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Citation: Baek, J., & Choe, Y. (2025).

Applying the SOR Framework to Food

Truck Dining: Consumption Needs,

Perceptions, and Behavioral Intentions.

Tourism and Hospitality,6(5), 265.

https://doi.org/10.3390/

tourhosp6050265

Licensee MDPI, Basel, Switzerland.

This article is an open access article

distributed under the terms and

conditions of the Creative Commons

Attribution (CC BY) license

(https://creativecommons.org/

licenses/by/4.0/).

Article

Applying the SOR Framework to Food Truck Dining:

Consumption Needs, Perceptions, and Behavioral Intentions

Jooa Baek 1and Yeongbae Choe 2,*

1Department of Tourism Management, Jeju National University, Jeju-si 63243, Jeju-do, Republic of Korea;

baekj@jejunu.ac.kr

2Department of Tourism Management, Gachon University, 1342 Seongnamdaero, Sujeong-gu,

Seongnam-si 13306, Gyeonggi-do, Republic of Korea

*Correspondence: ychoe@gachon.ac.kr

Abstract

This study investigated how consumers’ food consumption needs and perceptions in-

ﬂuence their attitudes and behavioral intentions toward food truck dining. Drawing on

the stimulus–organism–response (SOR) framework, perceived risks and beneﬁts were

conceptualized as external stimuli; food consumption needs (necessity vs. enjoyment)

and attitudes represented the organism; and behavioral intentions denoted the response.

Data were collected via Amazon Mechanical Turk and analyzed using structural equation

modeling and multigroup comparisons based on prior food truck experience. Perceived

beneﬁts and food enjoyment positively inﬂuenced attitudes, whereas perceived risks nega-

tively inﬂuenced attitudes. Attitude signiﬁcantly predicted future behavioral intentions,

whereas food as a necessity did not. The multigroup analysis revealed that prior experience

moderated these relationships; perceived beneﬁts and risks primarily guided inexperienced

consumers, whereas experienced consumers formed attitudes mainly through hedonic

needs. These ﬁndings contribute to the literature by integrating the SOR and value–attitude–

behavior hierarchies to explain cognitive and motivational mechanisms underlying food

truck patronage. They also highlight the moderating role of prior experience, which re-

shapes the strength of the model’s key paths. The study offers practical implications for

food truck operators seeking to balance risk mitigation with perceived beneﬁts to encourage

repeat patronage.

Keywords: food truck; stimulus–organism–response framework; food consumption needs;

behavioral intention; prior experience

1. Introduction

The increasing popularity of the food truck business is evident in its annual growth

rate of over 10%, making it a top performer in the food service sector (Peek,2023). The

COVID-19 pandemic spurred the industry to expand as consumers increasingly preferred

outdoor, mobile, and socially distanced dining options (IBISWorld,2023). Moreover, the

rapid adoption of digital platforms such as online ordering systems, delivery apps, and

cashless payment technologies has reshaped how food trucks connect with customers and

maintain competitiveness in the post-pandemic era (Mancuso et al.,2023). Beyond simple

affordability, food trucks cater to the needs of budget-conscious yet experience-seeking

consumers by offering a distinctive dining experience that combines convenience, novelty,

and social interaction (Holmes et al.,2018;Shin et al.,2019;Yoon & Chung,2018). From an

Tour. Hosp. 2025,6, 265 https://doi.org/10.3390/tourhosp6050265

Tour. Hosp. 2025,6, 265 2 of 19

entrepreneurial perspective, starting a food truck business requires a relatively low start-up

investment compared with traditional brick-and-mortar restaurants (McLaughlin,2009).

Moreover, the public relations strategy of this business relies heavily on online social media

platforms and mobile technologies as the marketing distribution channels to reach potential

consumers and generate buzz (Petersen,2014). Food trucks often operate temporarily

at various locations, offering diverse food choices from high-quality meals to innovative

fusion cuisines (Koutroumanis,2015;Shin et al.,2019).

Despite the growing popularity of food truck businesses, the mechanisms underlying

consumer choice remain unclear. Early studies on food trucks identiﬁed key antecedents,

such as perceived value, risk, and beneﬁts, as well as service quality, as drivers of behavioral

intention (Shin et al.,2019;Yoon & Chung,2018). Although these factors have insightful

managerial implications, they were often examined as direct predictors or through simple

attitude models. This limitation calls for further research on the interaction between

situational perceptions (e.g., the perceived beneﬁts of a speciﬁc food truck) and consumers’

stable, preexisting food consumption needs (e.g., whether they view food as a necessity or

enjoyment) (Bäckström et al.,2004;Onwezen & Bartels,2013).

To address this gap, we argued that a more advanced framework would differentiate

these components. A consumer’s decision can be inﬂuenced by the truck’s immediate

stimuli and their higher-order values related to the food. Therefore, we adopted the

stimulus–organism–response (SOR) framework (Mehrabian & Russell,1974). While the

SOR model is well established in hospitality research, the organism (O) component is

often conceptualized as a single, situational evaluative state (e.g., emotion or attitude).

We proposed a more nuanced model in which the “O” is a dual-component system, a

key contribution of this study. The “O” was conceptualized as comprising (1) stable,

high-order traits (i.e., food consumption needs) and (2) a situational, evaluative state (i.e.,

attitude toward the food truck). This model allowed us to investigate how external stimuli

(S: perceived risks and beneﬁts) are processed through a consumer’s underlying value

system and immediate evaluation, leading to a behavioral response (e.g., intention).

Based on this framework, this study addressed three research objectives. First, it

examined how consumers’ stable food consumption needs (necessity vs. enjoyment)

inﬂuence their situational attitudes and ﬁnal behavioral intentions. Second, it assessed

the role of immediate stimuli (perceived risks and beneﬁts) in shaping consumer attitudes.

Finally, this study explored how prior experience moderates these relationships by testing

whether the decision-making process differs between new and experienced consumers.

