This study aims to develop and validate a multidimensional scale that measures consumers' motivations to purchase local smallholder food products, with a particular focus on marketing-oriented consumer research and decision-making.
Based on a literature-derived motivation framework and expert review, an initial pool of 30 items was generated. Data were collected via an online survey of Hungarian consumers aged 18–65 (n = 1,000), with quotas based on gender, age group and region. The sample was randomly split, exploratory factor analysis was conducted using principal component analysis with Promax rotation, and confirmatory factor analysis was performed using consistent PLS (PLSc). Factorial structure, reliability, and construct validity were assessed.
Results support a validated seven-factor, 19-item scale capturing motivations related to quality and taste, health, fashion, personal contact, environmental protection, local patriotism, and provenance. Reliability and convergent validity indicators meet recommended thresholds, while discriminant validity is acceptable, with a close association observed between health and environmental motivations.
The scale can help smallholders and marketers segment consumers and tailor product, communication, and channel strategies, while enabling researchers to compare motivational profiles across settings and to undertake further cross-cultural validation. It may also inform policy measures supporting smallholder producers and short food supply chains.
The aim of this research is to address an existing gap in the literature. Currently, there is no validated scale specifically designed to explore consumer motivations for local smallholder food products from a marketing perspective. By developing such a tool, this research equips professionals and researchers with an instrument that enables them to make more informed decisions in the contemporary environment.
1. Introduction
Local products are gaining importance in food consumption across both developed and developing economies. At the same time, local food systems are frequently promoted as levers for more resilient and sustainable food systems, yet the evidence behind common claims is often context dependent, and outcomes vary across settings (Enthoven and Van den Broeck, 2021). Short food supply chains connect producers more directly with consumers and are therefore receiving growing attention. Recent synthesis work highlights the importance of understanding consumer participation and consumer side drivers in these arrangements (Jia et al., 2024). A key limitation in this literature is that “local” is often operationalised mainly through geographical distance, while other strands emphasise relational, cultural, and value proximity, which complicates comparability and cumulative knowledge building (Eriksen, 2013; Feldmann and Hamm, 2015).
Local smallholder food products have become more valued by consumers and are now increasingly important alternative sources of food supply relative to large retail chain based food provisioning (Neulinger et al., 2020). Prior research has examined motivations for buying local foods, yet much of it operationalises “local” through distance and relies on study specific item sets, which limits cumulative knowledge building and reduces comparability across settings (Eriksen, 2013; Feldmann and Hamm, 2015). There seems to be much less emphasis on motivations for consumption of locally produced food from smallholders, even though such motivations may differ from those studied in the broader local food literature (Poyoi et al., 2024).
The novelty of this study does not rest on the assumption that all motivational domains are new to food choice research. Motives such as taste, health, environmental concern and support for local producers have already been discussed in the broader literature on food choice, local food consumption and short food supply chains (Furst et al., 1996; Feldmann and Hamm, 2015; Memery et al., 2015; Jia et al., 2024). The originality of the present study lies instead in developing and validating a measurement instrument designed specifically for local smallholder food products. Prior research has often examined local food consumption more broadly, used different meanings of “local”, or relied on item sets developed for individual research contexts, which limits comparability across studies (Eriksen, 2013; Feldmann and Hamm, 2015; Memery et al., 2015). The proposed scale differs by bringing together motives linked to product experience, health and environmental beliefs, producer relations and place meanings within one validated multidimensional instrument. This is important because local smallholder food products are often embedded in direct exchange with producers, trust building, origin meanings and community support, which are not fully captured when local food is treated mainly as a matter of geographical proximity or general food choice (Eriksen, 2013; Forney and Häberli, 2016; Enthoven and Van den Broeck, 2021; Jia et al., 2024).
The study contributes by (1) providing a validated multidimensional measurement instrument for marketing-oriented consumer research in the local smallholder domain, (2) enabling more robust segmentation and communication decisions for smallholders and local food initiatives, and (3) offering a tool that can support evidence informed policy design in programmes aimed at strengthening smallholder production and local food systems (Neulinger et al., 2020; Nordin and Ravald, 2023).
2. Literature review
2.1 Defining local and smallholder foods in short food supply chains
Although “local food” is widely discussed, its meaning varies across studies and markets, which affects how consumer motivations are conceptualised and measured. Many contributions operationalise “local” mainly through geographical distance, while other approaches stress proximity in relational, cultural, or value terms, limiting direct comparability when different operational definitions are used (Eriksen, 2013; Feldmann and Hamm, 2015).
In this paper, we focus on local foods supplied through short food supply chains where consumers perceive closeness between production and consumption and where product choice may be shaped by both product attributes and perceived closeness to producers and place. Importantly, widely cited claims about the social, economic, and environmental benefits of local food systems are not uniform and tend to be context dependent, which further strengthens the need for careful measurement of consumer drivers (Enthoven and Van den Broeck, 2021).
Because definitions of “local” vary, we treat “local” as an empirical construct whose operationalisation must be made explicit, and we align the present study with the proximity-based view common in the local food literature (Eriksen, 2013).
We further narrow the scope to smallholder producers. Here, “smallholders” refers to small scale producers operating on limited land and relying largely on household labour, with production partly oriented to household needs and local markets (Food and Agriculture Organization of the United Nations, 2012). Concrete examples include seasonal produce sold at farmers' markets, artisanal cheese or honey sold directly by a family farm, or products distributed through local buying clubs. This context matters because smallholder local foods are often associated with direct selling, trust building, and perceived authenticity, which may alter the salience of motivations such as personal contact, provenance, and local support compared with local foods supplied by larger firms.
2.2 Integrative theoretical framework for motivation domains and the conceptual model
This study develops a deductive scale development framework by integrating three related streams of literature. First, food choice research shows that consumer decisions are shaped by motives linked to product experience, perceived health, values and practical considerations (Furst et al., 1996; Nardi et al., 2019). Second, local food and short food supply chain research highlights the importance of proximity, trust, producer contact, origin meanings and support for local communities (Eriksen, 2013; Feldmann and Hamm, 2015; Forney and Häberli, 2016; Jia et al., 2024). Third, sustainability and socially oriented consumption research emphasises that consumers may evaluate food choices not only through personal benefits, but also through perceived environmental and community related consequences (Granzin and Olsen, 1998; Granzin and Painter, 2000; Enthoven and Van den Broeck, 2021). Synthesising these streams, we organise motivations for local smallholder food products into four theoretical components: intrinsic product evaluations, credence beliefs, relational proximity and place related meanings.
