Evaluating Smokers’ Purchase Intentions Under the Stimulus-Organism-Response Framework: A Case Study of Tobacco Marketing Exposure in Vietnam

Abstract

Despite regulations restricting tobacco marketing and a purported global industry strategy to transition to less harmful products, smoking rates in emerging markets remain high. A paradox that needs to be paid attention to is that even though businesses have committed to complying with tobacco restriction policies, cigarette sales, and smokers still increase. The purpose of this study is to examine the nexus between tobacco marketing exposure as the stimulus factor and individual processes, including emotional and rational aspects, in forming smokers’ purchase intentions. A deductive strategy based on positivist philosophy was used to construct the study model to describe the influencing of smokers’ buying intentions. Cross-sectional research involving 999 respondents in southern Vietnam was undertaken by randomly sending questionnaires via face-to-face survey in the café shops. Before evaluating the measurement and structural models, Cronbach’s alpha was used to analyze the reliability and validity of measurement scales using SPSS software. The SmartPLS program was then used to analyze the measurement and structural models and test the hypotheses using partial least squares structural equation modelling. The positive associations between tobacco marketing exposure and pleasure, arousal, and purchase intention were identified. Although dominance has negative impacts on both tobacco marketing exposure and marketing receptivity, attitudes toward tobacco marketing have positive impacts on both marketing receptivity and smokers’ purchase intentions. Based on these findings, the study not only makes a significant theoretical contribution but also provides a comprehensive view to provide practical implications to limit and reduce smoking prevalence.

Keywords

tobacco marketing exposure pleasure-arousal-dominance irresponsible marketing current smokers purchase intention emerging markets

Introduction

Despite regulations restricting tobacco marketing and industry claims to support such regulation, as well as a purported global strategy to transition to less-harmful products, smoking rates in emerging markets remain high (Edwards et al., 2022; Hanh et al., 2024; Savell et al., 2014). In Vietnam, for example, 43.8% of men smoke, and the number of smokers has actually increased (Euromonitor International, 2022). Moreover, tobacco-related diseases currently account for approximately 40,000 global deaths annually, contributing to 25 distinct health diseases globally (WHO, 2023). The World Health Organization (WHO, 2023) estimates that the absence of robust tobacco control measures could see the mortality rate escalate to approximately 70,000 deaths per year by 2030, marking a significant increase of 57.1% from 2023 levels. Smokers’ research is therefore of paramount importance in the global endeavor to reduce smoking-related deaths. In the context of an emerging country, like Vietnam, a paradox that needs to be paid attention to is that even though businesses have committed to complying with tobacco restriction policies, cigarette sales and smokers still increase (T. B. Y. Tran et al., 2024). According to T. B. Y. Tran et al. (2024), intention to purchase, smoke, and seek information about cigarettes is significantly directly influenced by viewers’ emotional states and cigarette advertisements and promotion. Nevertheless, T. B. Y. Tran et al. (2024) did not mention the individual cognitive processes such as marketing receptivity or attitudes, while these factors were considered to be very crucial in forming behavioral intentions (Abzari et al., 2014). Hence, understanding smoking intention or purchase intention, alongside the implementation of anti-smoking regulations and bans, holds paramount importance in the global endeavor to reduce smoking prevalence, a particularly pertinent concern in Vietnam (Huong et al., 2017). Recognizing the critical role of reducing smoking prevalence as well as smoking harm (Greenland, 2019), the first aim of this study is to examine the formation mechanism of current smokers’ purchase intentions and provide insight into smokers’ behaviors and practical implications for policymakers in Vietnam.

Related to stimulus or environmental factors affecting current smokers’ purchase intentions, numerous studies indicated that marketing exposure had been shown to have an impact on smokers’ purchase intentions (Choi et al., 2021; Lee et al., 2020; O’Connor et al., 2017; Sharma et al., 2022; T. B. Y. Tran et al., 2024). Recent studies indicated that higher exposure to cigarette point-of-sale marketing was connected with a higher likelihood of purchase intention, thus shedding light on the association between marketing exposure and current smokers’ intention to purchase (Choi et al., 2021; Mantey et al., 2019; T. B. Y. Tran et al., 2024). Although these recent studies provided insight into smokers’ purchase intentions, they did not mention the nexus of stimulus factors and individual processes (e.g., smokers’ marketing receptivity, smokers’ emotional states, and attitudes towards tobacco marketing), especially emotional aspects (Choi et al., 2021; T. B. Y. Tran et al., 2024). In other words, there has been no research that provides a comprehensive and in-depth view of entire processes, from when individuals are exposed to tobacco advertising information to the individual cognitive and emotional processes, and the outcomes of these processes are the intentions or behaviors (T. B. Y. Tran et al., 2024). As a result, the second aim of this research is to investigate the nexus of stimulus factors (exposure to tobacco marketing), individuals’ processes (smokers’ marketing receptivity, emotional states, and attitudes towards tobacco marketing), and smokers’ purchase intentions.

On the other hand, most previous studies on tobacco have focused on examining factors that influence the intention to smoke or quit smoking while ignoring the causes leading to the intention to purchase cigarettes (Chen et al., 2021; Lareyre et al., 2021; Oh & Boo, 2023; Saleem et al., 2023). As mentioned, tobacco marketing exposure is one of the factors that has a direct impact on cigarette purchase intention and is influenced by cigarette manufacturers. Therefore, to reduce the prevalence of smoking and the negative consequences of tobacco, recognizing the influence of tobacco marketing on the intention to purchase cigarettes is seen as an essential foundation for developing interventions and regulations controlling tobacco advertising (T. B. Y. Tran et al., 2024). In line with this, Greenland et al. (2023) called for papers to conduct extensive studies on the detrimental consequences of harmful product promotion. Responding to this call, the last aim of this study is to provide a case study on the impact of exposure to tobacco advertising on current smokers’ cigarette purchase intention through emotional and rational aspects as well as providing practical implications to limit the harmful effects of tobacco on the community.

To better understand cigarette ordering intention, the stimulus–organism–response (S-O-R) framework has been applied by a few researchers and shown to be suitable for explaining consumer intention (T. B. Y. Tran et al., 2024). However, in this research approach, T. B. Y. Tran et al. (2024) only considered the processes from receiving stimuli to the temporary emotional states that lead to the intention to smoke and place an order, without considering the cognitive aspects of the smokers. To clarify the process of forming cigarette purchase intention, the research approach has been determined through the S-O-R conceptual framework to explain the process from receiving cigarette advertising information to emotional and rational aspects, in which, stimulus factors refer to exposure to tobacco marketing, organisms refer to emotional states (pleasure, arousal, and dominance), marketing receptivity, and attitudes toward tobacco marketing, and response refers to purchase intention. The uniqueness of this research approach is its success in demonstrating the entire process of forming the intention to order cigarettes through the process of receiving advertising information (stimulus), going through emotional stages, and then passing the cognitive process (marketing receptivity and attitudes toward tobacco marketing) to form the intention to order cigarettes.

The remainder of this research consists of five primary points. First, the theoretical framework and research hypotheses will be developed by synthesizing the available literature. The study approach will next be discussed, including data gathering and analysis techniques. The findings are also supplied and discussed in depth. The final portion pertains to the discussion of limitations and future research.

Literature Review

Exposure to Marketing and Receptivity, Purchase Intention of Current Smokers, S-O-R Framework in the Context of Purchase Intention, Emotional States, and Nature of Attitudes

Marketing exposure is defined as the scope and frequency of dissemination of marketing messages, according to research in BMC Public Health. How extensively and frequently a firm’s promotional communications reach its target audience is of great importance in ensuring its strategic visibility (Finlay et al., 2022). Studies have consistently shown that marketing exposure, such as product placements in movies and tobacco advertisements, as well as positive attitudes towards smoking, promotes smoking initiation and deters cessation efforts (Biener & Siegel, 2000; Braverman & Aarø, 2004; Choi & Forster, 2014; Dunbar et al., 2019; Feighery et al., 2004; Gilpin et al., 2007; Henriksen et al., 2008; Ling et al., 2009; Lovato et al., 2011; Pierce et al., 1998; Setodji et al., 2013; Siahpush et al., 2016; Thrasher, Jackson, et al., 2008; Thrasher, Rousu, et al., 2011; Weitzman & Lee, 2020). On the other hand, tobacco marketing receptivity indicates the degree to which exposure to tobacco marketing is favorably or unfavorably received by the smokers (Nguyen-Viet & Thanh Tran, 2024).

