Wine Economics and Policy 9(2): 3-21, 2020

Firenze University Press 
www.fupress.com/wep

ISSN 2212-9774 (online) | ISSN 2213-3968 (print) | DOI: 10.36253/web-8189

Wine Economics  
and Policy

Citation: Azzurra Annunziata, Lara 
Agnoli, Riccardo Vecchio, Steve Char-
ters, Angela Mariani (2020) The Influence 
of Alcohol Warning Labels on Consum-
ers’ Choices of Wine and Beer. Wine 
Economics and Policy 9(2): 3-21. doi: 
10.36253/web-8189

Copyright: © 2020 Azzurra Annunziata, 
Lara Agnoli, Riccardo Vecchio, Ste-
ve Charters, Angela Mariani. This is 
an open access, peer-reviewed arti-
cle published by Firenze University 
Press (http://www.fupress.com/wep) 
and distributed under the terms of the 
Creative Commons Attribution License, 
which permits unrestricted use, distri-
bution, and reproduction in any medi-
um, provided the original author and 
source are credited.

Data Availability Statement: All rel-
evant data are within the paper and its 
Supporting Information files.

Competing Interests: The Author(s) 
declare(s) no conflict of interest.

The Influence of Alcohol Warning Labels on 
Consumers’ Choices of Wine and Beer

Azzurra Annunziata1,*, Lara Agnoli2, Riccardo Vecchio3, Steve 
Charters4, Angela Mariani5

1 University of Naples Parthenope, Department of Economics and Legal Studies, Via 
Amm. F. Acton, 38 - 80133 Napoli, Italy, Email: azzurra.annunziata@uniparthenope.it
2 Burgundy School of Business, Université Bourgogne Franche-Comté, Dijon, France, 
Email: lara.agnoli@bsb-education.com
3 University of Naples Federico II, Department of Agricultural Sciences, Napoli, Italy, 
Email: riccardo.vecchio@unina.it
4 Burgundy School of Business - Université Bourgogne Franche-Comté, Dijon, France, 
Email: steve.charters@bsb-education.com
5 University of Naples Parthenope, Department of Economics and Legal Studies, Napoli, 
Italy, Email: mariani@uniparthenope.it
*Corresponding author

Abstract. This study aims to analyse the influence of alternative formats of health 
warnings on French and Italian Millennial consumers’ choices of beer and wine. Two 
Discrete Choice Experiments were built for wine and beer and two Latent Class choice 
models were applied in order to verify the existence of different consumer profiles. 
Results show that young consumers’ choices for wine and beer are influenced by fram-
ing, design and visibility of warnings. In both countries, the acceptance of warnings 
is higher for beer than for wine and in both cases consumers show higher utility for 
a logo on the front label: on the neck with a neutral message in the case of beer; on 
the front, without a message for wine. Latent Class choice models highlight the exist-
ence of different consumers’ groups with different levels of warning influencing their 
choices. In order to apply policies conducting to health benefits, our results suggest the 
need to focus on young individuals to communicate the risks of alcohol abuse through 
targeted messages and, more generally, to make them aware of the potential negative 
effects of excessive consumption of both wine and beer.

Keywords: alcohol warning labels, wine, beer, Discrete Choice Experiment, Latent 
Class.

1. INTRODUCTION

Considering that the harmful use of alcohol is the third leading cause 
of mortality and morbidity of population globally (WHO, 2018), many 
public health and consumer associations are urging the implementation 
of mandatory health warning labels on alcoholic beverages. Several stud-
ies have highlighted that a large share of drinkers worldwide have an inac-



4 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

curate knowledge of the potential risks associated with 
alcohol consumption (Stockwell et al., 2016). The World 
Health Organization suggests that the presence of warn-
ing labels on alcohol containers could be considered an 
important first step in raising awareness and it could 
have a longer-term utility in helping to establish a social 
understanding of the harmful use of alcohol (WHO 
Europe, 2017; Eurocare, 2016). Indeed, labelling infor-
mation is widely recognized as a means to constantly 
deliver a clear message to consumers at the point of pur-
chase, or at the time of use, by promoting awareness, 
comprehension, and subsequent behavioural changes 
in line with the message content (Jarvis and Pettigrew, 
2013).

However, alcohol warning labels (AWL) are cur-
rently used in 31 countries. They are often limited to 
the dangers of drinking when pregnant or drinking 
and driving, but the potential harm of excessive alco-
hol consumption could be extended to include other 
health conditions (WHO, 2010). Although Europe is the 
region with the highest per capita consumption of alco-
holic beverages in the world, warning labels are still not 
required in the majority of Member States, and there 
are significant differences in national legislation among 
the countries that have introduced mandatory warnings 
(WHO Europe, 2017). 

Much research has shown that support for health 
warnings on alcoholic beverages among consumers is 
high (Annunziata et al., 2019; Annunziata et al., 2016; 
Blackwell et al., 2018; Thomson et al., 2012; Greenfield et 
al., 2007), while other scholars have questioned the effi-
cacy of alcohol warning labels in influencing drinking 
behaviour and concluded that evidence of their influence 
on changing behaviour is limited (e.g. Brennan et al., 
2016; Coomber et al., 2015; 2018). 

Instead of analysing the effectiveness of AWL in 
reducing abusive consumption behaviours, this paper 
aims to analyse the influence of alternative formats of 
AWL on Millennial consumers’ choices of alcoholic bev-
erages (wine and beer) by extending the results of a pre-
vious research carried out in Italy and France (Annun-
ziata et al., 2019).

Specifically, this paper aims to verify 1) the influence 
of alternative formats of AWL on Millennial consum-
ers stated choices of wine and beer; 2) the existence of 
different segments of consumers with different level of 
influence of AWL when choosing wine and beer. 

To this purpose a Discrete Choice Experiment (DCE) 
and Latent Class choice models (LCM) were realized in 
Italy and France. The choice to analyse these two coun-
tries lies in their different regulations about AWL. Start-
ing from 2007, mandatory warnings are imposed in 

France to inform consumers about the dangers associated 
with the consumption of alcoholic beverages during preg-
nancy, with a statement or a specific pictogram. In Italy a 
voluntary and unregulated approach exists, with the mar-
ket offering bottles of alcoholic beverages with and with-
out warnings and with a heterogeneity of warnings. 

The decision to analyse Millennial generation con-
sumers stems from the awareness that they are recognised 
as a particularly risky population segment, especially 
considering that heavy episodic drinking is constantly 
increasing among these individuals worldwide (Calafat et 
al., 2011). Furthermore, this generation represent a seg-
ment of growing interest for marketing researchers both 
in the wine and beer markets (Agnoli et al., 2011; de Mag-
istris et al. 2011; Rivaroli et al. 2019). Compared with pre-
vious research, the originality of the current paper lies in 
the application of the choice experiment to two alcoholic 
beverages and the comparison of the outcomes.

Wine and beer were chosen as the objects of inves-
tigation of this study as: i) they are the most consumed 
alcoholic beverages in France and Italy (Table 1); ii) they 
are the most frequently consumed alcoholic beverages by 
Millennials in the two analysed countries (Euromonitor 
International, 2020; Agnoli et al., 2011); iii) wine is asso-
ciated to tradition in both countries, while beer is more 
linked to Northern European consumption patterns 
(Agnoli et al., 2018), and this can give rise to differences 
in the acceptability of AWLs in these two alcoholic bev-
erages, with relevant implications.

The paper is organised as follows: a brief overview 
of existing literature is presented in the first section; 
subsequently, a detailed description of the methodology 
and stimuli applied in the DCE is provided; then results 
from the DCE and Latent Class Analysis are presented 
and a discussion of the core implications is offered.

2. LITERATURE BACKGROUND 

The current study builds on the growing research 
prompted by insights of behavioural economics and 

Table 1. Consumption of alcoholic beverages in France and Italy, 
million litres, 2010-2019.

 
 

France Italy

2010 2019 2010 2019

Wine 2,466 2,157 2,550 2,395
Beer 1,909 2,151 1,634 1,706
Spirits 395 367 158 138

Source: Euromonitor International (2020).



5The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

the dual process theory (see, among others, Camerer 
and Loewenstein, 2004; Evans, 2008; Kahneman, 2011). 
Indeed, disentangling the relationship between con-
scious and unconscious elements in behaviour and 
decision-making, scholars have proved that consum-
ers’ choices are influenced by several contextual fac-
tors as social and environmental elements as well as 
cognitive shortcuts, emotions, and habits. Therefore, 
researchers have proposed to modify the choice archi-
tecture to alter individuals’ behaviour for the good, i.e.: 
nudging people to do the right thing (Thaler and Sun-
stein, 2008). In particular, nudges are “any aspects of 
the choice architecture that alters people’s behaviour in 
a predictable way without forbidding any options or sig-
nificantly changing their economic incentives” (Thaler 
and Sunstein, 2008, p. 6). Based on this premises several 
policy makers have favourably embraced the use of gen-
tle prompts and suggestions to increase healthier behav-
iours; also relying on high citizen support compared to 
other interventions - as taxes (Reisch et al., 2017). Recent 
evidences provided by cigarettes warnings suggests 
that labels that present health-aligned information may 
nudge behaviour that are in line with individuals’ health 
goals, reducing consumption (e.g. Noar et al., 2016). 
Questions remains, however, around the possibility that 
similar label-based nudges can be effective also on alco-
holic beverages.

Several studies suggest that AWLs may improve 
knowledge and attitudes regarding the harmful conse-
quences of alcohol consumption among adults (Annun-
ziata et al., 2017; Wigg and Stafford, 2016; Vallance et al., 
2017), while little impact on changing drinking behav-
iour was found (Glock et al., 2013; Brown et al., 2016). 

According to Al-Hamdani (2015) and Coomber 
et al. (2015), the limited impact of AWLs in changing 
behaviour is connected to the weak content of warnings 
and their poor visibility. In this regard, Agostinelli and 
Grube (2002) suggest that in order to improve the poten-
tial of warning labels in influencing behaviour, the key 
elements are label design and how well the information 
and messages on labels are targeted at their intended 
audience. 

Indeed, several studies suggest that warning mes-
sage framing, label design, format and visibility are cru-
cial elements in determining health warning effective-
ness and encouraging healthier behaviours (Blackwell 
et al., 2018; Al-Hamdani and Smith, 2017a; Knai et al., 
2015; Krischler and Glock, 2015; Jarvis and Pettigrew, 
2013). 

Many studies found that pictorial health warnings 
are more effective than text-based warnings and enhance 
warning recognition (Hassan and Shiu, 2018; Kersbergen 

and Field, 2017; Wigg and Stafford, 2016). Al-Hamdani 
and Smith (2017a) suggest that combined text and image 
warnings have a stronger effect on alcohol consum-
ers than the use of text only. Considering warning vis-
ibility, Kersbergen and Field (2017) reveal that increas-
ing the visual salience by using graphic warnings as 
well as front-of-pack labelling might be more effective 
in attracting and maintaining consumers’ attention. Al-
Hamdani and Smith (2017b) found that plain packaging 
warning increases the likelihood for correct recognition.