In line with this deductive approach, the motivation domains are not treated as isolated empirical categories. Instead, they are specified as measurable expressions of these four components (Nelson, 1970; Darby and Karni, 1973; León-Bravo et al., 2025). This logic guided the specification of the motivation domains and the subsequent item development process.
Despite the growing volume of research on local foods and short food supply chains, three limitations constrain cumulative knowledge building and weaken managerial usefulness. First, the evidence base remains context dependent and geographically uneven, with many influential insights emerging from developed country settings, which limits transferability across market structures and institutional environments (Enthoven and Van den Broeck, 2021; Jia et al., 2024). Second, much of the motivation literature addresses “local food” broadly and does not consistently distinguish smallholder contexts, even though smallholder exchange often involves stronger relational proximity, direct interaction, and authenticity and provenance cues that may alter which motivations are salient (Forney and Häberli, 2016; László and Wahlen, 2024). Third, existing studies frequently operationalise motivations using heterogeneous item sets, and there is a shortage of comprehensive scale development and validation efforts that yield comparable and context sensitive instruments for local smallholder food products (Feldmann and Hamm, 2015; Memery et al., 2015). These limitations motivate the present study's objective to develop and validate a multidimensional motivation scale tailored to local smallholder food products (Figure 1), with domain and item decisions documented in Table 1. Sections 2.2.1-2.2.7 synthesise evidence for each motivation domain and link it to the scale's domain definitions and item decisions.
A conceptual model diagram representing the factors influencing the consumption motivation for local smallholder food products. The central element is labeled Consumption motivation for local smallholder food products. Seven factors are connected to this central element through arrows, indicating their influence. These factors are Quality and taste, Local patriotism, Provenance, Fashion, Personal contact with the producer, Environmental protection and sustainability, and Health consciousness. Each factor is represented as a rectangular box, and arrows point from each box to the central element, signifying their contribution to the consumption motivation.Conceptual model of the consumption motivation scale for local smallholder food products. Source: Authors' editing
A conceptual model diagram representing the factors influencing the consumption motivation for local smallholder food products. The central element is labeled Consumption motivation for local smallholder food products. Seven factors are connected to this central element through arrows, indicating their influence. These factors are Quality and taste, Local patriotism, Provenance, Fashion, Personal contact with the producer, Environmental protection and sustainability, and Health consciousness. Each factor is represented as a rectangular box, and arrows point from each box to the central element, signifying their contribution to the consumption motivation.Conceptual model of the consumption motivation scale for local smallholder food products. Source: Authors' editing
Literature audit linking prior evidence to the objective and to domain and item decisions
| Motivational domain | Conceptual definition in local smallholder food context | Theory-facing rationale | Illustrative support from literature |
|---|---|---|---|
| Quality and taste | Preference based on expected freshness and superior sensory experience of local smallholder foods | Superior intrinsic attributes increase expected utility and reduce perceived product risk | Feldmann and Hamm (2015), Memery et al. (2015), Kovács et al. (2022), Benedek and Fertő (2024) |
| Local patriotism | Buying local smallholder foods to support local producers and community and to express place attachment | Place attachment and identity related helping behaviour guide pro local choices | Skallerud and Wien (2019), Granzin and Olsen (1998), Memery et al. (2015), Kovács et al. (2022) |
| Provenance | Motivation rooted in origin cues, heritage, and authenticity, including the product's story of place that adds value beyond distance | Origin cues shape perceived value and trust; provenance acts as a meaning and quality signal | Thøgersen (2023), D'Amico (2004), Berg and Sevón (2014), Figueiredo et al. (2022), László and Wahlen (2024) |
| Fashion | Choosing local smallholder foods because it feels trendy, socially valued, or novel, and can be experienced as shareable | Social influence and signalling increase adoption; digitally mediated contexts can amplify symbolic meanings | Özkan Önem et al. (2025), Leong et al. (2021), Nyagadza et al. (2023), Anwar et al. (2025), Bukhari et al. (2020, 2023) |
| Personal contact with the producer | Preference based on direct interaction with producers, trust building, and access to credible first-hand information | Relational proximity and trust reduce uncertainty and strengthen loyalty intentions | Forney and Häberli (2016), Jia et al. (2024), László and Wahlen (2024) |
| Environmental protection and sustainability | Motivation grounded in perceived environmental benefits, such as lower transport burden, less waste, or responsible production meanings | Moral and normative beliefs and perceived impact translate into more sustainable choices | Enthoven and Van den Broeck (2021), Jia et al. (2024), Benedek and Fertő (2024) |
| Health consciousness | Preference driven by perceived naturalness, lower processing, and alignment with personal health goals | Health goals and perceived naturalness guide food choice and justify higher effort or price | Memery et al. (2015), Moser et al. (2011), Kovács et al. (2022) |
| Motivational domain | Conceptual definition in local smallholder food context | Theory-facing rationale | Illustrative support from literature |
|---|---|---|---|
| Quality and taste | Preference based on expected freshness and superior sensory experience of local smallholder foods | Superior intrinsic attributes increase expected utility and reduce perceived product risk | |
| Local patriotism | Buying local smallholder foods to support local producers and community and to express place attachment | Place attachment and identity related helping behaviour guide pro local choices | |
| Provenance | Motivation rooted in origin cues, heritage, and authenticity, including the product's story of place that adds value beyond distance | Origin cues shape perceived value and trust; provenance acts as a meaning and quality signal | |
| Fashion | Choosing local smallholder foods because it feels trendy, socially valued, or novel, and can be experienced as shareable | Social influence and signalling increase adoption; digitally mediated contexts can amplify symbolic meanings | |
| Personal contact with the producer | Preference based on direct interaction with producers, trust building, and access to credible first-hand information | Relational proximity and trust reduce uncertainty and strengthen loyalty intentions | |
| Environmental protection and sustainability | Motivation grounded in perceived environmental benefits, such as lower transport burden, less waste, or responsible production meanings | Moral and normative beliefs and perceived impact translate into more sustainable choices | |
| Health consciousness | Preference driven by perceived naturalness, lower processing, and alignment with personal health goals | Health goals and perceived naturalness guide food choice and justify higher effort or price |
2.2.1 Quality and taste
Consumers may prefer local smallholder foods because they expect superior intrinsic attributes, especially freshness and sensory appeal, often experienced as inseparable from “quality” and “taste”. Evidence from local food research consistently identifies freshness, taste, and perceived quality among the most frequent drivers of local food purchasing (Feldmann and Hamm, 2015). Recent evidence from Hungary and from local food buying club research also confirms the salience of these expectations in comparable contexts (Kovács et al., 2022; Benedek and Fertő, 2024). Although quality and taste are sometimes discussed as distinct motives, prior research in local food contexts frequently reports them as closely related intrinsic product drivers (Feldmann and Hamm, 2015; Skallerud and Wien, 2019; Kovács et al., 2022). We therefore allow for the possibility that they may not separate cleanly at the measurement level. The scale captures this domain with items focusing on freshness and sensory experience, without forcing respondents to separate quality from taste. In the proposed framework, quality and taste therefore represent the intrinsic product evaluation component.