2. Literature Review

2.1. SOR Model as the Theoretical Foundation

This study was built on the SOR paradigm (Mehrabian & Russell,1974), a research

framework in environmental psychology. We considered perceived risks and beneﬁts as

stimuli, incorporated attitudes and food consumption needs as organisms, and deﬁned

behavioral intentions as the response. In the SOR paradigm, the “S” variables inﬂuence

the “O”, ultimately leading to changes in the “R” within the study context. A stimulus

is an external factor that triggers a speciﬁc response (e.g., approach or avoidance behav-

ior) through the organism’s internal evaluation (Mehrabian & Russell,1974;Wang et al.,

2024). In tourism and hospitality research, factors such as the servicescape (W. G. Kim

& Moon,2009), perceived quality (Jang & Namkung,2009), hotel atmosphere (H. Choi &

Kandampully,2019), and destination attributes (Chen et al.,2022) have been identiﬁed as

stimuli. The organism serves as the mediating component in the SOR model, representing

individuals’ internal states, including cognitive and emotional conditions. These states

mediate the relationship between external stimuli and ﬁnal response behaviors (Mehrabian

Tour. Hosp. 2025,6, 265 3 of 19

& Russell,1974). Several studies have examined satisfaction (Chen et al.,2022;H. Choi

& Kandampully,2019), customer value (Wu & Li,2018), and cognitive and emotional

states (Wang et al.,2024) as components of the organism. The response is deﬁned as the

individual’s ultimate decision or behavior and initially referred to as approach or avoidance

behaviors (Mehrabian & Russell,1974). Scholars in the tourism and hospitality industry

have used constructs such as intention (W. G. Kim & Moon,2009), word-of-mouth intention

(Wu & Li,2018), customer engagement (H. Choi & Kandampully,2019), and environmen-

tally responsible behavior (Wang et al.,2024) as responses within the SOR framework. We

built on this framework to conceptualize the key perceptions of food trucks (i.e., perceived

risks and beneﬁts) as external stimuli. These stimuli were evaluated through consumers’

internal organism, which comprises their stable traits (e.g., food consumption needs) and

evaluative states (e.g., attitude toward food trucks). Finally, behavioral intention was

regarded as the response.

While earlier studies demonstrate the SOR framework’s robustness, further research

should examine how the “O” is conceptualized. “O” has generally been regarded as a

single, transient evaluative state, such as satisfaction, customer value, and cognitive and

emotional states (Chen et al.,2022;H. Choi & Kandampully,2019;Wang et al.,2024;Wu &

Li,2018). This approach often overlooks the inﬂuence of more stable preexisting consumer

traits or values that ﬁlter external stimuli. Conversely, value-based models such as the

value–attitude–behavior (VAB) hierarchy excel at modeling these traits while neglecting

the role of immediate situational stimuli (S). Our study bridged this gap by proposing a

dual-component model of the organism that integrates stable traits (needs) and situational

states (attitudes) to provide a more comprehensive picture of consumer decision-making.

2.2. Perceptions of Food Trucks as Stimuli

In food consumption scenarios, consumer perceptions of risks and beneﬁts are essential

factors that inﬂuence individual decisions and food choices (J. Choi et al.,2013;D. J. Kim

et al.,2008;Yoon & Chung,2018). Therefore, this study employed perceived risks and

beneﬁts as the stimuli for food truck revisit intention within the research framework.

2.2.1. Perceived Risks

Perceived risk is deﬁned as a consumer’s subjective evaluation of the uncertainty

and potentially detrimental consequences associated with a decision (Bauer,1960). Jacoby

and Kaplan (1972) proposed ﬁve dimensions of perceived risk: physical, performance,

ﬁnancial, social, and psychological. In the context of food trucks, such risks are often

associated with food safety and hygiene concerns. As food is usually prepared in outdoor

street environments, concerns about physical risks arise. Consequently, consumers worry

about the cleanliness of food trucks and their surroundings, including ingredient handling,

the lack of sanitation facilities, and the overall environment. These concerns engender

perceptions of hygiene and environmental risks when deciding whether to patronize a

food truck (Baek & Choe,2025). An extensive review of the literature on food trucks

and perceived risk conﬁrmed a consistent negative impact on consumer attitudes toward

street food and food trucks, signiﬁcantly reducing their intention to visit (J. Choi et al.,

2013;Yoon & Chung,2018). However, the speciﬁc roles of perceived risk subdimensions

present complex and sometimes inconsistent results. For example, Yoon and Chung (2018)

found that hygienic risk weakened consumer attitudes, but environmental risk had no

signiﬁcant impact. Similarly, Loh and Hassan (2022) conﬁrmed that environmental risk was

not a signiﬁcant predictor of consumer attitudes toward food trucks, particularly among

repeat visitors. Based on the empirical results of previous studies, this study hypothesized

the following:

Tour. Hosp. 2025,6, 265 4 of 19

H1. Consumers’ perceived risks are negatively associated with their attitudes toward food trucks.

2.2.2. Perceived Beneﬁts

Consumers anticipate some positive outcomes or value from using a product or service.

Thus, perceived beneﬁt can be deﬁned as a consumer’s belief about the extent to which

they will be better off as a result of a decision (D. J. Kim et al.,2008). Consumers’ perceived

beneﬁts are often conceptualized across two dimensions: utilitarian and hedonic value

(Voss et al.,2003). Utilitarian value is task-oriented and emphasizes functional and practical

beneﬁts. Considering the mobile and quick-service nature of food trucks, the utilitarian

dimension of perceived beneﬁts is expected to be salient.

This utilitarian beneﬁt is primarily evident as convenience, encompassing the time and

effort saved through quick service and easy accessibility (Berry et al.,2002). Convenience,

including quick service and easy accessibility, has been identiﬁed as a signiﬁcant beneﬁt

for food trucks (J. Choi et al.,2013;Tinker,2003). Obtaining delicious food at a reasonable

price in accessible locations may provide immediate value to consumers. Studies on food

trucks have consistently veriﬁed this positive relationship, demonstrating that perceived

beneﬁts positively affect attitudes toward food trucks (J. Choi et al.,2013;Yoon & Chung,

2018). In addition, a qualitative study by Shin et al. (2020) highlighted that food truck

visitors’ behavioral beliefs were shaped by convenience (39%), quick service (34%), and a

convenient location (33%), emphasizing the importance of utilitarian beneﬁts. Based on

these results, we hypothesized the following:

H2. Consumers’ perceived beneﬁts are positively associated with their attitudes toward food trucks.