In relation to the message framing, specific rather 
than general health warnings were rated as more effec-
tive, and led to greater risk perceptions (Miller et al., 
2016; Pettigrew et al., 2014; Creyer et al., 2002). Jarvis 
and Pettigrew (2013) found that negatively framed mes-
sages had the highest utility whereas a positive message 
(about drinking and driving) could generate a boomer-
ang effect. In addition, Blackwell and colleagues (2018) 
reported that participants of their study are more moti-
vated to drink less after viewing negatively framed mes-
sages. Pettigrew et al. (2014) compared warnings with 
the wording ‘increases risk’ versus ‘can cause’ and found 
that the ‘increases risk ’ wording was more convincing 
and more believable than the ‘can cause’ wording. Fur-
thermore, Pettigrew et al. (2014) have examined the use 
of quantitative information in alcohol warnings and 
showed that quantitative messages performed poorly 
in terms of believability. Krischler and Glock (2015) 
showed that warning statements formulated as questions 
are more effective, especially among young adults, while 
Branco and Kaskutas (2001) found that warning labels 
that employ scare tactics can be perceived as overstating 
the risks and are not believable. 

Annunziata et al. (2019) found that the level of vis-
ibility of the warnings currently carried by wine bot-
tles in Italy and France is low and that consumers tend 
to prefer the “no warning option” attaching more utility 
to neutrally framed messages, even if some differences 
between Italian and French consumers exist.

Other researches highlighted that the extent to 
which the warning is read and elaborated by individu-
als is linked to the personal relevance of the message 
and individual motivation to actively respond, suggest-
ing that tailored and targeted warning labels may be bet-
ter received compared to generic ones (Hassan and Shiu 
2018; Wogalter, 2006; Argo and Main, 2004). 

In this regards other evidences revealed that tar-
geted messages should be particularly useful among 
populations where there is great heterogeneity. The use 
of customised messages seems to be more effective than 
generic ones, especially considering individual alcohol-
related beliefs, gender or age (Robertson et al. 2017; 



6 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

Miller et al. 2016; Jarvis and Pettigrew, 2013; Creyer 
et al., 2002; Wright et al., 2008). With reference to the 
latter, Argo and Main (2004) argue that age correlates 
negatively with warning perception, in particular young 
adults tend to perceive themselves as invulnerable to the 
negative consequences of risky behaviours. Jarvis and 
Pettigrew (2013) found that the messages with the great-
est utility differed across gender. Furthermore, concern-
ing the drinking behaviour, Cryer et al. (2002) reported 
that drinking frequencies (i.e. binge or non-binge drink-
ing) strongly affect the perception of different warnings 
on alcoholic beverages among students. 

Jarvis and Pettigrew (2013) found that for those who 
report higher consumption of alcohol, negative health 
messages had the highest utility. Further, Miller and col-
leagues (2016) found that high-risk drinkers perceived 
the warning labels to be less effective in altering drink-
ing behaviours than light-to-moderate drinkers. 

Robertson and colleagues (2017) found that heavy 
drinkers are more sensitive to alcohol warnings relat-
ed to concerns for self (e.g. liver damage) while lighter 
drinkers to warning related to potential risk for others 
(as violence). 

Previous research has also found that the effective-
ness of alcohol warning messages is influenced by dif-
ferent type of drink (e.g. wine, beer, vodka) (Thomson 
et al., 2012). In particular, messages matched with the 
type of drink were more relevant and acceptable to con-
sumers, suggesting the need to further assess the inter-
action between the type of drink and the warning mes-
sage but also to be cautious in generalising their results 
to other types of alcoholic beverages (Hassan and Shiu, 
2018;Wright et al., 2008). 

3. MATERIAL AND METHOD

3.1 Questionnaire and measurements

A consumer survey was conducted in order to reach 
the research objectives. Beyond the collecting data on 
socio-demographic characteristics, the questionnaire 
included information about alcohol consumption habits, 
selected from the Alcohol Usage Questionnaire (AUQ) 
developed by Mehrebian and Russell (1978) (Table 2). 
After assessing the level of attention paid to health warn-
ings, the questionnaire asked about what effects health 
warnings have on respondents and their attitude towards 
alcohol, drawing from the readiness to change question-
naire developed by Kersbergen and Field (2017). Respond-
ents were then asked to express their level of concern for 
some short and long-term side effects from alcohol con-
sumption (Vecchio et al., 2017; Coomber et al., 2017).

3.2 Discrete Choice Experiments design

Respondents were also subject to two Discrete 
Choice Experiments (DCEs) (Louviere and Woodworth, 
1983), depicting the hypothetical choice of a bottle of 
wine and beer. In order to avoid to sensitise respond-
ents to warning contents, the DCEs were introduced to 
respondents before the section asking for the effects of 
health warnings. 

The two DCEs include the same alternatives and 
attributes, selected considering the literature on health 
warnings and designed to test if consumer preference for 
wine and beer are influenced by the framing, design and 
visibility of different warnings (Table 3). Two non-man-
datory warnings about a short- and a long-term effect 
of alcohol on health have been selected as alternatives 
of the designs, plus a no-warning alternative. The choice 
to select the risk of brain damage as the long-term effect 
and the risk from drinking and driving as the short-term 
effect was suggested by the literature (Jarvis and Petti-
grew, 2013; Kaskutas and Greenfield, 1992; Coomber et 
al., 2017). These warnings have been graphically depicted 
on the label, and they could assume big size or small size 
and be placed on the neck or on the front label for beer, 
and on the front or the back label for wine, as in previous 
research (Al-Hamdani, and Smith, 2017b; Al-Hamdani, 
and Smith, 2015; Wigg and Stafford, 2016). Alcohol by 
volume is another attribute emerged as important in the 
literature (Jarvis and Pettigrew, 2013) and low, medium 
and high levels have been selected for beer according to 
general standards and for wine according to the specific 
grape variety involved in the hypothetical choice, Caber-
net Sauvignon. The choice of this grape variety is given 
by the fact that it is the most widespread grape variety in 
Europe (Eurostat, 2017).

A textual message for the two selected warnings has 
also been included as an attribute of the DCEs, neutrally 
or negatively framed as in previous studies on the sub-
ject (Jarvis and Pettigrew, 2013; Krischler and Glock, 
2015; Miller et al., 2016) or not included in the label 
(Table 4).

These alternatives, attributes and levels have been 
statistically combined in order to compose the experi-
ment designs for this study. A full factorial design 
including each possible combination of the elements 
composing the design would have given rise to an enor-
mous number of hypothetical choice situations. In order 
to show respondents with only a subset of possible 
choices, efficient fractional factorial designs were built 
with the software package Ngene (Rose and Bliemer, 
2009; ChoiceMetrics, 2018). This class of designs aims to 
give rise to results generating parameter estimates with 



7The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

Table 2. Collected data and measurement.

Topic Variable Measure References

Socio-demographics Gender 1 if male, 0 if female  
Age

Years of education
Continuous (from 18 to 40)

Total years of education
Alcohol consumption 
habits

Consumption frequency from 1 (never) to 5 (every day)
Alcohol Usage Questionnaire (AUQ) 

(Mehrebian and Russell, 1978)
Inebriation frequency in the last six 

months
from 1 (never) to 5 (more than 5 

times)

Alcoholic beverages consumption 
in %

% of beer consumption 

% of still wine consumption 
% of sparkling wine consumption 

% of spirits consumption 
% of ready to drink consumption

Attention towards labels 
and AW Front label

Back label
Health warning 

Scale from 1 to 5

Degree of attention towards 
information currently reported on 

front and back label
(Mueller et al.,

2010; Annunziata et al., 2016)

Discrete choice experiments for wine and beer

Effects of health warnings Decreased consumption
Multiple choice question, single 

answer
1 if is the case, 0 otherwise

 

Thought about decreasing 
consumption

Discussed with friends on risks
Thought about the risks

No effect

Attitudes towards alcohol Do not think to drink in excess Likert scale from 1 to 5
Readiness to change questionnaire 

(Kersbergen and Field 2017)
Like to drink and sometimes drink 

too much 
Trying to drink less  

Think that friends drink too much 
Concerns about the 
consequences of alcohol 
abuse 

Lack of coordination and slower 
reflexes 

Likert scale from 1 to 5
Concerns for long and short-term 

effects of alcohol intake (Vecchio et 
al., 2017; Coomber et al., 2017)

Reduced concentration 
Motor vehicle, bicycle and pedestrian 

accidents 
Injuries associated with falls, 

accidents, violence 
Alcohol poisoning  

Harm to unborn babies 
Obesity 

Brain damage 
Liver/Stomach problems 
Heart and blood disease



8 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

as small as possible standard errors. In order to reach 
this goal, they need to be fuelled by prior information on 
these parameters. ‘Priors’ to build two efficient designs 
were drawn from a pilot study involving 50 consumers 
from France and Italy and analysing their hypothetical 
choices of wine and beer. The efficient designs adopted 
in this study drove the allocation of alternatives, attrib-
utes and levels in the hypothetical choice scenarios of 
respondents and they were selected because they mini-

mised the expected D-errors1 (Ferrini and Scarpa, 2007; 
Scarpa and Rose, 2008; Sándor and Wedel, 2001). The 
final designs included 12 choice scenarios composed of 
three bottles each. In order to rationalise the response 
time to the questionnaire, three blocks of four choice 
scenarios were created adopting the blocking procedure. 
In this way, each respondent faced the choice of the pre-
ferred bottle of beer among four groups of three bottles 
and the choice of the preferred bottle of wine among 
four groups of three bottles each.

The choice scenarios were graphically represented to 
facilitate choice, adopting fictitious brands to avoid the 
conflicting impacts of knowledge and perceptions over 
real brands (Delmas and Lessem, 2017). For the beer 
choice task we applied only images of the front label 
(Fig. 1a), while for the wine choice task we used both 

1 The D-error is an aggregate measure drawn from the asymptot-
ic variance-covariance (AVC) matrix of the variables in the design. It 
is estimated according to the following equation: D-error = [Det(Ω(β, 
xtj)]1/K]where Ω is the AVC matrix of the variables in the design (xtj), 
β is the vector of estimated coefficients, j is the alternative, t is the 
choice task and K is the number of estimated coefficients.

Table 3. Alternatives, attributes and levels of the DCEs.

Design components 
Levels

Beer Wine

Alternatives Logo

1. Long-term 
health warning 
(Risk of brain 

damage) 
2. Short-term 

health warning 
(Risk from 

drinking and 
driving) 

    3. No logo
Attributes I. Logo position 1. Neck 1. Back label

2. Bottle 2. Front label
II. Logo size 1. Big

2. Small
III. Alcohol by 

Volume
1. Low (3%vol.) 1. Low (11.5%vol.)

2. Medium 
(5%vol.)

2. Medium 
(12.5%vol.)

  3. High (7%vol.)
3. High 

(13.5%vol.)

IV. Message
1. Neutrally 

framed
2. Negatively 

framed
3. No warning 

message

Table 4. Frame of the text messages associated with the warnings.

Message Risk of brain damage
Risk from drinking 

and driving

Neutrally framed
Keep your brain 

healthy. Lower your 
alcohol intake

To be safe, do not 
drink and drive

Negatively framed
Every drink of alcohol 

harms your brain
Drunk driving kills

Figure 1. An example of choice task for wine and beer.



9The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

front and back labels (Fig.1b). In line with the habits of 
Millennials, the hypothesised consumption situation is a 
dinner with friends (Mueller and Charters, 2011). 