2.2.2 Local patriotism
A distinct motive for choosing local smallholder foods is the desire to support local producers and the local community, rooted in place attachment and helping behaviour (Granzin and Olsen, 1998; Granzin and Painter, 2000). In local food and short supply chain settings, consumers often interpret buying local as a form of helping local producers and communities, and this orientation has been linked to local product preference and continued engagement (Skallerud and Wien, 2019), including in Hungary (Kovács et al., 2022; Benedek and Fertő, 2024). Accordingly, items in this domain should capture supportive intentions and positive identification with local products, while avoiding exclusionary wording.
2.2.3 Provenance
Provenance captures motivation driven by origin cues that signal authenticity, heritage and distinctive place based identity, shaping value beyond distance (D'Amico, 2004; Berg and Sevón, 2014). Prior work on origin information shows that provenance cues influence evaluation and choice by signalling trustworthiness and quality, although effects vary across contexts and competing cues (Thøgersen, 2023). Studies of provenance foods also link origin meaning to perceived territorial vitality and consumer value (Figueiredo et al., 2022). The scale therefore measures provenance as a motivation for choosing local smallholder foods because origin and heritage matter to the consumer, conceptually separated from helping motives. This positions provenance as a place related meaning based on origin, authenticity and heritage, while distinguishing it from local patriotism, which reflects support for the local community.
2.2.4 Fashion
Local smallholder food choices can also be motivated by trendiness, novelty, and social display, especially when food experiences are visible and shareable in digital contexts. Recent research suggests that symbolic meanings and status related tendencies can strengthen local food preferences, partly through variety seeking and perceived symbolic value (Özkan Önem et al., 2025). Evidence in food and beverage contexts also indicates that electronic word of mouth characteristics are associated with intention formation (Leong et al., 2021; Nyagadza et al., 2023). In the scale, this domain focuses on the consumer's internal motive, buying local because it feels trendy or shareable, while digital communication mechanisms are treated as potential antecedents in future models.
2.2.5 Personal contact with the producer
Personal contact reflects motivation to buy local smallholder foods because consumers value direct interaction with producers and credible firsthand information about products and practices. Short food supply chain research emphasises relational and informational proximity as key to transparency and trust, which can support engagement and repeated purchasing (Forney and Häberli, 2016; Jia et al., 2024). Qualitative work on “local” meanings also highlights relational proximity as central to how consumers experience local foods (László and Wahlen, 2024). Consequently, items in this domain capture the desire for direct communication, the ability to ask questions, and the value of a personal relationship.
2.2.6 Environmental protection and sustainability
Environmental protection captures motivation based on perceived environmental advantages of local smallholder foods, such as reduced transport, lower waste, or more responsible practices. Reviews and syntheses note that sustainability considerations can shape food choice but compete with other strong drivers and are interpreted heterogeneously by consumers (Enthoven and Van den Broeck, 2021; Jia et al., 2024). The scale therefore measures perceived environmental benefits as a motive, using product focused wording and avoiding broad societal trend statements. Within the framework, environmental protection captures the sustainability-oriented credence belief that local smallholder food products may generate wider environmental benefits.
2.2.7 Health consciousness
Health consciousness reflects motivation to choose local smallholder foods because they are perceived as healthier, more natural, or less processed, often expressed through preference for freshness and avoidance of additives. Empirical work links perceived health and naturalness to food choice and to local food preferences, with context dependent effect sizes (Moser et al., 2011; Memery et al., 2015; Kovács et al., 2022). The scale operationalises this domain via product focused items capturing perceived healthiness and naturalness, rather than measuring broader lifestyle constructs. Health consciousness captures the self-oriented credence belief that local smallholder food products may provide personal health benefits.
2.3 Summary and link to the study objective
Overall, prior work supports treating consumption motivation for local smallholder food products as a multidimensional construct spanning intrinsic evaluations (quality and taste), credence considerations (health and environmental protection), and relational and place related meanings (personal contact, provenance, local patriotism), with trend related motives (fashion) providing an experiential layer. To strengthen comparability and cumulative knowledge building, we translate these domains into a validated measurement instrument. Figure 1 summarises the conceptual model, while Table 1 provides an audit style overview linking evidence streams to domain and item decisions.
In line with deductive consumer decision models, Figure 1 positions the multidimensional motivation construct as an antecedent that can be integrated with variables such as consumer engagement and purchase intention in future explanatory models (Anwar et al., 2025; Bukhari et al., 2020, 2023), while the present study focuses on scale development and validation.
The following section describes how this theoretical structure was translated into a scale development and validation procedure.
3. Research methodology
3.1 Research design and research approach
In response to a gap in the literature, our research aimed to develop and validate the consumption motivation scale for local smallholder food products. As there is no evidence in the literature of a scale specifically measuring the consumption motivations of smallholder local food products from a marketing perspective, we set out to develop such a scale. Following Boateng et al. (2018), we adopted a sequential scale development design because each stage addresses a distinct validity threat. Item generation and expert review are required to establish content validity and ensure that items represent the construct in the local smallholder context. EFA is then necessary to test dimensionality empirically and remove redundant or cross-loading items, given that motivation domains may overlap conceptually. Finally, CFA in an independent subsample is required to confirm the stability of the factor structure and to provide evidence of construct validity and measurement quality that is less susceptible to overfitting.
Accordingly, the procedure comprised three stages: (1) item generation and content validation, (2) dimensionality assessment and construct refinement using EFA, and (3) confirmation of the factorial structure using CFA in an independent subsample. Taken together, these stages followed an established sequential scale development logic. The expert review served as the content assessment stage, the pilot test was used to check clarity and questionnaire flow, and the subsequent EFA and CFA provided empirical evidence on dimensionality, reliability and validity in independent subsamples. Thus, the pilot test was not intended as a substitute for psychometric validation, but as a preparatory step before large scale data collection.