In terms of the purchase intention of current smokers, almost all previous studies identified the effects of exposure to tobacco advertising or messages on smokers’ purchase intentions (negative or positive effects; Lee et al., 2020; T. B. Y. Tran et al., 2024). A few studies indicated that demographic factors made a significant difference in smokers’ purchase intentions (Azagba et al., 2020; Hyland et al., 2006). Other studies mentioned that the purchase intention of current smokers was the result of the impacts of emotional and cognitive aspects (Liu et al., 2021; T. B. Y. Tran et al., 2024). Although Liu et al. (2021) investigated the role of emotional states and perceptions of tobacco harms in shaping e-cigarette purchase intentions, this study focused merely on the indirect effects of information on the dangers of e-cigarettes and smoking, not the effects of tobacco advertising information. On the other hand, T. B. Y. Tran et al. (2024) only examined the impact of cigarette advertising exposure on the intention to purchase, smoke, and seek information about cigarettes, while not considering individual cognitive factors prior to the formation of behavioral intention. Therefore, the above studies, having significant practical and theoretical contributions, are still limited in not providing a comprehensive model of cigarette purchase intention in the context of exposure to cigarette advertising. Based on these findings, a big theoretical gap related to cigarette purchase intention that previous studies have not considered is the impact of smoking marketing exposure on emotional (e.g., temporary emotions) and cognitive (e.g., reception of advertising information, or attitudes related to tobacco marketing) aspects of forming smokers’ purchase intentions.

Regarding the application of the S-O-R conceptual framework to explain human intentions and behavior, most previous research focuses on the fields of consumer behavior, education, and technology use (Behera & Dadra, 2023; Ghani et al., 2022; Huo et al., 2023; Kim et al., 2020; Zhang et al., 2021). These studies demonstrated the suitability of the S-O-R framework in providing insight into human intentions and behaviors in numerous sectors.

In the context of purchase intention, this model (S-O-R) conceptualizes the process from stimulus to response, with the organism’s internal state as the mediator (Dua, 2024; T. D. Tran et al., 2024; Vazquez et al., 2023). However, the framework broadly represents influencing factors without identifying the specific nature of the stimulus, organism and response; moreover, it rarely presents the direct relationship between stimulus and response (Prashar & Prashar, 2024). This noteworthy constraint should be considered carefully in certain research contexts (Ling et al., 2024; Minh et al., 2024). Despite the extensive literature on determinants of purchase intention and its behavioral implications (Dua, 2024; Ling et al., 2024; Minh et al., 2024; Prashar & Prashar, 2024; T. D. Tran et al., 2024; Vazquez et al., 2023), the use of the SOR framework in smokers’ purchase intention remains modest, except for studies of Liu et al. (2021) and T. B. Y. Tran et al. (2024). One of the few attempts is a study by T. B. Y. Tran et al. (2024), who utilized this framework to examine the causes of cigarette purchasing intentions. The study demonstrated the relevance of the SOR framework in explaining the process from exposure to unrestricted advertising information to individual emotional states and cigarette purchasing intention. However, the study did not allow the researchers to explore how smokers’ purchase intention is created if there is exposure to tobacco marketing exposure via individual emotional states, marketing receptivity, and attitudes towards tobacco marketing. In the present study, the author aims to examine behavioral theories relevant to each component of the S-O-R for a better explanation of smokers’ purchase intention, such as TPB related to attitudes toward tobacco marketing and smokers’ purchase intention.

Emotional states were regarded as unstable (transient) emotions and are considered in studies related to intentions and behavior in many fields such as behavioral economics, marketing, smoking, etc. (Beig & Khan, 2022; Greenland & McGoldrick, 2005; Jaeger et al., 2021; T. B. Y. Tran et al., 2024). In the context of smokers’ purchase intentions, Liu et al. (2021) recognized that emotional states (scared, angry, worried, happy, hopeful, and relieved) had a direct effect on cognitive factors (perceived relative harm of e-cigarettes) and intention to purchase e-cigarettes. In addition, T. B. Y. Tran et al. (2024) emphasized that pleasure, arousal, and dominance (PAD emotional states) had a direct impact on the intention to smoke and purchase cigarettes. However, studies examining the overall emotional and cognitive impact of cigarette ordering intentions remain modest.

Attitudes are regarded as covert dispositions or tendencies to express favor or disfavor toward a psychological phenomenon (Hanson, 2018). The object of the attitude can encompass any identifiable aspect of an individual’s environment, including behavioral phenomena (Kokolakis, 2017). Attitudes possess an evaluative quality, which involves assigning a subject a position on a single evaluative continuum relative to the object in question, where this continuum ranges from negative to positive and encompasses a neutral point (Fazio, 1995). The basic feature of an attitude, according to modern theorists and investigators, is its bipolar evaluative nature (Eagly & Chaiken, 1993; Fishbein & Ajzen, 2005; Krosnick et al., 2005, 2008; Petty et al., 1986). In the academic world, the concept of attitude has shifted. While some scholars define attitudes as subjective evaluations (Gawronski, 2007; Kruglanski & Stroebe, 2005), the majority of researchers associate attitudes with an underlying cause (Eagly & Chaiken, 2005) to represent a specific behavior of an individual. This widely recognized approach, when combining attitudes with underlying causes in the social and behavioral sciences, suggests that evaluative responses serve as markers of a hidden concept that needs to be explored.

Based on these arguments, the research approach was confirmed by employing the S-O-R framework to explain smokers’ purchase intentions, in which “stimulus factor” was regarded as exposure to tobacco marketing; “organism” referred to PAD emotional states, marketing receptivity, and attitudes toward tobacco marketing; and response referred to smokers’ purchase intentions. The extended TPB theory was applied to explain the smokers’ purchase intentions in conjunction with their attitudes towards tobacco marketing as a component of TPB. PAD emotional states and marketing receptivity were added to complete the extended TPB due to its criticisms such as ignoring individual processes, perceptions (personality and outcome expectations; Bandura, 2003; Miles, 2012), and emotional aspects, while emotional aspects were critical factors in the decision-making process (Bruch & Feinberg, 2017; T. B. Y. Tran et al., 2024).

According to this approach, the novelty and uniqueness of this research were identified based on three main contributions, such as academic, methodology, and practice. Unlike the multitude of TPB studies that focus solely on rational factors, this research demonstrates that marketing exposure—considered marketing stimuli—elicits significant emotional responses that are crucial in influencing rational factors (marketing receptivity and attitudes) and smokers’ purchase intention. The inclusion of emotions such as arousal, pleasure and dominance alongside cognitive factors, such as marketing receptivity and attitudes provides a more comprehensive understanding of smokers’ purchase intention. This innovative approach does not just apply to understanding the purchase intention of smokers in Vietnam but also holds potential relevance across various industries. The methodological contribution of this research lies in its pioneering approach to operationalizing an integrated model that combines the Stimulus–Organism–Response (SOR) framework with the Theory of Planned Behavior (TPB), specifically by incorporating emotional responses. This novel methodology not only explores the influence of temporary emotions—from pleasure to dominance—on smokers’ purchase intentions but also demonstrates how these emotions can systematically be included in the analysis. By intertwining emotional awareness with rational cognitive assessments such as marketing receptivity and attitudes, this research method offers a comprehensive model that elucidates the complex interplay between emotions and rational decision-making in shaping behavioral intentions.

Hypothesis Development

In order to clarify the direct and indirect effects of marketing exposure on smokers’ purchase intention via emotional states (pleasure, arousal, and dominance) and cognitive processes (marketing receptivity and attitudes), the hypotheses were formulated based on each cluster in the S-O-R model as follows: Tobacco marketing exposure and emotional states, tobacco marketing exposure and smokers’ purchase intention, emotional states and marketing receptivity, marketing receptivity and attitudes toward tobacco marketing, attitudes toward tobacco marketing and smokers’ purchase intention.

Other studies have found favorable associations between approach behavior and greater pleasure and arousal ratings in response to marketing stimuli, lending credence to the original PAD concept (Loureiro et al., 2019; Wen et al., 2022). However, the outcomes for dominance and approach behaviors have been inconsistent. For example, Jaeger et al. (2021) discovered dominance to be the least important PAD characteristic, whereas Wen et al. (2022) discovered it to be the biggest predictor of purchase intention. In addition, the relationship between the stimulus factors and the emotional response has been proven in several studies (Brakus et al., 2009; Khan, 2022; Lang et al., 1997; Lee & Labroo, 2004; Wedel & Pieters, 2007). According to Dijksterhuis and Aarts (2003), emotional responses to negative and taboo stimuli within the context of heterosexual relationships demonstrate that such stimuli can elicit negative emotional responses. Advertising stimuli that were easier to process and comprehend led to more positive emotional responses and higher evaluations of the advertised brands (Lee & Labroo, 2004). In conjunction with these arguments, the following hypotheses were proposed:

H1: Tobacco marketing exposure has a positive effect on pleasure.

H2: Tobacco marketing exposure has a positive effect on arousal.

H3: Tobacco marketing exposure has a negative effect on dominance.

In addition, the impact of tobacco advertising or messaging on smokers’ purchasing intention (negative or positive effects) was also confirmed in previous studies (Lee et al., 2020; T. B. Y. Tran et al., 2024).

H4: Tobacco marketing exposure has a positive effect on smokers’ purchasing intention.

