Green hotels visit intention among young adults: integrating the familiarity, novelty, trust, perceived risk, and theory of planned behaviour

Abstract

Previous hospitality research typically focuses on consumers’ positive attitudes and intentions toward addressing an existing research gap in the literature on consumer attitude and behaviour in green hotel marketing. Those studies have frequently neglected to investigate the effects of negative attitudes and perspectives. This study aims to explore the relationships between seven indicators of perceived risk, familiarity, novelty, trust, attitude, subjective norm, perceived behavioural control, and intention to visit green hotels. A total of 606 questionnaires were collected and analysed using structural equation modelling. Results showed that perceived risk negatively influences trust, subjective norm, and perceived behavioural control. Familiarity positively influences perceived risk but negatively influences attitude. Novelty negatively influences perceived risk and attitude, while trust positively influences attitude and intention. Subjective norm positively influences attitude, perceived behavioural control, and intention, and attitude influences intention. This study provides an alternative negative factor perspective on green hotel visitation using a theoretically driven approach.

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ARTICLE
Green hotels visit intention among young adults:
integrating the familiarity, novelty, trust, perceived
risk, and theory of planned behaviour
Lei Wang 1, Qi Zhang2, Meng-Jie Ye2, Philip Pong Weng Wong3& Yue Gong4✉
Previous hospitality research typically focuses on consumers’positive attitudes and inten-
tions toward addressing an existing research gap in the literature on consumer attitude and
behaviour in green hotel marketing. Those studies have frequently neglected to investigate
the effects of negative attitudes and perspectives. This study aims to explore the relation-
ships between seven indicators of perceived risk, familiarity, novelty, trust, attitude, sub-
jective norm, perceived behavioural control, and intention to visit green hotels. A total of 606
questionnaires were collected and analysed using structural equation modelling. Results
showed that perceived risk negatively influences trust, subjective norm, and perceived
behavioural control. Familiarity positively influences perceived risk but negatively influences
attitude. Novelty negatively influences perceived risk and attitude, while trust positively
influences attitude and intention. Subjective norm positively influences attitude, perceived
behavioural control, and intention, and attitude influences intention. This study provides an
alternative negative factor perspective on green hotel visitation using a theoretically driven
approach.
https://doi.org/10.1057/s41599-024-03935-0 OPEN
1Faculty of Hospitality and tourism, Xuzhou University of Technology, Xuzhou, China. 2Business School, Xuzhou University of Technology, Xuzhou, China.
3School of Hospitality and Service Management, Sunway University, Petaling Jaya, Malaysia. 4Faculty of Hospitality and Tourism, Shanxi Vocational College
of Tourism, Taiyuan, China. ✉email: 522096938@qq.com
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1234567890():,;
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Introduction
The transformation of traditional hotels is contributing to
the commercialisation of green hotels in the hospitality
industry, which is accelerating the green hotel sector’s rise
in importance in hospitality and tourism marketing (Al-Gharibah
and Mahfod, 2022). Numerous hotel chains have begun to pro-
mote green construction practices and green business strategies
(Pan et al. 2022). To minimise the negative environmental impact
(Wang et al. 2023b), businesses like Hilton Hotels & Resorts,
InterContinental Hotels & Resorts, Marriott International, and
many other lower-level hotel chains have integrated green man-
agement and marketing initiatives in their operations (Fauzi et al.
2022). Sustainability is becoming increasingly important in the
hospitality sector (Agag and Colmekcioglu, 2020), as according to
academic, governmental, and marketing reports showing that the
hotel industry consumes an enormous amount of natural
resources, such as excessive water, energy, and lighting con-
sumption (Ansari et al. 2022). Because of this, green hotels have
developed several innovative programs that reduce costs while
protecting the environment by reducing the production of solid
waste, energy, and water (Green Hotel Association, 2024).
Considering consumers have to pay the Pigouvian tax, which is
regulated by economists and governments, they have been
adjusting their purchasing habits to be more ecologically friendly
(Goodwin et al. 2014). Green consumerism is also visible in the
service-oriented industries (Wahab and Ismael, 2022), and more
consumers have recently started to favour environmentally
friendly products and services because environmental issues such
as global warming and haze have a substantial negative impact on
their daily lives (Wang et al. 2022f). Primarily, tourists choose to
stay at green hotels in order to show their appreciation for the
environment (Verma et al. 2019). For example, almost 89% of
Taiwanese tourists reported that, given the option, they would
choose to stay at green hotels when travelling (Pan et al. 2022).
However, booking revenue for green hotels has been mostly
unchanged despite a rise in consumer awareness of the impor-
tance of environmental conservation (Wang et al. 2023a). In
other words, although consumers express a willingness to stay at
green hotels, there is insufficient evidence to substantiate the
notion that their environmental concerns will prompt them to
visit green hotels (Wang et al. 2023c).
Previous research has shown that there is an unstable corre-
lation, known as the attitude-behaviour gap, between consumers’
professedly favourable attitudes and their purchasing behaviours
when it involves green product/service consumption (Kumar,
2021; Wang, 2022). Studies utilising the theory of reasoned action
(TRA) (Al-Gharibah and Mahfod, 2022), theory of planned
behaviour (TPB) (Lim et al. 2019), value-attitude-behaviour
model (Wang et al. 2022f), moral norm-activation theory of
altruism (Rahman and Reynolds, 2019), value-belief-norm theory
(Wang et al. 2020a), and goal-framing theory (Wang et al. 2022b)
highlighted some of the inadequacy of these studies that embrace
a theoretical lens, and as such, the studies’conclusions are fre-
quently challenged, inconclusive, or even restricted in scope
(Wang et al. 2023a; Wang et al. 2022b). As the purpose of visits to
green hotels is noticeably underestimated (Nimri et al. 2020a), it
is important to comprehend the underlying factors influencing
tourists’intentions to visit green hotels (Ray et al. 2023) for hotels
to adapt their operations and satisfy the needs of environmentally
conscious visitors (Sultana et al. 2022). Therefore, new theoretical
perspectives need to be included in order to better understand
visitors’expectations when they visit green hotels (Wang et al.
2023c).
In contrast to the concept of negative behavioural intention,
which has not received much attention (Ulker-Demirel and Ciftci,
2020; Wang et al. 2022d), the majority of literature on hospitality
and tourism focused on positive attitudes and intentions by using
various antecedents of consumer behaviour (Han et al. 2020a;
Joshi et al. 2021; Patharia et al. 2020; Wang, 2022). In particular,
most tourists only learnt of the notion of green hotels (Wang
et al. 2022e) because it is still relatively new to them (Yeh et al.
2021). Because of this, the majority of tourists are ignorant of the
advantages and functions of green practices (Chen et al. 2021).
Additionally, they are unsure of what green hotels have to offer
(Wang et al. 2022e) or what benefits staying at green hotels may
provide (Fauzi et al. 2022). Thus, researchers need to understand
the reluctance and identify the barriers that retain travellers from
staying at green hotels (Fauzi et al. 2022) in order to investigate
the impact of negative attitudes and perspectives on consumer
behaviour (Ulker-Demirel and Ciftci, 2020; Wang et al. 2022d).
Indeed, while previous research on green hotels has focused
mostly on developed countries (Ansari et al. 2022), this kind of
perspective is particularly frequent in emerging countries (Ahn
and Kwon, 2020; Sadiq et al. 2022), including China (Wang and
Wong, 2021). Because of this, earlier studies were unable to offer
a solid theoretical foundation (Wang et al. 2022b) for an
approach that would theoretically lead to an investigation of how
consumers express unfavourable opinions about their stays at
green hotels. Hence, this study will contribute to a better
understanding of the factors that affect the decision to stay at
green hotels, which include perceived risk, familiarity, novelty,
trust, attitude, subjective norm, perceived behavioural control,
and intention.
Literature review
Theoretical background. TPB is a development of TRA since it
addresses the limitation that people cannot make decisions based
only on their own volition (Nimri et al. 2020a). A person’s
intention towards a particular actual behaviour depends on sev-
eral variables: attitude (i.e., beliefs about the perceived outcomes
associated with the behaviour), subjective norm (i.e., beliefs about
the normative expectations and actions of significant others), and
a newly added measurement variable named perceived beha-
vioural control (i.e., beliefs about the existence of the factors that
encourage or discourage conducting a specific behaviour) (Wang
et al. 2023b). The most direct precursor to identical behaviour is
the intention to act, which shows that the person is mentally able
to take action (Wang et al. 2020b). In general, when someone has
a positive attitude, a strong sense of perceived behavioural con-
trol, and a favourable subjective norm, they should be more
inclined to engage in the behaviour in question (Liu et al. 2020).
Because of its persistent nature, TPB has emerged as one of the
most prominent and important social-psychological models for
comprehending human behaviour in recent years (Kumar, 2021;
Niloy et al. 2023). In particular, since TPB can be expanded by
adding more constructs to improve the explanatory power of the
behaviour in varied circumstances (Wahab and Ismael, 2022),
many scholars have specifically used TRA and TPB as the
underpinning theory in various environmental-related areas of
consumer behaviour studies (Bahl and Kumar, 2019; Kumar,
2021), such as green consumer behaviour (Bahl and Kumar, 2019;
Kumar, 2021); low carbon emissions (Wahab and Ismael, 2022);
responsible environmental behaviour (Casado-Díaz et al. 2020;
Lin et al. 2021); organic foods (Cheng et al. 2023; Wibowo et al.