3.2 Construct specification and domain identification
As the first step in scale item development, following McCoach et al. (2013), we conducted a thorough literature review to define the construct boundaries and ensure comprehensive domain coverage before statistical refinement (see Section 2.2). This step is necessary because factor analysis cannot compensate for missing or poorly specified content. Drawing on prior work on local foods and short food supply chains, we specified eight candidate motivation domains deductively: quality, taste, health, fashion, personal contact, environmental protection, local patriotism, and provenance.
We then assessed existing motivation instruments and concluded that no available scale adequately captures these domains for local smallholder food products in a way that reflects the smallholder context and short supply chain settings. While related measures exist for broader food choice and local food consumption, using them without adaptation would risk conceptual mismatch and incomplete coverage of smallholder specific meanings. We treat these domains as theoretically meaningful but potentially related motivational streams rather than assuming perfect independence a priori. Conceptual differentiation is provided by distinct underlying mechanisms, while empirical differentiation is assessed through EFA (cross loadings) and CFA (HTMT and related validity criteria) (Boateng et al., 2018).
3.3 Measurement scaling and item pool generation
To develop the items, we initially aimed to combine deductive and inductive procedures. Due to resource constraints, we did not conduct consumer interviews for inductive item generation; we acknowledge this as a limitation. We therefore generated the initial pool deductively from the literature, resulting in 64 items. This exceeds the common recommendation that the initial pool should be at least twice the intended final scale length (Schinka et al., 2012). Items were distributed across the eight candidate domains (eight items per domain) and anchored to a five-point Likert response format. Respondents were instructed to think about local smallholder food products in short food supply chains (e.g. foods bought directly from small producers, farmers' markets, or local buying clubs) and to indicate agreement with each statement (1 = strongly disagree; 5 = strongly agree), following standard guidance on Likert scaling (Krosnick and Presser, 2009).
3.4 Content review procedure
Prior to factor analyses, the initial item pool was reviewed by four Hungarian academic reviewers with complementary expertise (local food products; tourism research on local products; consumer behaviour and motivation measurement). Reviewers evaluated items against explicit criteria, including relevance to the intended domain, clarity, and redundancy. Feedback was collected and discussed in a structured consensus meeting, and decisions were documented; items were revised or removed accordingly. As this stage was implemented as a consensus-based content review, formal content validity indices and interrater agreement statistics were not calculated, which we acknowledge as a limitation. Following this review, 30 items were retained from the initial 64 for subsequent analyses.
3.5 Instrument development and pilot testing
After item development, we operationalised the scale in an online questionnaire and conducted a pilot test with ten respondents to assess clarity and questionnaire flow. Feedback indicated that the items were easy to understand, thus no substantive wording changes were required. To reduce respondent fatigue and preserve response quality, the 30 scale items were split into two blocks of 15 and separated by non-scale questions. Item order was randomised to minimise potential order effects.
3.6 Sampling frame and data collection
Data were collected via an online survey administered by a professional market research company in Hungary (n = 1,000). The target population was Hungarian residents aged 18–65. The provider recruited respondents from an online access panel and applied quota controls to approximate population distributions by gender, age group, and region. The research company delivered a cleaned and anonymised dataset to the authors. Data cleaning was performed by the provider using their standard quality procedures, which included completeness checks and removal of low-quality responses. As the fieldwork was fully managed by the provider, detailed contact-level metrics, like number invited, number started, and overall response rate were not available to the authors.
Following standard scale development practice, the sample was randomly split for EFA and CFA (Lyden et al., 1999; Petrides and Furnham, 2000; Paic et al., 2017). Each subsample exceeded recommended minimum sizes for factor analysis (MacCallum et al., 1999). After excluding incomplete responses, the analytic samples were n = 425 (EFA) and n = 427 (CFA). Subsample equivalence was assessed using Mann-Whitney U and chi-squared tests at the 5% level (Paic et al., 2017).
3.7 Measurement instruments and analysis
We used EFA to empirically examine whether the proposed motivation domains are distinguishable in this context and to identify items that show weak loadings or cross-loadings, which would threaten discriminant validity and interpretability. When performing EFA, in line with the fact that our data were not normally distributed, we used principal component analysis with Promax rotation. Appropriateness of factor analysis was assessed using the KMO (Kaiser-Meyer-Olkin) index and the Bartlett's test. For the former, a result above 0.5 was considered acceptable, while the latter had to be significant to accept factor analysis (Sajtos and Mitev, 2007). IBM SPSS 28 was used for the EFA stage.
We then applied CFA in an independent subsample to confirm the factor structure obtained in EFA and to evaluate the measurement model using established reliability and validity criteria, thereby reducing the risk of capitalising on chance patterns in a single dataset. When conducting CFA, the factorial model obtained during EFA was created in SmartPLS 3 and then the consistent partial least squares (PLSc) algorithm of the variance-based methods was run, which is considered suitable for this type of analysis of latent variables (Jhantasana, 2023). To test the significance of factorial weights, we performed bootstrap sampling based on Henseler et al. (2009) and Hair et al. (2011), with the number of subsamples set at 5,000.
Discriminant validity of the factorial model was tested using the Heterotrait-Monotrait ratio (HTMT) of the pairwise correlations of variables, with the maximum acceptable threshold previously set at 0.9, following Henseler et al. (2015). In the CFA phase, fit of the factorial model was tested through model fit, using SRMR (standardized root mean squared residual) and NFI indicators used for the PLSc algorithm. The SRMR index is expected to be lower than the limit of 0.08 for an acceptable fit (Henseler et al., 2016). As for NFI, the expected minimum value was set at 0.9, following Lohmöller (1989).
During confirmatory factor analysis, the internal reliability of the dimensions was assessed along three different indicators: Cronbach's alpha, composite reliability (CR), and average variance extracted (AVE). In terms of Cronbach's alpha and CR, if their value exceeded 0.7, the internal reliability of the dimension was considered adequate, whereas for AVE the threshold was 0.5 (Bagozzi and Yi, 1988; Fornell and Larcker, 1981; Hair et al., 2010). Factorial structure was modified by eliminating items until the structure met predefined criteria. Finally, the resulting structure was considered to be the definitive one, providing a validated scale to measure different types of motivations for consuming local smallholder food products.
Together, these stages provide complementary evidence for content validity and construct validity, which is essential when proposing a new measurement instrument for cumulative research use.