Related to the relationship between emotional states and receptivity, it was also mentioned in other topics such as green consumption, smoking cessation intentions, etc. According to Bailey et al. (2016), green advertising receptivity was the degree to which customers paid attention to, were favorable to, and reacted to advertising that employed green messages in the promotion of items or a firm itself. A higher level of receptivity to anti-smoking policies can increase negative emotional responses about smoking and its consequences, which, in turn, may positively influence cessation intention among current smokers (Fleischer et al., 2017; Yong et al., 2014). In addition, the removal of misleading terms on cigarette packaging led to increased negative emotional responses among smokers, such as anger or annoyance. These emotional responses were associated with increased intentions to quit smoking and reduced misperceptions about the harmfulness of cigarette products (Adkison et al., 2013; Yong et al., 2014). Based on these arguments, the following hypotheses were identified:

H5: Pleasure has a positive effect on marketing receptivity.

H6: Arousal has a positive effect on marketing receptivity.

H7: Dominance has a negative effect on marketing receptivity.

Regarding the nexus between marketing receptivity and attitudes toward purchase intention, the positive effect of receptivity on attitudes toward intention was demonstrated in previous studies (Ahmed et al., 2023; Tewari et al., 2022). Besides, Bailey et al. (2016) identified receptivity to green advertising as a key factor in influencing customer attitudes and purchase intentions through eco-friendly advertising and promotional strategies. Hence, the following hypothesis was proposed:

H8: Marketing receptivity has a positive effect on attitudes toward tobacco marketing.

In relation to the association between attitudes towards purchase intention and purchase intention, numerous former scholars have proven the positive impact of attitudes towards purchase intention on purchase intention (Abzari et al., 2014; Nguyen et al., 2019; Puriwati & Tripopsakul, 2022; Rausch & Kopplin, 2021; Tewari et al., 2022). In addition, it is considered that the more favorable attitude toward a specific intention or behavior, the higher the possibilities of an individual performing that behavior (Ajzen, 1991). In alignment with these findings, the following hypothesis was proposed:

H9: Attitudes toward tobacco marketing have a positive impact on smokers’ purchase intentions.

Based on the research approach and the above hypotheses, the research conceptual framework was identified (Figure 1).

Figure 1.

The research conceptual framework related to smokers’ purchase intention.

Methods

Compliance with Ethical Standards

This study involved human participants recruited to complete a survey. Ethics approval was obtained from the relevant university ethics committee (Reference number anonymized for review) on 11 November 2021. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed Consent: Informed consent was obtained from all individual participants included in the study. Provided informed consent either online (by clicking the “Start survey” button) or in person (via a signed consent form) after reviewing the research information, and before starting interviews. The study posed minimal risk, as no identifying information was collected, participation was voluntary, and participants could skip the questions and withdraw at any time. Data were collected anonymously and stored securely in compliance with the university’s research ethics policy. The potential societal benefits—such as informing more effective tobacco control policies—outweigh the negligible risk to participants.

To assess a theory’s validity by comparing predictions to observed data, a deductive research technique based on positivist philosophy proved most effective (Gammelgaard, 2004). This part will offer three primary contents: data collection, measurement scales, and analytic processes.

Data Collection and Measurement Scales

As of 2023, Vietnam has approximately 18 million smokers, with nearly half of all adult males smoking regularly, while the prevalence among women remains substantially lower, at around 5% (Euromonitor International, 2023). Using convenience sampling method, the target respondents in this research are aimed at current smokers in Southern Vietnam. The “10 times rule” of sample size was applied in the PLS structural model based on the instructions of Hair et al. (2021). Almost all respondents are male (91.1%) and aged under 30 (62%). Regarding the educational level, most smokers have a high school education level or less, and 74.6% hold have a university degree (Table 1).

Table 1.

Respondents’ Demographic Profiles.

Indicator	Value	N/999	Percentage
Gender	Female	25	2.5
	Male	910	91.1
	Not mentioned	64	6.4
Age group	<30	619	62.0
	31–40	183	18.3
	41–50	126	12.6
	51–60	44	4.4
	61–70	10	1.0
	>70	3	0.3
	Not mentioned	14	1.4
Educational level	Never go to school	11	1.1
	High school or less	270	27.0
	College	89	8.9
	University degree	476	47.6
	Postgraduate	41	4.1
	Professional degree	112	11.2

Note. N = 999 current smokers in Southern Vietnam. Data were collected by the author in 2023 using a convenience sampling method. Percentages are calculated from total valid responses.

Source. Author’s own survey data.

Regarding the measurement scales, the seven-point Linkert scales were employed and shown in Table 2. A detailed description of operational definitions and the measurement of the constructs of this study is given in subsequent sections. For a logical presentation of the measurement of variables, the subsequent sections present the constructs in an arrangement identified in the two theories, that is, Theory of Planned Behaviour (TPB) and PAD, integrated to develop the conceptual model (S.O.R model) of this study.

Table 2.

The Measurement of Variables and Reliability Test Results.

Item code	Variable	Items/indicators	Cronbach’s alpha (α)	Source
During the past 30 days, have you seen/heard any advertisement and promotion (A) on tobacco products via those marketing media and how often (B)? 1 = never/7 = always			.853	Adapted from Mantey et al. (2019), Pokhrel et al. (2015), Schooler et al. (1996), Zhu et al. (2013)
MarExp1	Marketing exposure	Items (e.g., T-shirt, raincoat, cap) that display tobacco company logos/brands
MarExp2		Advertisement on the Internet (via social network communities, e.g., Page “Hem Thuoc La (cigarette alley)” or “Cho Thuoc La (cigarette market)”
MarExp3		Advertisement at vendors/shops (e.g., in-stores posters with impressive slogans are stuck)
MarExp4		Advertisement at social events (e.g., Vinataba’s donations for Covid-19 and central provinces’ flooding)
MarExp5		Promotional staff (e.g., PG and PB offered free samples at Café)
Emotions associated with communications from tobacco manufacturers			.763	Adapted from Hsieh et al. (2021), Jaeger et al. (2021), Koo and Lee (2011), Tseng et al., 2018)
P1	Pleasure	1 = annoyed/7 = pleased
P2		1 = unhappy/7 = happy
P3		1 = dissatisfied/7 = satisfied
A1	Arousal	1 = sleepy/7 = arousal	.810
A2		1 = anxious/7 = relaxed
A3		1 = bored/7 = excited
D1	Dominance	1 = controlled/7 = liberated	.858
D2		1 = inhibited/7 = uninhibited
D3		1 = guided/7 = autonomous
During the past 30 days, have you ever watched/heard about any advertisement and promotion following and to what extent do you oppose/support those? 1 = never/7 = always			.838	Adapted from Braun et al. (2016), Gilpin et al. (2007), Henriksen et al. (2008), Topuridze et al. (2020)
Recept 1	Marketing receptivity	Items (e.g., T-shirt, raincoat, cap) that display tobacco company logos/brands
Recept 2		Advertisement on the Internet (via social network communities, e.g., Page “Hem Thuoc La (Cigarette Alley)” or “Cho Thuoc La (Cigarette Market)”
Recept 3		Advertisement at vendors/shops (e.g., in-stores posters with impressive slogans are stuck)
Recept 4		Advertisement at social events (e.g., Vinataba’s donations for Covid-19 and Central provinces’ flooding)
Recept 5		Promotional staff (e.g., PG and PB offered free samples at Café)
I think that for me, to smoke cigarettes is … (ATT)			.801	Adapted from Gilpin et al. (2007), Hanson (2018), Noonan et al. (2011), Zhao et al. (2020)
ATT1	Attitudes towards smoking	1= Bad/ 7 = Good
ATT2		1= Unenjoyable/ 7 = Enjoyable
ATT3		1 = Unhealthy/ 7 = Healthy
ATT4		1 = Unpleasant/ 7 = Pleasant
In the next 30 days, I think… (PI)			.824	Adapted from Soroya et al. (2021), Yang and Kahlor (2013)
PI1	Purchase intention	I will continue to purchase my regular brand
PI2		I will speak positively about communications from tobacco manufacturers to my friends
PI3		If I knew someone who was looking for cigarettes, I would recommend my regular brand to them

Analytic Procedures

Cronbach’s Alpha (α) was used to assess the reliability of initial measurement scales using the SPSS application, preventing common technique bias (refer to Table 2). To establish the scale’s dependability, Cronbach’s Alpha index must be above .6 (Hair et al., 2011). Besides, Kock and Lynn (2012) revealed that the model was free of typical technique bias when all VIF values from the entire collinearity test were equal to or under 3.3. This study investigated the VIF values, and all were less than 3.3, hence the prevalent technique bias was not a worry.

After assessing common technique bias, this study evaluated the measurement and structural models using the SmartPLS software. In terms of the evaluation of the measurement model, convergent validity, composite reliability, and discriminant validity have been examined using the criteria of Hair et al. (2021). Furthermore, the authors recommend using Partial Least Squares Structural Equation Modelling (PLS-SEM) to evaluate the structural model and to validate hypotheses since it relates to analyzing the intricate interactions between the various indirect and direct outcomes (Hair et al., 2021).

Results

Evaluating Measurement Model

As mentioned the reliability and validity of scales, Cronbach’s alpha and composite reliability should be above the criterion of .6 (Hair et al., 2011). According to the research results, the minimum values of Cronbach’s alpha and composite reliability were .762 and .863, respectively (Table 3). Hence, the reliability and validity of the scales were guaranteed.