2.3. Consumers’ Internal States and Traits as an Organism

2.3.1. Food Consumption Needs

This study adopted the VAB hierarchy as the primary theoretical framework to explain

how consumers’ fundamental needs inﬂuence their attitudes and intentions. In the VAB

hierarchy, values—enduring organizations of beliefs—serve as the foundation for the

formation of attitudes, which ultimately lead to speciﬁc target behaviors (Homer & Kahle,

1988). This sequential path from abstract cognitions (i.e., values) to mid-range cognitions

(i.e., attitudes) to speciﬁc behaviors has been empirically veriﬁed in multiple studies.

Research has demonstrated the broad applicability of the VAB hierarchy to consumer

behavior, including food-related contexts (Deng et al.,2014;J. Jun et al.,2014). Similarly,

in tourism and hospitality, the framework has been used to better understand visitors’

behavior (Kang et al.,2015). For example, Han et al. (2019) empirically showed the effect

of perceived value on attitude and behavioral intentions. Additionally, Shin et al. (2017)

demonstrated the direct and indirect impact of values on behavioral intentions in the

context of organic food restaurants. J. H. Kim et al. (2024) conﬁrmed a sequential pathway

from values through attitudes to revisit intentions in Chinese nutraceutical restaurants.

We conceptualized the core value in the VAB hierarchy as consumers’ fundamental

food consumption needs. As consumers move along Maslow’s hierarchy of needs from

basic physiological needs (e.g., hunger) to higher-level needs (e.g., enjoyment and hap-

piness), food choices extend beyond functional utility to experiential value (Lazaridis &

Drichoutis,2005;Senauer,2001). Food consumption needs comprise necessity (i.e., food

as fuel) and enjoyment (i.e., food as a source of pleasure), which are essential in shaping

consumer preferences. Although research (e.g., Shin et al.,2019) has examined perceived

value in the context of food trucks, this study focused on fundamental food consumption

needs as antecedents of attitudes and behavioral intentions.

Two perspectives on food consumption needs were adopted: food as a necessity and

food as a source of enjoyment (Bäckström et al.,2004;Onwezen & Bartels,2013). Food as

Tour. Hosp. 2025,6, 265 5 of 19

enjoyment refers to food hedonism, which emphasizes the hedonic enjoyment derived from

food intake and regards food as shaping one’s way of life (Karisto et al.,1993). However, the

concept of food as merely a necessity suggests that it is a biological requirement (Bäckström

et al.,2004). These concepts correspond to the well-established hedonic and utilitarian

values, which are key predictors of consumer attitudes and behaviors in the food truck

context (Voss et al.,2003).

Additionally, food consumption needs must be distinguished from their perceived

beneﬁts. Perceived beneﬁts (e.g., convenience and quick service) function as external

stimuli and are more likely to be situational and cognitive evaluations of a speciﬁc food

truck’s attitudes and offerings. However, food consumption needs are stable high-order

traits within the organism. Derived from the VAB hierarchy, this represents a consumer’s

preexisting general value orientation toward the food before they encounter the stimulus.

The VAB hierarchy provides a clear rationale for the pathway from food consumption

needs to attitude and the indirect route to behavioral intention mediated by attitude.

The goal activation theory (Altmann & Trafton,2002) and the model of goal-directed

behavior (Perugini & Bagozzi,2001) suggest that fundamental needs may directly trigger

behavioral intentions without necessarily forming attitudes. Building on this view, our

study conceptualized consumers’ food consumption needs as higher-order goals that can

directly shape attitudes and inﬂuence behavior. Therefore, we formulated the following

two hypotheses:

H3. Consumers’ food consumption needs are positively associated with their attitudes toward

food trucks.

H4. Consumers’ food consumption needs are positively associated with their intentions to revisit

food trucks.

2.3.2. Attitude

Attitude refers to a person’s consistent favorable or unfavorable judgment about a

speciﬁc object or behavior, which inﬂuences their behavioral intentions (Fishbein & Ajzen,

1975). Attitude can be considered a psychological tendency toward a positive or negative

view of a particular object or behavior. As an internal state, attitude acts as a cognitive

and emotional ﬁlter, allowing consumers to comprehensively evaluate and judge various

attributes (stimuli) of a speciﬁc entity, such as food trucks.

Attitude is central to the theory of planned behavior (Ajzen,1985,1988), generally

functioning as a key psychological factor mediating the relationship between perceived

beneﬁts or risks and behavioral outcomes. From the SOR perspective, attitude is not merely

an antecedent of behavioral intention but serves as a core psychological variable that links

consumers’ beliefs. It represents the organism’s state, connecting external stimuli (i.e., risk

or beneﬁt perception) to ﬁnal behavioral intentions. Attitude is an essential antecedent of

behavioral intention in the theories of reasoned action (Fishbein & Ajzen,1975) and planned

behavior (Ajzen,1991). Numerous studies have consistently conﬁrmed the positive effect of

attitude on behavioral intention. However, recent studies have recognized that the strength

of this relationship is not absolute under various boundary conditions, such as situational

factors or individual characteristics (Sheeran & Webb,2016). In the context of food trucks,

favorable attitudes increase revisit and purchase intentions (J. Choi et al.,2013;Loh &

Hassan,2022;Yoon & Chung,2018). Therefore, this study posited the following hypothesis:

H5. Consumers’ attitudes toward food trucks are positively associated with their intentions to

revisit them.