2022); green hotel visitation (Al-Gharibah and Mahfod, 2022;
Bashir et al. 2019); and many others.
Attitude. Attitude refers to the degree to which an individual’s
overall appraisal of their actions is good or negative (Al-Gharibah
and Mahfod, 2022). It is a mental state that influences their
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reactions to people, objects, and situations (Shah et al. 2023).
Consumers’favourably or unfavourably biased opinions about
green products and services reflect how much they value and are
willing to purchase them (Wahab and Ismael, 2022). Consumers
awareness of environmental risks and their consciousness of the
environment have an impact on this decision (Wang et al. 2023a).
In general, a greater likelihood of purchasing green products and
services will result from a generally positive attitude among
consumers (Bryła, 2019). Attitude has been identified as a main
predictor of behaviour in psychological theories (e.g., TRA, TPB,
value-attitude-behaviour model, value-belief-norm theory), and
prior studies have confirmed this predictive capacity in the con-
text of green hotels (Al-Gharibah and Mahfod, 2022; Dwivedi
et al. 2022). For instance, Nimri et al. (2020a) found that attitude
is a critical predictor for travellers to stay at green hotels, while
Wang et al. (2023c) demonstrated that attitude positively influ-
enced consumers’intentions to select green hotels. Nevertheless,
the findings of certain studies showed that attitude does not
determine one’s intention to stay at green hotels (Haq et al. 2023).
Thus, the following hypothesis is proposed for testing:
H1: Attitude significantly influences intention.
Subjective norm. Subjective norm refers to the social pressure
people experience before they are able to establish their own
opinions on the stimuli currently present (Niloy et al. 2023). The
desire to conform to typical social network individuals’sugges-
tions on a given relationship influences people’s perceptions of
those people’s views (Al-Gharibah and Mahfod, 2022). As a
result, people act in their own best interests, and more impor-
tantly, they believe that what they are doing is appropriate if
others are acting in a similar manner (Yeow and Loo, 2022). A
person will typically be appropriately encouraged or discouraged
from engaging in a certain behaviour by an external social
influence (e.g., close friends, relatives, coworkers, or classmates)
(Shah et al. 2023). Recent studies in the field of green marketing
have found a positive correlation between subjective norm and
intention (Kumar, 2021; Sheraz et al. 2021). For example, sub-
jective norm positively influenced travel operators’intentions to
market low-carbon tours (Sung et al. 2021). Another study also
found that the subjective norm positively influenced guests’
intentions to stay at green hotels (Al-Gharibah and Mahfod,
2022; Shah et al. 2023). Thus, the following hypothesis is
proposed:
H2: Subjective norm significantly influences intention.
Several academics have recently questioned the significance of
the subjective norm in the TPB model because of its complexity
and flaws (Wang et al. 2022c; Wang et al. 2022d), especially in
societies that value collectivism heavily (Wang and Wong, 2021).
On the one hand, previous empirical research showed that, in the
context of green marketing, the subjective norm has a limited
capacity to predict consumer behaviour (Niloy et al. 2023; Shah
et al. 2023; Yeow and Loo, 2022). On the other hand, TPB
recognises that attitude, subjective norm, and perceived beha-
vioural control are three independent variables that can influence
a person’s behavioural intention (Ajzen, 1991), but little research
has examined potential links between these variables because the
fact that correlations between them are typically somewhat
significant (Quintal et al. 2010). The TPB’s sequence causalities
thus, may not be accurate (Wibowo et al. 2022). Consumers’
decision-making processes are unable to exclude the potential of a
substantial causal path from the subjective norm to attitude and
perceived behavioural control (Wang et al. 2019a; Wang et al.
2023c).
Because people construct their own opinions based on their
impressions of others’expectations and willingness to comply,
subjective norm may effect on attitudes (Oliver and Bearden,
1985; Quintal et al. 2010). In fact, because individuals uphold
collectivistic principles, those from highly collectivistic regions are
identifiable by their interdependence, cooperation, and lack of
competitiveness (Wang et al. 2022a). The subjective norm in
those societies operates on a large scale as social norms that
impact people’s decision-making (Wang et al. 2022d). Consumers
are probably more inclined to share their positive and negative
experiences with new or unfamiliar products or services with
significant others, which may affect their choice (Wang and
Wong, 2021). Similarly, because people’s perceived capacity to
carry out a certain behaviour is greatly influenced by their
agreements with others (Wang et al. 2022d), people’s perceptions
of external barriers to action are likely influenced by social
pressure to act (Quintal et al. 2010). Certain studies showed that
subjective norm had a significant effect on attitude and perceived
behavioural control towards green purchase intention (Cheng
et al. 2023; Quintal et al. 2010; Wang et al. 2023c). Therefore, the
following hypotheses are proposed:
H3: Subjective norm significantly influences attitude.
H4: Subjective norm significantly influences perceived beha-
vioural control.
Perceived behavioural control. An individual’s perceived ability
or confidence, the availability of opportunities and resources like
time and money, and external factors like facility accessibility can
all influence how easy or difficult behaviour is perceived to be
(Shah et al. 2023). The drivers of perceived behavioural control
are hence direct experience and comparison evaluation of various
possibilities (Yeow and Loo, 2022) that are generated by self-
evaluation (Niloy et al. 2023). Ajzen (2002) states that the two
components that jointly contribute to perceived behavioural
control are controllability, or an individual’s perception of whe-
ther or not the behaviour is fully within his or her control, and
self-efficacy, or an individual’s perceived confidence and ease in
performing a particular behaviour (Liu et al. 2020). Thus, people
are more likely to engage in certain actions that they believe are
easier to complete than in behaviours they believe are more dif-
ficult and over which they have less control (Niloy et al. 2023).
Possessing complete control over behaviour might help or hinder
someone from realising that certain behaviour is possible (Haq
et al. 2023). Numerous earlier studies established the connection
between perceived behavioural control and intention on green
purchasing behaviour (Kumar, 2021; Sung et al. 2021). Never-
theless, some studies have also shown no significant correlation
between perceived behavioural control and consumers’adoption
of green hotels (Eid et al. 2021; Han and Yoon, 2015). As such,
the following hypothesis is proposed:
H5: Perceived behavioural control significantly influences
intention.
Contribution of the current study through extended TPB. The
most extensively utilised theory by scholars in the area of green
hotels is the TPB (Acampora et al. 2022; Arun et al. 2021). The
fundamental reason is that this theory has been extended or
modified to include more or new constructs (Ong et al. 2023; Pan
et al. 2022) since it enables researchers to incorporate more
determinants to raise the amount of variance in intention or
behaviour in diverse circumstances (Ajzen, 1991; Eid et al. 2021).
However, in order to extend the theory, most earlier research
frequently used known conceptual validations that were mostly
based on literature review; these validations might not apply to
the population of interest (Han et al. 2020b; Nimri et al. 2020a).
While some studies used TPB to predict guests’intentions to stay
at green hotels, they failed to extract voluntaristic elements and
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belief elements such as an individual’s risk beliefs and outcome
expectations (Nimri et al. 2020a; Shehawy, 2023), which are cri-
tical to enhancing the precision of motivational prediction models
like the TPB (Nekmahmud et al. 2022; Shehawy, 2023).
For example, a number of studies on green hotels have
observed an increase in greenwashing and green scepticism,
whereby these establishments only offer environmentally friendly
amenities and services in places where they can sway public
opinion without truly advancing the cause of sustainability (Arun
et al. 2021; Chen et al. 2019). Therefore, the normative and
attitudinal elements influenced by this green trust should be taken
into account by researchers. Comparably, the majority of visitors
are unaware of the benefits and functions of green hotels since
they have only heard of the concept (Choi et al. 2015) and are not
familiar with what green hotels have to offer (Wang et al. 2022e).
Nevertheless, relatively few studies have examined the degree to
which familiarity affects guests’perceptions and behaviours with
regard to green hotels, although familiarity is a crucial
precondition that influences guests’perceptions of green hotels,
decision-making processes, and future behaviour (Wang et al.
2022e). Meanwhile, familiarity and novelty are typically seen as
being at different extremes of the spectrum in the literature on
familiarity in tourism (Casali et al. 2020). The novelty has been a
major theme in the literature on tourism, and the majority of
earlier research has shown that people are more inclined to visit a
destination if they have higher novelty orientations towards it
(Assaker and Hallak, 2013; Ponsignon et al. 2020). However,
novelty has received very little attention in the literature on green
hotels. Further, studies have demonstrated that travellers’
decisions to visit a destination are highly influenced by their
perception of risk (Gong et al. 2024; Yi et al. 2020). Because
emotional perceptions play a significant role when considering
risky accommodations (Alvarez and Campo, 2014), measuring
perceived risk in addition to TPB might assist researchers in
comprehending the influence of attitude, subjective norm, and
perceived behavioural control on the intention to stay at green
hotels. This is consistent with the proposal made by Ulker-
Demirel and Ciftci (2020) that additional research is necessary to
examine the impact of negative attitudes and expressions on an
individual’s behaviour.