Table 3.

Outer Loadings, Reliability and Convergent Validity.

Variables	Items	Loading	α	CR	AVE
Marketing exposure	MarExp1	.732	.853	.895	.632
	MarExp2	.868
	MarExp3	.719
	MarExp4	.874
	MarExp5	.768
PAD emotional states	P1	.771	.762	.863	.678
	P2	.862
	P3	.835
	A1	.775	.810	.887	.723
	A2	.892
	A3	.880
	D1	.873	.858	.914	.779
	D2	.910
	D3	.865
Marketing receptivity	Rec1	.759	.840	.886	.608
	Rec2	.789
	Rec3	.769
	Rec4	.823
	Rec5	.756
Purchase intention	PI1	.863	.826	.895	.740
	PI2	.884
	PI3	.835

Note. Model fit: standardized root mean square residual (SRMR) = .064. AVE = average variance extracted; CR = composite reliability.

Regarding the convergent validity, Hair et al. (2011) recommended that the outer loading values should be greater than 0.708 and the average variance extracted (AVE) should be greater than .5 in the exploratory study. Based on the results (Table 3), all values of outer loading were higher than .708 and AVE were higher than .5. Therefore, the convergent validity of the measurement model was assured. On the other hand, the model fit was recognized due to the Standardized Root Mean Square Residual (SRMR) = .064 < .08 (Hair et al., 2021).

In terms of the discriminant validity of the measurement model, the Fornell–Larcker criteria and the Heterotrait–Monotrait ratio (HTMT) were both applied. Henseler et al. (2015) suggested that the HTMT index should be less than .85. As a result, all values were less than .85, ensuring the measurement model’s discriminant validity (Table 4).

Table 4.

Heterotrait–Monotrait Ratio Results for Discriminant Validity.

Constructs	1	2	3	4	5	6
1. Arousal
2. Attitudes	.107
3. Dominance	.405	.061
4. Marketing exposure	.239	.040	.477
5. Pleasure	.116	.088	.366	.251
6. Purchase intention	.154	.219	.117	.187	.123
7. Marketing receptivity	.300	.267	.350	.108	.349	.124

Note. All HTMT values are below .85, confirming discriminant validity (Henseler et al., 2015).

Source. Author’s own analysis using SmartPLS 4.

In terms of the normality of residuals, the results in Table 5 show that the mean values are all close to 0, and the standard deviation is close to 1; therefore, the residual distribution is approximately normal, and the assumption of normal distribution of the residuals is not violated.

Table 5.

Normality of Residuals.

Constructs	Median	Observed min	Observed max	SD	Excess kurtosis	Skewness	Number of observations used
Arousal	.025	−3.192	2.826	.979	.372	−.235	999
Attitudes	−.096	−3.905	3.033	.977	.855	.108	999
Dominance	−.01	−2.75	2.916	.91	−.246	−.13	999
Pleasure	.022	−2.564	2.823	.978	−.171	−.043	999
Purchase intention	−.021	−3.776	2.748	.969	.603	−.243	999
Marketing receptivity	−.029	−3.199	3.729	.916	.915	.246	999

Source. Author’s own analysis using SmartPLS 4.

Evaluating Structural Model

Figure 2 and Table 6 present the findings of hypothesis testing and structural coefficient paths. As expected, all direct nexuses between the components of the S-O-R framework were significant (p < .01). The positive effects of marketing exposure on pleasure (β = .207), arousal (β = .206), and purchase intention (β = .168) were significant and confirmed. In addition, the negative effect of marketing exposure on dominance was also identified (β = −.415). Hence, H1, H2, H3, and H4 were supported. Similarly, the positive impacts of pleasure on marketing receptivity (β = .220), arousal on marketing receptivity (β = .157), marketing receptivity on attitudes (β = .213), and attitudes on purchase intention (β = .182), as well as the negative effect of dominance on marketing receptivity (β = −.189), were significant and confirmed. As a result, H5, H6, H7, H8, and H9 were supported.

Figure 2.

Results of structural paths.

Table 6.

Hypothesized Structural Paths (PLS-SEM Bootstrapping Results).

Hypothesis	Relationships	Estimate	SD	T-value	p-Value	2.5%	97.5%	Result
H1	Marketing exposure → pleasure	.207	.031	6.747*	.000	.145	.269	AC
H2	Marketing exposure → arousal	.206	.033	6.250*	.000	.143	.272	AC
H3	Marketing exposure → dominance	−.415	.030	13.825*	.000	−.475	−.356	AC
H4	Marketing exposure → purchase intention	.168	.032	5.262*	.000	.106	.232	AC
H5	Pleasure → marketing receptivity	.220	.038	5.765*	.000	.143	.298	AC
H6	Arousal → marketing receptivity	.157	.038	4.149*	.000	.083	.235	AC
H7	Dominance → marketing receptivity	−.189	.039	4.784*	.000	−.269	−.108	AC
H8	Marketing receptivity → attitudes	.213	.039	5.446*	.000	.137	.289	AC
H9	Attitudes → purchase intention	.182	.033	5.564*	.000	.120	.249	AC

Note. Path coefficients (Estimate), standard deviation (SD), t-values, and p-values are based on 5,000 bootstrap subsamples. All hypothesized relationships are significant at p < .01 (two-tailed test).

Source. Author’s own analysis using SmartPLS 4.

SD = standard deviation; ns = not significant; AC = accepted; RJ = rejected; R²_Pleasure = .043; R²_Arousal = .042; R²_Dominance = .172; R²_Attitudes = .045; R²_Rec = .161; R²_{Purchase intention} = .060.

p < .01.

Discussion

Based on the results, this study provided a holistic conceptual model to explain the current smokers’ purchase intentions. The research findings also demonstrated the suitability of the S-O-R frameworks in expressing the mechanism of forming smokers’ purchase intentions. Regarding the direct associations of components in the S-O-R framework, tobacco marketing exposure has significant positive impacts on pleasure (β = .207, p < .01), arousal (β = .206, p < .01), and smokers’ purchase intentions (β = .168, p < .01). Similarly, pleasure and arousal are the emotional states that have significantly positive impacts on marketing receptivity (β_{Pleasure→Marketing receptivity)} = .220, p < .01; β_{Arousal→Marketing receptivity} = .157, p < .01). As expected, tobacco marketing exposure had a negative effect on dominance (β = −.415, p < .01) and dominance also had a negative effect on advertising receptivity (β = −.189, p < .01). At last, attitudes towards tobacco marketing have positive associations with both marketing receptivity (β = .213, p < .01) and smokers’ purchase intentions (β = .182, p < .01). Additionally, this study responded to the call for papers by T. B. Y. Tran et al. (2024) aimed to consider not only emotional aspects but also other factors such as rationality (marketing receptivity and attitudes towards tobacco marketing) while explaining the process of forming tobacco purchase intention.

In practice, Vietnam continues to face a high prevalence of smoking, with significant gender disparity. Smoking is prevalent among adult males, with a substantial portion being regular smokers, often using traditional tobacco products (Viet Nguyen et al., 2021). Smoking rates among adult females are also notable, and there are concerns about a growing trend of smoking among women. In Vietnamese society, smoking has traditionally been well accepted among men, considered a social activity enjoyed between colleagues and business partners (Dinh & van Teijlingen, 2019). Hence, the belief remains among many teenage boys that smoking is a demonstration of maturity and masculinity (Govender & Bhana, 2023). According to the positive effects of tobacco marketing exposure on pleasure (β = .207, p < .01) and arousal (β = .206, p < .01), the findings reveal a nuanced strategy for tobacco companies to enhance their advertising effectiveness. By focusing on creating advertisements that evoke feelings of enjoyment and excitement through specific imagery, narratives, or music, these companies can make their marketing more appealing and engaging. This approach not only aligns with consumer motivations and preferences, seeking emotional gratification, but also potentially leads to higher engagement rates and reinforces brand loyalty. Understanding the significant role of pleasure and arousal in consumer receptivity enables marketers to craft strategies that resonate deeply with the emotional states consumers desire, underlining the importance of emotional connectivity in marketing campaigns. However, these findings also raise critical public health concerns and necessitate stringent regulatory considerations. The ability of tobacco advertising to manipulate emotional responses, particularly pleasure and arousal, underscores the urgency for comprehensive policies aimed at curtailing the emotional appeals utilized in such marketing. This is pivotal in safeguarding vulnerable demographics from being disproportionately influenced by tactics that exploit emotional triggers to enhance receptivity towards tobacco products. From a broader perspective, the strategic use of emotional appeals by tobacco manufacturers presents ethical dilemmas, given the well-known health hazards associated with tobacco consumption. Consequently, this calls for a delicate balance between innovative marketing strategies and the imperative to protect public health, highlighting the essential role of regulatory bodies in monitoring and controlling the marketing practices of tobacco companies to mitigate the adverse health impacts of tobacco use. On the other hand, interests and ethics seem to be at odds in this situation. Both businesses and governments understand the harmful effects of tobacco, but they also bring economic benefits (cigarette sales from the business perspective and excise taxes from the government perspective).