4. Results of the exploratory and confirmatory factor analyses (EFA and CFA)
Before conducting EFA and CFA, the sample was randomly divided into two independent subsamples. Subsample equivalence was assessed using the Mann Whitney U test for age and chi-squared tests for nominal variables. As shown in Table 2, no significant differences were found between the subsamples, supporting their use for exploratory and confirmatory analyses.
Equivalence test data for the subsamples split for analysis
| Mann-Whitney U | Z | p-value | |
|---|---|---|---|
| Age | 128382.5 | −0.741 | 0.459 |
| Mann-Whitney U | Z | p-value | |
|---|---|---|---|
| Age | 128382.5 | −0.741 | 0.459 |
| Pearson's chi square | df | p-value | |
|---|---|---|---|
| Gender | 0.257 | 1 | 0.329 |
| Marital status | 1.071 | 4 | 0.899 |
| Highest level of education | 4.765 | 6 | 0.574 |
| Net family income | 5.572 | 5 | 0.350 |
| Economic activity | 6.386 | 10 | 0.782 |
| Frequency of purchasing local food products | 4.451 | 5 | 0.486 |
| Preference for local food products | 0.315 | 2 | 0.854 |
| Pearson's chi square | df | p-value | |
|---|---|---|---|
| Gender | 0.257 | 1 | 0.329 |
| Marital status | 1.071 | 4 | 0.899 |
| Highest level of education | 4.765 | 6 | 0.574 |
| Net family income | 5.572 | 5 | 0.350 |
| Economic activity | 6.386 | 10 | 0.782 |
| Frequency of purchasing local food products | 4.451 | 5 | 0.486 |
| Preference for local food products | 0.315 | 2 | 0.854 |
EFA of the 30-item pool supported a clear and interpretable seven-factor structure with 19 retained items. Using the predefined item retention criteria, items with weak loadings or problematic cross loadings were removed to improve interpretability and measurement quality. The adequacy of the data for factor analysis was confirmed by the KMO index (0.947) and Bartlett's test (p < 0.001). The final structure explained 81.4% of the variance, indicating strong explanatory capacity for a multidimensional motivation scale. Substantively, the retained items formed coherent domains reflecting quality and taste, health, fashion, personal contact, environmental protection, local patriotism and provenance. Table 3 summarises the final EFA structure, while Appendix Table A1 lists the specific statements corresponding to the individual items.
Pattern matrix with Promax-rotated factor loadings
| Factors | |||||||
|---|---|---|---|---|---|---|---|
| Items | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| QUALITY1 | 0.883 | 0.023 | −0.102 | −0.002 | −0.007 | 0.019 | 0.103 |
| TASTE1 | 0.859 | 0.024 | −0.024 | −0.022 | −0.059 | 0.053 | 0.085 |
| QUALITY3 | 0.717 | −0.084 | 0.054 | 0.091 | 0.305 | 0.015 | −0.162 |
| TASTE4 | 0.644 | 0.079 | 0.094 | 0.010 | 0.293 | −0.048 | −0.131 |
| PERSCONT1 | 0.020 | 0.958 | −0.192 | −0.031 | 0.053 | 0.031 | 0.039 |
| PERSCONT2 | −0.017 | 0.948 | 0.111 | −0.039 | −0.116 | 0.033 | −0.061 |
| PERSCONT3 | 0.049 | 0.651 | 0.233 | 0.043 | 0.153 | −0.092 | −0.084 |
| LOCPAT3 | −0.082 | 0.000 | 0.878 | 0.056 | 0.097 | 0.014 | −0.011 |
| LOCPAT4 | −0.089 | −0.030 | 0.860 | −0.024 | 0.131 | 0.170 | −0.051 |
| LOCPAT1 | 0.246 | 0.032 | 0.720 | −0.035 | −0.310 | −0.067 | 0.306 |
| FASHION2 | 0.054 | −0.118 | 0.005 | 1.032 | −0.104 | 0.015 | −0.149 |
| FASHION1 | −0.019 | 0.117 | −0.050 | 0.794 | −0.182 | 0.122 | 0.172 |
| FASHION4 | −0.052 | 0.035 | 0.104 | 0.600 | 0.374 | −0.180 | 0.126 |
| HEALTH4 | 0.026 | 0.078 | 0.003 | −0.124 | 0.768 | 0.026 | 0.211 |
| HEALTH3 | 0.172 | −0.100 | −0.017 | −0.063 | 0.712 | 0.077 | 0.192 |
| PROVE1 | 0.076 | −0.009 | 0.155 | 0.009 | −0.064 | 0.819 | 0.032 |
| PROVE3 | −0.005 | 0.056 | −0.029 | 0.030 | 0.356 | 0.683 | −0.047 |
| ENVPRO3 | 0.019 | −0.093 | 0.144 | −0.087 | 0.285 | −0.039 | 0.770 |
| ENVPRO2 | −0.009 | 0.070 | −0.109 | 0.146 | 0.293 | 0.085 | 0.608 |
| Factors | |||||||
|---|---|---|---|---|---|---|---|
| Items | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| QUALITY1 | 0.883 | 0.023 | −0.102 | −0.002 | −0.007 | 0.019 | 0.103 |
| TASTE1 | 0.859 | 0.024 | −0.024 | −0.022 | −0.059 | 0.053 | 0.085 |
| QUALITY3 | 0.717 | −0.084 | 0.054 | 0.091 | 0.305 | 0.015 | −0.162 |
| TASTE4 | 0.644 | 0.079 | 0.094 | 0.010 | 0.293 | −0.048 | −0.131 |
| PERSCONT1 | 0.020 | 0.958 | −0.192 | −0.031 | 0.053 | 0.031 | 0.039 |
| PERSCONT2 | −0.017 | 0.948 | 0.111 | −0.039 | −0.116 | 0.033 | −0.061 |
| PERSCONT3 | 0.049 | 0.651 | 0.233 | 0.043 | 0.153 | −0.092 | −0.084 |
| LOCPAT3 | −0.082 | 0.000 | 0.878 | 0.056 | 0.097 | 0.014 | −0.011 |
| LOCPAT4 | −0.089 | −0.030 | 0.860 | −0.024 | 0.131 | 0.170 | −0.051 |
| LOCPAT1 | 0.246 | 0.032 | 0.720 | −0.035 | −0.310 | −0.067 | 0.306 |
| FASHION2 | 0.054 | −0.118 | 0.005 | 1.032 | −0.104 | 0.015 | −0.149 |
| FASHION1 | −0.019 | 0.117 | −0.050 | 0.794 | −0.182 | 0.122 | 0.172 |
| FASHION4 | −0.052 | 0.035 | 0.104 | 0.600 | 0.374 | −0.180 | 0.126 |
| HEALTH4 | 0.026 | 0.078 | 0.003 | −0.124 | 0.768 | 0.026 | 0.211 |
| HEALTH3 | 0.172 | −0.100 | −0.017 | −0.063 | 0.712 | 0.077 | 0.192 |
| PROVE1 | 0.076 | −0.009 | 0.155 | 0.009 | −0.064 | 0.819 | 0.032 |
| PROVE3 | −0.005 | 0.056 | −0.029 | 0.030 | 0.356 | 0.683 | −0.047 |
| ENVPRO3 | 0.019 | −0.093 | 0.144 | −0.087 | 0.285 | −0.039 | 0.770 |
| ENVPRO2 | −0.009 | 0.070 | −0.109 | 0.146 | 0.293 | 0.085 | 0.608 |