In conclusion, there is not much research that uses an
expanded version of the TPB model that includes perceived risk,
trust, familiarity, and novelty into account. These factors have
primarily been employed in different investigations. Therefore,
there was not plenty of research done in the past to construct a
comprehensive model that takes into account the transitory
correlations between perceived risk, trust, familiarity, novelty, and
TPB. This is also consistent with the critique that other factors are
required to explain the diversity in behavioural intention because
the TPB is unable to fully explain variation in an individual’s
intention and behaviour (Al-Gharibah and Mahfod, 2022;
Yadegaridehkordi et al. 2021).
Impact of trust. Trust is a belief (Waris and Hameed, 2020) that
pertains to an individual’s relationship with a business and
encompasses attributes such as general dependability, credibility,
honesty, and kindness (Ganesan, 1994). It may also be defined as
one’s level of confidence in another individual (Hart and
Saunders, 1997). Trust in green marketing is the desire of a
consumer to purchase products or services because of their
expectations or perceptions of their reliability and ecological
performance (Chen, 2010). Consumers purchase environmentally
friendly products and services because they consider these goods
to be dependable and capable of protecting the environment
(Shah et al. 2023). As a result, trust gauges how confident con-
sumers are with their purchases (Moorman et al. 1993), and they
use trust to select products and services that align with their
environmental beliefs (Haq et al. 2023). In consumer behaviour
and green marketing, the relationship between trust and beha-
vioural intention has become well-established (Han et al. 2019;
Shah et al. 2023). Meng and Choi (2016), for instance, showed
that individuals are more likely to buy products and services
when they think that they are being given more accurate infor-
mation about them and when they have a higher degree of trust
in them. Trust is also seen to be the main element influencing
travellers’intentions to use electric aircraft (Han et al. 2019).
Nevertheless, there is currently little evidence to back up the
assertion that consumers’pro-environmental behaviour is
influenced by trust (Shah et al. 2023). Recent studies showed
that trust is essential for the development of attitudes and the
perception of behavioural control over particular behaviours
(Dwivedi et al. 2022; Shah et al. 2023). Businesses with a solid
track record of trustworthiness, reputation, and strong perceived
brand equity are better able to create distinctive brands than
simply rank other products or services according to general
objective standards (Salazar-Ordóñez et al. 2018). Therefore,
more positive attitudes towards the decision are likely to arise
from a higher level of trust regarding the decision’s outcomes
(Quintal et al. 2010). Meanwhile, trust can also influence an
individual’s perceived ability to manage their behaviour towards
environmentally friendly products and services (Sung et al. 2021).
For example, people who have less faith in the ecological quality
of the products and services associated with green purchases will
feel less secure in the perceived behavioural control of their
purchases (Koklic et al. 2017). On the other hand, a larger degree
of trust in a specific purchasing activity can offset consumers’
inadequacies in control-believing (Koklic et al. 2017). However,
other research indicates that the intention to stay at green hotels
is not always correlated with green trust (Fauzi et al. 2022). Based
on the above arguments, the following hypotheses are proposed:
H6: Trust significantly influences attitude.
H7: Trust significantly influences perceived behavioural
control.
H8: Trust significantly influences intention.
Impact of perceived risk. The concept of perceived risk originally
came forth by Bauer (1960). It is the conviction that uncertainty
may have a detrimental psychological effect on people’s behaviour
(Park et al. 2022; Wei and Onder, 2022). People worry about the
potential losses they might incur in the future if they make a
particular decision (Afshardoost and Eshaghi, 2020). Real risk
and perceived risk are two categories of risk (Bauer, 1960). Real
risk is the extent to which potential losses are felt subjectively,
while perceived risk is the objective assessment of the likelihood
of adverse outcomes. Therefore, while evaluating perceived risk,
uncertainty and the seriousness of the purchase’s repercussions
must be carefully taken into account (Zhang et al. 2021). Most
researchers agree that perceived risk is an important theoretical
concept that shapes how decision-making processes and con-
sumer behaviour are developed (Aufa and Gunanto, 2023; Stone
and Grønhaug, 1993). Particularly because services are intangible
and challenging to standardise, decision-making in the sector is
heavily influenced by perceived risk (Fuchs and Reichel, 2011).
Numerous research studies substantiate the notion that con-
sumers’perception of risk significantly influences their intentions
or reluctance to participate in a specific action (Chang and Tseng,
2013; Mitchell and Greatorex, 1993).
Perceived risk can be measured using a range of indicators and
categorised into numerous dimensions based on different cultural
backgrounds, research subjects, and situations (Wang et al.
2019b; Zhang and Yu, 2020). Roehl and Fesenmaier (1992)
suggested that perceived risk should take satisfaction and
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environmental risks into account, while Witte et al. (1996)
suggested that perceived risk might be assessed based on severity
and susceptibility. These risk factors were expanded by Sönmez
and Graefe (1998a,1998b), who included the possibility of
terrorism, political instability, and health risks. Information risk,
economic risk, time risk, psychological risk, privacy risk,
distribution risk, service risk, and operational risk are some of
the factors identified by Aufa and Gunanto (2023) as possibly
influencing online shoppers. Overall, financial risk, performance
risk, psychological risk, physical risk, social risk, and time risk are
the most often utilised categories of perceived risks in marketing
research (Zhang et al. 2021).
According to literature on hospitality and tourism, when
choosing hotels’products and services, guests may perceive a
number of dangers, such as the potential to lose time or endanger
their safety (Zhang et al. 2021). Kim et al. (2010) categorised risks
into physical, health, social, and economic categories and
investigated how tourists’perceived risk affected their attitudes.
Park (2017) classified the perceived risk of passengers reducing
their air service into five categories: functional, temporal,
physical, psychological, and economic risk. Zhang et al. (2021)
drew the conclusion that the most frequently perceived risk
aspects associated with tourism-related products and services are
financial risk, performance risk, psychological risk, physical risk,
and social risk.
This study, therefore, considers the effects of financial risk,
performance risk, functional risk, psychological risk, physical risk,
time risk, and health risk on consumers’intentions to visit green
hotels. Accordingly, consumers are primarily affected by financial
risk, which is the possibility of losing money on investments in
products (Aufa and Gunanto, 2023). Performance risk is the
possibility that consumers will be dissatisfied with products or
services for a variety of reasons, which could be detrimental to the
interests and reputations of firms. Failures in delivery, inferior
products or benefits, and a lack of post-purchase assistance are
the usual causes of this risk. Performance risk is important in
influencing travel intention (Khan et al. 2019) and is closely
related to the worry that the products or services in question may
not function as intended or offer consumers the benefits that have
been promised (Küpeli and Özer, 2020). Functional risk is the
conviction that inadequate service will be absent, meaning that
guests will not get what they expected out of their stay (Fuchs and
Reichel, 2011). Psychological risk is a factor that could cause an
in-person, psychological, or emotional reaction (Najar and
Rather, 2022). It is the likelihood that someone will suffer
psychological damage as a result of being in an unfavourable
environment (Park et al. 2022). Physical risk is the possibility of a
product or service having a negative physical impact on an
individual’s health or well-being (Quintal et al. 2010). When
tourists purchase products or services at tourist locations, they
suffer the perceived risk of health problems (Al-Ansi et al. 2019).
It illustrates the possibility that utilising the service might place
the consumer’s health at formerly unprecedented risk (Tsaur et al.
1997).
Several studies used TPB in conjunction with perceived risk to
determine consumers’behavioural intention in marketing
(Arshad et al. 2021; Sujood et al. 2021). For example, Cuong
and Jian (2014) showed that investors’attitudes are negatively
influenced by perceived risk, and tourists’attitudes about travel
are similarly negatively impacted by perceived risk (Wu et al.
2022). Rather (2021) demonstrated that attitudes and consumer
brand engagement were significantly influenced by perceived risk.
Meanwhile, perceived risks are negative perceptions of employees
concerning their environments and generate a social amplifica-
tion effect (i.e., subjective norm) (Kapuściński and Richards,
2016), continuously producing negative impacts on attitudes,
emotions, and behaviours (Xie et al. 2023). When an individual
engages in a certain behaviour, the perception of risk interacts
with perceived behavioural control, which then engages in some
positive or preventive behaviours (Sujood et al. 2021). Park et al.
(2022) found a substantial negative association between perceived
risk and attitudes, subjective norm, and perceived behavioural
control in their study of dangerous airborne pollutants and
particulate matter that threaten human health. Based on the
above studies that emphasise the importance of risk perception in
traveller behaviour, the following hypotheses were developed:
H9: Perceived risk significantly influences attitude.
H10: Perceived risk significantly influences subjective norm.
H11: Perceived risk significantly influences perceived beha-
vioural control.
Consumers’favourable opinions about products and services
or companies that will meet their expectations are referred to as
their trust in business (Ye et al. 2019). Because trust can reduce
high-risk perceptions and help people move over their worries or
uncertainty about their actions and prospective repercussions,
perceived risk and trust play a critical role in determining
consumer purchase intentions (Ganesan, 1994; McKnight et al.