The negative impact of dominance in tobacco marketing communications on marketing receptivity (β = −.189, p < .01) suggests that when consumers perceive marketing messages as too controlling or overpowering, it can lead to decreased receptivity and engagement. This observation implies that overly assertive advertising strategies may backfire, reducing the effectiveness of marketing efforts. From a regulatory standpoint, this insight supports the need for guidelines that limit aggressive marketing tactics, particularly in industries like tobacco, where there is a significant public health interest in reducing consumption. Policymakers could leverage these findings to develop regulations that discourage dominance in marketing, aiming to protect consumers from potentially manipulative advertising practices and contribute to public health objectives by moderating the influence of tobacco advertising.

The positive correlation between marketing receptivity to tobacco company activities and more favorable attitudes toward smoking (β = .213, p < .01), leading to higher purchase intentions (β = .182, p < .01), suggests that effective tobacco marketing can significantly influence consumer perceptions and behaviors. This inference highlights the power of marketing in shaping attitudes, suggesting that individuals exposed to and receptive to tobacco advertising are more likely to view smoking in a positive light and, consequently, show a greater likelihood of purchasing tobacco products. Such findings underscore the role of marketing in reinforcing the appeal of smoking, despite widespread awareness of its health risks. From a regulatory perspective, these insights advocate for stringent controls on tobacco marketing to mitigate its influence on public attitudes and behaviors. By implementing stricter advertising regulations, policymakers can aim to reduce the effectiveness of tobacco marketing in promoting smoking, especially among vulnerable populations such as the youth. This could include measures like banning advertising in certain media, restricting the use of promotional tactics that target younger audiences, and ensuring that marketing materials clearly communicate the health risks associated with smoking. Ultimately, such regulatory actions are crucial for public health efforts aimed at decreasing smoking rates and preventing tobacco-related diseases.

Another highlight of this research is the success in combining unstable emotions (PAD emotional states) and rational aspects (marketing receptivity and attitudes toward tobacco marketing) when explaining the purchase intention in the context of current smokers. The research findings pointed out the critical role of emotional aspects in explaining behavioral intention and were consistent with the findings of T. B. Y. Tran et al. (2024) and Bruch and Feinberg (2017), in which emotions could strengthen advertising acceptance or weaken marketing receptivity. In addition, the important role of marketing receptivity has been identified through its direct impact on smokers’ attitudes toward cigarette advertising when forming cigarette purchase intentions. It can be said that this research approach brings novelty in the context of cigarette purchase intentions and there has not been any previous research that has examined the process of forming smokers’ purchase intentions like this study. This study validated an integrated SOR-based model that explains the interrelationship between environmental stimuli, smokers’ organisms, attitudes and smokers’ purchase intentions, successfully expanding the TPB to cover both cognitive and emotional aspects of intention. The integration of PAD into the TPB not only elevates its theoretical robustness in capturing the complexities of smokers’ purchase intentions, but also aligns with Mehrabian and Russell (1974) conclusions about PAD emotional responses being appropriate for predicting approach-avoidance behaviors.

Former scholars have always strived to find an optimal theoretical model to explain human decisions through their intentions (Bruch & Feinberg, 2017); however, there are many debates and even conflicts about the factors to make the final decision (e.g., the roles of emotion and rationality). The question to consider is whether people can just rely on data analysis to make decisions and eliminate emotional elements-affective response, or if emotional considerations are the major drivers in decision-making. Based on this research results, the theoretical model in this study has proven that emotions (PAD emotional states) and reason (attitudes towards tobacco marketing) are two parallel elements; they completely complement each other and serve as the necessary bridge between the two. Besides, despite the fact that this model is not an optimal theoretical model to explain human decisions through their intentions (smokers’ purchase intentions), it contributes to improving and providing more research approaches to an optimal decision via the intention. On the other hand, most previous studies in the context of tobacco focused on the public health sector, such as smokers’ intentions to quit smoking or smoke (Chen et al., 2021; Lareyre et al., 2021; Oh & Boo, 2023; Saleem et al., 2023) while there have been limited marketing aspects. Hence, this is a typical study in the field of tobacco marketing and will bring significant theoretical and practical contributions in explaining in depth the factors that influence cigarette purchase intentions in both emotional and rational aspects.

In relation to the significant contribution of this research to the theoretical material in this field, practical implications were also proposed according to the direct effects of this research model:

Further limiting marketing appeal: Introduce stricter controls on the tone and aesthetic of tobacco marketing to ensure it does not employ tactics that are specifically designed to be pleasing or engaging in a manner that increases receptivity among current smokers.

Comprehensive ban on indirect advertising: Ensure that even indirect or subtle forms of marketing, which might not overtly promote tobacco but create a positive association with smoking, are prohibited.

Enhanced monitoring and enforcement: Strengthen the enforcement of existing marketing restrictions and closely monitor tobacco company practices to ensure compliance with regulations that aim to make tobacco marketing less appealing and dominant.

Public education campaigns: Amplify public health campaigns that counteract positive attitudes towards smoking, focusing on the health risks and social consequences of tobacco use to counterbalance any increased receptivity due to marketing.

These considerations would build on Vietnam’s existing tobacco control efforts, aiming to further reduce the influence of tobacco marketing on smoking behavior and ultimately decrease tobacco use among the population.

Conclusions

Along with the results, this study validated the significance of the research technique by clearly illustrating the process of creating smokers’ purchase intentions. The research outcomes satisfied the intended aims effectively. First, the study revealed the process by which existing smokers establish purchase intentions, as well as insights into smokers’ actions and practical consequences for Vietnamese policymakers. Second, the research has obviously explained the nexus of stimulus factors (exposure to tobacco marketing), individuals’ processes (smokers’ marketing receptivity, emotional states, and attitudes toward tobacco marketing), and smokers’ purchase intentions. Third, the study provided a unique and innovative approach to the tobacco sector and served as a basis for intervention measures to enhance regulations restricting tobacco advertising without limitation and reducing future smoking rates. Finally, the research findings indicate that when smokers are exposed to marketing that is pleasant and not overly dominant, their receptivity to tobacco advertising increases, subsequently improving their attitudes toward smoking and leading to higher cigarette purchase intentions. These insights call for concise regulatory considerations focused on the manner and content of tobacco marketing. Regulators should consider implementing strict guidelines that limit the appeal of marketing tactics used by tobacco companies, particularly those that are crafted to be pleasing without appearing dominant, to prevent the normalization or positive framing of smoking. Policies could include restrictions on the aesthetic and emotional appeal of advertisements, the contexts in which tobacco marketing is allowed, and the direct targeting of consumers through personalized marketing strategies. The goal of such regulations would be to minimize the impact of tobacco marketing on consumer attitudes and behaviors, ultimately aiming to reduce smoking prevalence and protect public health.

In addition to the significant contributions, several limitations have been recognized. First, some biases may be happened such as measurement errors, generalizability, etc. due to the cross-sectional study. Second, although this study focused on both emotional and rational aspects in explaining smokers’ purchase intentions, the level of rationality was low (receptivity and attitudes). Therefore, future studies may consider cigarette purchase intention in a different approach such as behavioral cognition instead of just stopping at low cognitive levels such as marketing receptivity and individual attitudes toward advertising information. To further clarify the mechanism of cigarette purchase intention formation, a model testing the cognitive process from low to high should be conducted in the future, for example low and high thinking ability in shaping the purchase intention. Will individuals with low and high recognition differ in their intention to order cigarettes, and will this lens allow them to easily accept tobacco advertising information. Finally, this study aims to study the case of smokers in Vietnam, and the sample size is a limitation, so it is necessary to expand the research to other regions in the world to perfect the current research model.

Footnotes

ORCID iD

Thi Bach Yen Tran

Ethical Considerations

Consent to Participate

Informed consent was obtained from all individual participants included in the study. All participants provided informed consent either online (by clicking the “Start survey” button) or in person (via a signed consent form) after reviewing the research information. The study posed minimal risk, as no identifying information was collected, participation was voluntary, and participants could skip the questions and withdraw at any time. Data were collected anonymously and stored securely in compliance with the university’s research ethics policy. The potential societal benefits—such as informing more effective tobacco control policies—outweigh the negligible risk to participants.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

References

Abzari

Ghassemi

R. A.

Vosta

L. N.

(2014). Analysing the effect of social media on brand attitude and purchase intention: The case of Iran Khodro Company. Procedia-Social and Behavioral Sciences, 143, 822–826. https://doi.org/10.1016/j.sbspro.2014.07.483

Adkison

S. E.

O’Connor

R. J.

Borland

Yong

H.-H.