3.3 Modelling approach 

Data collected through the discrete choice experi-
ment where analysed applying Multinomial Logit (MNL) 
models (McFadden, 1974) and Latent Class (LC) Choice 
Models (Greene and Hensher, 2003). MNL models 
assume that all respondents behave in the same way and 
present the same preferences, with a choice probability 
described as follows:

 (1)

where n is the individual, who assesses for t times j 
alternatives and chooses alternative i. Following the ran-
dom utility theory (Thurstore, 1927) Vnit is the part of 
the utility observed by the researcher, as discrete choice 
models assume that utility is a stochastic function, com-
posed of a deterministic part, the function of the attrib-
utes of the good, and a stochastic part. 

As reported in equation (1), the deterministic part of 
the utility can be written as:

Vnit=β'xnit (2)

where β is a vector of estimated coefficients and xnit are 
the attributes of alternative i of the t choice which com-
pose the utility of individual n (Train, 2009). 

LC models create C latent classes grouping respond-
ents with similar underlying preferences. Respondents 
are therefore assigned to a class up to a probability and 
given membership of a given class c, the probability of 
respondent n’s sequence of choices yn over the T choice 
occasions, is:

 
where yn=(in1;in2,…,inTn) (3)

MNL models are applied in this study to analyse the 
influence of alternative formats of AWL on Millennial 
consumers stated choices of wine and beer. LC models 
were applied to identify different segments of consumers 
with different level of influence of AWL when choosing 
wine and beer. 

Following the theory of Lancaster (1966), according 
to which the utility of a good is given by the attributes 

composing the good itself, in our models for the choice 
of wine and beer the utility of consumer n belonging to 
the latent class c can be explained as follows:

Unjt|c=β1|clogonit+β2|csizenit+β3|cpositionnit+β4|c 
messagenit +β5|cABVnit

 (4)

where logo is a nominal variable composed by three lev-
els/logos (risk of brain damage, from drinking and driv-
ing and no logo); size is a binary variable assuming value 
1 if the logo is big, 0 if it is small; position is a binary 
variable assuming value 1 if the logo is on the front label 
and 0 if it is on the back label/neck of the bottle; mes-
sage is a binary variable assuming value 1 if the warning 
message is neutrally framed on the label, 0 if it is nega-
tively framed and ABV is a continuous variable repre-
senting the three levels of alcohol by volume (low, medi-
um and high) of the experimental design. 

The emerged latent classes were characterised intro-
ducing socio-demographic and behavioural character-
istics of respondents as covariates in the model. Data 
analysis was conducted using the software LatentGOLD 
(Vermunt and Magidson, 2013).

3.4 Data Collection

In line with other studies analysing wine and beer 
consumption and involving young respondents, the 
questionnaire was submitted online to a convenience 
sample of Millennials from France and Italy in 2018 
(Vecchio, 2013; Szolnoki and Hoffmann, 2013). Respond-
ents were recruited through social networks, blogs, 
forum and the word of mouth. 

There is no common agreement among scholars 
defining the boundaries of Millennial generation. Some 
Authors consider this generation as born between 1981 
and 1999 (Brosdahl and Carpenter, 2011; Bolton et al., 
2013), others between 1980 and 2000 (Macky et al., 
2008) or between 1978 and 2000 (Lancaster and Still-
man, 2002; Thach and Olsen, 2006). In the present study 
individuals were screened to be born between 1978 and 
2000 and to be of the legal age limit to drink alcoholic 
beverages at the time of the survey administration.

The final sample is composed of 659 individuals, 394 
from Italy and 265 from France (Table 5). The sample is 
well balanced between male and female and is mostly 
composed of the younger segment of Generation Y. Half 
of the Italian part of the sample comes from the South, 
while half of the French sample comes from the Cen-
tre of France. As the French and the Italian education 
systems are different, a continuous variable was drawn 
explaining the years of education for each respondent 



10 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

and highlighting a similar education level for the two 
segments.

4. RESULTS 

4.1 Preferences for warning labels on wine and beer

Two MNL models were applied to understand dif-
ferent influences of AWL in the choice of wine and beer 
by Millennial respondents. Figure 2 shows that the most 
important elements driving consumer’s choices for beer 
are a warning logo, alcohol by volume and warning 
message explaining the consequences of alcohol intake. 
Concerning wine, the presence and typology of warning 
logo is still the most important element, with a higher 
degree of importance than beer, and it is followed by the 
position of the logo and by the warning message. These 
results are in line with the study by Al-Hamdani (2014), 
highlighting the strong inf luence of pictorial health 
warnings on consumers. 

For beer, positive utility is associated with the logo 
warning about the risks of drinking and driving, which is 
actually common on the bottles of beer both in Italy and 
France, depicting a focus on the short-term side effect of 
alcohol intake. A lower but still positive utility is regis-
tered if no logo is depicted on the label. Concerning wine, 
people associate positive utility to a bottle with no logo, 
and the logo about the consequences of alcohol on brain 
decreases consumer utility, as it does with beer (Table 6). 

Unlike other studies (Pham et al., 2018; Al-Hamdani 
and Smith, 2017b), a clear preference does not emerge in 

consideration of the logo size for both alcoholic bever-
ages. Concerning the position, consumers prefer a logo 
on the neck of the bottle for beer and on the front label 
for wine. 

When it comes to choosing a bottle of beer, people 
prefer to be informed about the possible negative con-
sequences of consumption, but with a neutrally framed 
message. When it comes to choosing wine, they prefer 
no warning message. In both cases a negatively framed 
message decreases consumers’ utility, in line with stud-
ies by Al-Hamdani and Smith (2017a, 2017b). 

The alcohol by volume indication results in a sig-
nificant impact on consumers only for beer, and with a 
positive sign.

Two Latent Class choice models were run to analyse 
the hypothetical choices for both the alcoholic beverages 
and better explain these differences and understand con-
sumers’ preferences. The identification of latent classes 
aims to highlight differences in preferences and influ-
ences of health warning labels among young consum-
ers. Despite being considered as a unique cohort, this 
generation is composed by a heterogeneous group of 
consumers, also in the light of the large age group that 
characterise it (Bucic et al., 2012; Agnoli et al., 2018). It 
becomes therefore important to identify these heteroge-
neities and characterise them according to their drink-
ing behaviours and perceptions towards AWLs.

4.2 Latent class choice model for beer

The five-class solution was selected as the optimal to 
explain consumers’ choices of beer, in line with the data 
fit criteria (Ferrini and Scarpa, 2007) (Table 7). After 
estimating the latent class model, socio-demographics 
and behavioural characteristics collected through the 
survey questionnaire have been included in the estima-

Table 5. Socio-demographic characteristics of the sample.

 
 

Sample (N=659) Italy (n=394) France (n=265)

n % n % n %

Gender
  Male 286 43.4 168 42.6 118 44.5
  Female 369 56.0 226 57.4 143 54.0

Age class
  18-24 years old 397 60.2 195 49.5 202 76.2
  25-31 years old 197 29.9 141 35.8 56 21.1
  32-40 years old 65 9.9 58 14.7 7 2.6

Area of residence
  North 208 31.6 154 39.1 54 20.4
  Centre 152 23.1 20 5.1 132 49.8
  South 245 37.2 219 55.6 26 9.8

Mean S.D. Mean S.D. Mean S.D.
Years of education 14.8 1.6 14.3 1.8 15.6 1.0

Figure 2. Attribute importance for beverages, full sample.



11The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

tion as covariates (Table 8). This allowed the study to 
characterise classes also in the light of their alcohol con-
sumption habits, effects of health warnings, attitudes 
towards alcohol and concerns about the consequences of 
alcohol abuse. This last aspect was included in the model 
as a single variable composed by the sum of the different 
items depicting individual’s concerns about the conse-
quences of alcohol abuse.

Latent class 1 (LC1) is composed of 28% of respond-
ents and bases its choice on alcohol content, whose 
importance accounts for one third of the total util-
ity. In particular, the utility of this LC increases with the 
increase of the alcohol by volume. The warning logo is the 

second most important attribute driving choice and con-
sumers belonging to this class prefer a bottle of beer with 
no logo. Anyway, a bottle with a logo informing about the 
negative consequences of drinking and driving is posi-
tively perceived, differently from a logo informing about 
the negative effects of alcohol on brain. When a logo is 
present, they prefer it small and on the neck of the bot-
tle. They prefer a bottle of beer with no warning message 
and negatively framed messages impact negatively on util-
ity. This class particularly includes French male respond-
ents, who do not consume alcoholic beverages very fre-
quently, who declare that warnings about the negative 
consequences of alcohol on health have no impact on 

Table 6. Multinomial Logit estimation for choice of wine and beer, full sample.

 
 

Beer Wine

Coeff. S.E. Wald p-value Coeff. S.E. Wald p-value

Logo                    
   Brain damage -0.544 *** 0.036 246.598 0.000 -0.693 *** 0.039 339.748 0.000
   No driving 0.318 *** 0.030 0.050 0.033
   No logo 0.226 *** 0.037 0.644 *** 0.041

Logo size
   Big vs Small -0.054 0.054 0.996 0.320 -0.094 0.061 2.339 0.130

Message
   Negatively framed -0.163 *** 0.045 15.728 0.000 -0.141 *** 0.046 10.376 0.006
   Neutrally framed 0.144 *** 0.043 0.031 0.048
   No message 0.019 0.041 0.109 *** 0.046

Logo position
   Label vs Neck -0.159 *** 0.054 8.622 0.003
   Front vs Back label 0.383 *** 0.061 39.050 0.000

Alcohol by volume 0.085 *** 0.013 45.827 0.000 -0.011 0.025 0.200 0.650

Goodness of fit                    
   Observations 2636 2636
   Cases 659 659
   Log likelihood -2,689.476 -2,611.704 
   R² 0.073         0.1019        

* p<.10; **p<.05; ***p<.01.

Table 7. Data fit criteria for alternative Latent Class Models for beer choice.

  Log Likelihood BIC AIC CAIC N. Parameters R²

Multinomial Logit -2689.4759 5424.387 5392.952 5431.387 7 0.073
2-Class -2380.1775 4857.716 4790.355 4872.716 15 0.367
3-Class -2311.849 4772.985 4669.698 4795.985 23 0.445
4-Class -2266.5442 4734.301 4595.088 4765.301 31 0.517
5-Class -2227.7592 4708.657 4533.518 4747.657 39 0.604
6-Class -2206.0983 4717.261 4506.197 4764.261 47 0.642



12 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

Ta
bl

e 
8.

 E
st

im
at

es
 o

f L
at

en
t C

la
ss

 c
ho

ic
e 

m
od

el
 fo

r 
be

er
 a

nd
 c

la
ss

 c
ha

ra
ct

er
is

at
io

n 
(n

=6
59

).

La
te

nt
 c

la
ss

LC
1

LC
2

LC
3

LC
4

LC
5

La
te

nt
 c

la
ss

 s
iz

e
28

%
24

%
22

%
19

%
7%

R
²

38
%

7%
8%

14
%

68
%

 
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
Lo

go
27

%
51

%
51

%
39

%
2%

  B
ra

in
 d

am
ag

e
-0

.9
19

**
*

0.
12

4
-1

.0
72

**
*

0.
32

3
0.

64
0

**
*

0.
13

8
-3

.9
80

**
*

1.
34

6
-0

.1
76

0.
25

7
  N

o 
dr

iv
in

g
0.

26
8

**
*

0.
11

1
1.

54
4

**
*

0.
16

5
0.