Tour. Hosp. 2025,6, 265 6 of 19

2.4. Behavioral Intention as a Response

Behavioral intention refers to an individual’s intention or plan to perform a spe-

ciﬁc behavior (Fishbein & Ajzen,1975). As a cornerstone of the theories of reasoned

action and planned behavior, behavioral intention is considered the most proximal pre-

dictor of actual behavior (Ajzen,1991;Fishbein & Ajzen,1975). While acknowledging the

well-documented “intention–behavior gap,” behavioral intention remains a vital outcome

variable in consumer behavior research and is often inﬂuenced by satisfaction and per-

ceived value (Sheeran & Webb,2016). In the hospitality context, revisit intentions and

recommendations are widely used as key factors in assessing performance and customer

loyalty (Oliver,1999;Zeithaml et al.,1996).

In the SOR framework, behavioral intention is conceptualized as the ﬁnal behavioral

response, which is primarily driven by consumers’ organism state, such as attitudes.

Therefore, those with a positive attitude toward food trucks are more likely to revisit and

recommend them to others. For such a mobile business that relies heavily on social media

buzz and customer tracking, behavioral intentions are critical for survival and growth.

2.5. Moderating Role of Prior Experience

Consumer behavioral research has often identiﬁed prior experience as a moderating

variable that inﬂuences information processing and decision-making (Alba & Hutchinson,

1987). This study drew on two complementary theories to hypothesize the moderating role

of prior experience. First, the elaboration likelihood model suggests that consumers process

information differently based on knowledge and involvement (Petty & Cacioppo,1986;

Petty et al.,1983). Depending on the level of knowledge gained from prior experience, con-

sumers’ criteria for interpreting and judging information vary, particularly when evaluating

a new service such as food trucks. When making decisions in highly uncertain situations,

people without prior experience may rely heavily on extrinsic cues. This study posited that

inexperienced consumers, who lack a knowledge base, would rely on simple peripheral

cues (i.e., salient perceived risks and beneﬁts). By contrast, experienced consumers (not

necessarily experts) evaluate intrinsic attributes by drawing on their established schemas.

Thus, experienced consumers use the central route, with their internal food consumption

needs as the primary basis for forming an attitude. Second, the habit formation theory

(Verplanken & Aarts,1999) indicates that as behaviors become routine, the deliberate,

attitude-driven cognitive link can weaken. Therefore, we expected the strength of the path

from attitude to behavioral intention to diminish for the experienced group.

Thus, prior experience with food trucks represents an important moderating factor

in the relationships between risks, beneﬁts, attitudes, and behavioral intentions. In the

context of shared accommodation services (e.g., Airbnb), risk perceptions differ between

users and nonusers, with experienced users evaluating risk factors with greater granularity

and being less inﬂuenced by psychological risks (S. H. Jun,2020). First-time food truck

customers are more likely to be inﬂuenced by perceptions of risk, whereas experienced

consumers rely more on enjoyment and intrinsic attributes to form attitudes. Therefore, we

proposed the following hypothesis:

H6. Consumers’ prior experience with food trucks moderates the pathways inﬂuencing their

attitudes and behavioral intentions.

The research framework, including all hypotheses, is illustrated in Figure 1.

Tour. Hosp. 2025,6, 265 7 of 19

Figure 1. Research Framework.

3. Methodology

3.1. Survey Questionnaire

We developed a survey questionnaire based on previous research on food trucks, food

consumption needs, and food choices. The instrument comprised four distinct sections. The

ﬁrst section included general questions on the food truck experience (i.e., number of dining

out experiences in the previous month, number of food truck experiences in the previous

month, average spending per single visit in the previous month, and average spending per

single visit at the food truck in the previous month). The second section asked respondents

to indicate their level of agreement with several statements on food consumption needs

(i.e., food as a necessity and food as enjoyment; Onwezen & Bartels,2013). The third section

contained three constructs related to food truck perceptions—perceived risk, perceived

beneﬁts, and attitude toward food trucks—along with future behavioral intention. These

were derived from earlier studies on food trucks (J. Choi et al.,2013;Yoon & Chung,2018),

and a 7-point Likert scale was used (ranging from 1 = “strongly disagree” to 7 = “strongly

agree”). The ﬁnal section inquired about demographic characteristics (i.e., age, sex, and

annual household income). Hospitality and restaurant scholars who had conducted similar

studies were invited to review the initial survey questionnaire. Based on their comments

and feedback, the questionnaire was revised to enhance the validity of the questions and

measurement items. The revised version was used in a pilot test with graduate students

majoring in tourism and hospitality programs.

3.2. Data Collection and Analysis

Data were collected using Amazon Mechanical Turk (MTurk). To ensure the quality

of the collected data, we employed two strategies: (1) targeted samples and (2) response

validation using attention check questions and response times. First, only US-based MTurk

workers with a high task approval rating (>95%) and a high level of experience (>100 tasks)

were considered for participation, ensuring the reliability of the sample. Second, the

questionnaire included multiple attention check questions. Respondents who failed to

Tour. Hosp. 2025,6, 265 8 of 19

answer correctly at least once were excluded owing to the lack of attention during the survey.

Responses with extremely short (

≤

2 min, indicating inattentiveness) or long (>20 min,

indicating distraction) completion times were removed (Curran,2016). In addition, we

blocked repeated responses from the same IP address. A total of 410 participants completed

the questionnaire (bounce rate: approximately 22%; average completion time: 6 min).

We employed structural equation modeling (SEM) in R version 4.5.1, using the lavaan

0.6-20 package (Rosseel,2012) to analyze the relationships among the proposed constructs

(Figure 1). We followed Anderson and Gerbing’s (1988) two-step approach to ensure the

validity and reliability of the measures. A multigroup analysis was conducted to examine

the differences in the proposed relationships among the constructs between individuals

with (n= 123) and without (n= 282) food truck experience. To conﬁrm the adequacy of the

sample size for multigroup SEM, a post hoc power analysis was conducted using G*Power

3.1. The sample, including the smallest group (n= 123), had power greater than 0.80 to

detect medium effect sizes (f

= 0.15) at

= 0.05. This conﬁrmed that the sample was

adequately powered for the proposed analyses.

