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Alternatives for Targeting Women in Anti-Smoking Campaigns: Insights from a Smoking Perceived Value Perspective.

Smoking continues to be one of the main health problems worldwide. According to the World Health Organization, tobacco kills almost 6 million people every year. If current trends continue, tobacco could cause one billion deaths in the 21st century. On average, more women and girls smoke in Spain compared with other high-income countries (Eriksen et al. 2015). Unlike other legal addictive products, in the case of tobacco there is no such thing as a safe level of consumption (Capella, Taylor, and Kees 2012). Due to this concern, the World Health Organization (WHO) Framework Convention on Tobacco Control in its article 12 advocates promoting awareness of tobacco dangers through public campaigns (FCTC 2003).

Despite the considerable endeavors, over many years, to reduce the number of smokers, there remains significant controversy regarding the effectiveness of public anti-smoking campaigns (Paek 2009). This suggests the need for a fresh approach to campaign design. One of the more critical conditions for the success of most public health mass media campaigns is the understanding of the pathways of the health behavior targeted, which is often overlooked (Randolph and Viswanath 2004). It is based on the premise that human behavior is influenced by a well-defined set of factors, and a successful campaign can influence behavior by influencing the determinants leading to that behavior. Several theories of health behavior identify pathways and determinants that ultimately lead to health behavior change. Notwithstanding, these theories differ in the individual weights they give different factors and the sequence through which individuals move through the paths (Randolph and Viswanath 2004). In our study, we have explored other concepts in order to analyze if another perspective, based on the value that smokers attribute to their smoking experience, could be a source of new insights to understand the pathways of the health behavior targeted.

So, a little explored concept in the field of health that has proven useful as a predictor of consumer behavior (e.g., satisfaction or intentions) (Gil and Gonzalez 2008) within the discipline of Marketing is that of Perceived Value (PV). The concept of PV captures the value that consumers attribute to their experiences (e.g., Zeithaml 1988). Usually it perceived as a trade-off between the benefits and drawbacks associated with the purchase/consumption experience.

The approach to smoking behaviors might appear to follow the line of that commonly advanced in the scientific literature linked to perceptions of risks and benefits (Song et al. 2009). However, the idea behind the PV takes for granted that consumer behaviors take place after an overall simplified assessment of the positive (benefits) and negative (sacrifices) experiences. In these cases, the overall assessment is more than the sum of the parts. As the concept indicates, there is a direct correlation between these positive and negative experiences. These experiences cannot be separated or their effects isolated as is usual in tobacco literature. It is viewing them as a whole that they can be predicted and thus have an impact on behaviors. This implies that any attempt to modify consumer behavior supposes attaining a minimum level in the value attributed to each and all the benefits and sacrifices. It is a question of, thus, acting on the whole of the experience.

Hence we explore in this paper whether the PV approach is applicable to aspects of smoking as is the intention to quit. If the PV is applicable to smoking habits, then it could provide new insights serving as a basis to design public anti-tobacco campaigns.


The most widely accepted definition of PV is that submitted by Zeithaml (1988, 14): "Perceived value is a consumer's overall assessment of the utility of a product based on perceptions of what is received and what is given." There are currently acknowledged to be four key characteristics of the PV concept: (1) it is a trade-off between what the customer receives (benefits) and what they give up in return (sacrifices); (2) it is composed of both cognitive and affective components; and (3) perceptions of value are subjective and contextual (Holbrook and Hirschman 1982; Oliver 1997; Peter and Olson 1999).

Different typologies of benefits and sacrifices have been used when measuring PV (Sanchez-Fernandez and Iniesta-Bonillo 2007, for an overview). Broadly speaking these typologies can be summarized into three main dimensions: functional, social and emotional. The functional dimension relates to the utility derived from the financial aspects and intrinsic features of the product. The social dimension refers to the utility derived from the product's capacity to improve one's self-concept and how consuming the product helps the user to feel more accepted by others. The emotional dimension refers to the utility derived from the feelings or affective states generated by the product (Sweeney and Soutar 2001). This dimensional approach is valid, in our view, for studying Smoking PV (SPV). In our review of many of the studies that link the benefits and damage caused by smoking habits, we found a parallel with the dimensions of PV.