2002). In other words, it is possible to gain authority over
consumers trust by recognising and reducing perceived risks
(Han et al. 2019). Al-Ansi and Han (2019) asserted that perceived
risk has a direct impact on trust, and Huifeng et al. (2020)
indicated the role of trust in moderating the relationship between
perceived risk and revisit intention. Ratasuk and Gajesanand
(2022) support the significant mediating effects of trust and
perceived risk on customers’purchase intentions. Abror et al.
(2022) found that environmental risk and financial risk have a
significant negative correlation with trust. Additionally, Alrawad
et al. (2023) verified the relationship between trust and perceived
risk, and the results showed that perceived risk significantly
influenced feature-based trust, process-based trust, and process-
based trust. Hence, the following hypothesis is proposed:
H11: Perceived risk significantly influences trust.
Familiarity. Familiarity is the amount of consumer accumulated
product-related experiences (Kim et al. 2019), which is regarded
as one of the most important marketing variables (Stylidis et al.
2020). In the tourism industry, familiarity is commonly used to
contrast the experiences of frequent visits and revisits in order to
highlight the differences in destination selection between first-
time and repeat tourists (Wang et al. 2022e). Most people
associate familiarity with two types of experiences: direct
experience (i.e., experience familiarity) and indirect familiarity
(i.e., informational familiarity) (Baloglu, 2001). Thus, travellers
can become more familiar with products and services directly
through purchases and usage (Alcocer and Ruiz, 2020) and
through indirect channels contracts with others, advertisements,
travel guides, movies, brochures, mass media, and education
(Gursoy, 2011; Kim et al. 2018). Familiarity is the basis for
comprehending how people perceive a destination (Soliman,
2021) since it can potentially impact travel decisions and visitors
feel more secure in familiar surroundings (Chi et al. 2020). Pre-
vious research on tourism has shown that visitors with greater
familiarity with a destination typically exhibit more positive
functional and psychological features (Casali et al. 2020) and a
greater intention to visit (Tan and Wu, 2016). Hence, the fol-
lowing hypothesis is proposed:
H13: Familiarity significantly influences attitude.
While searching for new places to visit is one of the main
reasons people travel (Chi et al. 2020), the degree of familiarity
travellers require from a destination has a significant impact on
how they perceive risk (Rather, 2020). Travellers seeking
familiarity will likely view strange environments as more risky
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(Lepp and Gibson, 2003). Information collection to lessen
perceived risk is part of assessing a destination’s risk, which has
a significant impact on travel intention (Kozak et al. 2007). As
opposed to travelling somewhere they are unfamiliar with or not
concerned much about in order to reduce risks, visitors are more
likely to choose locations they have read about in some ways
when choosing a destination (Ju et al. 2021). For example,
travellers would particularly seek out information regarding the
risk of contracting influenza during a pandemic, as this would
greatly influence their travel intentions (Helfenberger et al. 2010).
Pandemic anxiety increased the likelihood that travellers would
postpone or cancel their journeys (Leggat et al. 2010). Therefore,
familiarity reduces risk perceptions and gives travellers greater
assurance when choosing a destination (Soliman, 2021), and the
following hypothesis is proposed for testing:
H14: Familiarity significantly influences perceived risk.
Novelty. Travel motivation is a specific subset of an individual’s
drive that encompasses the network of biological and cultural
factors that provide meaning to and impact travel behaviour,
choice, and experience (Pearce, 2011). Visitors act for a variety of
reasons, including personal experiences, psychological char-
acteristics, and external social and cultural influences (Soliman,
2021). Travellers’attitudes toward a place are thought to be
predicted by their behavioural beliefs about motivational variables
(Ulker-Demirel and Ciftci, 2020; Wang et al. 2021). The novelty-
seeking theory is one such theory that provides a strong theore-
tical foundation for comprehending destination choice behaviour
(Assaker and Hallak, 2013). Accordingly, novelty is described as
consumers’needs for stimulation being addressed by switching
from a previous product or service to a novel one (Kim and Kim,
2015), even when they are satisfied with their initial purchase
(Assaker and Hallak, 2013). There are a number of reasons for
this, such as the need for change to address the boredom that
consumers associate with certain products or services, attribute
satisfaction (Kim and Kim, 2015), or the fact that certain
experiences like fascinating, fun, enjoyable, emotional, exciting,
and multisensorial benefit specific categories of consumers
(Ponsignon et al. 2020). In the tourism industry, consumers’
novelty refers to the need for stimulation that drives visitors to
select a new location over one they have previously visited (Kim
and Kim, 2015). High novelty-seeking travellers also frequently
show their desire to explore new locations (Hong et al. 2009),
especially those travelling alone who value seeking other cultures
over local traditions (Lepp and Gibson, 2003). Thus, the following
hypothesis is proposed:
H15: Novelty significantly influences attitude.
Furthermore, previous research on tourism marketing has
shown that a visitor’s behavioural paradigm is split between
familiarity and novelty (Casali et al. 2020). Individuals who have a
strong attraction to novelty tend to choose different destinations
and are therefore less likely to go back to the same place (Lepp
and Gibson, 2003), and compared to people who desire
familiarity, they are more prone to believe that unknown
environments are less threatening (Assaker and Hallak, 2013).
Under this circumstance, travellers may be drawn to a place by its
novelty, while others may be repelled (Elsrud, 2001), because they
are driven to vacation and seek a state of disequilibrium (Lepp
and Gibson, 2003). Furthermore, because various people have
varying needs for novel experiences, tourists range in how much
novelty they seek, and this could significantly affect how risky a
destination is judged to be (Lepp and Gibson, 2003). Rather
(2020) found that novelty considerably reduced tourists’risk
perceptions towards visiting a destination, while other studies
suggested that tourists derive greater novelty value from their
travel experience, increasing their satisfaction with new destina-
tions (Assaker and Hallak, 2013; Kim and Kim, 2015; Ponsignon
et al. 2020) Fig. 1. Based on the preceding discussion, the
following hypothesis is proposed:
H16: Novelty significantly influences perceived risk.
Research methods
Research design. The positivist philosophy is used in this study
because it guarantees that researchers are using mathematical and
statistical techniques to observe the external world in an objective
and value-free manner, leading to results that can be applied to
other contexts (Saunders et al. 2011; Yin, 1994). The type of
Fig. 1 Conceptual research model.
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research is considered an explanatory one since explanatory
studies focus on explaining the nature of the causal relationships
between dependent and independent variables and can identify
which variables are the cause and which are the effect that needs
to be predicted (Saunders et al. 2011). A cross-sectional data
collection approach was used in this study due to time and cost
constraints. As it is difficult to obtain a sampling frame for this
type of study, a non-probability sampling technique was used to
collect samples (Saunders et al. 2011). When selecting samples,
judgemental sampling is employed because it helps researchers
choose the most qualified respondents to answer their questions
and achieve their research objectives (Saunders et al. 2011).
Previous studies revealed mixed results regarding the will-
ingness of younger and older generations to engage in green
consumption, including visiting green hotels (Bhutto et al. 2019;
Wang et al. 2020b), but researchers generally agree that the
younger generation, particularly students, have significantly lower
financial capacity and expenditure than the working population
(Wang et al. 2024b), and it may be extremely difficult for
researchers across disciplines to replicate student results on non-
students (Henry, 2008). However, many recent studies have
advocated that green marketing-related studies including green
hotels studies needed to select younger generation respondents as
their target research sample due to: 1) young adults are better
equipped to compare and assess currently operating green hotels
(Shah et al. 2023); 2) young adults exhibit greater environmental
consciousness than older consumers (Ansari et al. 2022); 3)
young adults possess greater education and knowledge regarding
green consumption (Wang et al. 2022f); and 4) many businesses
target the younger generation as their short-term target market
(Pan et al. 2022) because they have the power to shape
consumption patterns in the future (Bahl and Kumar, 2019).
Hence, the target sample for this study was young adults.
Data collection. An online survey was used for the primary data
collection because of its many benefits, including instant access to a
large audience, the ability to collect data regardless of respondents’
geographic location, high speed of data collection, low cost, better
content display, better access to unique populations, and con-
venience (Wang et al. 2019a). Self-administered questionnaires were
posted and distributed on www.wenjuan.com to gather primary
data from online users between 20 December 2023 and 6 January
2024 because the questionnaire enables a greater geographical
coverage, less cost, involves less pressure, provides anonymity,
allows for quicker collection, and reduces levels of bias compared
with the interview technique (Saunders et al. 2011). Besides, wen-
juan.com is the largest free online survey platform, which is similar
to Google Forms and is well known among individuals, researchers,
businesses, and organisations that focus on providing questionnaire
creation, distribution, management, collection, and analysis services
in China. Wenjuan.com is a member of the CIIA Marketing
Research Association and has more than 10 million users in 2020.
In addition, 3 Chinese yuan (RMB) per person is offered as a
necessary incentive to increase the response rate. A brief explana-
tion of green hotels was provided at the start of the survey, and to
be eligible to complete the survey, all respondents needed to: 1) be
between 18 and 25 years old, and 2) have stayed at green hotels
within the previous twelve months or have the plan to visit green
hotels within twelve months after responding to the survey before
they can proceed to answer the rest of the questions in the survey. A
total of 606 usable responses were collected for analysis, which can
be regarded as adequate for structural equation modelling purposes
(Hair et al. 2019), as a minimum sample size of 384 is recom-
mended when the target population is unknown or infinite based
on Cochran’sFormula(Sarmahetal.2013).