4. Results

4.1. Demographic Characteristics

Our sample included 188 males (49.8%) and 201 females (50.2%) participants, after

excluding 10 participants who declined to specify their gender. For annual household

income, after excluding 15 respondents who refused to provide information, a relatively

even distribution was observed across categories. The most common income bracket was

$50,000–$75,000 (87 respondents, 21.8%), followed by $40,000–$50,000 (55 respondents,

13.4%), $30,000–$40,000 (53 respondents, 12.9%), and $75,000–$100,000 (49 respondents,

12.0%). The average age of the respondents was 38.8 years (standard deviation = 11.3), with

a median age of 36.0 years.

4.2. Validity and Reliability

The conﬁrmatory factor analysis conﬁrmed that the data ﬁt the measurement model

well (CFI = 0.988, TLI = 0.986, RMSEA = 0.031, SRMR = 0.034). Moreover, the chi-square

test statistic was signiﬁcant (MLM

χ2

(237) = 300.382, p< 0.01;

χ2

/df = 1.446). The data

presented in Tables 1and 2conﬁrm the convergent and discriminant validity (Hair et al.,

2006). All average variance extracted (AVE) values were greater than 0.5, the standardized

factor loadings were greater than 0.7, and all construct reliability values were greater than

0.7. In addition,

√AVE

> correlation, maximum shared variance < AVE, and average

shared variance < AVE. The inter-construct correlation between food as enjoyment and

perceived beneﬁts was low (0.298), and the square root of the AVE for both constructs

was substantially greater than the correlation. This provided strong statistical support for

their distinctiveness and theoretical separation. Overall, the measures used in this study

demonstrated adequate validity and reliability, allowing for further examination of the

relationships among the constructs.

Table 1. Conﬁrmatory Factor Analysis Results.

Construct Items Coef.

Food as a necessity

I do not care what I eat, as long as I am not hungry. 0.811

I do not care how my food is produced. 0.798

It makes no difference to me what kind of food is served at parties. 0.791

I do not really need information about new foods. 0.764

Tour. Hosp. 2025,6, 265 9 of 19

Table 1. Cont.

Construct Items Coef.

Food as enjoyment

Eating is very important to me. 0.825

Delicious food is an essential part of my daily life. 0.849

Eating is a highlight of my day. 0.792

I treat myself to something really delicious. 0.762

Perceived risk

Improper food storage 0.920

Not using fresh ingredients 0.856

Unsanitary conditions 0.898

Insufﬁcient water supply 0.776

Poor food quality 0.839

High risk for food poisoning 0.894

Perceived beneﬁts

Easy accessibility 0.925

Eating convenience 0.940

Fast or prompt service 0.881

Attitude

Disadvantageous vs. advantageous 0.806

Foolish vs. wise 0.814

Unpleasant vs. pleasant 0.919

Unattractive vs. attractive 0.914

Behavioral intention

I am planning to visit a food truck when eating out in the future. 0.927

I intend to visit a food truck when eating out in the future. 0.959

I will make an effort to visit a food truck when eating out in the future. 0.880

Table 2. Validity and Reliability.

Correlations Among Constructs

(1) (2) (3) (4) (5) (6)

Food as a necessity (1) 0.792 a

Food as enjoyment (2) −0.315 0.809

Perceived risk (3) 0.030 −0.043 0.865

Perceived beneﬁts (4) 0.047 0.298 −0.232 0.916

Attitude toward food trucks (5) 0.067 0.291 −0.438 0.596 0.869

Future behavioral intention (6) 0.072 0.328 −0.295 0.648 0.702 0.922

Cronbach’s alpha 0.869 0.879 0.946 0.939 0.921 0.945

Construct reliability 0.870 0.882 0.947 0.940 0.924 0.944

Average variance explained 0.627 0.655 0.748 0.839 0.754 0.850

Maximum shared variance 0.099 0.108 0.192 0.420 0.493 0.493

Average shared variance 0.022 0.076 0.067 0.184 0.226 0.223

Notes. aThe square root of the average variance explained values are along the diagonal.

4.3. Hypothesis Testing

Before testing the proposed hypotheses, we constructed a research model with several

control variables (e.g., age, income, frequency of dining out per week, and average check

size per meal). However, the results were consistent across those with and without the con-

trol variables; therefore, subsequent interpretations excluded them. The proposed research

model was tested using SEM and had a good ﬁt with the data (

MLM χ2(239) = 333.805

p< 0.001

;

χ2/d f

= 1.397; CFI = 0.983; TLI = 0.980; RMSEA = 0.038 [90% conﬁdence interval:

0.028–0.047]; SRMR = 0.044). All the paths were evaluated based on their coefﬁcients and

t-values (Figure 2). As hypothesized, all paths in our research model were statistically

signiﬁcant, except for the direct path from food as a necessity to behavioral intention. Per-

ceived risk was negatively related to consumers’ attitude toward food trucks (

β=−0.322

p< 0.001), whereas perceived beneﬁt was positively associated with attitude (

= 0.486,

Tour. Hosp. 2025,6, 265 10 of 19

p< 0.001

). Food as a necessity (

= 0.101, p< 0.05) and food as enjoyment (

= 0.160,

p< 0.01) were positively related to consumer attitudes toward food trucks. Food as enjoy-

ment (

= 0.168, p< 0.01) and attitude toward food trucks (

= 0.661, p< 0.001) were related

to future behavioral intention. Meanwhile, food as a necessity (

= 0.083, p> 0.05) was

not directly associated with behavioral intention. The variances in attitude toward food

trucks and future behavioral intention were 49.4% and 53.6%, respectively. In the overall

model, perceived beneﬁt, not perceived risk, was a primary driver of consumers’ positive

attitude toward food trucks. Moreover, the attitude toward food trucks yielded the highest

standardized coefﬁcient, leading to behavioral intention, followed by food as enjoyment.

Figure 2. Hypothesis Testing: Overall Group.