49
5

**
*

0.
11

7
-1

.7
79

1.
19

7
0.

14
9

0.
22

8
  N

o 
lo

go
0.

65
1

**
*

0.
11

9
-0

.4
71

**
0.

24
0

-1
.1

35
**

*
0.

16
9

5.
75

9
**

*
2.

29
9

0.
02

7
0.

32
6

Lo
go

 s
iz

e
10

%
11

%
1%

9%
14

%
  B

ig
 v

s 
Sm

al
l

-0
.6

20
**

*
0.

18
7

0.
57

8
**

0.
27

2
-0

.0
35

0.
11

6
2.

31
4

1.
67

7
2.

17
1

1.
65

2
Lo

go
 p

os
iti

on
6%

10
%

15
%

12
%

13
%

  L
ab

el
 v

s 
N

ec
k

-0
.3

72
**

0.
18

6
0.

50
2

**
0.

29
6

-0
.5

28
**

*
0.

13
9

-3
.0

65
*

1.
71

9
-2

.0
72

1.
65

5
M

es
sa

ge
24

%
19

%
20

%
24

%
9%

  N
eg

at
iv

el
y 

fr
am

ed
-0

.7
93

**
*

0.
16

9
0.

42
2

*
0.

25
4

-0
.0

47
0.

12
5

0.
67

8
1.

76
3

-0
.9

33
**

*
0.

35
5

  N
eu

tr
al

ly
 fr

am
ed

0.
16

6
0.

12
4

0.
12

6
0.

16
6

0.
37

9
**

*
0.

12
2

-3
.3

23
3.

42
3

0.
43

1
0.

33
0

  N
o 

m
es

sa
ge

0.
62

8
**

*
0.

13
5

-0
.5

47
0.

19
6

-0
.3

31
**

*
0.

11
1

2.
64

5
1.

84
5

0.
50

2
0.

34
3

A
lc

oh
ol

 b
y 

vo
lu

m
e

33
%

0.
48

4
**

*
0.

05
6

9%
0.

11
8

**
0.

05
7

12
%

0.
10

8
*

0.
05

6
15

%
-0

.9
50

 
0.

74
6

62
%

-2
.4

23
*

1.
44

2
So

ci
o-

de
m

og
ra

ph
ic

s
  I

ta
lia

n 
-0

.8
16

**
*

0.
19

0
0.

27
1

0.
19

9
0.

83
6

**
*

0.
25

6
-0

.5
34

**
*

0.
18

6
0.

24
4

0.
29

5
  M

al
e

0.
74

2
**

*
0.

17
9

-0
.1

22
0.

19
0

-0
.1

75
0.

21
5

0.
06

8
0.

18
3

-0
.5

14
*

0.
30

2
  A

ge
-0

.0
31

0.
02

3
0.

01
2

0.
02

2
0.

05
0

**
*

0.
02

2
-0

.0
06

0.
02

2
-0

.0
26

0.
03

4
A

lc
oh

ol
 c

on
su

m
pt

io
n 

ha
bi

ts
  C

on
su

m
pt

io
n 

fr
eq

ue
nc

y
-0

.2
68

**
*

0.
12

9
0.

35
1

**
*

0.
13

3
0.

22
5

*
0.

11
7

-0
.1

64
0.

11
4

-0
.1

44
0.

19
6

  D
ru

nk
 fr

eq
ue

nc
y 

in
 th

e 
la

st
 6

 m
on

th
s

 
-0

.1
28

0.
08

1
0.

55
5

**
*

0.
08

9
-0

.0
90

0.
07

8
0.

20
1

**
*

0.
07

3
-0

.5
38

**
*

0.
16

8
  B

ee
r 

co
ns

um
pt

io
n 

vs
 o

th
er

 a
lc

oh
ol

ic
s

-0
.0

04
0.

00
5

0.
01

4
**

*
0.

00
6

0.
00

4
0.

00
5

-0
.0

04
0.

00
4

-0
.0

10
0.

00
7

Eff
ec

ts
 o

f h
ea

lth
 w

ar
ni

ng
s 

  D
is

cu
ss

ed
 w

ith
 fr

ie
nd

s 
on

 r
is

ks
-0

.0
82

0.
42

9
0.

08
7

0.
38

7
-0

.2
10

0.
42

1
0.

82
7

**
0.

39
8

-0
.6

22
0.

78
8

  D
ec

re
as

ed
 c

on
su

m
pt

io
n

-0
.6

90
*

0.
39

7
-0

.0
59

0.
34

1
0.

53
4

*
0.

29
2

-0
.5

82
0.

45
5

0.
79

7
*

0.
40

9
  N

o 
eff

ec
t

0.
92

1
**

*
0.

17
0

-0
.1

32
0.

20
2

0.
31

6
*

0.
18

0
-0

.7
33

**
*

0.
30

8
-0

.3
72

0.
33

4
  Th

ou
gh

t a
bo

ut
 th

e 
ri

sk
s

-0
.2

34
0.

23
0

0.
32

0
*

0.
19

2
-0

.4
72

**
0.

24
0

0.
32

5
0.

21
5

0.
06

1
0.

32
5

  Th
ou

gh
t a

bo
ut

 d
ec

re
as

in
g 

co
ns

um
pt

io
n

0.
08

5
0.

31
8

-0
.2

16
0.

33
5

-0
.1

68
0.

33
3

0.
16

3
0.

35
3

0.
13

7
0.

46
9

A
tt

itu
de

s 
to

w
ar

ds
 a

lc
oh

ol
  D

o 
no

t t
hi

nk
 to

 d
ri

nk
 in

 e
xc

es
s 

-0
.2

57
**

*
0.

08
2

-0
.1

48
0.

09
3

-0
.1

15
0.

08
4

-0
.0

08
0.

08
4

0.
52

7
**

*
0.

16
7

  L
ik

e 
to

 d
ri

nk
 a

nd
 s

om
et

im
es

 d
ri

nk
 to

o 
m

uc
h 

0.
37

3
**

*
0.

08
1

-0
.3

18
**

*
0.

09
7

-0
.0

57
0.

08
7

0.
13

8
*

0.
07

8
-0

.1
37

0.
12

9
  T

ry
in

g 
to

 d
ri

nk
 le

ss
  

-0
.0

70
0.

08
0

-0
.0

91
0.

08
8

-0
.0

70
0.

08
1

-0
.1

59
*

0.
08

2
0.

39
0

**
*

0.
10

2
  Th

in
k 

th
at

 fr
ie

nd
s 

dr
in

k 
to

o 
m

uc
h 

-0
.0

87
0.

08
2

0.
00

5
0.

08
7

0.
01

4
0.

07
9

0.
05

2
0.

08
0

0.
01

6
0.

11
9

C
on

ce
rn

 a
bo

ut
 th

e 
co

ns
eq

ue
nc

es
 o

f a
lc

oh
ol

 a
bu

se
a  

 
-0

.0
30

**
*

0.
01

1
 

0.
04

3
**

*
0.

01
3

 
0.

00
0

 
0.

01
0

 
-0

.0
14

 
0.

01
0

 
0.

00
1

 
0.

01
8

N
ot

e:
 L

C
=L

at
en

t C
la

ss
; A

I=
A

tt
ri

bu
te

 I
m

po
rt

an
ce

; S
E=

st
an

da
rd

 e
rr

or
; *

 p
<.

10
; *

*p
<.

05
; *

**
p<

.0
1;

 a
 th

is
 v

ar
ia

bl
e 

is
 g

iv
en

 b
y 

th
e 

su
m

 o
f t

he
 it

em
s 

co
m

po
si

ng
 th

e 
to

pi
c.

 



13The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

their behaviour as they are not concerned about the con-
sequences. Despite not consuming alcoholic beverages fre-
quently, they admit to drinking too much sometimes.

LC2’s utility is strongly driven by the warning logo. 
They prefer the warning logo related to risks of drink-
ing and driving in big size on the front label of a bot-
tle of beer. However, their utility is also positively driven 
by the alcohol content of a beer.  No clear socio-demo-
graphic characterisation emerges for this class. They 
consume alcoholic beverages frequently, and beer is their 
favourite drink. In the last six months they have fre-
quently felt drunk, but they do not think that they drink 
too much. They are concerned about the negative effects 
of alcohol abuse on health.

LC3, comprising 22% of respondents, is also strong-
ly driven by the warning logo when choosing a bottle 
of beer and its utility is higher when there is a warning 
logo on the label. Respondents in this class prefer the 
warning about the negative effects of alcohol on brain 
and in a second instance on the negative consequences 
of drinking and driving.  Their utility is positively influ-
enced by a logo on the neck label and a neutrally framed 
warning message.  This class is more likely to be com-
posed of Italian respondents and respondents belonging 
to the higher age segment of the generation. This class 
particularly includes individuals that do not think about 
the risks when faced with a health warning. 

Differently from LC2 and LC3, the utility of indi-
viduals associated to LC4 (19% of respondents) decreases 
when any kind of logo is included on the beer label, and 
when a logo is present, it is preferred on the neck label. 
This class more likely includes French people who state 
that they have had frequent episodes of drunkenness in 
the last six months. Warning labels have an effect on the 
behaviour of this class, including discussing with friends 
the risks of alcohol intake. 

LC5 (7% of the sample) is strongly driven by the alco-
hol content and it prefers low-alcohol beers. The warning 
logo has little influence on its choice, and respondents 
from this class do not want to have a warning message 
negatively framed on the label. This class includes more 
women, people who do not tend to be involved in risky 

consumption behaviours and who tend to decrease con-
sumption when they see a health warning label.

4.3 Latent class choice model for wine

A Latent Class analysis was applied also to analyse 
the wine choice of respondents and a four-class solution 
was selected as optimal according to the data fit criteria 
(Table 9).

LC.I (35% of the sample) is strongly driven by the 
logo when choosing wine and in particular any logo 
included on a wine label decreases their utility (Table 
10). The logo about brain damage depresses the utility of 
individuals from this class more than the ‘drinking and 
driving’ one. Their utility is positively correlated with 
the alcohol content of a bottle of wine. French and male 
respondents are more likely to belong to this latent class. 
They do not consume alcoholic beverages frequently but 
when they drink, they tend to drink too much so that 
they feel drunk. This segment more probably includes 
respondents who declare to reduce consumption when 
they see the health warnings, but also some respondents 
for who these warnings have no effect or do not think 
about the risks. They are not concerned about the nega-
tive effects of alcohol on health.

LC.II (33% of the sample) is driven both by the logo 
and the warning message when choosing a bottle of 
wine. Individuals from this class prefer to see no logo, 
but if a logo is present they prefer the ‘no driving’ one 
as the logo on brain damage depresses their utility. They 
prefer a small logo, posted on the front label of the bot-
tle. They prefer to have no warning message accompany-
ing the logo on the label and a negatively framed mes-
sage depresses their utility. The alcohol by volume of a 
bottle positively drives their choice. This class is more 
likely composed of female from the younger segment 
of the generation, who frequently consume alcoholic 
beverages even if they do not think to drink too much, 
and who declare that alcohol warnings have no effect 
on their behaviour as they are not concerned about the 
risks of alcohol abuse.

Table 9. Data fit criteria for alternative Latent Class Models for wine choice.