Questionnaire operationalisation. A closed-ended questionnaire
was used in this study, consisting of a set of verified scales (De
Vaus, 2013). This study used a seven-point Likert scale from (1)
strongly disagree to (7) strongly agree to measure the constructs
because a seven-point Likert scale will be more likely to produce
slightly higher mean scores within the highest possible attainable
score, compared with a ten-point Likert scale (Dawes, 2008). All
questionnaire contents were initially translated into Chinese and
then back-translated to English by a second team of bilinguals. In
addition, the questionnaire was validated by two experts, and the
pilot test was conducted with 30 undergraduate students to assess
its reliability before data collection. Overall, the endogenous
variables in this study are perceived risk, trust, attitude, subjective
norm, perceived behavioural control, and intention to visit green
hotels. The exogenous variables in the research model are
familiarity and novelty. In addition, many previous studies have
shown that using demographic variables to predict consumer pro-
environmental attitude and behaviour can produce inconsistent
and even contradictory results (Caniëls et al. 2021; Wang et al.
2020b). Thus, this study considers demographic variables such as
gender, age, educational level, and income as control variables in
the research model.
The questionnaire was designed in four sections. Section A
includes perceived risk-related items, three items used to measure
financial risk were adapted from Abror et al. (2022) and Küpeli
and Özer (2020); three items used to measure performance risk
were adapted from Khan et al. (2019) and Küpeli and Özer
(2020); three items used to measure functional risk were adapted
from Han et al. (2019) and Park et al. (2022); three items used to
measure psychological risk were adapted from Quintal et al.
(2010) and Küpeli and Özer (2020); three items used to measure
physical risk were adapted from Lee (2020) and Küpeli and Özer
(2020); four items used to measure time risk were adapted from
Zhang et al. (2021) and Küpeli and Özer (2020); and three items
used to measure health risk were adapted from Shin and Kang
(2020). Section B includes familiarity, novelty, and trust-related
items; four items used to measure familiarity were adapted from
Chi et al. (2020), Soliman (2021), and Wang et al. (2022e); 4 items
used to measure novelty were adapted from Kim and Kim (2015)
and Thipsingh et al. (2022); and 4 items used to measure trust
were adapted from Choi et al. (2015) and Dwivedi et al. (2022).
Section C includes TPB’s component-related items; four items
used to measure attitude were adapted from Wang et al. (2023c);
three items used to measure subjective norm were adapted from
Taufique and Vaithianathan (2018); three items used to measure
perceived behavioural control were adapted from Wang and
Wong (2021); and three items used to measure intention were
adapted from Wang et al. (2023a). Section D includes
demographic characteristics including gender, age, education
level, and income.
Common method bias (CMB).Consideringtheinfluence of
CMB, respondents were guaranteed confidentiality and privacy
with personal information and answers as all questionnaires
were distributed and collected via an online system (i.e., the
questionnaire QR code linking within the Chinese electronic
survey platform). Most studies still adopt Harman’ssingle-
factor test to examine the potential response bias for marketing
studies (Hulland et al. 2018). Results show that the single factor
score for data is 40.049%, which is below the threshold of 50%.
In addition, the full collinearity of constructs was computed to
comment on CMB. The variance inflation factor (VIF) of all
constructs was calculated, which was found to be less than 10
(Hair et al. 2010). These results indicate that CMB is not an
issue in this study.
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Results
For data to be deemed normal, skewness should be between −2
and +2, and kurtosis should be between −7 and +7 (Byrne,
2016). The results show that normality was achieved as the data’s
skewness value was between 0.506 and −0.053, and the kurtosis
value was between 0.336 and 1.849. The Kaiser-Meyer-Olkin and
Bartlett’s test of sphericity indicates sampling adequacy with
0.962 and a p-value below 0.001. The Cronbach’s alpha test
results indicate the presence of internal consistent reliability, as all
Cronbach’s alpha values were higher than 0.7. Table 1displays
respondents’demographic characteristics; 23.4% were male and
76.6% were female, and most of the respondents were aged 19
years, with the majority of respondents reporting monthly
spending of between 1000 and 2000 Chinese yuan, and
approximately 63% of them were freshmen.
Assessment of measurement model. According to Hair et al.
(2010), all factor loadings should be greater than 0.5, and ideally
higher than 0.7 for the measurement model. For convergent
validity, the composite reliability (CR) should be higher than 0.7
and the average variance extracted (AVE) should be greater than
0.5. For discriminate validity, the AVE value should be greater
than the maximum shared variance (MSV) and the average shared
variance (ASV) (Hair et al. 2010). In addition, all construct-related
values should be less than 0.9 (Meyers et al. 2006). After dropping
off the low factor loading items (i.e., finance risk1, time risk4,
familiarity4, novelty4, trust4), Table 2and Table 3display the
acceptable convergent and discriminate validity of the measure-
ment model. Next, the model fit indices show that
CMIN =3244.75, DF =907, CMIN/DF =3.577, p< 0.001,
CFI =0.929, AGFI =0.75, PGFI =0.663, PNFI =0.793,
PCFI =0.814, NFI =0.905, RFI =0.891, IFI =0.929, TLI =0.919,
SRMR =0.0635, RMSEA =0.065.
Assessment of structural model. The overall goodness-of-fit
indices show that CMIN =5270.696, DF =925, CMIN/
DF =5.698, p < 0.001, CFI =0.868, AGFI =0.677, PGFI =0.62,
PNFI =0.755, PCFI =0.776, NFI =0.845, RFI =0.827,
IFI =0.869, TLI =0.853, RMSEA =0.088. The results of the
structural model of the proposed hypotheses are illustrated in Fig.
2and Table 4.
As shown in Fig. 2and Table 4, the structural model results
show that there is a positive correlation between attitude and
intention with β=0.386, p< 0.05, and C.R. =9.505, thus, H1 was
supported. Subjective norm and intention are positively corre-
lated since β=0.221, p< 0.05, C.R. =4.875; hence, H2 was
supported. Subjective norm and attitude are positively related due
to β=0.447, p< 0.05, and C.R. =15.553; hence, H3 was
supported. Results show that there is a positive relationship
between subjective norm and perceived behavioural control as
β=0.664, p< 0.05, C.R. =18.357; thus, H4 was supported.
However, perceived behavioural control and intention are not
significantly correlated with β=−0.07, p> 0.05, and
C.R. =−1.649; hence, H5 was rejected. Trust and attitude are
considered positively correlated since β=0.315, p< 0.05, C.R. =
11.519; hence, H6 was supported. Results show a non-significant
relationship between trust and perceived behavioural control with
β=−0.013, p> 0.05, C.R. =−0.397; hence, H7 was rejected.
There is a positive correlation between trust and intention found
in this study as β=0.516, p< 0.05, C.R. =13.285; hence, H8 was
supported. Perceived risk and attitude are statistically non-
significantly correlated with β=0.028, p> 0.05, and C.R. =0.777;
hence, H9 was rejected. Perceived risk negatively influences
subjective norm (β=−0.162, p< 0.05, C.R. =−3.164), perceived
behavioural control (β=−0.265, p< 0.05, C.R. =−6.627), and
trust (β=−0.114, p< 0.05, C.R. =−2.229); thus, H10, H11, and
H12 were supported. Familiarity negatively influences attitude
with β=−0.247, p< 0.05, C.R. =−5.376 but positively influences
perceived risk since β=0.503, p< 0.05, C.R. =9.341; thus, H13
and H14 were supported. In addition, results show that novelty
negatively correlated with attitude (β=−0.59, p< 0.05,
C.R. =−13.383) and perceived risk (β=−0.288, p< 0.05,
C.R. =−5.571); hence, H15 and H16 were supported.
Moreover, due to the research model being a second-order one,
a regression test was also performed to determine the relationship
between first-order variables (i.e., financial risk, performance risk,
functional risk, psychological risk, physical risk, time risk, and
health risk) and the second-order variable, which is perceived
risk. The results showed that all first-order variables are
significantly correlated to perceived risk since the critical ratio
value exceeded 1.96 and the p-value was below the threshold
value of 0.05. Indeed, the standardised coefficients for these
relationships are 0.944 (financial risk), 0.889 (performance risk),
0.945 (functional risk), 0.956 (psychological risk), 0.925 (physical
risk), 0.743 (time risk), and 0.92 (health risk), and all associations
are significant at a p< 0.05 level. About 89.1%, 79%, 89.3%,
91.3%, 85.6%, 55.3%, and 84.6% of the total variance in financial
risk, performance risk, functional risk, psychological risk, physical
risk, time risk, and health risk are accounted for by the higher
structure, respectively.
Discussions and implications of the study
The study posited that consumers’negative perceptions and
barriers to visiting green hotels are largely unexplored. It found
that perceived risk encompassing financial, performance, func-
tional, psychological, physical, time, and health risks as its first-
order dimensions are direct predictors of trust, subjective norm,
and perceived behavioural control towards the intention of vis-
iting green hotels. Familiarity and novelty are immediate ante-
cedents of perceived risk. Trust, novelty, and familiarity are the
determinants of attitude towards patronising green hotels.
Additionally, the subjective norm is an important predictor of
attitude and perceived behavioural control towards green hotel
visit intention.