To test the full SOR paths and VAB-based logic, we conducted a formal mediation

analysis using the bootstrapping method. The results conﬁrmed that attitude signiﬁcantly

mediated these relationships. The indirect effect of perceived risk on behavioral intention

via attitude was signiﬁcantly negative (

= 0.213, p< 0.001), whereas the indirect effect of

perceived beneﬁt on behavioral intention via attitude was signiﬁcantly positive (

= 0.321,

p< 0.001

). Food as a necessity (

= 0.067, p< 0.05) and food as enjoyment (

= 0.106,

p< 0.01

)

indirectly affected behavioral intention. These ﬁndings support our conceptualization of

attitude as the key mechanism through which both external stimuli and internal traits are

converted into behavioral intentions.

4.4. Group Differences

Once the overall group results were conﬁrmed, the participants were divided into

two groups based on their prior food truck experience. We then conducted a measurement

invariance test across the two subgroups, followed by a group difference test. As suggested

by Hair et al. (2006), conﬁgural, metric, scalar, and strict factorial invariances were tested

sequentially using the

χ2

difference test, with the Satorra–Bentler correction applied. All

the measurement invariance tests conﬁrmed that the measurement model was invariant

across the two groups (Table 3).

Tour. Hosp. 2025,6, 265 11 of 19

Table 3. Model Invariance Test.

Model Fit Measures Model Differences

χ2df pRMSEA CFI TLI SRMR AIC BIC ∆χ2p

Separate groups

Visitor group 298.28 237 0.004 0.053 0.960 0.953 0.064 8478.16 8654.29

Non-visitor group

283.79 237 0.020 0.033 0.987 0.985 0.041

19,366.11 29,593.74

Measurement

invariant test

Conﬁgural

invariance 581.26 474

>0.001

0.040 0.980 0.977 0.046

27,940.27 28,632.59

Metric invariance 601.05 492

>0.001

0.040 0.980 0.977 0.048

27,929.35 28,550.05

19.58

0.357

Full scalar

invariance 636.75 510

>0.001

0.042 0.977 0.975 0.049

27,927.78 28,476.86

48.52

>0.001

Partial scalar

invariance 616.01 507

>0.001

0.039 0.980 0.978 0.049

27,912.12 28,473.14

13.43

0.569

Strict factorial

invariance 640.52 531

>0.001

0.039 0.979 0.978 0.049

27,941.48 28,407.01

26.82

0.313

Based on this result, we compared the strength of each relationship between the expe-

rienced and inexperienced groups (Figure 3). Out of the seven hypotheses (Table 4), two hy-

potheses observed signiﬁcant differences across the two groups: Food as enjoyment

→

Atti-

tude (

βexperienced =

0.555,

βinexperienced =

0.036,

∆χ1=

6.663,

0.01) and Attitude

→

Behavioral intention (

βexperienced =

0.463,

βinexperienced =

0.643,

∆χ1=

3.651,

0.10).

However, the path from food as enjoyment to behavioral intention was statistically sig-

niﬁcant only for the inexperienced group (

βinexperienced =

0.151). An interesting pattern

emerged for the role of food as enjoyment. For the experienced group, the relationship

between food as enjoyment and attitude was statistically signiﬁcant. However, for the inex-

perienced group, the relationship between food enjoyment and attitude was statistically

signiﬁcant for behavioral intention. We also observed a marginally signiﬁcant difference

in the path from attitude to behavioral intention. As suggested by the habit formation

framework, this ﬁnding provides initial evidence that the relationship between attitude

and intention may weaken with increasing the level of experience and habit formation;

however, attitude may remain a signiﬁcant predictor in both groups. The remaining four

paths showed no signiﬁcant differences between the two groups.

Table 4. Group Differences.

Path

Experienced

Group

Inexperienced

Group χ2Difference Test

Coefﬁcient Coefﬁcient

Perceived risk →Attitude −0.404 *** −0.364 *** χ2

d f =1= 1.990

Perceived beneﬁt →Attitude 0.243 * 0.458 *** χ2

d f =1= 0.078

Food as a necessity →Attitude 0.2 0.067 χ2

d f =1= 1.039

Food as enjoyment →Attitude 0.555 *** 0.036 χ2

d f =1= 6.663 ***

Attitude →Behavioral intention 0.463 ** 0.643 *** χ2

d f =1= 3.651 †

Food as a necessity →Behavioral intention 0.04 0.069 χ2

d f =1= 0.357

Food as enjoyment →Behavioral intention 0.286 0.151 ** χ2

d f =1= 0.903

Note: *** p< 0.001, ** p< 0.01, * p< 0.05, † p< 0.10.

Tour. Hosp. 2025,6, 265 12 of 19

Figure 3. Group Differences.

5. Conclusions and Discussion

5.1. Conclusions

This study examined the inﬂuence of food consumption needs and perceptions of

food trucks on consumers’ future behavioral intentions as well as the differences between

groups based on their prior experience with food trucks. The attitude toward food trucks

was the strongest predictor of behavioral intention and was primarily shaped by increased

Tour. Hosp. 2025,6, 265 13 of 19

perceived beneﬁts and reduced perceived risks. While food as enjoyment led to attitude

formation, the impact of food as a necessity was limited. In our multigroup analysis, the

inexperienced group relied more on general cues, such as perceived beneﬁts and risks, to

form their attitudes. Meanwhile, food as enjoyment was directly associated with behavioral

intention, without being mediated by the attitude toward food trucks. Conversely, for the

experienced group, the inﬂuence of attitude on behavioral intention was relatively weaker.

Food as enjoyment became crucial for attitude formation. Simultaneously, the impact of

perceived beneﬁts diminished, and the direct effect of food as enjoyment disappeared.

The group invariance test demonstrated signiﬁcant differences in the path from food as

enjoyment to attitude, while indicating a weaker, marginal difference in the path from

attitude to behavioral intention.

5.2. Theoretical Implications

This study contributes to the literature by outlining fundamental insights into the

characteristics of food truck consumers and examining the dynamic relationship between

food consumption needs, attitudes, and decision-making. The theoretical implications are

as follows. First, this study enhances understanding of consumer behavior in the context of

food trucks by integrating the dual perspectives of food as both a necessity and a source of

enjoyment. Both consumption needs were positively associated with attitude formation in

the overall group, with enjoyment exerting a stronger inﬂuence than necessity. Importantly,

only consumers with prior experience with food trucks showed a signiﬁcant relationship

between enjoyment and attitude. By contrast, the inexperienced group demonstrated a

signiﬁcant relationship between enjoyment and future intentions. This ﬁnding aligns with

recent studies on food trucks (Shin et al.,2019), indicating that food truck consumers are

motivated by fun and enjoyable dining experiences.