  Log Likelihood BIC AIC CAIC N. Parameters R²

Multinomial Logit -2611.704 5268.844 5237.409 5275.844 7 0.102
2-Class -2230.962 4559.286 4491.925 4574.286 15 0.434
3-Class -2150.245 4449.777 4346.490 4472.777 23 0.532
4-Class -2109.622 4420.456 4281.243 4451.456 31 0.584
5-Class -2088.329 4429.797 4254.658 4468.797 39 0.616



14 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

Ta
bl

e 
10

. E
st

im
at

es
 o

f L
at

en
t C

la
ss

 c
ho

ic
e 

m
od

el
 fo

r 
w

in
e 

an
d 

cl
as

s 
ch

ar
ac

te
ri

sa
tio

n.

La
te

nt
 c

la
ss

LC
.I

LC
.II

LC
.II

I
LC

.IV
La

te
nt

 c
la

ss
 s

iz
e

35
%

33
%

19
%

13
%

R
²

88
%

17
%

64
%

32
%

 
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE
A

I
C

oe
ff.

SE

Lo
go

50
%

35
%

49
%

40
%

  B
ra

in
 d

am
ag

e
-3

.0
58

**
*

0.
98

3
-0

.8
89

**
*

0.
14

8
-0

.2
48

0.
21

7
1.

05
9

**
*

0.
23

7
  N

o 
dr

iv
in

g
-1

.1
92

*
0.

61
2

0.
30

2
**

*
0.

09
4

2.
15

6
**

*
0.

42
6

-0
.5

80
**

*
0.

23
9

  N
o 

lo
go

4.
24

9
**

*
1.

46
5

0.
58

7
**

*
0.

12
7

-1
.9

08
**

*
0.

55
1

-0
.4

79
**

0.
24

1
Lo

go
 s

iz
e

9%
11

%
5%

7%
  B

ig
 v

s 
Sm

al
l

1.
27

7
0.

83
4

-0
.4

65
**

*
0.

18
0

0.
44

8
0.

27
4

-0
.3

02
0.

23
3

Lo
go

 p
os

iti
on

1%
20

%
3%

11
%

  L
ab

el
 v

s 
N

ec
k

-0
.0

82
0.

57
3

0.
86

7
**

*
0.

18
0

0.
20

9
0.

22
0

0.
44

7
*

0.
25

7
M

es
sa

ge
35

%
25

%
18

%
19

%
  N

eg
at

iv
el

y 
fr

am
ed

2.
36

9
1.

78
3

-0
.5

68
**

*
0.

13
5

0.
21

1
0.

22
7

0.
36

0
0.

23
0

  N
eu

tr
al

ly
 fr

am
ed

0.
37

9
1.

74
8

0.
10

3
0.

10
0

0.
65

0
**

*
0.

25
7

-0
.4

28
0.

27
5

  N
o 

m
es

sa
ge

-2
.7

49
3.

40
8

0.
46

5
**

*
0.

12
3

-0
.8

61
**

*
0.

29
9

0.
06

9
0.

18
7

A
lc

oh
ol

 b
y 

vo
lu

m
e

5%
0.

37
2

*
0.

22
0

8%
0.

16
1

**
0.

00
8

25
%

-1
.0

43
**

*
0.

35
8

23
%

-0
.4

62
**

*
0.

16
1

So
ci

o-
de

m
og

ra
ph

ic
s

  I
ta

lia
n 

-0
.5

78
**

*
0.

20
6

0.
06

1
0.

24
6

0.
23

8
0.

28
6

0.
27

9
0.

40
5

  M
al

e
0.

34
7

**
0.

17
2

-0
.3

62
*

0.
21

4
0.

01
8

0.
21

8
-0

.0
03

0.
28

3
  A

ge
-0

.0
16

0.
01

9
-0

.0
44

*
0.

02
3

0.
00

5
**

*
0.

02
2

0.
05

5
**

0.
02

7
A

lc
oh

ol
 c

on
su

m
pt

io
n 

ha
bi

ts
  C

on
su

m
pt

io
n 

fr
eq

ue
nc

y
-0

.2
41

**
0.

11
5

0.
23

0
*

0.
13

8
0.

33
4

**
*

0.
14

0
-0

.3
22

0.
20

7
  D

ru
nk

 fr
eq

ue
nc

y 
in

 th
e 

la
st

 6
 m

on
th

s
0.

22
2

**
*

0.
08

1
0.

14
2

0.
10

1
-0

.1
27

0.
10

4
-0

.2
37

0.
16

2
  B

ee
r 

co
ns

um
pt

io
n 

vs
 o

th
er

 a
lc

oh
ol

ic
s

0.
00

5
0.

00
4

0.
00

6
0.

00
4

-0
.0

03
0.

00
6

-0
.0

09
0.

00
7

Eff
ec

ts
 o

f h
ea

lth
 w

ar
ni

ng
s 

  D
is

cu
ss

ed
 w

ith
 fr

ie
nd

s 
on

 r
is

ks
-0

.3
73

0.
33

2
-0

.3
44

0.
43

3
0.

02
3

0.
38

4
0.

69
3

0.
46

9
  D

ec
re

as
ed

 c
on

su
m

pt
io

n
0.

62
9

**
*

0.
28

2
-0

.2
25

0.
57

5
-0

.3
98

0.
44

3
-0

.0
06

0.
54

6
  N

o 
eff

ec
t

0.
43

5
**

*
0.

19
2

0.
69

0
**

*
0.

24
1

-0
.1

97
0.

26
4

-0
.9

28
**

0.
44

5
  Th

ou
gh

t a
bo

ut
 th

e 
ri

sk
s

-0
.4

50
**

*
0.

19
8

0.
05

0
0.

23
2

0.
20

0
0.

20
5

0.
20

0
0.

23
9

  Th
ou

gh
t a

bo
ut

 d
ec

re
as

in
g 

co
ns

um
pt

io
n

-0
.2

41
0.

28
9

-0
.1

72
0.

37
1

0.
37

2
0.

30
7

0.
04

1
0.

39
6

A
tt

itu
de

s 
to

w
ar

ds
 a

lc
oh

ol
  D

o 
no

t t
hi

nk
 to

 d
ri

nk
 in

 e
xc

es
s 

0.
10

4
0.

06
8

0.
14

2
*

0.
08

2
-0

.0
76

0.
08

1
-0

.1
70

*
0.

10
1

  L
ik

e 
to

 d
ri

nk
 a

nd
 s

om
et

im
es

 d
ri

nk
 to

o 
m

uc
h 

0.
00

7
0.

08
3

0.
01

4
0.

09
7

-0
.1

14
0.

11
5

0.
09

3
0.

16
1

  T
ry

in
g 

to
 d

ri
nk

 le
ss

  
0.

08
5

0.
06

8
0.

03
2

0.
08

6
-0

.1
53

0.
09

9
0.

03
6

0.
09

8
  Th

in
k 

th
at

 fr
ie

nd
s 

dr
in

k 
to

o 
m

uc
h 

-0
.0

25
0.

06
9

-0
.0

18
0.

08
3

0.
00

6
0.

09
1

0.
03

8
0.

10
9

C
on

ce
rn

 a
bo

ut
 th

e 
co

ns
eq

ue
nc

es
 o

f a
lc

oh
ol

 a
bu

se
 

 
-0

.0
32

**
*

0.
01

0
 

-0
.0

34
**

*
0.

01
2

 
0.

00
5

 
0.

01
3

 
0.

06
0

**
*

0.
01

7

N
ot

e:
 L

C
=L

at
en

t C
la

ss
; A

I=
A

tt
ri

bu
te

 I
m

po
rt

an
ce

; S
E=

st
an

da
rd

 e
rr

or
; *

 p
<.

10
; *

*p
<.

05
; *

**
p<

.0
1 

a 
th

is
 v

ar
ia

bl
e 

is
 g

iv
en

 b
y 

th
e 

su
m

 o
f t

he
 it

em
s 

co
m

po
si

ng
 th

e 
to

pi
c.

 



15The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

LC.III (19% of the sample) is driven by the logo 
and the alcohol content when choosing a bottle of wine. 
Differently from the previous two classes, individuals 
from this class prefer to see a warning logo on the wine 
label, and in particular the one connected to the risks of 
drinking and driving. Their utility increases also when a 
warning message accompanies the logo, when the mes-
sage is neutrally framed. They choose wine based on 
low alcohol content. These individuals are more likely 
to belong to the older age segment of Millennials and be 
frequent consumers of alcoholic beverages. 

LC.IV (13% of the sample) includes respondents 
who want to be warned about the negative consequences 
of alcohol on the brain when choosing a bottle of wine. 
They want the logo on the front label and low alco-
hol content for wine. The older segment of Millennials 
is more likely to belong to this latent class, who think 
about the risks when faced with a warning label and 
who are worried about the consequences of alcohol on 
health. 

5. DISCUSSION

The introduction of health warnings on the label of 
alcoholic beverages is a topic of renewed interest in the 
field of consumer studies, due to the current debate on 
its mandatory or voluntary nature. Alcohol labelling 
issues are highly controversial due to the clash between 
different interests. On one side, there is the industry 
goal to increase sales volumes (and not costs) and on the 
other side, there is public interest in protecting consum-
ers’ health and right to be informed. Alcohol industry 
actors lobby for voluntary or self-regulatory initiatives 
and frame alcohol consumption issues as a part of their 
corporate social responsibility practices (McCambridge 
et al., 2018; Mialon and McCambridge, 2018). In this 
regards, it is useful to recall the fierce debate occurred 
among EU policy makers and the wine industry for the 
introduction of mandatory labelling of potentially aller-
genic substances in wine, including sulphites2 . As well 
as the  ongoing discussion related to the ingredients and 
nutritional labelling for alcoholic drinks for which the 
spirits and beer sectors signed in 2019 a Memorandum 
of Understanding3.

2 Regulation (EU) No. 579/2012 required mandatory labelling of a vari-
ety of allergenic substances in wine.
3 Following the submission of the industry self-regulatory proposal on 
the provision of nutrition and ingredients listing from the European 
alcoholic beverages sectors, during the 2019 a series of bilateral dia-
logues with the sectors’ representatives took place to encourage their 
commitment. As a consequence, representatives of the spirits and brew-
ery industries signed the Memorandum of Understanding in which they 

With reference to health warnings, according to sev-
eral research, current experience of voluntary alcohol 
warning in England (Petticrew et al., 2016), Australia 
(Coomber et al., 2018; O’Brien, 2019) and New Zea-
land (Tinawi et al., 2018) failed to inform individuals 
of health implications of alcohol consumption. If a self-
regulatory approach prevails on mandatory standard-
ised labelling, best practices for warning labels should be 
developed taking into account the results of the numer-
ous studies that have analysed the impact of design and 
placement of health messages on alcohol labels; together 
with sector specific aspects.

In this scenario, the present study contributes to 
the literature by deepening the analysis of the influence 
of alternative formats of health warnings on French and 
Italian Millennial consumers’ choices of beer and wine. 

Overall, our results confirm that AWL effects on 
consumer choices of wine and beer are influenced by the 
alcoholic beverages considered suggesting the need to 
consider the interaction between the type of drink and 
the warning message (Thomson et al., 2012; Wright et 
al., 2008). Indeed, for beer a positive utility is associated 
with the option of logo warning on the risks of drinking 
and driving, while for wine consumers attach more util-
ity to the  ‘no-warning option’, confirming the results of 
previous study conducted in Italy and France (Annun-
ziata et al., 2019). 

