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Factors Determining Consumer Beer Brand Preference (Study in Addis Ababa,

Ethiopia)
Article in International Journal of Economics and Business Research · March 2019
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International Journal of Economics & Business
ISSN: 2717-3151, Volume 3, Issue 1, page 140 - 157
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Factors Determining Consumer

Beer Brand Preference
(Study in Addis Ababa, Ethiopia)
Tsegaye Fereja1 & Leykun Birhanu Demeke2
1
Tsegaye Fereja & 2Leykun Birhanu Demeke
1
St. Marry University Addis Ababa, Ethiopia
2
Ethiopian Sugar Corporations, Addis Ababa, Ethiopia
Abstract: In every product category, consumers have more choices, more information and higher expectations
than ever before. To move consumer from trial to preference, brands need to deliver on their value preposition,
as well as dislodge someone else from the consumer’s existing preference set. The study was on Factors
Determining Consumer Beer Brand Preference in Addis Ababa, Ethiopia. Therefore; the objective of the study
was to assess factors determining consumer beer brand preference in Addis Ababa, Ethiopia. The finding from
the multinomial logistic regression revealed what factors determine the probability attached to respondents beer
brand preference. Accordingly; age, perceived beer quality, perceived social benefit, situational influence and
peer influence had positive sign and significantly affect the probability of preferring St. George beer. Whereas;
family size had sign and significantly affect the probability of preferring St. George. Moreover; advertisement,
situational and peer influence had positive sign and significantly affect the probability of preferring Habesha
beer. Whereas family size had negative sign and significantly affect the probability of preferring Habesha beer.
Furthermore; advertisement and situational influence had positive sign and significantly affect the probability of
preferring Walia beer. Whereas sex and marital status had negative sign and significantly affect the probability
of preferring Walia beer. Still there is untapped market potential that producers should take such as a market
segmentation strategy and design their products in a manner that make the products appeal to different
categories of individuals that can influence of personal factors on customer satisfaction. A potentially successful
strategy can be that which provides products that correspond to and appreciate customers’ social status and age.
It is also advised that any advertisement for beer brands should convey information about the advantages which
the brand being advertised would offer over other brands. Moreover; situational influence was found to be
significantly relevant to brand preference of beer, producers should in their advertisement emphasis social
groups. They should exploit this further through segmenting the market into distinctive social classes.
Keywords: Factors Determining, Consumer, Beer Brand, Preference & Market.
1. INTRODUCTION
Beer consumption in developing countries is often seen as one revealing (if crude) proxy for gauging
the strength of economic activity. If beer sales are high and rising, incomes and economic activity are
presumably growing strongly while the reverse should be true if beer sales are flat or falling (Access
capital research, 2010). Ethiopia‟s beer industry is currently comprised of eight companies are
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Fereja, T. & Demeke, L. B. 2019. Factors Determining Consumer Beer Brand Preference ............
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participating in the beer production. These are Diageo, Heineken, Raya, Habash, BGI, and Dashen already
under production; whereas Zemen & Zabider beer are under construction. One of the major actor for the
growth of the industry came in the past few years when the government of Ethiopian transferred all state-
owned breweries to private companies only keeping 49% share of Dashen Brewery, which still belongs to
Tiret Endowment Fund that is owned by Amhara National Democratic Movement (ANDM) one of the four
member parties of the ruling party coalition (Ethiopian Peoples‟ Revolutionary Democratic Front) (Access
capital research, 2010).
Therefore, this research was focused on the determinants of consumer beer brand preference in
Ethiopian a case study on Addis Ababa City beer consumers.
Ethiopia with a population closer to 100 million, the per capita consumption of beer stands at eight
liters and is expected to reach nine or 10 by the end of 2015/16, which is very small compared to Kenya‟s
above 15 liters and South Africa and around 60 liters. Moreover; in the capital Addis Ababa at least about
half of the country‟s total beer production is consumed (Fortune Magazine, 2010).
In aggressive and costly marketing campaigns, Ethiopian breweries with a small production capacity
may soon be swallowed by the big ones. Thus, their profit margins will not be as it used to be in the old
days. For some of them survival depends on their marketing strategy and winning the minds to secure loyal
customers. In opposite argument with the above; there will be no merger or one being swallowed by
another at this stage of Ethiopia‟s beer industry because the market is fragmented and un served.
Furthermore, it is crucial to examine the company specific factors or internal factors as well as the external
factors that influence customer brand preference. There are also customer specific factors that influence
customer satisfaction (Henning-Thurau & Klee, 2010).
Therefore; the general objective of the study was to look at the determinants of consumer beer brand
preference in Ethiopia in case of Addis Ababa City beer consumers. Specifically to examine the effects of
consumers demographic characteristics on beer brand preference and volume of consumption, to determine
advertizing influence on consumer beer brand preference, to examine the effects of reference groups
influence on consumer beer brand preference and to examine the effects of consumers‟ situational
variation on beer brand preference.
Even though, beer markets widespread around the world but the authors focused on Ethiopia
specifically Addis Ababa. However, it needs far too much time to study the determinants consumers‟ beer
brand preferences in Addis Ababa so the authors have scoped to study civil servant consumers‟ in Addis
Ababa City Administration in a given period.
With the limit of time, this research was it is not realistic to conduct interviews or administer
questionnaires with a large number of the population so the sample group would be the representative of
the whole population. The questions in questionnaire are adapted from other researches in the same field.
In addition, the author analyzed the difference of all demographic features but not every relationship‟s
strength and direction. Thirdly, lack of relevant study literature in Ethiopia case. Marketing mangers and
sales representative from producer side and hotel, bar, grocery and restaurant managers were included so
as to generate information the author made a lot of time devotion during late hours.
Thus; this study can significantly add value to the existing limited body of knowledge in the area of
beer brand preference especially in Ethiopia. Moreover, understanding of the determinants of consumer
beer brand preference can generate relevant information that can be used as an input in decision making
process of reconsidering or reaffirming their marketing strategies for breweries currently operating in
Ethiopia as firm in beer industry, researcher and trader of beer.
2. DATA AND METHOD

