit generalizability to Italy’s sociocultural context. However, SCT’s flexibility suggests potential for replication in other Global North countries, enabling cross-cultural comparisons in local food consumer behavior (Sheth, 2021). Another limitation is the potential for self-selection bias. Since participation was voluntary, the sample may have skewed toward certain types of participants or attitudes. In addition, although Study 2 incorporates insights into how local food purchase intention translates into behavior (Study 1) from an experiential perspective (Carrington et al., 2014; León, 2023; Thompson et al., 1990), we call for future research endeavors based on experimental research designs to better capture and improve the generalizability of insights into the influence of ‘place’ on local food purchase behavior, particularly by examining differences in social identity constructions varying across alternative and conventional food retail spaces (e.g. McEachern and Warnaby, 2006; O’Neill, 2024). Indeed, different retail spaces – including consumer visits to, and direct purchase from, production sites – would provide different atmospheres and place-based contexts that would affect a consumer’s self-identity construction from an SCT perspective (e.g. Steadman and Coffin, 2024). Moreover, given the current international emphasis on sustainable local food systems development to counter the issues of displaced, global supply chains (United Nations Development Programme, 2024), we also recommend future research expanding on the ethics of local food purchase by investigating how consumers’ local identity, attachment to tradition, and connectedness with nature is affected by different sustainable packaging choices, labeling, and other forms of advertising.