This difference could be due to the fact that wine is 
still considered as a traditional product in both coun-
tries and it is not considered as transgressive, or linked 
to harmful and risky behaviours (Agnoli et al., 2018); on 
the contrary, wine is often touted for its potential health 
benefits (Higgins and Llanos, 2015). In this regard, sev-
eral studies in Mediterranean countries reveal that wine 
consumption among Millennial consumers is decreas-
ing for the shift in the preferences towards other prod-
ucts such as beer and spirits (Marinelli et al., 2014; De 
Magistris et al., 2011). In addition, specifically for wine, 
a range of studies has investigated the use of different 
information sources and indicated that in-store or in-
restaurant sources are most valued (Atkin, Nowak, and 
Garcia, 2007; Atkin and Thach, 2012). 

Considering t he warning content, consumers 
attached a negative utility to the brain damage logo, for 
both beer and wine. This could be due to the fact that 
as shown by previous research young consumers are not 
very interested in potential long-term effects of alcohol 
(Annunziata et al., 2017; Annunziata et al., 2019; Jones 
and Parri, 2010; Jones and Parri, 2009). Indeed, these 

commit over the coming years, to voluntary provide nutritional infor-
mation and the list of ingredients for spirits and beer (even if in differ-
ent manners).



16 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

consumers perceive themselves as not personally vulner-
able to the long-term consequences of alcohol consump-
tion at this point in their lives, attaching more impor-
tance to the short-term consequences of their decisions 
(Coomber et al., 2017).

Furthermore, the current study points out that the 
preference for the drinking and driving logo on beer 
could be linked to a strong public awareness of the prob-
lem of alcohol-related car accidents, but also to the fact 
that the beer industry is already involved in various pub-
lic campaigns against drinking and driving4.

The present results also confirm that framing, design 
and visibility of AWL affects consumers’ choices of wine 
and beer and the impact varies in relation to alcoholic 
beverages considered. In particular, with reference to the 
warning visibility, consumers prefer to have a logo on the 
neck of the beer bottle; while for wine it should be on the 
front label. In relation to beer, our result is interesting con-
sidering that, according to recent research, most beer bot-
tles already carry warning labels on the back (GfK, 2014).  
While, concerning wine, when warnings are available, they 
are usually located on the back label. Considering that Pab-
st et al. (2019) in a recent study reveal that the back label 
plays a minor role in the wine buying decision, according 
to our results, moving the logo on the front label could 
increases the warning visibility and effectiveness.

The size of the logo, according to current results, 
does not seem to be an influential attribute, contrarily 
to findings of other researchers (Pham et al., 2018; Al-
Hamdani and Smith, 2017b). Concerning the message 
framing, results show that in the case of beer, consumers 
tend to choose a bottle with a neutrally framed message, 
while for wine they prefer the option without a message. 
However, negatively framed messages reduce consumers’ 
utility for both alcoholic beverages, confirming that this 
type of message could have a stronger emotional impact 
on consumers choices (Al-Hamdani and Smith, 2017a; 
Al-Hamdani and Smith, 2017b). In this regard, Sillero-
Rejon et al. (2018) found for beer that very stringent 
health warnings were judged to be more effective, lead-
ing to a greater motivation to reduce alcohol consump-
tion, as well as greater avoidance and reactance.

Results from the LC models confirm the existence of 
different groups of young consumers whose choices are 
differently influenced by different AWL. According to 
previous research, our results show that these groups are 
characterised by different drinking behaviours and aware-
ness of social and health risks related to alcohol consump-
tion (Annunziata et al., 2017; Scholes-Balog et al., 2012).

4 For a review of main educational campaign promoted by Worldwide 
Brewing Alliance see http://ec.europa.eu/health/ph_determinants/life_
style/alcohol/Forum/docs/alcohol_lib6_en.pdf

Overall, the results reveal once more that consumer 
preferences diverge among beer and wine. Taking into 
account beer, two classes of consumers show a higher 
utility for the bottle with warning labels (LC2 and LC3, 
46% of total sample), but at the same time these con-
sumers hold significant differences in consumption pat-
terns. While, LC2 included heavy beer drinkers, worried 
about the consequences of alcohol abuse and preferring 
the presence of warning on drinking and driving, LC3 
included consumers with moderate consumption habits, 
who assign a positive utility to both warning logos but 
prefer the ‘brain damage’ warning. Considering socio-
demographic variables, a higher number of older Mil-
lennials are included in this group. Conversely, LC1 and 
LC4 (47% of sample) are characterised by a higher con-
centration of consumers that do not want any warning 
logo on beer. In particular, LC1 (the most numerous) 
consumers are not worried about the consequences of 
alcohol abuse and strongly believe that health warnings 
have no effect. Men are the majority in this group.

Considering wine, a clear preference emerges 
towards a label without any warning. Specifically, the 
biggest groups LC.I and LC.II (which together represent 
68% of sample) include consumers who are not worried 
of the consequences of alcohol abuse and consider health 
warnings ineffective.

Conversely, consumers in the other two classes (32% 
of respondents) that attach a positive utility to warnings 
on the label, are worried about the negative effects of 
alcohol, and consider health warnings as effective. Both 
groups have a high presence of older Millennials. 

In brief, our results extend previous findings, high-
lighting that the older segment of Millennials with a 
moderate consumption behaviour tend to be influenced 
by the presence of AWL in their choices of alcoholic 
beverages, while this influence is weaker among young-
er Millennials (Creyer et al., 2002; Wright et al., 2008).  
Overall, Millennials are little concerned about the con-
sequences of alcohol abuse and the only two groups that 
claim to be worried fall among those who prefer the 
bottle with the warning. Therefore, in line with other 
research (Comber et al., 2015), our results suggest that 
warnings can be a useful tool to spread more knowl-
edge and awareness of the short- and long-term negative 
health and social effects of alcohol abuse. 

5. CONCLUSION

This study analyses the influence of alternative for-
mats of AWL on Millennials’ beer and wine choices, in 
order to provide further insights to the current debate 



17The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

on the introduction of health warnings on alcoholic bev-
erages’ labels. Despite it does not focus on the analysis 
of the effectiveness of health warnings policy in reducing 
abusive consumption behaviours, current results should 
be valuable for producers, providing practical indica-
tions on the influence of alternative formats of labels on 
young consumer choices. 

In brief, findings highlight that the inf luence of 
AWL on the choice of wine and beer by Millennial con-
sumers are driven by the type of alcoholic beverage and 
are affected by framing, design and visibility of warn-
ings. In the two Mediterranean countries considered – 
Italy and France - the acceptance of warnings is higher 
for beer than for wine and in both cases consumers 
show an higher utility for a logo on the front label: on 
the neck with a neutral message in the case of beer; on 
the front, without a message for wine. 

From a consumer behaviour point of view, the 
results confirm the existence of different segments of 
individuals in relation to their choices of alcoholic bev-
erages with AWL, also characterised by different drink-
ing behaviours and awareness of the social and health 
risks related to alcohol consumption. In particular, the 
older segment of Millennials with moderate consump-
tion behaviour, a group which is to some extent worried 
about the negative effects of alcohol, chooses the bot-
tle of beer with warning labels. The same is true, but 
with a lesser extent, when they chose a bottle of wine. 
The awareness of alcohol related health risks and the 
preference for bottles carrying warning labels is weak-
er among younger Millennials. Thus, in order to apply 
policies fostering health benefits, our results suggest the 
need to focus on young Millennials, effectively com-
municating the risks of alcohol abuse through target-
ed messages. In addition, and more generally, policies 
should increase young adults’ awareness of the potential 
negative effects of excessive consumption of both wine 
and beer.

Some segments of Millennials declared that they are 
not affected at all by health warnings on the labels of 
wine and beer. This could be also a consequence of the 
excess of labelling information, in particular for wine, 
where labels are already very detailed, often including 
sensory descriptions and food pairings suggestions. In 
order to avoid overloading consumers with too many 
stimuli on the label, a valid alternative could be repre-
sented by providing detailed health related information 
online, using for example QR codes or specific links to 
websites that provide useful information about alcohol 
and drinking combining on-label and on-line informa-
tion. Furthermore, companies should be stimulated to 
insert the website link in their general advertisements.  

Moreover, considering that current results under-
line that Millennials, regardless of age, are not very 
concerned about the long–term consequences of alcohol 
abuse, more extensive education and information cam-
paigns are needed aiming to inform young individu-
als about the potential negative consequences of alco-
hol intake, which go beyond the effects on driving and 
on pregnant women. This type of interventions can be 
more effective if combined with the use of warnings on 
the label, specifically rotating negative framed messages. 
Finally, considering that the awareness of alcohol-relat-
ed health risks is weaker among younger Millennials 
and that they mainly drink alcoholic beverages during 
weekends in out-of-home contexts (Bazzani et al., 2020), 
new tools should be developed to provide information in 
this contexts, as posters in bars and stores, and adver-
tisements; together with  tools designed to explain how 
responsible drinking messages translates into actual 
drinks (such as the pocket-sized unit calculator intro-
duced by UK drink-aware campaign).

The results of our analysis cannot be generalised as 
they are hardened by several limitations. First, the use of 
self-reported measurements is prone to generate social 
desirability bias; second the use of a convenience sam-
ple does not allow inferences on the populations of the 
two countries; third, the study analyses stated choices 
of respondents, which can be in line or not with actual 
choices when called to buy a bottle of wine (or beer) in 
everyday life. Lastly, the choice of the two countries (i.e.: 
Italy and France), where wine has an historical tradi-
tion of daily consumption, may limit the generalisation 
of results to other countries with different cultural back-
grounds. 

Based on these considerations, our analysis should 
be extended to other contexts with different drinking 
patterns and culture, like North European countries, 
and to other types of alcoholic beverages with a higher 
alcohol content, even more harmful and currently up 
surging among younger individuals. A laboratory exper-
iment analysing actual choices of wine and beer with 
different AWL stimuli and monetary incentives for par-
ticipants could partially bridge the lack of realism of dis-
crete choice analysis.

REFERENCES

Agnoli L., Begalli D., Capitello R., Generation Y’s 
perception of wine and consumption situa-
tions in a traditional wine-producing region. Int. 
J. Wine Bus. Res., 23(2) (2011), 176-192. doi: 
10.1108/17511061111143025



18 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

Agnoli L., Boeri M., Scarpa R., Capitello R., Begalli D., 
Behavioural patterns in Mediterranean-style drink-
ing: Generation Y preferences in alcoholic beverage 
consumption. J. Behav. Exp. Econ., 75 (C) (2018) 
117–125. doi:10.1016/j.socec.2018.06.001

Agostinelli G., J.Grube W., Alcohol counter-advertising 
and the media. Alcohol Res. Health 26(1) (2002) 
15–21.

Al M.-Hamdani, The case for stringent alcohol warning 
labels: lessons from the tobacco control experience. J. 
Public Health Policy 35(1) (2014) 65-74 doi: 10.1057/
jphp.2013.47

Al M.-Hamdani, Smith M.S., Alcohol health-warning 
labels: promises and challenges. J. Public Health 39 
(1) (2017a) 3–5. doi: 10.1093/pubmed/fdx010.