2.1 Data
In this study, both quantitative and qualitative research strategies was employed. The quantitative
strategy was used to analyze the data using structured survey questionnaire from a representative sample of
261 that were selected from 51,168 study population of Addis Ababa City civil servants. The qualitative

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research strategy was used to analyze the data by using unstructured interviews with key informants: hotel
managers and marketing officers.
The sampling area for this study were bars and restaurants that are found around condominium.
Condominiums are the most preferable residential area this studies because it's easy of accessibility for the
author and availability of rational consumer. The study was done specifically at week end (Friday,
Saturday and Sunday) since weekends are leisure time for most of civil servants.
There were three ways to measure brand preference directly; survey questions, brand choice
measure, and constant sum measure. This study adopted the question measurement of brand preference.
This Survey method was chosen because of its' capacity to measure human attitude and opinion. The study
was done specifically at week end (Friday, Saturday and Sunday) since weekends are leisure time for most
of civil servants.
Therefore; structured questionnaires mainly based on categorical scale type was used as a major
instrument to collection of primary data. The questionnaires consist three sections; the first section was to
elicited information on the demographic characteristics of the respondents, the second section was made up
of items that seeks as source of information on independent variables of the study (i.e. beer quality and
price, situational factors, advertisement influence and Social and peer group influence from beer
consumers).While the third section was to measure the dependant variables of the study (i.e. beer brand
preference). In addition, secondary sources such as documents and related materials were also used to back
up the findings from primary sources.
The total population of Addis Ababa is 3.38 million in 2007 census and in 2016 it is expected to
reached 4.04 million out of it 1.02 million are assumed to drink beer in one or another time. The city is
assumed to have 5% civil servant out of 1.02 million. Thus, the study population was 51,168 in Addis
Ababa city during the specified study period. Therefore, following Fisher, (2007) the size of sample survey
result for study population of 51,168 is 261 samples with 5% margin of error.
Thus; by applying two stage sampling was employed to collect primary data. In the first stage
purposive sampling was used to select 25 bar and restaurants across Addis Ababa city condominiums
based on their customers size by the judgment of researcher himself and data collectors and in the second
stage by using simple randomly sampling from each bar and restaurants 12 respondents who are civil
servants were selected. Moreover; the study employed three types of questionnaires these are dichotomous
question, multiple choice questions, and likert scales each consisting 1-5 question. This helped respondents
to issue their opinion about beer products they consume. Moreover, the collected was computed using
Stata-12 which is widely used by previous researchers.
2.2 Model Specification