Previous studies on green purchase behaviour verified that
attitude is a robust predictor of intention (Niloy et al. 2023; Shah
et al. 2023). The results of this study show that attitude has a
Table 1 Demographic characteristics.
Item Characteristic Frequency Percentage (%)
Gender Male 142 23.4
Female 464 76.6
Age 18 112 18.5
19 206 34
20 153 25.2
21 70 11.6
22 35 5.8
23 22 3.6
24 8 1.3
Educational level Freshman 382 63
Sophomore 34 5.6
Junior 153 25.2
Senior 31 5.1
Master 2 0.3
Ph.D. 4 0.7
Monthly spending
(RMB)
Below 1000 35 5.8
1000–2000 458 75.6
2001–3000 86 14.2
3001–4000 12 2
Above 4001 15 2.5
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Table 2 Convergent validity of the measurement model.
Construct (Cronbach’s Alpha) Items Factor
loadings
CR AVE S.D. VIF
Financial risk (α=0.841) 1. Rooms in green hotels are very expensive (delete).
2. Green hotels may run the risk of incurring additional charges.
3. I wasted or did not get my money’s worth from services provided by
green hotels.
0.835
0.884
0.85 0.739 1.204
1.247
3.46
Performance risk (α=0.96) 1. I worried whether the green hotels provide services as well as they are
supposed to.
2. I worried that green hotels would not provide the level of benefits that I
expected.
3. Caused me to concern for how really dependable and reliable the
services green hotels would be.
0.948
0.946
0.948
0.963 0.897 1.188
1.199
1.167
5.734
Functional risk (α=0.944) 1. Green hotels are at risk of problems with the quality of accommodation
facilities.
2. Compared with traditional hotels, green hotels have the risk of low
quality of function.
3. There is a risk of low service in green hotels.
0.929
0.932
0.915
0.944 0.85 1.268
1.322
1.333
4.312
Psychological risk (α=0.899) 1. Visting green hotels made me feel psychologically uncomfortable.
2. Visiting green hotels gave me a feeling of unwanted anxiety.
3. Visiting green hotels caused me to experience unnecessary tension.
0.873
0.861
0.862
0.899 0.749 1.412
1.448
1.377
4.742
Physical risk (α=0.887) 1. Green hotels can be uncomfortable.
2. Green hotels are less clean than traditional hotels due to using certain
recyclable materials.
3. Green hotels may be in an unsafe, remote place.
0.876
0.903
0.772
0.888 0.726 1.303
1.322
1.373
3.651
Time risk (α=0.946) 1. Choosing to stay at a green hotel is not efficient.
2. Choosing a green hotel can take a lot of time.
3. Choosing to stay at a green hotel was a waste of my personal time.
4. Choosing to stay at a green hotel during a trip can put time pressure
on me (delete).
0.917
0.937
0.926
0.948 0.859 1.25
1.203
1.244
4.42
Health risk (α=0.95) 1. Staying at green hotels can lead to health problems.
2. Green hotels are at risk of contracting infectious diseases due to using
certain recyclable materials.
3. Staying at a green hotel was a risky decision for my health.
0.934
0.953
0.918
0.954 0.874 1.281
1.277
1.309
4.481
Familiarity (α=0.929) 1. I obtain information about green hotels from brochures, pamphlets,
newspaper, magazines, travel guidebooks and official website.
2. I obtain information about green hotels from friends and relatives’
interactions and travel agency.
3. Compared to my friends and other people, I am very familiar with
green hotels.
4. Compared to people who travel a lot, I am very familiar with green
hotels (delete).
0.92
0.896
0.91
0.934 0.826 1.102
1.066
1.136
4.176
Novelty (α=0.958) 1. I want to experience new and different things or environment on
vacation (e.g., staying at green hotels).
2. I want there to be a sense of discovery (e.g., visit green hotels)
involved as part of my trip.
3. I want to experience green hotels’cuisine, crafts, handiwork, and new
foods.
4. My ideal vacation involves looking at things I have not or rarely seen
before (e.g., visit green hotels) (delete).
0.943
0.951
0.941
0.962 0.893 1.143
1.133
1.147
7.56
Trust (α=0.939) 1. I feel that green hotels’environmental commitments are generally
reliable.
2. I feel that green hotels’environmental performances are generally
dependable.
3. I feel that green hotels environmental arguments are trustworthy.
4. I feel that green hotels keep the environmental promises and
commitment they make (delete).
0.939
0.939
0.896
0.947 0.855 1.276
1.339
1.288
2.688
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positive impact on consumers’intentions to stay at green hotels.
This indicates that customers believe staying at green hotels is an
intelligent choice and have an overall positive opinion of the
attributes of these establishments.
There are controversial results about the effect of subjective
norm and perceived behavioural control on intention in green
marketing (Shah et al. 2023; Wang and Wong, 2021; Yeow and
Loo, 2022). The results of this study show that subjective norm
positively influences intention, which means that people (e.g.,
friends, relatives, and family members) can positively influence
consumers to stay at green hotels when they think it is the right
choice and when they support their decision to stay at green
hotels. Those results are in line with Wang et al. (2024b), who
stated that subjective norm plays an important role in deter-
mining consumers’intention to select green hotels. However, the
results of this study show that perceived behavioural control does
not influence intention. This means that consumers’perceptions
of their ability and available resources, such as money, time, or
opportunity, do not always translate into their decision to stay at
green hotels. Those results correspond with certain studies that
showed that perceived behavioural control cannot be considered a
predictor of intention (Patharia et al. 2020; Yeow and Loo, 2022),
which is in contrast with some studies showing that perceived
behavioural control positively influences intention (Kumar, 2021;
Sung et al. 2021).
The subjective norm should be considered as an antecedent of
attitude and perceived behavioural control within the TPB model
(Wang et al. 2024a), and certain studies confirmed that the
subjective norm significantly influences one’s attitude and per-
ceived behavioural control towards intention (Wang et al. 2023c;
Wang et al. 2022d). Results of this study show that subjective
norm positively influences attitude and perceived behavioural
control, respectively. This demonstrates how an individual’s
positive assessments of the attributes of green hotels and ability to
visit, as well as his or her intention to visit green hotels, are
greatly influenced by the opinions of one’s close friends, cow-
orkers, family members, and relatives.
Certain studies demonstrated that trust has an important role
in determining consumer attitude, perceived behavioural control,
and intention in green marketing (Shah et al. 2023; Sung et al.
2021). Results of this study show that trust positively influences
attitude and intention. This implies that consumers will have a
more favourable attitude and be more likely to visit green hotels if
they believe that green hotels are trustworthy and dependable and
that their environmental performances are dependable. However,
the results of this study show that trust insignificantly influences
perceived behavioural control. This indicates that there is no
correlation between consumers’ability and confidence to visit
green hotels and their beliefs about the attributions and envir-
onmental performances of green hotels.
Familiarity may enhance an individual’s understanding of
perceptions and knowledge of products or destinations through
direct or indirect information (Wang et al. 2022e), leading to a
higher or lower recognition of products or services’attributes (Ju
et al. 2021), which will influence his intention to purchase pro-
ducts/services or visit a particular destination (Soliman, 2021).
Results of this study showed that familiarity positively influences
consumers’perceived risk and negatively influences attitude
towards visiting green hotels. This means that consumers who
perceive they are knowledgeable about green hotels through
information received either from publicity (e.g., newspapers,
magazines, green hotels’websites) or close friends’and other
people’s recommendations, think that green hotels are generally
riskier compared to conventional hotels. They also have negative
evaluations and assessments of visiting green hotels and the
hotels’attributes.
Table 2 (continued)
Construct (Cronbach’s Alpha) Items Factor
loadings
CR AVE S.D. VIF
Attitude (α=0.951) 1. I think it is wise to choose a green hotel.
2. I think it is important to choose a green hotel.
3. I think there is value in choosing a green hotel.
4. I am interested in green hotels.
0.936
0.923
0.901
0.897
0.953 0.836 1.041
1.076
1.053
1.174
6.376
Subjective norm (α=0.945) 1. People around me think it is a good choice to stay at a green hotel.
2. The people around me were understanding of my choice to stay at a
green hotel.
3. The people around me were supportive of my choice to stay at a green
hotel.
0.917
0.937
0.936
0.951 0.865 1.088
1.038
1.082
4.219
Perceived behavioural control
(α=0.874)
1. I have unlimited choice of green hotels if I want.
2. I can choose to stay at a green hotel or not.
3. I have the ability to choose green hotels.
0.774
0.876
0.886
0.883 0.717 1.227
1.198
1.13
2.332
Intention (α=0.879) 1. I will make an effort to stay at a green hotel when travelling.
2. I am likely to stay at a green hotel.
3. I am more likely to stay at a green hotel over a non-green hotel.
0.922
0.948
0.739
0.906 0.765 1.224
1.23
1.484
–
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Fig. 2 Results of the study.
Table 4 Results of the regression model.