Taking the functional dimension as a reference point, among the perceived benefits identified as predictors of behavior or attitudes toward tobacco use (such as starting or giving up smoking, or a relapse) are weight control, improved concentration, pain relief or stress relief and relaxation (Fidler and West 2009; Herd, Borland, and Hyland 2009; Jane et al. 2001; McEwen et al. 2006; Rindfleisch and Crockett 1999; Smith et al. 2010; Velicer et al. 1985; Weinberger, Mazure, and McKee 2010; Zlatev, Pahl, and White 2010).

Among the functional sacrifices, the literature highlights the existence of: (1) financial sacrifices (the financial cost borne by the consumer when acquiring and consuming the product or service) (e.g., Cengiz and Kirkbir 2007; Joo 2007; Kumar and Lim 2008); (2) time sacrifices associated with the user's acquisition and consumption of the product or service (e.g., Gallarza and Gil-Saura 2006a, 2006b; Hsu 2006; Pura 2005; Sigala 2005); and (3) the risks perceived by the consumer in terms of the performance of the product or service and the effects that consuming it will have (e.g., Andrews et al. 2007; Joo 2007; Soltani and Gharbi 2008). All of these sacrifices may play a role in the smoking habit, and notably there is a significant incidence of health-related risks for the smoker--in fact, health risks are the most common type of PV explored in the literature (Baha and Le Faou 2010; Behn et al. 2001; Herd, Borland, and Hyland 2009; Rindfleisch and Crockett 1999; Weinberger, Mazure, and McKee 2010).

When it comes to social benefits, smoking helps users to socialize, make friends, and strengthen their self-concept (Aryal, Petzold, and Krettek 2013; Behn et al. 2001; Fidler and West 2009; Jane et al. 2001; McEwen et al. 2006; Rindfleisch and Crockett 1999; Song et al. 2009; Velicer et al. 1985; Weinberger, Mazure, and McKee 2010). Social sacrifices associated with smoking are the bad impression it can cause, the pressure from others to kick the habit or the bad social example it sets (Aryal, Petzold, and Krettek 2013; Baha and Le Faou 2010; Curry et al. 2001; Rindfleisch and Crockett 1999; Song et al. 2009; Velicer et al. 1985; Weinberger, Mazure, and McKee 2010).

Among emotional benefits dimension, there are aspects of self-confidence and entertainment (Aryal, Petzold, and Krettek 2013; Behn et al. 2001; Fidler and West 2009; Herd, Borland, and Hyland 2009; Jane et al. 2001; McEwen et al. 2006; Rindfleisch and Crockett 1999; Song et al. 2009; Velicer et al. 1985; Weinberger, Mazure, and McKee 2010; Zlatev, Pahl, and White 2010). As regards the sacrifices involved in smoking, here too emotional issues can be found, such as: feeling disheartened when attempting to give up, or feeling a loss of self-control (Baha and Le Faou 2010; Curry et al. 2001; Rindfleisch and Crockett 1999; Smith et al. 2010; Velicer et al. 1985; Weinberger, Mazure, and McKee 2010). Once the different benefits and sacrifices associated with the smoking habit had been identified, an SPV modelization was proposed (Figure 1).

In this model, the SPV (third-order factor) is reflected in the trade-off of perceived benefits and perceived sacrifices of smoking behaviors (second-order factors). These in turn are reflected in functional social and emotional nature (first-order factors) benefits and sacrifices where the SPV, at the same time, becomes a predictor of intention to quit smoking.