Cummings

K. M.

Hammond

Fong

G. T.

(2013). Impact of reduced ignition propensity cigarette regulation on consumer smoking behavior and quit intentions: Evidence from 6 waves (2004–11) of the ITC Four Country Survey. Tobacco Induced Diseases, 11, 1–7. https://doi.org/10.1186/1617-9625-11-26

Ahmed

R. R.

Streimikiene

Qadir

Streimikis

(2023). Effect of green marketing mix, green customer value, and attitude on green purchase intention: Evidence from the USA. Environmental Science and Pollution Research, 30(5), 11473–11495. https://doi.org/10.1007/s11356-022-22944-7

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Azagba

Shan

Manzione

L. C.

Latham

Rogers

Qeadan

(2020). Single cigarette purchasers among adult US smokers. Preventive Medicine Reports, 17, Article 101055. https://doi.org/10.1016/j.pmedr.2020.101055

Bailey

A. A.

Mishra

Tiamiyu

M. F.

(2016). Green advertising receptivity: An initial scale development process. Journal of Marketing Communications, 22(3), 327–345. https://doi.org/10.1080/13527266.2014.904812

Bandura

(2003). Social cognitive theory for personal and social change by enabling media. In Singhal

Rogers

E. M.

Cody

M. J.

Sabido

(Eds.), Entertainment-education and social change (pp. 97–118). Routledge.

Behera

C. K.

Dadra

(2023). Understanding young consumers’ attitude formation for new-age fintech credit products: An SOR framework perspective. Journal of Financial Services Marketing, 29, 964–978. https://doi.org/10.1057/s41264-023-00247-3

Beig

F. A.

Khan

M. F.

(2022). Romancing the brands on social media. Global Business Review, 23(3), 841–862. https://doi.org/10.1177/0972150919866082

10.

Biener

Siegel

(2000). Tobacco marketing and adolescent smoking: More support for a causal inference. American Journal of Public Health, 90(3), 407–411. https://doi.org/10.2105/ajph.90.3.407

11.

Brakus

J. J.

Schmitt

B. H.

Zarantonello

(2009). Brand experience: What is it? How is it measured? Does it affect loyalty? Journal of Marketing, 73(3), 52–68. https://doi.org/10.1509/jmkg.73.3.052

12.

Braun

Kollath-Cattano

Barrientos

Mejía

Morello

Sargent

J. D.

Thrasher

J. F.

(2016). Assessing tobacco marketing receptivity among youth: integrating point of sale marketing, cigarette package branding and branded merchandise. Tobacco Control, 25(6), 648–655.

13.

Braverman

M. T.

Aarø

L. E.

(2004). Adolescent smoking and exposure to tobacco marketing under a tobacco advertising ban: findings from 2 Norwegian national samples. American Journal of Public Health, 94(7), 1230–1238. https://doi.org/10.2105/ajph.94.7.1230

14.

Bruch

Feinberg

(2017). Decision-making processes in social contexts. Annual Review of Sociology, 43, 207–227. https://doi.org/10.1146/annurev-soc-060116-053622

15.

Chen

Zhao

Xie

(2021). Nicotine dependence, perceived behavioral control, descriptive quitting norms, and intentions to quit smoking among Chinese male regular smokers. Substance Use & Misuse, 56(1), 145–152. https://doi.org/10.1080/10826084.2020.1846195

16.

Choi

Forster

(2014). Tobacco direct mail marketing and smoking behaviors in a cohort of adolescents and young adults from the US upper Midwest: A prospective analysis. Nicotine & Tobacco Research, 16(6), 886–889. https://doi.org/10.1093/ntr/ntu013

17.

Choi

Kreuger

McNeel

T. S.

Osgood

(2021). Point-of-sale cigarette pricing strategies and young adult smokers’ intention to purchase cigarettes: An online experiment. Tobacco Control, 31(3), 473–478. https://doi.org/10.1136/tobaccocontrol-2020-056004

18.

Dijksterhuis

Aarts

(2003). On wildebeests and humans: The preferential detection of negative stimuli. Psychological Science, 14(1), 14–18. https://doi.org/10.1111/1467-9280.t01-1-014

19.

Dinh

T.-H.

van Teijlingen

E. R.

(2019). Factors influencing engagement in premarital sex among Vietnamese young adults: A qualitative study. International Journal of Adolescent Medicine and Health, 33(4), 20180201–20180201. https://doi.org/10.1515/ijamh-2018-0201

20.

Dua

(2024). Building purchase intention through live streaming platforms: Mediating role of customer engagement. Journal of Promotion Management, 30(4), 657–680. https://doi.org/10.1080/10496491.2023.2289900

21.

Dunbar

M. S.

Martino

S. C.

Setodji

C. M.

Shadel

W. G.

(2019). Exposure to the tobacco power wall increases adolescents’ willingness to use e-cigarettes in the future. Nicotine and Tobacco Research, 21(10), 1429–1433. https://doi.org/10.1093/ntr/nty112

22.

Eagly

A. H.

Chaiken

(1993). The psychology of attitudes. Harcourt Brace Jovanovich College Publishers.

23.

Eagly

A. H.

Chaiken

(2005). Attitude research in the 21st century: The current state of knowledge. In Albarracín

Johnson

B. T.

Zanna

M. P.

(Eds.), The handbook of attitudes. Lawrence Erlbaum Associates Publishers.

24.

Edwards

Hoek

Karreman

Gilmore

(2022). Evaluating tobacco industry ‘transformation’: A proposed rubric and analysis. Tobacco Control, 31(2), 313–321. https://doi.org/10.1136/tobaccocontrol-2021-056687

25.

Euromonitor International. (2022). Tobacco in Vietnam, euromonitor international passport. Euromonitor International. https://www.portal.euromonitor.com/ResultsList/Index

26.

Fazio

R. H.

(1995). Attitudes as object-evaluation associations: Determinants, consequences, and correlates of attitude accessibility. Attitude Strength: Antecedents and Consequences, 4(1), 247–282.

27.

Feighery

E. C.

Ribisl

K. M.

Schleicher

N. C.

Clark

P. I.

(2004). Retailer participation in cigarette company incentive programs is related to increased levels of cigarette advertising and cheaper cigarette prices in stores. Preventive Medicine, 38(6), 876–884. https://doi.org/10.1016/j.ypmed.2003.12.027

28.

Finlay

Robinson

Jones

Maden

Cerny

Muc

Evans

Makin

Boyland

(2022). A scoping review of outdoor food marketing: Exposure, power and impacts on eating behaviour and health. BMC Public Health, 22(1), 1–1431. https://doi.org/10.1186/s12889-022-13784-8

29.

Fishbein

Ajzen

(2005). Theory-based behavior change interventions: Comments on Hobbis and Sutton. Journal of Health Psychology, 10(1), 27–31. https://doi.org/10.1177/1359105305048552

30.

Fleischer

N. L.

Thrasher

J. F.

Reynales-Shigematsu

L. M.

Cummings

K. M.

Meza

Zhang

Levy

D. T.

(2017). Mexico SimSmoke: How changes in tobacco control policies would impact smoking prevalence and smoking attributable deaths in Mexico. Global Public Health, 12(7), 830–845. https://doi.org/10.1080/17441692.2015.1123749

31.

Gammelgaard

(2004). Schools in logistics research? A methodological framework for analysis of the discipline. International Journal of Physical Distribution & Logistics Management, 34(6), 479–491. https://doi.org/10.1108/09600030410548541

32.

Gawronski

(2007). Attitudes can be measured! But what is an attitude? Social Cognition, 25(5), 573–581. https://doi.org/10.1521/soco.2007.25.5.573

33.

Ghani

A. W. A.

Ngah

A. H.

Yaakop

A. Y.

(2022). Why should I continue using it? Factors influencing continuance intention to use e-wallet: The SOR framework. In Al-Emran

Al-Sharafi

M. A.

Shaalan

(Eds.), International conference on information systems and intelligent applications. ICISIA 2022. Lecture notes in networks and systems (Vol. 550). Springer .

34.

Gilpin

E. A.

White

M. M.

Messer

Pierce

J. P.

(2007). Receptivity to tobacco advertising and promotions among young adolescents as a predictor of established smoking in young adulthood. American Journal of Public Health, 97(8), 1489–1495. https://doi.org/10.2105/AJPH.2005.070359

35.

Govender

Bhana

(2023). Smoking, swearing and strong muscles: Becoming boys in the primary school. International Journal of Educational Research, 121, 102225–102225. https://doi.org/10.1016/j.ijer.2023.102225

36.

Greenland

McGoldrick

(2005). Evaluating the design of retail financial service environments. International Journal of Bank Marketing, 23(2), 132–152. https://doi.org/10.1108/02652320510584386

37.

Greenland

S. J.

(2019). Future sustainability, innovation and marketing: A framework for understanding impediments to sustainable innovation adoption and corporate social responsibility. In Crowther

Seifi

(Eds.), The components of sustainable development. Approaches to global sustainability, markets, and governance. Springer.

38.

Greenland

S. J.

Nguyen

Strong

(2023). Irresponsible marketing and the need to support pro-sustainable production and consumption. Journal of Strategic Marketing, 1–5. https://doi.org/10.1080/0965254X.2023.2230487

39.

Hair

J. F.

Ringle

C. M.

Sarstedt

(2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202

40.

Hair

J. F.

Jr. Hult

G. T. M.

Ringle

C. M.

Sarstedt

Danks

N. P.

Ray

(2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature.

41.