At this point, it is important to note that the eight dimensions defined based on the theory basically assume the existence of eight factors. The EFA indicated that items originally intended to capture “quality” and “taste” loaded on a single factor. This outcome is in line with the conceptual expectation outlined in Section 2.2.1 that quality and taste may be empirically bundled in local food contexts. This suggests that, in the context of local smallholder foods, these motives may not separate cleanly at the measurement level and are instead expressed as a unified experiential evaluation. This interpretation is consistent with prior local food evidence where freshness, taste and perceived quality tend to co-occur as closely linked drivers of choice (Feldmann and Hamm, 2015; Memery et al., 2015; Kovács et al., 2022; Benedek and Fertő, 2024). In short food supply chain settings, quality judgements are often anchored in sensory expectations and holistic product experience, with taste and freshness functioning as salient indicators of perceived product excellence. Accordingly, the results support modelling Quality – Taste as a single domain in the final scale and clarify how intrinsic product evaluations manifest in the local smallholder context.
CFA in the independent validation subsample confirmed the stability of the 19-item, seven-factor structure. Model fit was satisfactory, with SRMR of 0.038 and NFI of 0.912, meeting the predefined criteria. The bootstrapping results further showed that all item factor relationships were significant and sufficiently strong. These findings support the interpretation that the EFA solution was not merely sample specific but reflected a stable factorial structure in the validation subsample. Table 4 summarises the item weights and bootstrapping results.
Beta values and results of bootstrap sampling of the final factorial structure
| Factors and their items | Beta value | STD | t-value | p-value |
|---|---|---|---|---|
| FASHION1 <- Fashion | 0.808 | 0.035 | 23.388 | 0.000 |
| FASHION2 <- Fashion | 0.556 | 0.054 | 10.299 | 0.000 |
| FASHION4 <- Fashion | 0.943 | 0.029 | 32.618 | 0.000 |
| HEALTH3 <- Health | 0.842 | 0.029 | 29.183 | 0.000 |
| HEALTH4 <- Health | 0.839 | 0.029 | 28.626 | 0.000 |
| PERSCONT1 <- Personal contact | 0.711 | 0.040 | 17.987 | 0.000 |
| PERSCONT2 <- Personal contact | 0.830 | 0.026 | 31.796 | 0.000 |
| PERSCONT3 <- Personal contact | 0.922 | 0.029 | 31.271 | 0.000 |
| ENVPRO2 <- Environment protection | 0.855 | 0.025 | 33.618 | 0.000 |
| ENVPRO3 <- Environment protection | 0.758 | 0.032 | 23.733 | 0.000 |
| LOCPAT1 <- Local patriotism | 0.768 | 0.032 | 24.250 | 0.000 |
| LOCPAT3 <- Local patriotism | 0.862 | 0.026 | 32.605 | 0.000 |
| LOCPAT4 <- Local patriotism | 0.870 | 0.023 | 37.566 | 0.000 |
| TASTE1 <- Quality-Taste | 0.819 | 0.030 | 27.720 | 0.000 |
| TASTE4 <- Quality-Taste | 0.830 | 0.031 | 26.853 | 0.000 |
| QUALITY1 <- Quality-Taste | 0.814 | 0.027 | 30.415 | 0.000 |
| QUALITY3 <- Quality-Taste | 0.841 | 0.034 | 24.692 | 0.000 |
| PROVE1 <- Provenance | 0.824 | 0.031 | 26.549 | 0.000 |
| PROVE3 <- Provenance | 0.850 | 0.022 | 39.087 | 0.000 |
| Factors and their items | Beta value | STD | t-value | p-value |
|---|---|---|---|---|
| FASHION1 <- Fashion | 0.808 | 0.035 | 23.388 | 0.000 |
| FASHION2 <- Fashion | 0.556 | 0.054 | 10.299 | 0.000 |
| FASHION4 <- Fashion | 0.943 | 0.029 | 32.618 | 0.000 |
| HEALTH3 <- Health | 0.842 | 0.029 | 29.183 | 0.000 |
| HEALTH4 <- Health | 0.839 | 0.029 | 28.626 | 0.000 |
| PERSCONT1 <- Personal contact | 0.711 | 0.040 | 17.987 | 0.000 |
| PERSCONT2 <- Personal contact | 0.830 | 0.026 | 31.796 | 0.000 |
| PERSCONT3 <- Personal contact | 0.922 | 0.029 | 31.271 | 0.000 |
| ENVPRO2 <- Environment protection | 0.855 | 0.025 | 33.618 | 0.000 |
| ENVPRO3 <- Environment protection | 0.758 | 0.032 | 23.733 | 0.000 |
| LOCPAT1 <- Local patriotism | 0.768 | 0.032 | 24.250 | 0.000 |
| LOCPAT3 <- Local patriotism | 0.862 | 0.026 | 32.605 | 0.000 |
| LOCPAT4 <- Local patriotism | 0.870 | 0.023 | 37.566 | 0.000 |
| TASTE1 <- Quality-Taste | 0.819 | 0.030 | 27.720 | 0.000 |
| TASTE4 <- Quality-Taste | 0.830 | 0.031 | 26.853 | 0.000 |
| QUALITY1 <- Quality-Taste | 0.814 | 0.027 | 30.415 | 0.000 |
| QUALITY3 <- Quality-Taste | 0.841 | 0.034 | 24.692 | 0.000 |
| PROVE1 <- Provenance | 0.824 | 0.031 | 26.549 | 0.000 |
| PROVE3 <- Provenance | 0.850 | 0.022 | 39.087 | 0.000 |
Discriminant validity of the factor model was tested using the Heterotrait-Monotrait ratio (HTMT) of the pairwise correlations of variables. Most construct pairs were below the 0.90 threshold. HTMT values were: 0.565, 0.581, 0.608, 0.616, 0.616, 0.672, 0.696, 0.705, 0.715, 0.717, 0.734, 0.763, 0.791, 0.797, 0.813, 0.841, 0.865, 0.868, 0.870, 0.903. One pair (Health – Environmental protection) was marginally above 0.90 (HTMT = 0.903), suggesting a borderline overlap, however, the overall pattern remained consistent with acceptable discriminant validity across the measurement model. Substantively, this is plausible in the local smallholder context because consumers often bundle “healthy” and “environmentally responsible” meanings into a single better-for-me or better-for-world evaluation, and both domains rely on credence beliefs rather than direct verification at the point of consumption. We therefore interpret the result as evidence of a strong association between two related but conceptually distinct credence-based motivations. Given their different managerial and theoretical implications, we retained them as separate domains, while noting this proximity as a limitation and a potential avenue for future refinement.