To carry out this study, a sampling of female smokers was designed by accessing an online panel of female consumers. The relevance of a sampling limited to women is based on the evidence of the differences between the smoking behaviors of men and women due to aspects such as aesthetics (like smoking as a way to maintain or lose weight or even as something fashionable), lack of social support, stress and depression (Giacobbi et al. 2016; Rey Pino and Gallopel-Morvan 2013; World Health Organization 2010). On the other hand, differences have also been found between men and women regarding the way they perceive risks. Specifically, some studies reveal that women perceive a higher risk of smoking than men (Finucane et al. 2000). The WHO through the Framework Convention on Tobacco Control insists in the need of generating strategies for fighting the alarming increase of tobacco consumption among women (FCTC 2003).

For many years the tobacco industry has been interested in women as consumers (Mackay and Amos 2003). Additionally, typical anti-smoking campaigns are being found to be less effective among women smokers than among men (Amos et al. 2011; Gilbert 2008; Jonsdottir 2013; World Health Organization 2010).

Data provided by the Tobacco Atlas (Eriksen etal. 2015) reveal that 23.4% of Spain's female population are smokers as compared to 29.9% of the male population. The most worrying fact is that 16% of female smokers are under 18 years of age compared to 11% of males. This statistic points to a reverse in the tendency of smoking frequency among men and women.

This study applied the steps proposed by Churchill (1979) including: (1) a qualitative study, on the basis of which the content of the dimensions and the items relating to each dimension were determined; (2) a pre-test, that was conducted, enabling the smoking PV items to be refined, and; (3) a quantitative empirical study that was undertaken, with which the smoking PV measurement instrument was validated.

Qualitative Study

A judging panel comprising experts was created (11 professors and researchers on social marketing, public health, and tobacco control from universities in diverse countries). The panel members were asked to pay attention to content validity, representativeness, dimensionality, comprehensibility and lack of ambiguity, related to the items previously identified. If two judges encountered an issue in assigning an item deemed not to be valid or representative, it was deleted. Some items were reworded to address the judges' comments. This procedure yielded 21 items (Table 1), which represented overall the benefits and sacrifices components, including functional, social, and emotional aspects.


This stage involved an initial gathering of quantitative data and an evaluation of the 21 items obtained in the qualitative study. On line interviews were carried out among Spanish female smokers. The sample was obtained using the convenience technique, once it had been confirmed that each interviewee fulfilled the key requirement, namely that participants were regular smokers. Some 29 valid interviews were carried out and, in light of the results, statistical tests were then conducted to assess the individual reliability of each of the proposed items. Following this analysis, all the items were retained.

Quantitative Empirical Study

A self-administered questionnaire, contracted with a market research company, was completed by female smokers through an online consumer panel. The questionnaire had 21 items (Table 1) on perceived benefits and sacrifices of the smoking habit (SPV) and a smoking cessation intention scale based on the approach recommended by Wong and Cappella (2009). SPV and smoking cessation intention were measured by applying a 10-point Likert scale, on which "zero" equaled "totally disagree" and "ten" equaled "totally agree."

The sampling excluded occasional smokers since the intention of the study was to analyze consolidated smoking behavior. We took a "smoker" to be a person who had smoked for at least 1 year, most recently on the day of the survey or the day before, and at least 100 times in total over the course of that year (Kestila et al. 2006).

In addition, we chose quota-based sampling based on the percentage of women smokers, our chosen age ranges were those employed by the Spanish National Health Survey (ENSE): 16-24 years (21%); 25-35 years (28.3%); 36-44 years (28.3%); and 45-54 years (30%). Taking into account our requirements and the panelists' availability, the final sample comprised 703 individuals. With the number of responses obtained and for a 95% confidence interval in the case of estimations of a proportion where p = q = 0.5 and assuming a simple random sampling, the sample error was [+ or -]3.7%.

Table 2 reveals the profile of the sampling. The profile of the respondents was similar to those in other studies conducted on smoking behavior in terms of age, education level or employment status (e.g., Croghan et al. 2006; Honjo and Siegel 2003).