Hanh

T. T. T.

Van Can

Nguyen-Tien

Anh

N. Q.

Trang

P. T. T.

Huong

N. T.

Minh

D. L. H.

Khue

L. N.

Hai

P. T.

Linh

N. T.

(2024). Secondhand smoke and socio-demographic associated factors: Results from the Vietnam population-based provincial global adult tobacco survey in 2022. Tobacco Use Insights, 17, Article 1179173X241257683. https://doi.org/10.1177/1179173X241257683

42.

Hanson

M. J. S.

(2018). Attitudes and perceptions about cigarette smoking among nonsmoking high school students. Journal of the American Association of Nurse Practitioners, 30(2), 60–63. https://doi.org/10.1097/JXX.0000000000000005

43.

Henriksen

Feighery

E. C.

Schleicher

N. C.

Fortmann

S. P.

(2008). Receptivity to alcohol marketing predicts initiation of alcohol use. Journal of Adolescent Health, 42(1), 28–35. https://doi.org/10.1016/j.jadohealth.2007.07.005

44.

Henseler

Ringle

C. M.

Sarstedt

(2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8

45.

Huo

Wang

Sadiq

M. W.

Pang

(2023). Exploring factors affecting consumer’s impulse buying behavior in live-streaming shopping: An interactive research based upon SOR model. SAGE Open, 13(2), Article 21582440231172678. https://doi.org/10.1177/21582440231172678

46.

Huong

L. T. T.

Long

T. K.

Van Anh

T. T.

Tuyet-Hanh

T. T.

Giang

K. B.

Hai

P. T.

Huyen

D. T.

Khue

L. N.

Lam

N. T.

Nga

P. Q.

(2017). Exposure to tobacco advertising, promotion among the adult population in Vietnam and its implications for public health. Asia Pacific Journal of Public Health, 29(7), 569–579. https://doi.org/10.1177/1010539517735630

47.

Hsieh

S. H.

Lee

C. T.

Tseng

T. H.

(2021). Branded app atmospherics: Examining the effect of pleasure–arousal–dominance in brand relationship building. Journal of Retailing and Consumer Services, 60, 102482–102482. https://doi.org/10.1016/j.jretconser.2021.102482

48.

Hyland

Laux

F. L.

Higbee

Hastings

Ross

Chaloupka

Fong

G. T.

Cummings

K. M.

(2006). Cigarette purchase patterns in four countries and the relationship with cessation: Findings from the International Tobacco Control (ITC) Four Country Survey. Tobacco Control, 15(Suppl 3), Article iii59. https://doi.org/10.1136/tc.2005.012203

49.

Euromonitor International. (2023). Tobacco in Vietnam. Euromonitor International.

50.

Jaeger

S. R.

Jin

Ryan

G. S.

Schouteten

J. J.

(2021). Emoji for food and beverage research: Pleasure, arousal and dominance meanings and appropriateness for use. Foods, 10(11), Article 2880. https://doi.org/10.3390/foods10112880

51.

Khan

(2022). Do brands’ social media marketing activities matter? A moderation analysis. Journal of Retailing and Consumer Services, 64, Article 102794. https://doi.org/10.1016/j.jretconser.2021.102794

52.

Kim

M. J.

Lee

C.-K.

Jung

(2020). Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. Journal of Travel Research, 59(1), 69–89. https://doi.org/10.1177/0047287518818915

53.

Kock

Lynn

(2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recommendations. Journal of the Association for Information Systems, 13(7), 546–580. https://doi.org/10.17705/1jais.00302

54.

Kokolakis

(2017). Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon. Computers & Security, 64, 122–134. https://doi.org/10.1016/j.cose.2015.07.002

55.

Koo

D.-M.

Lee

J.-H.

(2011). Inter-relationships among dominance, energetic and tense arousal, and pleasure, and differences in their impacts under online vs. offline environment. Computers in Human Behavior, 27(5), 1740–1750. https://doi.org/10.1016/j.chb.2011.03.001

56.

Krosnick

J. A.

Judd

C. M.

Wittenbrink

(2005). The measurement of attitudes. In Albarracín

Johnson

B. T.

Zanna

M. P.

(Eds.), Handbook of attitudes and attitude change (pp. 21–76). Erlbaum.

57.

Krosnick

J. A.

Judd

C. M.

Wittenbrink

(2018). The measurement of attitudes. In Albarracin

Johnson

B. T.

(Eds.), The handbook of attitudes, volume 1: Basic principles (2nd ed., Vol. 1, pp. 45–105). Routledge.

58.

Kruglanski

A. W.

Stroebe

(2005). The influence of beliefs and goals on attitudes: Issues of structure, function, and dynamics. In Albarracin

Johnson

B. T.

Zanna

M. P.

(Eds.), The handbook of attitudes. Psychology Press.

59.

Lang

P. J.

Bradley

M. M.

Cuthbert

B. N.

(1997). Motivated attention: Affect, activation, and action. In Balaban

M. T.

Lang

P. J.

Simons

R. F.

(Eds.), Attention and orienting: Sensory and motivational processes (Vol. 97, p. 135). Lawrence Erlbaum Associates.

60.

Lareyre

Gourlan

Stoebner-Delbarre

Cousson-Gélie

(2021). Characteristics and impact of theory of planned behavior interventions on smoking behavior: a systematic review of the literature. Preventive Medicine, 143, Article 106327. https://doi.org/10.1016/j.ypmed.2020.106327

61.

Lee

A. Y.

Labroo

A. A.

(2004). The effect of conceptual and perceptual fluency on brand evaluation. Journal of Marketing Research, 41(2), 151–165.

62.

Lee

S. J.

Sanders-Jackson

Tan

A. S.

(2020). Effects of current and enhanced tobacco corrective messages on smokers’ intention to quit smoking and intention to purchase cigarettes. Nicotine and Tobacco Research, 22(4), 569–575. https://doi.org/10.1093/ntr/ntz063

63.

Ling

P.-S.

Liong

Ling

L.-S.

Lee

K. Y. M.

(2024). Intention to purchase eco-friendly stationery: A study on university students using SOR framework. Multidisciplinary Reviews, 7(12), Article 2024298. https://doi.org/10.31893/multirev.2024298

64.

Ling

P. M.

Neilands

T. B.

Glantz

S. A.

(2009). Young adult smoking behavior: A national survey. American Journal of Preventive Medicine, 36(5), 389–394.e2. https://doi.org/10.1016/j.amepre.2009.01.028

65.

Liu

Wright

Elizarova

Dahne

Bian

Tan

A. S.

(2021). Emotional responses and perceived relative harm mediate the effect of exposure to misinformation about e-cigarettes on twitter and intention to purchase e-cigarettes among adult smokers. International Journal of Environmental Research and Public Health, 18(23), Article 12347. https://doi.org/10.3390/ijerph182312347

66.

Loureiro

S. M. C.

Bilro

R. G.

Japutra

(2019). The effect of consumer-generated media stimuli on emotions and consumer brand engagement. Journal of Product & Brand Management, 29(3), 387–408. https://doi.org/10.1108/JPBM-11-2018-2120

67.

Lovato

Watts

Stead

L. F.

(2011). Impact of tobacco advertising and promotion on increasing adolescent smoking behaviours. Cochrane Database of Systematic Reviews, (3), CD003439. https://doi.org/10.1002/14651858.CD003439

68.

Mantey

D. S.

Pasch

K. E.

Loukas

Perry

C. L.

(2019). Exposure to point-of-sale marketing of cigarettes and e-cigarettes as predictors of smoking cessation behaviors. Nicotine and Tobacco Research, 21(2), 212–219. https://doi.org/10.1093/ntr/ntx246

69.

Mehrabian

Russell

J. A.

(1974). An approach to environmental psychology. The MIT Press.

70.

Miles

J. A.

(2012). Management and organization theory: A Jossey-Bass reader (Vol. 9). John Wiley & Sons.

71.

Minh

N. H.

Hai

L. S.

Phi

N. A.

Duyen

L. B. T.

Giang

L. T. Q.

(2024). The impact of TikTok UGC videos on online purchase intention: Mediating role of cognitive states. Pacific Asia Journal of the Association for Information Systems, 16(1), Article 7. https://doi.org/10.17705/1pais.16107

72.

Nguyen-Viet

Thanh Tran

(2024). Sustaining organizational customers’ consumption through corporate social responsibility and green advertising receptivity: The mediating role of green trust. Cogent Business & Management, 11(1), Article 2287775. https://doi.org/10.1080/23311975.2023.2287775

73.

Nguyen

H. V.

Nguyen

B. K.

Lobo

P. A.

(2019). Organic food purchases in an emerging market: The influence of consumers’ personal factors and green marketing practices of food stores. International Journal of Environmental Research and Public Health, 16(6), Article 1037. https://doi.org/10.3390/ijerph16061037

74.

Noonan

Kulbok

Yan

(2011). Intention to smoke tobacco using a waterpipe among students in a southeastern U.S. College. Public Health Nursing (Boston, Mass.), 28(6), 494–502. https://doi.org/10.1111/j.1525-1446.2011.00945.x

75.