As the last step of CFA, the internal reliability was tested of the factors established. Internal reliability was satisfactory across all domains (Cronbach's alpha: Fashion = 0.821; Health = 0.828; Environmental protection = 0.787; Local patriotism = 0.872; Quality – Taste = 0.896; Personal contact = 0.864; Provenance = 0.824). Composite reliability values were similarly acceptable (CR: 0.790–0.896), and convergent validity was supported as AVE exceeded 0.50 for all constructs (AVE: Fashion = 0.617; Health = 0.707; Environmental protection = 0.653; Local patriotism = 0.697; Quality – Taste = 0.682; Personal contact = 0.682; Provenance = 0.701). On this basis we can state that in terms of internal reliability, the predefined reliability criteria were met for all constructs, and thus the internal reliability of the scale is appropriate.
After iterative model refinement, further item deletion did not yield meaningful improvements in model fit or discriminant validity. Additional deletions would have required removing whole dimensions and would have reduced content coverage of the construct. Therefore, we retained the 19-item, seven-factor solution as the final validated scale for motivations towards local smallholder food products (see Appendix Table A1).
5. Discussion
Local food motivation research often relies on heterogeneous, study specific measures and varying meanings of “local”, which limits comparability and cumulative knowledge building (Eriksen, 2013; Feldmann and Hamm, 2015). At the same time, claims about the benefits of local food systems are strongly context dependent, which increases the value of robust consumer side measurement (Enthoven and Van den Broeck, 2021). This study addresses these shortcomings by developing and validating a concise motivation scale tailored to local smallholder food products in short food supply chains, enabling marketing-oriented research and future deductive modelling of intention, engagement, and purchasing behaviour (Jia et al., 2024; Nordin and Ravald, 2023; Ajzen, 1991).
The validated structure supports a multidimensional view of motivation consistent with established food choice and consumer decision frameworks, where motivations act as goal and value based proximal drivers of intention and behaviour (Furst et al., 1996; Nardi et al., 2019). The domains map onto intrinsic evaluations, credence-based considerations, and relationship and place meanings that are salient in short supply chain settings (Nelson, 1970; Darby and Karni, 1973; Forney and Häberli, 2016). This strengthens theoretical interpretability and clarifies how the construct is organised in the local smallholder context.
A key substantive result is that quality and taste converged into a single factor. Prior syntheses consistently identify freshness, taste, and perceived quality as central drivers of local food purchasing (Feldmann and Hamm, 2015), and recent evidence from Hungary and local buying clubs confirms their salience in comparable contexts (Kovács et al., 2022; Benedek and Fertő, 2024). Our results suggest that consumers may treat quality and taste as one experiential motivation in this category, where taste and freshness function as primary indicators of product excellence. This supports modelling quality and taste as a unified intrinsic domain in measurement and in subsequent explanatory research (Memery et al., 2015).
The borderline overlap between health and environmental protection (HTMT 0.903) also has substantive meaning. Both motives depend on credence beliefs and can be bundled into a broader responsible choice evaluation, especially when consumers cannot directly verify claims at consumption (Nelson, 1970; Darby and Karni, 1973; Enthoven and Van den Broeck, 2021). We retain them as distinct constructs because they reflect different goal orientations, self-related wellness versus normative impact beliefs, with different implications for marketing and policy design (Memery et al., 2015; Jia et al., 2024).
Three domains reinforce the scale's specificity for smallholder settings. Personal contact reflects relational proximity and transparency emphasised in short supply chain research (Forney and Häberli, 2016; Jia et al., 2024; László and Wahlen, 2024). Provenance captures origin and heritage meanings and authenticity cues (D'Amico, 2004; Berg and Sevón, 2014; Thøgersen, 2023; Figueiredo et al., 2022). Local patriotism reflects community support and place attachment motives discussed as helping behaviour and identity related consumption drivers (Granzin and Olsen, 1998; Granzin and Painter, 2000; Skallerud and Wien, 2019). Together, these domains operationalise relational and place meanings that are often acknowledged but not consistently measured in local food motivation studies (Memery et al., 2015; Jia et al., 2024).
From a theoretical and managerial perspective, the seven dimensions indicate different ways in which consumers may assign value to local smallholder food products. Quality and taste reflect experiential value, where freshness and sensory appeal are central to product evaluation. Health represents a personal benefit logic, while environmental protection reflects a broader responsibility logic linked to perceived ecological consequences. Personal contact captures relational proximity and the value of direct information exchange with producers. Provenance reflects origin, authenticity and heritage meanings, whereas local patriotism captures support for local producers and communities. Fashion adds a symbolic dimension, suggesting that local smallholder products may also carry visibility, distinctiveness or trend value. For smallholders and local food initiatives, these distinctions can support more precise segmentation and communication. Rather than treating local food consumers as a homogeneous group, the scale can help identify whether consumers are primarily motivated by sensory experience, personal wellbeing, environmental considerations, producer relationships, origin meanings, community support or symbolic consumption.
Building on these distinctions, the structure supports segmentation and communication. Quality and taste-oriented consumers may respond most to sensory and freshness cues, while credence-oriented consumers require credible information about production and impact (Feldmann and Hamm, 2015; Enthoven and Van den Broeck, 2021). Relationship and provenance-oriented consumers can be addressed through interaction, storytelling, and origin narratives (Forney and Häberli, 2016; Berg and Sevón, 2014). Fashion suggests a smaller experiential and social visibility segment, consistent with evidence that digital word of mouth relates to food purchase intention (Leong et al., 2021; Nyagadza et al., 2023).