The Structural Equation Model (SEM) with AMOS software was applied to estimate the research model. Given the objective of exploring the applicability of the SPV as a predictor of the intention to quit, the SPV scale was first tested to determine whether it yields appropriate values of Reliability and Validity before moving on to considering the effect that the SPV has on the intention to quit smoking.

The model was estimated in this first phase to test the validity of the SPV scale. The psychometric properties of the proposed model were estimated and evaluated. (1) Since the Chi-square test of multivariate normality of the variables included in the proposed model proved significant, estimation was undertaken by means of the maximum likelihood method combined with the bootstrap method (Yuan and Hayashi 2003).

The results lead to the elimination of "health-risk sacrifices" items and items referring to emotional sacrifices (HS1, HS2, and ES3 in Table 1) as it presented a standardized loading significantly under the reference value of 0.70 and an individual reliability or [R.sup.2] significantly below the minimum reference value of 0.50.

Excluding the "health-risk sacrifice" dimension helped to achieve an improved statistic for the model. There were no problems of convergent validity. Once this dimension had been eliminated, the individual reliability of the rest of the dimensions and items included in the model was above, or close to, the reference threshold. On this basis, the refining process was then stopped. The fit--global (CMIN/DF = 3.32; GFI = 0.92; RMSEA = 0.058) and incremental (CFI = 0.94; IFI = 0.94; TLI = 0.93)--of the model can be said to be acceptable.

As regards the check for adequate composite reliability, Table 3 shows the composite reliability and variance extracted indices corresponding to each dimension (all the values obtained were acceptable CR>0,7 and VE>0,5).

With regard to the test for the existence of convergent validity, this can be taken as the significance and direction of the factorial loads and the individual reliability that each item presents with respect to the dimension to which it belongs. In all cases the factorial loads were significant and had a value over, or close to, 0.70 (the reference value); and the individual reliability was significant and had a value over, or close to, the reference value of 0.50 (Hair et al. 2008, 649-651) (Table 3).

The confidence interval test was used to check for discriminant validity between dimensions. According to this test, for discriminant validity to exist the value "one" should not be found in the confidence interval of correlations between the different dimensions of the same level of analysis. Results were satisfactory in all cases. The results reveal that the SPV scale adequately gathers the global assessment of females of their smoking experience.

The second phase considered the effect that the SPV has on the intention to break the habit. The result shows that the SPV has a considerable influence on the intention to quit (significance level of p < 0.01). Furthermore, the effect detected is quite marked (-0.34), with a confidence interval of between -0.43 and -0.24. These results indicate that the SPV is a mechanism that can induce changes in intention to quit smoking.


With the ultimate goal of providing insight into improving the design of public anti-smoking campaigns targeting women, this work has explored the potential utility of the concept of PV. The results of the present study pave the way to two relevant conclusions. The first is the obtention of empirical evidence regarding the predictive value of the SPV on the intention of quitting smoking. The second, in turn, is the obtention of proof of the multidimensional nature of the SPV where the whole is greater than the sum of its parts--the benefits and sacrifices dimensions--and where the various different dimensions of PV can interact and generate a greater overall effect than may be predicted if focusing only on how the individual effects add together. Given the factorial nature of the construct, the model leads us to the conclusion of the necessity of jointly coordinating communication campaigns with the different dimensions with the goal to achieve, in each case, a minimum (positive or negative) level of perception. Once the minimum values are attained, the correlation between the dimensions supposes that partial advances in the perception of one can influence the others.

Of particular note is the fact that these results show that the "sacrifices" dimension relating to the health risks linked to smoking do not count as part of their SPV. This may seem surprising given that the literature continually makes the association between smoking and health problems and that the majority of the communication campaigns under public health strategies endlessly convey the harmful effects of tobacco on health (such as via cigarette packaging). Working on this premise, the vast amount of information received by smokers ensures that they are fully aware of the health problems associated with smoking.