O’Connor

R. J.

Lewis

M. J.

Adkison

S. E.

Bansal-Travers

Cummings

K. M.

(2017). Perceptions of “natural” and “additive-free” cigarettes and intentions to purchase. Health Education & Behavior, 44(2), 222–226. https://doi.org/10.1177/1090198116653935

76.

Boo

(2023). A cross-sectional study on factors affecting the intention to quit smoking among female call centre employees. Nursing Open, 10(8), 5711–5719. https://doi.org/10.1002/nop2.1821

77.

Petty

R. E.

Cacioppo

J. T.

Petty

R. E.

Cacioppo

J. T.

(1986). The elaboration likelihood model of persuasion. Springer.

78.

Pierce

J. P.

Choi

W. S.

Gilpin

E. A.

Farkas

A. J.

Berry

C. C.

(1998). Tobacco industry promotion of cigarettes and adolescent smoking. JAMA, 279(7), 511–515. https://doi.org/10.1001/jama.279.7.511

79.

Pokhrel

Herzog

T. A.

Muranaka

Fagan

(2015). Young adult e-cigarette users’ reasons for liking and not liking e-cigarettes: A qualitative study. Psychology & Health, 30(12), 1450–1469. https://doi.org/10.1080/08870446.2015.1061129

80.

Prashar

(2024). Digital fashion and metaverse platforms: Do platform attributes drive shopper’s purchase intention? Australian Journal of Management. Advance online publication. https://doi.org/10.1177/03128962241246696

81.

Puriwati

Tripopsakul

(2022). Consumers’ attitude towards digital social responsibility: Impacts on electronic word of mouth and purchase intention. Emerging Science Journal, 6(1), 64–74. https://doi.org/10.28991/ESJ-2022-06-01-05

82.

Rausch

T. M.

Kopplin

C. S.

(2021). Bridge the gap: Consumers’ purchase intention and behavior regarding sustainable clothing. Journal of Cleaner Production, 278, Article 123882. https://doi.org/10.1016/j.jclepro.2020.123882

83.

Saleem

M. A.

Shafiq

Afzal

Khalid

Nguyen

(2023). Addiction or social need: Towards a model to predict smoking cessation intentions. Journal of Social Marketing, 13(2), 295–322. https://doi.org/10.1108/JSOCM-04-2022-0079

84.

Savell

Gilmore

A. B.

Fooks

(2014). How does the tobacco industry attempt to influence marketing regulations? A systematic review. PLoS One, 9(2), Article e87389. https://doi.org/10.1371/journal.pone.0087389

85.

Schooler

Feighery

Flora

J. A.

(1996). Seventh graders’ self-reported exposure to cigarette marketing and its relationship to their smoking behavior. American Journal of Public Health, 86(9), 1216–1221. https://doi.org/10.2105/ajph.86.9.1216

86.

Setodji

C. M.

Martino

S. C.

Scharf

D. M.

Shadel

W. G.

(2013). Friends moderate the effects of pro-smoking media on college students’ intentions to smoke. Psychology of Addictive Behaviors, 27(1), 256–261. https://doi.org/10.1037/a0028895

87.

Sharma

June

K. M.

Norton

K. J.

Fix

Bansal-Travers

Rees

V. W.

O’Connor

R. J.

(2022). Intention to purchase alternative tobacco products as a function of smoking status and responses to advertising, packaging, and sensory experiences. Addictive Behaviors, 130, Article 107291. https://doi.org/10.1016/j.addbeh.2022.107291

88.

Siahpush

Shaikh

R. A.

Smith

Hyland

Cummings

K. M.

Sikora Kessler

Dodd

M. D.

Carlson

Meza

Wakefield

(2016). The association of exposure to point-of-sale tobacco marketing with quit attempt and quit success: Results from a prospective study of smokers in the United States. International Journal of Environmental Research & Public Health, 13(2), 203–203. https://doi.org/10.3390/ijerph13020203

89.

Soroya

S. H.

Farooq

Mahmood

Isoaho

Zara

S.-E.

(2021). From information seeking to information avoidance: Understanding the health information behavior during a global health crisis. Information Processing & Management, 58(2), Article 102440.

90.

Tewari

Mathur

Srivastava

Gangwar

(2022). Examining the role of receptivity to green communication, altruism and openness to change on young consumers’ intention to purchase green apparel: A multi-analytical approach. Journal of Retailing and Consumer Services, 66, Article 102938. https://doi.org/10.1016/j.jretconser.2022.102938

91.

Thrasher

J. F.

Jackson

Arillo-Santillán

Sargent

J. D.

(2008). Exposure to smoking imagery in popular films and adolescent smoking in Mexico. American Journal of Preventive Medicine, 35(2), 95–102. https://doi.org/10.1016/j.amepre.2008.03.036

92.

Thrasher

J. F.

Rousu

M. C.

Hammond

Navarro

Corrigan

J. R.

(2011). Estimating the impact of pictorial health warnings and “plain” cigarette packaging: Evidence from experimental auctions among adult smokers in the United States. Health Policy, 102(1), 41–48. https://doi.org/10.1016/j.healthpol.2011.06.003

93.

Tran

T. B. Y.

Nguyen

Greenland

Saleem

M. A.

(2024). Unrestricted tobacco marketing prompts young adults to smoke in an emerging market: A study of emotional responses. Journal of Strategic Marketing, 32(5), 575–589. https://doi.org/10.1080/0965254X.2023.2268667

94.

Tran

T. D.

Van Pham

Nguyen

P. C. T.

Louis

L. T.

N. N. T.

(2024). A case study of decision-making towards using online food distribution services after Covid-19 in Vietnam. Journal of Distribution Science, 22(3), 33–47. https://doi.org/10.15722/jds.22.03.202403.33

95.

Topuridze

Berg

C. J.

Dekanosidze

Torosyan

Grigoryan

Bazarchyan

Sargsyan

Hayrumyan

Maglakelidze

Sturua

(2020). Smokers’ and nonsmokers’ receptivity to smoke-free policies and pro-and anti-policy messaging in Armenia and Georgia. International Journal of Environmental Research & Public Health, 17(15), 1–14.

96.

Tseng

Y.-F.

Wang

K.-L.

Lin

C.-Y.

Lin

Y.-T.

Pan

H.-C.

Chang

C.-J.

(2018). Predictors of smoking cessation in Taiwan: Using the theory of planned behavior. Psychology, Health & Medicine, 23(3), 270–276. https://doi.org/10.1080/13548506.2017.1378820

97.

Vazquez

E. E.

Patel

Alvidrez

Siliceo

(2023). Images, reviews, and purchase intention on social commerce: The role of mental imagery vividness, cognitive and affective social presence. Journal of Retailing and Consumer Services, 74, Article 103415. https://doi.org/10.1016/j.jretconser.2023.103415

98.

Viet Nguyen

T. T.

Nguyen

N. H.

(2021). The impact of cigarette prices on smoking participation and tobacco expenditure in Vietnam. PloS One, 16(12), e0260415–e0260415. https://doi.org/10.1371/journal.pone.0260415

99.

Wedel

Pieters

(2007). Visual marketing: From attention to action. Psychology Press.

100.

Weitzman

Lee

(2020). Similarities between alcohol and tobacco advertising exposure and adolescent use of each of these substances. Journal of Studies on Alcohol and Drugs, Supplements, Suppl. 19, 97–105. https://doi.org/10.15288/jsads.2020.s19.97

101.

Wen

T. J.

Choi

C. W.

Morris

J. D.

(2022). Empowering emotion: The driving force of share and purchase intentions in viral advertising. Journal of Current Issues & Research in Advertising, 43(1), 47–67. https://doi.org/10.1080/10641734.2021.1937408

102.

WHO. (2023). WHO report on the global tobacco epidemic, 2023: Protect people from tobacco smoke. https://www.who.int/publications/i/item/9789240077164

103.

Yang

Z. J.

Kahlor

(2013). What, me worry? The role of affect in information seeking and avoidance. Science Communication, 35(2), 189–212.

104.

Yong

H.-H.

Borland

Thrasher

J. F.

Thompson

M. E.

Nagelhout

G. E.

Fong

G. T.

Hammond

Cummings

K. M.

(2014). Mediational pathways of the impact of cigarette warning labels on quit attempts. Health Psychology, 33(11), Article 1410. https://doi.org/10.1037/hea0000056

105.

Zhang

Yue

Peng

M. Y.-P.

(2021). Understanding the impact of the psychological cognitive process on student learning satisfaction: Combination of the social cognitive career theory and SOR model. Frontiers in Psychology, 12, Article 712323. https://doi.org/10.3389/fpsyg.2021.712323

106.

Zhao

Dichtl

F. F.

Foran

H. M.

(2020). Predicting smoking behavior: Intention and future self-continuity among Austrians. Psychology, Health & Medicine, 1–10. https://doi.org/10.1080/13548506.2020.1842898

107.

Zhu

Cai

Zhu

Redmon

Qiao

(2013). Predictors of intention to smoke among junior high school students in Shanghai, China: An empirical test of the information-motivation-behavioral skills (IMB) model. PloS One, 8(11), e80482. https://doi.org/10.1371/journal.pone.0080482