Second, based on previous food truck experience, our multigroup analysis provides a

more nuanced understanding of how food truck visitors make decisions. It reveals how

prior experience inﬂuences the determinants of attitude formation by altering the core

inputs. Our ﬁndings align with the elaboration likelihood model, which suggests that

consumers with lower involvement and knowledge rely on peripheral cues, which are

easier to judge; by contrast, consumers with higher knowledge use the central route and

evaluate the core logic of an offering (Petty & Cacioppo,1986;Petty et al.,1983). For

the inexperienced group, perceived risk and convenience served as peripheral cues that

were immediate and easier to understand, shaping their attitudes toward food trucks.

Meanwhile, the experienced group processed these cues through the central route to assess

whether the food truck experience aligned with their core values, such as considering food

as a source of enjoyment. Evidently, prior experience played a key role in food truck-related

decision-making. Through repeated exposure, food truck consumers identify effective and

diagnostic cues to anticipate satisfaction and adjust their evaluation process accordingly

(Alba & Hutchinson,1987;Feldman & Lynch,1988). In our study, utilitarian perceptions

initially dominated attitude formation; however, after the experience, hedonic aspects, such

as enjoyment, emerged as the primary predictor.

Third, our ﬁndings reveal the boundary conditions of how attitude inﬂuences behav-

ioral intention. Our results support and expand the theory of planned behavior (Ajzen,

1985,1988), emphasizing the central role of attitude toward food trucks in the decision-

making. Simultaneously, experience functions as a boundary condition that reshapes the

attitude–intention relationship. According to the habit formation model (Verplanken &

Aarts,1999), repeated behaviors become routinized, leading to a habit-driven process

that is automatically triggered by speciﬁc contexts or cues. This process can weaken the

connection between attitude, intention, and behavior. Consistent with the habit formation

Tour. Hosp. 2025,6, 265 14 of 19

model, our results demonstrate a diminished effect of attitude on behavioral intention in

the presence of prior experience, indicating a shift in routinized decision-making patterns.

Fourth, our research framework integrates multiple theoretical perspectives into a

parsimonious but robust model, possessing two theoretical strengths. The VAB hierarchy

(Homer & Kahle,1988), which posits that individual values lead to attitudes and then

behaviors, is combined with the SOR framework (Mehrabian & Russell,1974). Notably,

this study differentiates consumers’ organisms using trait-based elements (e.g., food con-

sumption needs) and situationally variable, state-based elements (e.g., attitude toward

food trucks). We incorporate prior experience as a boundary condition to illustrate that

the salience of core paths within the model is dynamically reconﬁgured as a function of

consumers’ learning and accumulated knowledge (Bagozzi,1992). This dynamic view

improves the generalizability of the theoretical framework by conceptualizing consumer

decision-making as an evolving, rather than static, process.

Finally, food as a necessity was not a direct driver of behavioral intention for all models

(e.g., overall group, experienced group, and inexperienced group). This suggests that while

satisfying basic hunger is a prerequisite for any food service, it is neither a differentiator

nor a driver of choice for food trucks. Consumers do not visit food trucks out of necessity;

rather, this need is a baseline, and the decision to visit is driven by hedonic needs, risk

perceptions, and perceived beneﬁts.

5.3. Practical Implications

Our ﬁndings propose actionable data-driven strategies for food truck operators. The

most critical implication is the need for segmented marketing based on customer experience.

Our multigroup analysis found that inexperienced consumers’ attitudes were primarily

driven by perceived beneﬁts (

= 0.458, p< 0.001) and risks (

−

0.364, p< 0.001). Their

food truck choice was not inﬂuenced by hedonic needs, thereby prioritizing utilitarian

value (e.g., speed, convenience, and accessibility) and mitigating risk (e.g., visible hygiene

and clean surfaces; J. Choi et al.,2013). Implementing visible hygiene practices, such as

on-site cleaning stations, regular inspections, and transparent ingredient handling, can

reduce the perceived risk. Moreover, social media can be leveraged to display proactive

efforts, such as posting videos of daily grill and fryer basket cleaning, oil replacement, or

surface sanitization, and demonstrating the use of fresh, high-quality local ingredients. By

signaling cleanliness and safety, food truck entrepreneurs can establish trust and attract a

broader customer base. This strategy is well-suited for small food truck operators. How-

ever, a completely different strategy is required to retain customers. Perceived beneﬁts

did not drive experienced consumers’ attitude but were overwhelmingly inﬂuenced by

food as enjoyment (

= 0.555, p< 0.001). Therefore, to promote loyalty, food truck opera-

tors should switch strategies from convenience to hedonic value. Food truck owners and

operators should enhance the dining experience by combining affordability with memo-

rable and enjoyable features, particularly for repeat customers. For example, hosting live

cooking demonstrations, displaying interactive menu boards, or hosting themed events

(e.g., “Sushi Monday” or “Taco Friday”) can create a memorable, enjoyable atmosphere,

thereby strengthening repeat visits. Meeting hedonic needs is as important as provid-

ing affordable meals to encourage repeat visits. These hedonic-oriented strategies are

more suitable for larger food truck operators or well-funded vendors and require careful

cost–beneﬁt analysis.