Al M.-Hamdani, Smith M.S., Alcohol warning label per-
ceptions: do warning sizes and plain packaging mat-
ter?. J. Stud. Alcohol Drugs, 78 (1) (2017b) 79–87. 
doi: 10.15288/jsad.2017.78.79

Al M.-Hamdani, Smith M.S., Alcohol warning label 
perceptions: Emerging evidence for alcohol policy. 
Can J Public Health 106 (6) (2015): e395–e400. doi: 
10.17269/cjph.106.5116.

Argo J.J., Main K.J., Meta-analyses of the effectiveness of 
warning labels. J. Public Policy Mark. 23(2) (2004) 
193-208. doi: 10.1509/jppm.23.2.193.51400

Camerer C.F., Loewenstein G., Rabin M., Advances in 
behavioral economics. Princeton university press. 2004

Annunziata A., Agnoli L., Vecchio R., Charters S., Mari-
ani A., Health warnings on wine labels: a discrete 
choice analysis of Italian and French Generation Y 
consumers. Wine Econ. Policy 8(1) (2019) 81–90. 
doi: 10.1016/j.wep.2019.03.001

Annunziata A., Vecchio R., Mariani A.. Alcohol warn-
ings and moderate drinking patterns among Italian 
university students: an exploratory study. Nutrients. 9 
(6) (2017): 628 doi: 10.3390/nu9060628 

Annunziata A., Pomarici E., Vecchio R., Mariani A.. 
Health warnings on wine: A consumer perspective. 
Brit. Food J., 118 (3) (2016): 647–659 doi: 10.1108/
BFJ-08-2015-0300

Atkin T., Nowak L., Garcia R.. Women wine consumers: 
information search and retailing implications. Int. J. 
Wine Bus. Res. 19 (4) (2007) 327–339.

Atkin T., Thach L.. Millennial wine consumers: risk per-
ception and information search. Wine Econ. Policy 1 
(1) (2012): 54–62. doi:10.1016/j.wep.2012.08.002

Bazzani C., Capitello R., Ricci C. E., Scarpa R., Begalli D., 
Nutritional Knowledge and Health Consciousness: 
Do They Affect Consumer Wine Choices? Evidence 
from a Survey in Italy. Nutrients 12(1) (2020) 84. doi: 
10.3390/nu12010084

Blackwell A.K.M., Drax K., Attwood A.S., Munafò 
M.R., Maynard O.M. Informing drinkers: Can cur-
rent UK alcohol labels be improved? Drug Alcohol 
Depen, 192 (2018) 163–170. doi: 10.1016/j.drugal-
cdep.2018.07.032

Bolton R.N., Parasuraman A., Hoefnagels A., Migchels 
N., Kabadayi S., Gruber T., Solnet D. Understanding 
Generation Y and their use of social media: a review 
and research agenda. J. Serv. Manag, 24(3) (2013) 
245-267. doi: 10.1108/09564231311326987

Brosdahl D.J., Carpenter J.M. Shopping orientations 
of US males: A generational cohort comparison. 
J. Retail. Consum. Serv., 18(6) (2011) 548-554. 
doi:10.1016/j.jretconser.2011.07.005

Branco E., Kaskutas L.A. “If it burns going down…”: How 
focus groups can shape fetal alcohol syndrome (fas) 
prevention. Subst. Use Misuse, 36 (3) (2001) 333–
345. doi:10.1081/JA-100102629

Brennan L., Previte J., Fry M.L. Social marketing’s con-
sumer myopia: Embracing a systems view of social 
change markets. J. Social Mark., 6 (3) (2016) 219–239 
doi:10.1108/JSOCM-12-2015-0079

Brown K.G., Stautz K., Hollands G.J., Winpenny E.M.,  
Marteau T.M. The cognitive and behavioural impact 
of alcohol promoting and alcohol warning advertise-
ments: an experimental study. Alcohol alcoholism. 51 
(3) (2016) 354–362. doi: 10.1093/alcalc/agv104

Bucic T., Harris J., Arli D. Ethical consumers among the 
millennials: A cross-national study. J. Bus. Ethics, 
110(1) (2012) 113-131. doi: 10.1007/s10551-011-1151-z

Calafat A., Blay N.T., Hughes K.E., Bellis M., Juan M., 
Duch M., Kokkevi A.. Nightlife young risk behav-
iours in Mediterranean versus other European cit-
ies: are stereotypes true? Eur. J. Public Health 21 (3) 
(2011) 311–315. doi:10.1093/eurpub/ckq141

ChoiceMetrics. Ngene 1.2 User Manual and Reference 
Guide. Australia. 2018. http://www.choice-metrics.
com/NgeneManual120.pdf.

Coomber K., Hayley A., Miller P.G. Unconvincing and 
ineffective: Young adult responses to current Austral-
ian alcohol product warnings. Aust. J. Psychol. 70 (2) 
(2018) 131-138 doi: 10.1111/ajpy.12177

Coomber K., Mayshak R., Curtis A., P.G. Miller. Aware-
ness and correlates of short-term and long-term con-
sequences of alcohol use among Australian drinkers. 
Aust. Nz. J. Publ. Heal. 41 (3) (2017) 237–242. doi: 
10.1111/1753-6405.12634

Coomber K., Florentine M., Barbour I.R., Mayshak R., 
Miller P.G. Do consumers ‘get the facts’? A survey of 
alcohol warning label recognition in Australia. BMC 
Public Health, 15 (2015)  816. doi: 10.1186/s12889-
015-2160-0



19The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

Creyer E.H., Kozup J.C., Burton S. An experimental 
assessment of the effects of two alcoholic beverage 
health warnings across countries and binge-drink-
ing status. J. Consum. Aff. 36 (2) (2002) 171–202. 
doi:10.1111/j.1745-6606.2002.tb00429.x

Delmas M.A., Lessem N., Eco-premium or eco-pen-
alty? Eco-labels and quality in the organic wine 
market. Bus Soc. 56 (2) (2017) 318–356. doi: 
10.1177/0007650315576119

T. de Magistris, Groot E., Gracia A., Albisu L.M.. Do mil-
lennial generation’s wine preferences of the “New 
World” differ from the “Old World”? A pilot study. 
Int. J. Wine Bus. Res. 23 (2) (2011) 145–160. doi: 
10.1108/17511061111143007

Eurocare. 2016. European Report on Alcohol Policy: A 
Review. https://www.eurocare.org/media/GENERAL/
docs/reports/2016europeanreportonalcoholpolicy.pdf.

Euromonitor International. 2020. Market size. https://
www.portal.euromonitor.com/.

Eurostat. 2017. Agriculture, forestry and fishery sta-
t i s t i c s .  h t t p s : / / e c . e u r o p a . e u / e u r o s t a t / d o c u -
ments/3217494/8538823/KS-FK-17-001-EN-N.pdf/
c7957b31-be5c-4260-8f61-988b9c7f2316.

Evans J.S.B., Dual-processing accounts of reason-
ing, judgment, and social cognition. Annu. Rev. 
Psychol. 59 (2008) 255-278. 10.1146/annurev.
psych.59.103006.093629

Ferrini S., Scarpa R., Designs with a priori information 
for nonmarket valuation with choice experiments: A 
Monte Carlo study. J. Environ. Econ. Manag. 53 (3) 
(2007) 342–363. doi: 10.1016/j.jeem.2006.10.007

Glock S., Krolak-Schwerdt S., Changing outcome expec-
tancies, drinking intentions, and implicit attitudes 
toward alcohol: a comparison of positive expectan-
cy-related and health-related alcohol warning labels. 
Appl. Psychol. Health Well-Being 5 (3) (2013) 332–
347. doi:10.1111/aphw.12013

GfK. 2014. State of play in the use of alcoholic bever-
age labels to inform consumers about health aspects. 
Action to prevent and reduce harm from alcohol. 
https://ec.europa.eu/health/sites/health/files/alcohol/
docs/alcohol_beverage_labels_full_report_en.pdf.

Greenfield T.K., Ye Y., Giesbrecht N. Alcohol policy opinions 
in the United States over a 15-year period of dynamic 
per capita consumption changes: Implications for today’s 
public health practice. Contemp. Drug Probl. 34 (4) 
(2007) 649–680. doi: 10.1177/009145090703400408

Greene W.H., Hensher D.A., A latent class model for 
discrete choice analysis: contrasts with mixed 
logit. Transportation Research Part B: Methodo-
logical, 37 (8) (2003) 681–698. doi: 10.1016/S0191-
2615(02)00046-2

Hassan L.M., Shiu E. A systematic review of the efficacy 
of alcohol warning labels: Insights from qualitative 
and quantitative research in the new millennium. 
J. Soc. Mark., 8 (3) (2018) 333–352. doi: 10.1108/
JSOCM-03-2017-0020

Higgins L.M., Llanos E. A healthy indulgence? Wine 
consumers and the health benefits of wine. Wine 
Econ. Policy, 4 (1) (2015) 3–11. doi:10.1016/j.
wep.2015.01.001

Jarvis W., Pettigrew S.. The relative influence of alcohol 
warning statement type on young drinkers’ stated 
choices. Food Qual. Prefer. 28 (1) (2013) 244–252. 
doi: 10.1016/j.foodqual.2012.08.011

Jones S.C., Parri G. Health warning labels on alcohol 
products. The views of Australian university students. 
Contemp. Drug Probl. 37 (1) (2010) 109–137. doi: 
10.1177/009145091003700106

Jones S.C., Parri G. The impact of more visible standard 
drink labelling on youth alcohol consumption: Help-
ing young people drink (ir) responsibly? Drug Alco-
hol Rev. 28 (3) (2009) 230–234. doi:10.1111/j.1465-
3362.2008.00020.x

Kahneman D., Thinking, fast and slow. Macmillan. 2011
Kaskutas L., Greenfield T.K. First effects of warning 

labels on alcoholic beverage containers. Drug. Alco-
hol Depen. 31 (1) (1992) 1–14. doi:10.1016/0376-
8716(92)90002-T

Kersbergen I., Field M. Alcohol consumers’ attention to 
warning labels and brand information on alcohol 
packaging: Findings from cross-sectional and experi-
mental studies. BMC Public Health, 17 (1) (2017) 
123. doi: 10.1186/s12889-017-4055-8

Knai C., Petticrew M., Durand M.A., Mays N., Are the pub-
lic health responsibility deal alcohol pledges likely to 
improve public health? An evidence synthesis. Addic-
tion, 110 (8) (2015) 1232–1246. doi:10.1111/add.12855

Krischler M., Glock S.. Alcohol warning labels for-
mulated as questions change alcohol-related 
outcome expectancies: A pilot study. Addict. 
Res. Theor y, 23 (4) (2015) 343–349. doi: 
10.3109/16066359.2015.1009829

Lancaster K.J. A new approach to consumer theo-
ry. J. Political Econ. 74(2) (1966).  132-157. doi: 
10.1086/259131?journalCode=jpe

Lancaster L.C., Stillman D. When Generations Collide: 
Who they are. Why they clash. How to solve the gen-
erational puzzle at work. New York: Harper Business, 
2002

Louviere J., Woodworth G. Design and analysis of simu-
lated consumer choice or allocation experiments: an 
approach based on aggregate data. J. Mark. Res. 20 (4) 
(1983) 350–367. doi: 10.1177/002224378302000403



20 Azzurra Annunziata, Lara Agnoli, Riccardo Vecchio, Steve Charters, Angela Mariani

Macky K., Gardner D., Forsyth S., Cennamo L., Genera-
tional differences in work values, outcomes and per-
son‐organisation values fit. J. Manag. Psychol. 23 (8) 
(2008) 891-906. doi: 10.1108/02683940810904385

Marinelli N., Fabbrizzi S., Alampi Sottini V., Sacchelli 
S., Bernetti I., Menghini S.. Generation Y, wine and 
alcohol. A semantic differential approach to con-
sumption analysis in Tuscany. Appetite, 75 (2014) 
117–127. doi: 10.1016/j.appet.2013.12.013

Mc J.Cambridge, Mialon M., Hawkins B., Alcohol indus-
try involvement in policymaking: a systematic review. 
Addiction. 113 (9) (2018) 1571-84 doi: 10.1111/
add.14216

Mc D.Fadden, Conditional logit analysis of quantitative 
choice behavior. In Frontiers in Econometrics, edited 
by Paul Zarembka (105–142). Academic Press: New 
York, NY, 1974.