We propose that one possible explanation for this factor is that while the other sacrifices and benefits included in the SPV construct make reference to effects that are immediately perceived and evaluated by female smokers (such as the time they spend buying cigarettes), those effects related to health risks are neither immediately noticeable nor direct. In fact, the literature recognizes that one of the innumerable problems of sustained smoking is that, generally speaking, there are no immediately visible damaging effects of intoxication (Russo et al. 2011). As a result, their assessment of the health risks may be based on the messages they receive from public health campaigns using fear appeals--for example, graphic labels in packaging--rather than on their own direct experience, unlike their assessment of the rest of the sacrifices and benefits included in smoking PV. However, the current study was carried out in a country with a long tradition of raising awareness about the risks of tobacco (since 2003 cigarette packets must bear the phrase "smoking causes lung cancer," and since 2011 shocking images illustrating the risks of smoking have been added); therefore, the health risks variable can be significant and modify the structure of the VPS.

A number of practical recommendations to help guide the design of anti-tobacco campaigns targeting women arise from the results and conclusions. First, public authorities in each country should be provided with an assessment of the perceptions among women of the benefits and sacrifices of smoking in order to come to an overall judgment regarding the smoking experience. In this sense, the scale developed in this work could be useful. Second, given the diversity of themes applied by governments in anti-tobacco campaigns, and the prevalence of relying on the fear appeal, the authorities of each country should draw up an inventory of the items used to detect the most useful benefits or sacrifices. Third, the two previous points regarding the perceptions found in the themes should be connected in order to minimize the perceptions of benefits and maximize the sacrifices in order to achieve a minimum level in all reviews of the smoking experience. This would lead to a better planning of the content of anti-tobacco campaigns, laying the groundwork for more effective approach to refining the individual themes to work in each case adjusting to an effective choice of the media and creative strategies.

This paper is centered on the segment of female smokers and presents a first approach to the use of PV in the smoking framework. It would be interesting to advance this line of research to reflect on the question if smoker age has an influence on SPV and the intention to quit. However, and in spite of the great social relevance cited above, this focus has an important drawback. It would also be important, so as to compare results, to carry out this research on the segment of male smokers. Yet this facet is beyond the scope of the current paper. In present-day societies the smoking habit has undeniably become an issue of concern, and while progress has been made in the fight against it, new approaches and tools are still very much needed to improve the effectiveness of social policies. It is this understanding that has provided the inspiration for the present work.


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Maria Jose Montero-Simo ( is associate professor at Universidad Loyola Andalucfa, Cordoba, Spain, Ana Isabel Polo-Pena ( is associate professor at Universidad de Granada, Granada, Spain, Rafael Araque-Padilla ( is associate professor at Universidad Loyola Andalucfa, Cordoba, Spain and Juan Miguel Rey-Pino ( is assistant professor at Universidad de Granada, Granada, Spain.

The Journal of Consumer Affairs, Summer 2018: 480-494

Copyright 2017 by The American Council on Consumer Interests

DOI: 10.1111/joca.l2169

(1.) It is important to note that the sacrifices were codified in the inverse direction in the present study.
Items Used on the Scales from the Empirical Study

Dimension                        Item

PV as viewed by the smoker
Benefits component
Functional benefit              FB1: In general, smoking helps me keep
                                  my weight down.
                                FB2: In general, smoking helps my
                                FB3: In general, smoking helps me
                                  cope with stress.
Social benefit                  SB1: In general, smoking helps
                                  me socialize.
                                SB2: Smoking helps me make friends.
Emotional benefit               EB1: In general, smoking gives
                                  me confidence.
                                EB2: In general, smoking gives me
something to do.
Sacrifices component
Financial functional sacrifice  FS1: In general, smoking makes me go
                                around asking for cigarettes.
                                FS2: On occasion I have had to assume
                                  the cost of replacing
                                  something I accidentally burned
                                  with a cigarette.
                                FS3: In general, I never have any
                                  money to spare because I smoke.
Time-related functional         TS1: In general, I waste a lot of time
sacrifice                         having to go outside to smoke.
                                TS2: In general, I waste
                                 studying/working time by stopping
                                 to have a cigarette.
                                TS3: In general, I have to make a
                                  specialtrip to the store to buy
Health risk functional          HS1: As a smoker, I run a higher risk of
sacrifice                         developing a serious illness (such as
                                  lung cancer, heart disease, emphysema,
                                HS2: In general, smoking is harmful to
                                  my physical fitness.
Social sacrifice                SSI: In general, when I light a
                                  cigarette Iirritate my relatives.
                                SS2: In general, I annoy my friends
                                  by smoking.
                                SS3: In general, smoking makes a bad
                                  impression when dating a non-smoker.
Emotional sacrifice             ESI: In general, I feel psychologically
                                  bad when I try to quit smoking.
                                ES2: I'm concerned that I won't be
                                  able to quit smoking whenever I want.
                                ES3: I rely on tobacco to deal with
                                  problems or negative moods.