Furthermore, our results provide a clear strategic direction for proactively manag-

ing consumer attitudes. Attitude was the single most powerful predictor of behavioral

intention (

= 0.661, p< 0.001). This ﬁnding conﬁrms that fostering a positive attitude is

extremely crucial for repeat visits. Our model demonstrates how attitudes are constructed

Tour. Hosp. 2025,6, 265 15 of 19

or destroyed. Attitudes were signiﬁcantly inﬂuenced by perceived beneﬁts (

= 0.486,

p< 0.001

) and risks (

−

0.322, p< 0.001). In particular, the negative coefﬁcient for per-

ceived risk indicates that the fear of poor hygiene or food safety is the primary factor

weakening positive attitudes. Cleanliness is necessary but not sufﬁcient; operators should

visibly and proactively manage perceptions of risk. Therefore, a key practical implication is

for operators to adopt a strategy of radical transparency, particularly on social media, to

mitigate negative risk perceptions directly. The example of the Gwangju chicken restaurant

(Chosun News,2024), which tripled its sales by posting daily photos of cleaning, is a perfect

real-world application of our principle, which our model validates. Food truck operators

should adopt similar strategies, such as (1) posting behind-the-scenes videos of daily sani-

tation, ingredient handling, and oil replacement; (2) clearly displaying health certiﬁcations

on the truck and all online proﬁles; and (3) actively responding to customer comments

and questions about hygiene practices. This transparent approach directly addresses the

powerful negative path from perceived risk to attitude in our study. By neutralizing this

negative relationship, operators can sustain the positive relationship between attitude and

behavioral intention, which is key to long-term success.

Finally, our ﬁnding of a marginally weaker path from attitude to behavioral intention

for the experienced group has subtle but essential managerial implications. As suggested

by the habit formation theory, with increasing experience, customers’ decisions to revisit

may become more automatic or habituated. For new customers, the relationship between

attitude and behavioral intention was exceptionally strong (

= 0.643, p< 0.001). Here, the

managerial priority is attitude creation. Every effort must be made to ensure that the ﬁrst

experience is positive, as the initial attitude is the single most critical factor in securing a

future visit. However, for repeat customers, the relationship is weaker (

= 0.463, p< 0.01).

This does not mean that attitude is unimportant but that a positive attitude alone cannot

guarantee a return visit, as habit plays a more substantial role. The managerial priority

then shifts to habit reinforcement. Operators must focus on consistency, friction removal,

and loyalty rewards to ensure that the habit loop is not broken.

5.4. Future Research Directions

Although our study addressed several key questions, some areas warrant further

exploration in future research. First, studies should examine the differences in usage

contexts, perceptions, and behaviors between regular food truck consumers and non-

consumers. They should investigate how demographic variables (e.g., age, income, and

lifestyle) and cultural differences affect food truck patronage, preferences, and perceptions

of food safety and enjoyment. For example, comparing ﬁndings from countries where

tipping is less common than in the US or where hygiene standards differ could provide

valuable insights into attitudes as well as perceived beneﬁts and risks. Additionally, future

studies should compare the effectiveness of various risk mitigation strategies (e.g., hygiene

practices and food quality assurances) across regions and consumer groups to identify best

practices. This knowledge can guide marketing efforts and operational plans for food truck

operators in multicultural settings.

Second, given the growing importance of digital marketing and social media cam-

paigns, researchers should examine their effects on perceptions of food truck safety and

consumer trust. Food truck owners often use social media to share their hygiene practices

and quality guarantees; however, systematic research is required to evaluate the effective-

ness of these digital strategies across various platforms and consumer segments. Such

insights could help identify how social media can best be utilized to boost consumer trust

and credibility. Additionally, future studies should evaluate the role of digital platforms

and test them as potential mediators. For instance, the mediating role of a digital platform’s

Tour. Hosp. 2025,6, 265 16 of 19

perceived quality (e.g., ease of use or usefulness for ordering) in the relationship between a

food truck’s perceived beneﬁts and consumers’ subsequent attitudes could be examined. A

similar research question could be posed regarding the relationship between perceived risk

and attitude through the quality of a digital platform.

Third, researchers should conduct longitudinal studies to understand how consumer

attitudes and behaviors toward food trucks evolve over time, especially in response to

changing health regulations, food trends, and events such as the COVID-19 pandemic or

food scandals. For instance, events such as the Chipotle E. coli outbreak, the 2015 Blue Bell

Listeria contamination, and food poisoning cases linked to food trucks underscore the need

to examine consumer behavior before, during, and after such crises. Monitoring this shift

would offer valuable insights into the long-term impacts of external factors on the food

truck industry.

Fourth, we obtained our sample from MTurk. Despite careful management through

attention checks and screening criteria, this sample may not represent all demographic

or cultural segments of food truck patrons, limiting the external validity of the ﬁndings.

Future studies should use more diverse demographics, on-site intercept surveys, or online

review-based studies to verify our ﬁndings.

Finally, future studies should evaluate the broader economic impact of food trucks

on local communities. With lower initial investment requirements, food trucks can create

employment opportunities for chefs, servers, and support staff while expanding income

streams through localized sourcing. For example, a single food truck can create employ-

ment for several people, ranging from cooks preparing food to vendors selling it. By

sourcing ingredients locally, food trucks support regional agriculture and boost the econ-

omy. Moreover, popular food trucks can stimulate trafﬁc and beneﬁt the surrounding retail

and service businesses by attracting tourists and locals. Simultaneously, festivals or special

events can enhance local tourism and generate additional revenue for the community. Poli-

cymakers and community developers can draw on such observations to design favorable

regulations, establish designated food truck zones, and provide infrastructure for mobile

vendors. Recognizing the socioeconomic contributions of food trucks will enable their

integration into regional development and growth strategies.

Author Contributions: J.B.: Conceptualization, Methodology, Investigation, Validation, Writing—

original draft, Writing—review and editing. Y.C.: Conceptualization, Data curation, Formal analysis,

Methodology, Writing—original draft, Writing—review and editing. All authors have read and

agreed to the published version of the manuscript.

Funding: This research received no external funding.

Institutional Review Board Statement: Ethical review and approval were waived for this study due

to the University of Macau’s internal regulation. It does not require professors and researchers in the

social sciences to obtain IRB approval, particularly for self-funded studies using surveys.

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement: The original contributions presented in the study are included in the

article, further inquiries can be directed to the corresponding author.

Conﬂicts of Interest: The authors declare no conﬂicts of interest.

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Applying the SOR Framework to Food Truck Dining: Consumption Needs, Perceptions, and Behavioral Intentions PDF Free Download

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