Hypothesis Parameter βC.R. Sig. Decision
H1 Attitude ------------> Intention 0.386 9.505 *** Supported
H2 Subjective norm --> Intention 0.221 4.875 *** Supported
H3 Subjective norm --> Attitude 0.447 15.553 *** Supported
H4 Subjective norm --> Perceived behavioural control 0.664 18.357 *** Supported
H5 Perceived behavioural control --> Intention −0.07 −1.649 0.099 Not supported
H6 Trust ---------------> Attitude 0.315 11.519 *** Supported
H7 Trust ---------------> Perceived behavioural control −0.013 −0.397 0.692 Not supported
H8 Trust ---------------> Intention 0.516 13.285 *** Supported
H9 Perceived risk ----> Attitude 0.028 0.777 0.437 Not supported
H10 Perceived risk ----> Subjective norm −0.162 −3.164 0.002 Supported
H11 Perceived risk ----> Perceived behavioural control −0.265 −6.627 *** Supported
H12 Perceived risk ----> Trust −0.114 −2.229 0.026 Supported
H13 Familiarity --------> Attitude −0.247 −5.376 *** Supported
H14 Familiarity --------> Perceived risk 0.503 9.341 *** Supported
H15 Novelty ------------> Attitude −0.59 −13.383 *** Supported
H16 Novelty ------------> Perceived risk −0.288 −5.571 *** Supported
*** denotes p-value < 0.001.
Table 3 Discriminate validity of the measurement model.
Item CR AVE MSV ASV 1 2 3 4 5 6 7 8
1. Intention 0.906 0.765 0.707 0.484 0.875
2. Perceived risk 0.957 0.765 0.1 0.034 −0.047 0.874
3. Familiarity 0.934 0.826 0.781 0.484 −0.685 0.279 0.909
4. Novelty 0.962 0.893 0.783 0.528 −0.762 0.139 0.884 0.945
5. Trust 0.947 0.855 0.701 0.382 0.837 −0.076 −0.566 −0.63 0.925
6. Perceived behavioural control 0.883 0.717 0.476 0.353 0.54 −0.316 −0.686 −0.676 0.452 0.847
7. Subjective norm 0.951 0.865 0.757 0.521 0.799 −0.114 −0.766 −0.825 0.705 0.69 0.93
8. Attitude 0.953 0.836 0.783 0.567 0.841 −0.136 −0.827 −0.885 0.74 0.686 0.87 0.914
Bold values denote the square root of AVE.
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Furthermore, the results of this study verified novelty nega-
tively influences perceived risk. This finding correlates with pre-
vious studies that show consumers who are novelty-oriented
reduce their risk perceptions about a particular destination
(Ponsignon et al. 2020) and are more willing to visit higher-risk
destinations than the destinations they are familiar with (Lepp
and Gibson, 2003). Results of this study also showed that novelty
negatively influences consumers’attitudes to visit green hotels.
This finding corresponds to some empirical evidence showing
that novelty significantly influences consumers’purchasing atti-
tudes and behaviours (Kim and Kim, 2015; Wang et al. 2022a;
Wang et al. 2022b). Those findings mean that although con-
sumers are willing to experience something new like visiting
green hotels in this study because of its novel attributions such as
curiosity, sense of discovery, and emotional stimulus, they may
have negative perceptions and attitudes toward visiting green
hotels. Meanwhile, they also have risk concerns about various
aspects of the nature of green hotels. They do not want to sacrifice
the quality of hotels’services and products, suffer psychological
discomfort, waste time, and take health-related risks compared
with traditional hotels.
Previous studies indicated that perceived risk negatively influ-
ences consumer’s attitude, subjective norm, perceived behavioural
control, and trust (Arshad et al. 2021; Han et al. 2019; Haq et al.
2023; Küpeli and Özer, 2020;Sujoodetal.2021; Teeroovengadum
et al. 2021). Results of this study show that perceived risk nega-
tively influences subjective norm, perceived behavioural control,
and trust. This means that consumers’apprehension about
patronising green hotels is related to additional charges, low quality
of service and facilities, psychological discomfort and anxiety, and
health concerns that may result in their low assessments of green
hotels. In addition, a lack of reliable and trustworthy recommen-
dations, negative information received from their close-friends,
relatives, colleagues, and family members on choosing green hotels,
and low confidence to overcome obstacles (e.g., time, opportunity,
money) to booking green hotels will result in a higher perception
of risk. Those findings correspond to previous studies that showed
that financial risk, performance risk, functional risk, psychological
risk, physical risk, time risk, and health risk as perceived risk
dimensions negatively influence consumers’subjective norm,
perceived behavioural control, and trust (Park, 2017;Parketal.
2022;Sujoodetal.2021; Zhang et al. 2021).
Nevertheless, our findings show that perceived risk does not
significantly influence consumers’attitudes towards visiting green
hotels, which is in contrast with previous studies showing that
perceived risk negatively influences one’s attitude (Han et al.
2019; Haq et al. 2023). This means that consumers’positive or
negative assessment of green hotels’attributes when travelling
would not pose a threat to their psychological discomfort and
well-being, physical safety concerns, quality and function con-
cerns, psychological discomfort, anxiety, and health concerns, as
well as additional charge concerns.
In addition, perceived risk should be considered by measuring
various indicators based on different research objects and cultural
backgrounds for consumers’behaviours (Aufa and Gunanto,
2023; Küpeli and Özer, 2020; Zhang et al. 2021). The hierarchical
dimension’s structure of perceived risk is verified in this study.
The empirical assessment of the structural model revealed that
the second-order latent variables (i.e., perceived risk) sufficiently
acquire the commonality underlying among first-order variables,
and they are financial risk, performance risk, functional risk,
psychological risk, physical risk, time risk, and health risk.
Theoretical contributions. The majority of earlier research in the
fields of hospitality and tourism marketing examines how
different variables positively impact consumers’attitudes and
perceptions of intention and behaviour (Patharia et al. 2020).
More research should be conducted to gain a better under-
standing of the negative antecedents of consumers’attitudes and
behaviours (Wang et al. 2022d), as there has not been enough
research done on the negative influence on consumers’behaviour
within the behavioural intention framework (Ulker-Demirel and
Ciftci, 2020). This study demonstrated that consumers’perceived
risk negatively influences trust, subjective norm, and perceived
behavioural control towards visiting green hotels. Meanwhile,
even though the influence of perceived risk does not significantly
influence attitude, the correlation between perceived risk and
attitude is negative. Hence, future research should look at the
influence of perceived risk as an antecedent of consumers’per-
ceptions and behaviours towards visiting green hotels.
Second, previous studies considered perceived risk as a
multidimensional concept including various indicators of con-
sumer behaviours based on different research objects and settings,
and cultural backgrounds (Zhang and Yu, 2020). The results of
this study offer a comprehensive assessment of perceived risk
structure to predict consumers’attitudes, subjective norm,
perceived behavioural control, and trust towards visiting green
hotels. In other words, the financial risk, performance risk,
functional risk, psychological risk, physical risk, time risk, and
health risk sufficiently acquire the commonality for perceived
risk. The results of this study provide a basic understanding of
various indicators of perceived risk that can influence consumers’
perceptions and intentions to patronise green hotels.
Third, the majority of consumers are still unfamiliar with the
benefits and functions of green hotels (Wang et al. 2022e) because
the concept is still relatively new to them (Wang et al. 2024b).
The majority of tourists are unaware of the wide variety of
facilities and services offered by green hotels (Choi et al. 2015),
having only heard of the concept in recent years (Wang et al.
2022e). This study explored the relationship between familiarity,
perceived risk, and attitude towards green hotel selection. Results
showed that familiarity positively influences perceived risk and
negatively influences attitude. Future studies should consider
examining why individuals who are familiar with green hotels but
have a more negative overall evaluation of green hotels and a
higher-risk perception about visiting green hotels.
Consumers may act irrationally in order to obtain stimulation
that elicits strong emotions (Wang et al. 2022a). The concept of
novelty views that people concentrate on personal enjoyment and
comfort improvement while seeking curiosity and fun, which is
influenced by motivational and emotional elements (Wang et al.
2022b). These elements can be included in the TPB to predict an
individual’s behaviour (Ulker-Demirel and Ciftci, 2020). This
study confirmed that novelty significantly influences perceived
risk and attitude towards visiting green hotels, but it does not
replace the components of TPB but rather works as an extension
of consumption theories.
Consumers make decisions prior to receiving the service and
since services are classified as highly unpredictable scenarios (Haq
et al. 2023), consumers believe having trust in a business or
company can help them feel more confident in their purchase of
environmentally friendly products or services (Ponnapureddy et al.
2017). Currently, there is not much empirical evidence regarding
how trust influences consumer behaviour in green marketing (Shah
et al. 2023) including the selection of green hotels (Dwivedi et al.
2022;Sultanaetal.2022). This study empirically validated the
association between trust, attitude, and intention to visit green
hotels. Therefore, adding trust to TPB increases its predictive
capacity and broadens its application in the selection of green hotels.
TPB and its components are widely applied in green marketing
to predict consumer behaviour (Ferreira et al. 2023; Sung et al.
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2021). Nevertheless, the interrelationships between attitude,
subjective norm, and perceived behavioural control concerning
consumers’intentions to visit green hotels have not been
adequately researched (Wang et al. 2024a; Wang et al. 2023c).
Results of this study showed that subjective norm positively
influences perceived behavioural control, attitude, and intention
towards visiting green hotels respectively. Thus, subjective norm
should be considered as an antecedent of perceived behavioural
control and attitude towards visiting green hotels, although those
findings have stood in contrast within the theoretical framework
of TPB.