Descriptive Characteristics of the Sample

Variable                                                         %

Age                           16-24                           19.5
                              25-34                           26.2
                              35-44                           26.5
                              45-54                           27.9
Number of cigarettes smoked   More than 20                    25.5
per day
                              from 10 to 20                   32.7
                              from 1 to 9                     41.8
Civil status                  Single                          43.1
                              Married                         38.8
                              Divorced                         8.1
                              Widowed                          1.3
                              Other                            8.7
Education level               No studies                       0.1
                              Basic studies                    8.7
                              High school                     16.8
                              Vocational training (medium)    10.7
                              Vocational training (high)      17.1
                              University/post-graduate        46.7
Employment status             Student                         11.8
                              Housework                        5.7
                              Unemployed                      23.6
                              Employed in the private sector  35.5
                              Employed in the public sector   14.5
                              Liberal profession               5.0
                              Businesswoman                    3.8
Monthly household net income  Less than 600 [euro]             9.5
                              600-1,200 [euro]                21.3
                              1,201-1,800 [euro]              16.4
                              1,801-3,000 [euro]              16.9
                              3,001-5,000 [euro]               6.1
                              More than 5,000 [euro]           0.9

Indicators of Convergent Validity and Internal Consistency

                                  Standardized Coefficients,
Factor (items)                       Interval and p-value

First-order confirmatory
factor model
1. Functional benefit
(CR = 0.79; VE = 0.56)
1.FB1                             0.69 (0.64; 0.73) p = .001
2. FB2                            0.89 (0.85; 0.93) p = .001
3. FB3                            0.64 (0.59; 0.69) p = .001
2. Social benefit
(CR = 0.94; VE = 0.89)
4. SB1                            0.96 (0.94; 0.98) p = .001
5. SB2                            0.93 (0.90; 0.96) p = .002
3. Emotional benefit
(CR = 0.72; VE = 0.56)
6. EB1                            0.87 (0.82; 0.91) p = .002
7.EB2                             0.61 (0.55; 0.66) p = .001
4. Financial functional
sacrifice (CR = 0.73; VE = 0.47)
8. FS1                            0.65 (0.59; 0.70) p = .001
9. FS2                            0.68 (0.63; 0.74) p = .001
10. FS3                           0.73 (0.67; 0.79) p = .001
5. Time-related functional
sacrifice (CR = 0.88; VE = 0.72)
11.TS1                            0.90 (0.87; 0.92) p = .001
12. TS2                           0.89 (0.86; 0.92) p = .001
13. TS3                           0.74 (0.70; 0.78) p = .001
6. Social sacrifice
(CR = 0.78; VE = 0.54)
14. SSI                           0.71 (0.66; 0.76) p = .001
15. SS2                           0.79 (0.75; 0.83) p = .001
16. SS3                           0.70 (0.64; 0.75) p = .001
7. Emotional sacrifice
(CR = 0.80; VE = 0.54)
17. ESI                           0.66 (0.61; 0.71) p = .001
18. ES2                           0.79 (0.73; 0.82) p = .001
Second-order confirmatory
factor model
Benefits smoker women
PV (CR = 0.83; VE = 0.62)
1. Functional benefit             0.67 (0.61; 0.73) p = .001
2. Social benefit                 0.72 (0.66; 0.77) p = .001
3. Emotional benefit              0.92 (0.86; 0.98) p = .001
Sacrifices smoker women
PV (CR = 0.82; VE = 0.54)
4. Financial functional
sacrifice                         0.83 (0.77; 0.88) p = .001
5. Time-related functional
sacrifice                         0.85 (0.80; 0.89) p = .001
6. Social sacrifice               0.65 (0.58; 0.71) p = .001
7. Emotional sacrifice            0.56 (0.49; 0.64) p = .001
Third-order confirmatory
factor model
Smoker women PV
(CR = 0.79; VE = 0.67)
Benefits                          0.59 (0.45; 0.72) p = .001
Sacrifices                        0.99 (0.83; 10.27) p = .001