The scale can be implemented in several practical ways. Smallholders, farmers' markets, local food networks and local food initiatives can use the 19-item instrument in customer surveys to identify dominant motivational profiles among their buyers. For example, if consumers score highly on quality and taste, communication can emphasise freshness, sensory experience and product excellence. If health or environmental protection scores are high, producers and market organisers may provide more credible information about production practices, naturalness, reduced processing or environmental benefits. If personal contact is an important motive, direct interaction with producers, farm visits, tasting events or question and answer opportunities may become central elements of the marketing approach. Provenance and local patriotism scores can inform storytelling about origin, heritage, local identity and support for local producers. Fashion-oriented consumers may be addressed through visually attractive communication, social media content and experience-based product presentation. Policymakers and local development agencies can also use the scale to assess which consumer motivations are strongest in a given region and to design support programmes, communication campaigns or short supply chain initiatives that better match local demand.
Given that this validation was conducted in a single national context, further cross-national validation and invariance testing are needed. The present study focuses on measurement development, while future work can integrate these motivations as antecedents in deductive models alongside engagement and intention constructs (Bukhari et al., 2020, 2023; Anwar et al., 2025).
6. Conclusion
This study developed and validated a concise multidimensional scale for measuring consumer motivations toward local smallholder food products in short food supply chains. In doing so, it addresses an important limitation in local food motivation research. Previous studies have often used heterogeneous, study specific measures and different interpretations of what “local” means, making comparison across studies and cumulative knowledge building more difficult (Eriksen, 2013; Feldmann and Hamm, 2015).
The final structure is theoretically interpretable within established food choice and consumer decision frameworks, capturing intrinsic experience-based motives, credence-based motives, and relationship/place-based meanings (Furst et al., 1996; Nelson, 1970; Darby and Karni, 1973; Forney and Häberli, 2016). Two results are especially informative: quality and taste converge into a single experiential domain, and health shows a close association with environmental protection, consistent with coupled credence-based evaluations (Feldmann and Hamm, 2015; Enthoven and Van den Broeck, 2021). Importantly, the inclusion of personal contact, provenance, and local patriotism operationalises relational and place meanings that are central to smallholder contexts yet often not measured consistently (Forney and Häberli, 2016; Skallerud and Wien, 2019).
7. Limitations and future research
This validation was conducted in one national context using an online panel, which limits generalisability across market structures and institutional settings. At the same time, validating a new scale in a clearly defined national context is consistent with scale development practice and provides valid evidence on the factorial structure, reliability and construct validity of the instrument in that context.
Future research should test cross-national robustness and measurement invariance and establish nomological validity by integrating the scale into deductive models linking motivations to purchase intention, consumer engagement, and purchasing behaviour (Ajzen, 1991; Bukhari et al., 2020, 2023; Anwar et al., 2025). Given the close association between health and environmental protection observed in this study, further work should examine whether a higher-order credence-based factor emerges across contexts or whether more distinct items improve discriminant validity (Nelson, 1970; Darby and Karni, 1973).
Overall, the scale provides a practical and research-ready measurement basis for profiling motivational segments and supporting comparable consumer research in short supply chain settings (Jia et al., 2024; Nordin and Ravald, 2023).
Appendix
Validated version of the scale measuring motivations to consume local smallholder food products
| Factors | Item labels | Items |
|---|---|---|
| Fashion | FASHION1 | Consuming local products is popular |
| FASHION2 | Consuming local products is fashionable | |
| FASHION4 | Local products are more and more popular, and so I have also become interested in consuming them | |
| Health | HEALTH3 | No chemicals frequently used in mass production are used for their production/cultivation |
| HEALTH4 | They do not contain materials that could be harmful for the human body | |
| Personal contact | PERSCONT1 | I maintain good personal relationship with the producer |
| PERSCONT2 | I like to talk to producers/manufacturers in person about their products | |
| PERSCONT3 | I like to buy directly from the producers | |
| Environment protection | ENVPRO2 | The makers of such products take care of and protect their environment |
| ENVPRO3 | They are more environment friendly than their mass-produced counterparts | |
| Local patriotism | LOCPAT1 | I can support local smallholders by consuming their products |
| LOCPAT3 | I would like to help the local economy with my purchases | |
| LOCPAT4 | I know that the money I spend helps the development of the local economy | |
| Quality-taste | TASTE1 | They are more fresh than mass-produced goods |
| TASTE4 | Traditional local tastes are more delicious | |
| QUALITY1 | These products are higher quality than mass-produced ones | |
| QUALITY3 | Usually, they represent a noticeably higher quality | |
| Provenance | PROVE1 | I know where they come from |
| PROVE3 | The origin of these products is precisely known |
| Factors | Item labels | Items |
|---|---|---|
| Fashion | FASHION1 | Consuming local products is popular |
| FASHION2 | Consuming local products is fashionable | |
| FASHION4 | Local products are more and more popular, and so I have also become interested in consuming them | |
| Health | HEALTH3 | No chemicals frequently used in mass production are used for their production/cultivation |
| HEALTH4 | They do not contain materials that could be harmful for the human body | |
| Personal contact | PERSCONT1 | I maintain good personal relationship with the producer |
| PERSCONT2 | I like to talk to producers/manufacturers in person about their products | |
| PERSCONT3 | I like to buy directly from the producers | |
| Environment protection | ENVPRO2 | The makers of such products take care of and protect their environment |
| ENVPRO3 | They are more environment friendly than their mass-produced counterparts | |
| Local patriotism | LOCPAT1 | I can support local smallholders by consuming their products |
| LOCPAT3 | I would like to help the local economy with my purchases | |
| LOCPAT4 | I know that the money I spend helps the development of the local economy | |
| Quality-taste | TASTE1 | They are more fresh than mass-produced goods |
| TASTE4 | Traditional local tastes are more delicious | |
| QUALITY1 | These products are higher quality than mass-produced ones | |
| QUALITY3 | Usually, they represent a noticeably higher quality | |
| Provenance | PROVE1 | I know where they come from |
| PROVE3 | The origin of these products is precisely known |
Note(s): Please think about why you consume local food products. Please rate on a scale of 1–5 how much you agree with each statement below. A score of 1 means you strongly disagree, and a score of 5 means you strongly agree. I consume local food products because…