Practical implications. The results of this study can offer
important managerial implications since green hotels are looking
for factors that would differentiate them from other competing
traditional hotels. First, the utilisation of specific facets of the
multi-dimensional model of perceived risk is essential. Recog-
nising the importance of perceived risk, green hotel operators
need to help their customers understand the financial, perfor-
mance, functional, psychological, physical, time, and health/safety
aspects of green hotels. In fact, green hotels should demonstrate
to potential customers that they can provide a higher level of
quality services for guests to make them feel they are getting
better value compared to traditional hotels. For performance risk
issues, green hotels need to assure potential customers that green
hotels would be able to provide reliable service and that they carry
out environmentally friendly business practices. Since green
hotels’guests are concerned about the risk of low-quality func-
tional benefits when compared with traditional hotels, green hotel
operators should provide exceptional green products, facilities,
and services to reduce functional concerns. Moreover, green
hotels should provide more user-friendly and reliable recyclable
materials and products to make consumers feel that staying at
green hotels is comfortable and safe. Highlighting the recyclable
materials and products’certificate of origin, production process
and certification by accreditation agencies can also reduce con-
sumers’risk perceptions. Basically, green hotel operators should
make consumers feel that their decision to stay at a green hotel is
desirable and ethical which can achieve or exceed their (green)
expectations.
The results of this study identified the essential role of
familiarity in increasing consumers’perceived risk and decreasing
their attitudes towards visiting green hotels. Potential consumers
of green hotels may receive more negative than positive
information from various channels such as green hotels’websites,
brochures, pamphlets, magazines, and newspapers. Thus, green
hotel operators should pay more attention to spreading the right
information about the concept of green hotels to the public; for
example, that they can provide pro-environmental products and
services to the public without sacrificing consumers’comfort and
safety when compared with traditional hotels, and how green
hotels’products (e.g., recyclable materials, organic foods) and
resource management system (e.g., solar energy and recycled
water system) are superior to traditional hotels. Specifically, they
need to highlight why it is necessary to implement green
management strategies in the hotel industry to evoke consumers’
environmental consciousness.
The results of this study showed that novelty negatively
influences consumers’perceived risk and attitude towards visiting
green hotels. Consumers who are seeking new experiences with
green hotels’facilities, cuisine, amenities, and foods, do not wish
to undertake any financial, performance, functional, psychologi-
cal, physical, time, or health risks. Meanwhile, it seems that
consumers do not think that green hotels can provide something
different from traditional hotels, resulting in a negative attitude
towards visiting green hotels. Hence, the key point green hotels
should advertise is they can provide different green products and
services compared with traditional hotels by ensuring the quality
of such services and products, keeping the products and services
performance, and highlighting they provide a better and healthier
lifestyle in a timely manner for consumers.
In their promotional messages, green hotel managers and
operators should clearly demonstrate the amount of energy and
water they can save through their implementation of green
business strategies to consumers. For example, they can
indicate how the amount of water and electricity that can be
savedinayearofoperationontheirofficial website. Therefore,
consumers will know that green hotels are contributing to the
conservation of the environment and natural resources, and
feel their green hotel selection decisions are reliable, depend-
able, and trustworthy.
Subjective norm plays an important role in determining
consumer attitude, perceived behavioural control, and intention
to visit green hotels. On one hand, green hotel operators should
continue to advertise their green hotels’attributes and functions
to the public via traditional channels (e.g., newspaper, radio,
magazines) to influence traditional word-of-mouth consumers
(e.g., relatives, close-friends, co-workers). On the other hand,
electric word-of-mouth communication (e.g., online reviews,
social media posts, blogs) should be used as an alternative method
to attract and influence potential consumers (e.g., students,
netizens). Green hotel operators need to monitor negative
feedback and comments on their official websites, booking
applications, and online media. They should resolve the issues
in a timely manner or leave a reply with a positive message on the
relevant online channels, thus, strengthening their reputation
and image.
The present study found that attitude positively influences the
intention to visit green hotels. Based on this finding, green hotel
operators need to make various endeavours to enhance
consumers’level of confidence in green hotels’attributes. As
demonstrated in this study, green hotel operators can reduce
consumers’perceived risk by providing appropriate information
to consumers, highlighting their unique green characteristics,
increasing their trust in what green hotels can provide, and
advertising their green hotels’attributes to potential consumers
via various media channels. This can help green hotel consumers
feel that the performance quality of green hotels is reliable and
that visiting green hotels would be an excellent choice.
Limitations. This study has certain limitations. First, selecting the
young generation as respondents in this study has many advan-
tages, as they are more environmentally conscious than older
consumers (Jaiswal and Kant, 2018) and they can shape future
consumption patterns (Bahl and Kumar, 2019). However, the
financial status and spending power of younger consumers are
relatively lower than the working population. Hence, this study’s
sample respondents are not representative of the whole popula-
tion. Second, the concept of green hotels is quite new and
investigation on green hotel selection is comparatively lower than
in developed countries. Thus, the findings of this study may only
apply to similar developing countries, but its reliability and use-
fulness may need to be re-examined in other settings. Third, the
current study investigated the adoption intention of green hotels
in a single country context, which presents a generalisability issue.
Since consumer behaviour is a function of culture and people of
different nationalities show different behavioural tendencies
(Arun et al. 2021), further research is required to perform cross-
cultural comparisons of consumer behaviour. Moreover, although
intention is a robust predictor of consumer actual purchase
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behaviour, future studies should investigate consumers’actual
green hotel visits since intention does not always equate to actual
behaviour. Lastly, the TPB can be expanded to include other
psychological or contextual variables to increase its predictive
power so that future studies can replicate and expand the current
research framework to increase its accuracy and reliability.
Conclusion. The decision-making process of visiting green hotels
has not been fully examined empirically in the literature, despite the
fact that there are numerous studies on consumers’intention to visit
green hotels based on different consumer antecedents (Nimri et al.
2020b; Ray et al. 2023). Specifically, research on the impact of
unfavourable psychological traits on an individual’sintentionin
green hotel marketing is lacking (Ulker-Demirel and Ciftci, 2020).
The current study investigates how trust, perceived risk, familiarity,
novelty, along TPB affect consumers’intentions to visit green
hotels. Attitude and subjective norm have been proven to be
valuable predictors of intention, and subjective norm can also affect
one’s attitude and perceived behavioural control towards visiting
green hotels. Nevertheless, perceived behavioural control does not
always lead to intention. Trust has a significant influence on attitude
and intention but does not affect perceived behavioural control.
Familiarity has been proven to be a significant predictor of attitude
and perceived risk whereas novelty is also considered to be an
important antecedent of one’s attitude and perceived risk. Perceived
risk negatively influences consumers’subjective norm, perceived
behavioural control, and trust, but does not correlate with attitude.
Moreover, the results of this study showed that perceived risk
should be considered as a multi-dimensional concept which can be
accessed via financial, performance, functional, psychological,
physical, time, and health risks for explaining consumers’perceived
risk towards visiting green hotels. In conclusion, this study can be
considered to be one of the pioneer studies that examined the
influence of trust, perceived risk, familiarity, novelty, and TPB on
consumers’intention to visit green hotels. The results of this study
can provide a more comprehensive understanding of consumers’
green hotel visitation intention based on TPB, which will contribute
to the growth of the green hotel marketing literature.
Data availability
The data obtained and examined in this study are documented in
the paper and provided in the supplemental data file.
Received: 11 March 2024; Accepted: 14 October 2024;
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Author contributions
Conceptualization, Methodology: Lei Wang, Qi Zhang, and Yue Gong; Design of the
work: Lei Wang and Philip Pong Weng Wong; Literature search, Data interpretation: Qi
Zhang, Meng-Jie Ye, and Yue Gong; Data collection: Qi Zhang and Meng-Jie Ye; Formal
analysis: Lei Wang, Qi Zhang, and Meng-Jie Ye; Writing –original draft preparation,
Writing –review and editing, Critical revision of the article, Visualization, Validation,
and Supervision: Lei Wang, Philip Pong Weng Wong, and Yue Gong; Funding acqui-
sition: Lei Wang and Yue Gong.
Competing interests
The authors declare no competing interests.
Ethical approval
The procedures used in this study adhered to the ethical standards set out in the
Declaration of Helsinki. As this study was not medical research nor considered human
experimentation as stated in the Declaration of Helsinki, and because the questionnaire
did not adversely affect the mental health of the respondents, ethical approval was
required for this questionnaire-based study according to the regulations of the authors’
institution (Business School Research Ethics Review Committee, Xuzhou University of
Technology, (decision of November 2023)). Moreover, by completing the questionnaire,
each respondent who was at least 18 years old consented to participate in the research
study. The information collected was used exclusively for the study and was treated as
strictly confidential and anonymous.
Informed consent
Informed consent was obtained from all participants prior to their participation in the
study. The nature and objectives of the study, together with the participants ability to
withdraw at any time, were explained to the participants. The informed consent process
was conducted from December 2023 to January 2024, concurrently with the ques-
tionnaire distribution.
Additional information
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1057/s41599-024-03935-0.
Correspondence and requests for materials should be addressed to Yue Gong.
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