Mehrabian A., Russell J.A., A questionnaire measure of 
habitual alcohol use. Psychological reports, 43 (3) 
(1978) 803–806. doi:10.2466/pr0.1978.43.3.803

Mialon M., McCambridge J., Alcohol industry corporate 
social responsibility initiatives and harmful drinking: 
a systematic review. Eur. J. Public Health 28(4) (2018) 
664–73 doi: 10.1093/eurpub/cky065

Miller E.R., Ramsey I.J., Baratin G.Y., Olver I.N. Message 
on a bottle: are alcohol warning labels about cancer 
appropriate? BMC public health, 16 (1) (2016) 139. 
doi:10.1186/s12889-016-2812-8

Mueller S., Charters S., Generation Y and wine: Guest 
editorial. Int. J. Wine Bus. Res. 23 (2) (2011) 2–4. 
doi: 10.1108/ijwbr.2011.04323baa.001

Noar S.M., Hall M.G., Francis D.B., Ribisl K.M., Pepper 
J.K., Brewer N.T., Pictorial cigarette pack warnings: 
a meta-analysis of experimental studies. Tob. Con-
trol 25 (3) (2016) 341-354 doi: 10.1136/tobaccocon-
trol-2014-051978

O’Brien P., Warning Labels about Alcohol Consumption 
and Pregnancy: Moving from Industry Self-regula-
tion to Law, J. Law Med. 27 (2) (2019) 259-273

Pabst E., Szolnoki G., Mueller Loose S., The effects of 
mandatory ingredient and nutrition labelling for 
wine consumers–A qualitative study. Wine Econ. Pol-
icy 8 (1) (2019) 5–15. doi: 10.1016/j.wep.2019.02.001

Pham C., Rundle-Thiele S., Parkinson J., Shanshi Li, 
Alcohol warning label awareness and attention: a 
multi-method study. Alcohol Alcohol. 53 (1) (2018) 
39–45. doi: 10.1093/alcalc/agx087

Petticrew M., Douglas N., Knai N., Durand M.A., East-
mure E., Mays N., Health information on alcoholic 
beverage containers: Has the alcohol industry’s pledge 
in England to improve labelling been met? Addic-
tion,111 (1) (2016) 51-55 doi: 10.1111/add.13094

Pettigrew S., Jongenelis M., Chikritzhs T., Slevin T., Pratt 
I.S., Glance D., Liang W., Developing cancer warn-
ing statements for alcoholic beverages. BMC public 
health, 14 (1) (2014) 786. doi: 10.1186/1471-2458-14-
786

Reisch L.A., Sunstein C.R., Gwozdz W., Beyond car-
rots and sticks: Europeans support health nudges. 
Food Policy 69 (2017) 1-10. doi: 10.1016/j.food-
pol.2017.01.007

Rivaroli S., Kozák V., Spadoni R., What motivates 
Czech and international “millennial-aged” univer-
sity students to consume craft beers? Int. J. Wine 
Bus. Res, 31 (3) (2019) 441-455. doi:10.1108/IJW-
BR-11-2018-0067

Robertson K., Thyne M., Hibbert S., Drinkers ‘perceived 
negative alcohol-related expectancies: Informing 
alcohol warning messages. Drugs. 24 (2) (2017) 197–
205. doi: 10.1080/09687637.2016.1188880

Rose J.M., Bliemer M.C., Constructing efficient stated 
choice experimental designs. Transp. Rev. 29 (5) 
(2009) 587-617. doi: 10.1080/01441640902827623

Sandor Z., Wedel M., Designing conjoint choice experi-
ments using managers’ prior beliefs. J. Mark. Res. 38 
(4) (2001) 430-444. doi 10.1509/jmkr.38.4.430.18904

Scarpa R., Rose J.M., Design efficiency for non‐mar-
ket valuation with choice modelling: how to meas-
ure it, what to report and why. Aust. J. Agr. Resour. 
Ec. 52 (3) (2008) 253-282. doi: 10.1111/j.1467-
8489.2007.00436.x

Scholes‐Balog K.E., Heerde J.A., Hemphill S.A., Alcohol 
arning labels: Unlikely to affect alcohol related beliefs 
and behaviours in adolescents. Aust. Nz. J. Publ. 
Heal. 36 (6) (2012) 524–529. doi: 10.1111/j.1753-
6405.2012.00934.x

Sillero-Rejon C., Attwood A.S., Blackwell A.K.M., Ibáñez-
Zapata J., Munafò M.R., Maynard O.M., Alcohol picto-
rial health warning labels: the impact of self-affirmation 
and health warning severity. BMC public health, 18 (1) 
(2018) 1403. doi: 10.1186/s12889-018-6243-6

Stockwell T., Zhao J., Panwar S., Roemer A., Naimi T., 
Chikritzhs T., Do “moderate” drinkers have reduced 
mortality risk? A systematic review and meta-anal-
ysis of alcohol consumption and all-cause mortality. 
J. Stud. Alcohol Drugs 77 (2) (2016) 185–198. doi: 
10.15288/jsad.2016.77.185

Szolnoki G., Hoffmann D., Online, face-to-face and tele-
phone surveys—Comparing different sampling meth-
ods in wine consumer research. Wine Econ. Policy 2 
(2) (2013) 57–66. doi: 10.1016/j.wep.2013.10.001

Thach E.C., Olsen J.E., Market segment analysis to tar-
get young adult wine drinkers. Agribusiness, 22(3) 
(2006) 307-322. doi: 10.1002/agr.20088



21The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer

Thaler R.H., Sunstein C.R., Nudge: Improving Decisions 
about Health, Wealth and Happiness. 2008, Boston 
Yale University Press

Thomson L.M., Vandenberg B., Fitzgerald J.L., An explor-
atory study of drinkers views of health information 
and warning labels on alcohol containers. Drug Alco-
hol Rev. 31 (2) (2012) 240–247. doi: 10.1111/j.1465-
3362.2011.00343.x

Thurstone L.L., A law of comparative judgment. Psychol. 
Rev. 34 (4) (1927) 273–286. Doi: 10.1037/h0070288

Tinawi G., Gray T., Knight T., Glass C., Domanski N., 
Wilson N., Hoek J., Thomson G., Highly deficient 
alcohol health warning labels in a high-income coun-
try with a voluntary system. Drug Alcohol Rev. 37 
(5) (2018) 616-626 doi: 10.1111/dar.12814

Train K.E., Discrete Choice Methods with Simulation, 
New York: 2nd ed. 2009. Cambridge University Press. 

Vallance K., Romanovska I., Stockwell T., Hammond D., 
Rosella L., Hobin E., “We Have a Right to Know”: 
Exploring Consumer Opinions on Content, Design 
and Acceptability of Enhanced Alcohol Labels. Alcohol 
Alcohol. 53 (1) (2017) 20–25. doi:10.1093/alcalc/agx068

Vecchio R., Decordi G., Grésillon L., Gugenberger C., 
Mahéo M., Jourjon F.. European consumers’ percep-
tion of moderate wine consumption on health. Wine 
Econ. Policy 6 (1) (2017). 14–22. doi: 10.1016/j.
wep.2017.04.001

Vecchio R., Determinants of willingness-to-pay for sus-
tainable wine: Evidence from experimental auctions. 
Wine Econ. Policy 2 (2) (2013) 85–92. doi: 10.1016/j.
wep.2013.11.002

Vermunt J.K., Magidson J., Technical guide for Latent 
GOLD 5.0: Basic, advanced, and syntax. Belmont, 
MA: Statistical Innovations Inc. 2013

Wigg S., Stafford L.D., Health warnings on alcoholic 
beverages: perceptions of the health risks and inten-
tions towards alcohol consumption. PLoS One, 11 (4) 
(2016) e0153027. doi: 10.1371/journal.pone.0153027

Wogalter M.S. ed., Handbook of Warnings. Lawrence Erl-
baum Associates, Mahwah, NJ, 2006.

World Health Organization. 2010. Global strategy to 
reduce the harmful use of alcohol. https://www.who.
int/substance_abuse/publications/global_strategy_
reduce_harmful_use_alcohol/en

World Health Organization Europe. 2017. Alcohol label-
ling: A discussion document on policy options. 
h t t p : / / w w w. e u r o . w h o . i n t / _ _ d a t a / a s s e t s / p d f _
file/0006/343806/WH07_Alcohol_Labelling_full_
v3.pdf ?ua=1.

World Health Organization. 2018. Global status report 
on alcohol and health 2018. http://www.who.int/sub-
stance_abuse/publications/global_alcohol_report/en.

Wright C.A., Bruhn C.M., Heymann H., Bamforth C., 
Beer and wine consumers’ perceptions of the nutri-
tional value of alcoholic and nonalcoholic beverages. 
J. Food Sci. 73 (1) (2008) 8–11. doi: 10.1111/j.1750-
3841.2007.00606.x


	Wine Economics and Policy
	Volume 9, Issue 2 - 2020
	Firenze University Press
	The Influence of Alcohol Warning Labels on Consumers’ Choices of Wine and Beer
	Azzurra Annunziata1,*, Lara Agnoli2, Riccardo Vecchio3, Steve Charters4, Angela Mariani5
	A Bad Year? Climate Variability and the Wine Industry in Chile
	Eduardo Haddad1,*, Patricio Aroca2, Pilar Jano3, Ademir Rocha4, Bruno Pimenta5
	Sparkling Wine International Market Structure and Competitiveness
	Karim Marini Thome*, Vitoria A. Leal Paiva
	The Role of Context Definition in Choice Experiments: a Methodological Proposal Based on Customized Scenarios
	Fabio Boncinelli*, Caterina Contini, Francesca Gerini, Caterina Romano, Gabriele Scozzafava, Leonardo Casini
	The Impact of Country of Origin on Brand Equity: An Analysis of The Wine Sector
	Nádia Passagem1, Cátia Fernandes Crespo2,*, Nuno Almeida3
	Competitive Strategies for Wine Cooperatives in the German Wine Industry
	Barbara Richter1,*, Jon Hanf2
	Valuation of Viticultural Adaptation to Climate Change in Vineyards: A Discrete Choice Experiment to Prioritize Trade-Offs Perceived by Citizens
	Verónica Farreras1,2, Laura Abraham3,*
	Does the Institutional Quality Affect Labor Productivity in Italian Vineyard Farms?
	Maria Raimondo1,*, Concetta Nazzaro4, Annamaria Nifo3, Giuseppe Marotta2
	The Role, Scope and Management of R&D and Innovation in the Wine Sector: an Interview with Antonio Graca 
	Peter Hayes AM