                                  Individual Reliability (R2),
                                     Confidence Interval
Factor (items)                           and p-value

First-order confirmatory
factor model
1. Functional benefit
(CR = 0.79; VE = 0.56)
1.FB1                             0.48 (0.42; 0.54) p = .001
2. FB2                            0.79 (0.72; 0.86) p = .001
3. FB3                            0.41 (0.35; 0.47) p = .001
2. Social benefit
(CR = 0.94; VE = 0.89)
4. SB1                            0.92 (0.88; 0.96) p = .001
5. SB2                            0.87 (0.82; 0.91) p = .002
3. Emotional benefit
(CR = 0.72; VE = 0.56)
6. EB1                            0.76 (0.68; 0.83) p = .002
7.EB2                             0.37 (0.30; 0.43) p = .001
4. Financial functional
sacrifice (CR = 0.73; VE = 0.47)
8. FS1                            0.42 (0.35; 0.50) p = .001
9. FS2                            0.47 (0.39; 0.54) p = .001
10. FS3                           0.53 (0.45; 0.62) p = .001
5. Time-related functional
sacrifice (CR = 0.88; VE = 0.72)
11.TS1                            0.80 (0.76; 0.84) p = .001
12. TS2                           0.80 (0.75; 0.84) p = .001
13. TS3                           0.55 (0.49; 0.61) p = .001
6. Social sacrifice
(CR = 0.78; VE = 0.54)
14. SSI                           0.50 (0.44; 0.57) p = .001
15. SS2                           0.63 (0.56; 0.70) p = .001
16. SS3                           0.49 (0.41; 0.56) p = .001
7. Emotional sacrifice
(CR = 0.80; VE = 0.54)
17. ESI                           0.43 (0.37; 0.50) p = .001
18. ES2                           0.61 (0.53; 0.67) p = .001
Second-order confirmatory
factor model
Benefits smoker women
PV (CR = 0.83; VE = 0.62)
1. Functional benefit             0.45 (0.37; 0.53) p = .001
2. Social benefit                 0.51 (0.44; 0.59) p = .001
3. Emotional benefit              0.85 (0.74; 0.96) p = .001
Sacrifices smoker women
PV (CR = 0.82; VE = 0.54)
4. Financial functional
sacrifice                         0.69 (0.59; 0.78) p = .001
5. Time-related functional
sacrifice                         0.72 (0.64; 0.80) p = .001
6. Social sacrifice               0.42 (0.33; 0.5l) p = .001
7. Emotional sacrifice            0.32 (0.24; 0.40) p = .001
Third-order confirmatory
factor model
Smoker women PV
(CR = 0.79; VE = 0.67)
Benefits                          0.35 (0.21; 0.52) p = .001
Sacrifices                        0.99 (0.69; 10.61)p = .001

CR, composite reliability; VE, variance extracted.
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Article Details
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Author:Montero-Simo, Maria Jose; Polo-Pena, Ana Isabel; Araque-Padilla, Rafael; Rey-Pino, Juan Miguel
Publication:Journal of Consumer Affairs
Article Type:Report
Geographic Code:4EUSP
Date:Jun 22, 2018
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