Given the nature of beer brand preference (BPi) for Walya, Harare , Bedale, St. George, Meta Abo,
Habash and Others (Meta, Bedele, Harar & Dashen) the estimation was based on multinomial logit (MNL)
model which enabled us to treat the possible outcomes of brand preference. This method was used to
analyze the impact of various explanatory variables on the probability of being in one or another brand
category (outcome). The advantage of the MNL is that it permits the analysis of decisions across more than
two categories, allowing the determination of choice probabilities for different categories (Wooldridge,
2002).
To describe the MNL model, let y denote a random variable taking on the values {1, 2...J} for J , a
positive integer, and let x denote a set of conditioning variables. In this case, y denotes respondents' beer
brand preference and x contains respondents' attributes like age, education, reference group influence,
advertisement, situational variation and so forth. The question is how, ceteris paribus, changes in the
elements of x affect the response probabilities P(y = j / X), j =1, 2 ...J. Since the probabilities must sum to
unity, P(y = j / x) is determined once we know the probabilities for j = 2...J. Let x be a 1× K vector with
first element unity. The MNL model has response probabilities:

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exp( X j )
P(Y  j / X )  ...............................................................................................(1)
 J

1   exp( X K )
 K 1 
Where j is Kx1, j=1…J. Because the response probabilities must sum to unity,
1
P( y  0 / X )  ................................................................................................(2)
 J

1   exp( X K )
 K 1 
When J=1, 1 is the Kx1 vector of unknown parameters, and we get the binary logit model.
The outcome or response probabilities of this study was categorized based the number of
respondents' preference to beer brand. Accordingly the top three highly preferred beer brands and the
remaining as others was possible outcomes or response probabilities.
Unbiased and consistent parameter estimates of the MNL model in equation (1) require the
assumption of independence of irrelevant alternatives (IIA) to hold. More specifically, the IIA assumption
requires that the probability of preferring a beer brand in one category by a given respondent needs to be
independent from the probability of preferring another brand in another category (that is, Pj/Pk is
independent of the remaining probabilities). The premise of the IIA assumption is the independent and
homoscedastic disturbance terms of the basic model in equation (1).
The parameter estimates of the MNL model provide only the direction of the effect of the
independent variables on the dependent (response) variable, but estimates do not represent either the actual
magnitude of change nor probabilities.
The magnitudes of the coefficients of MNL model are difficult to interpret. Thus, either we compute
partial effects, as in equation (3), or compute differences in probabilities. These results are easily obtained
by comparing fitted probabilities after multinomial logit estimation. The fitted probabilities can be used for
prediction purposes: for each observation i, the outcome with the highest estimated probability is the
predicted outcome. This can be used to obtain a percent correctly predicted, by category if desired
(Wooldridge, 2002).
Therefore, differentiating equation (1) with respect to the explanatory variables provides partial
effects of the explanatory variables given as:
 J 
P ( y  j / X )


   hK exp( X K ) 
  .........................................................(3)
 P( y  j / X ) jK   K 1 
X K  g( X ,  ) 

 

Where hk is the k element of h and
th
g ( X ,  )  1  h1 exp( X h ) .......................................................................................................(4)

J
The marginal effects or marginal probabilities are functions of the probability itself and measure the
expected change in probability of a particular category with respect to a unit change in an independent
variable from the mean (Wooldridge, 2002).
Regarding the overall model fit, chi-square (i.e. the LR (likelihood ratio) test for the current model
compared to the null model) and the McFadden‟s Pseudo R-square will be used to validate the regression
output.

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2.3 Method of Data Analysis
Both descriptive and econometric method analysis of data was employed in this study. Descriptive
statistics such as mean, percentage, frequency, chi-square and one-way analysis of variance was used to
present demographic features of the finding.
One-way ANOVA hypothesis-testing technique was used to test the equality of two or more means
by examining the variances of samples that are taken. This test allowed us to determine whether the
differences between the samples are simply due to random error (sampling errors) or whether there are a
systematic treatment effect that causes the mean in one group to differ from the mean in another.
Moreover; Pearson's chi-squared test (χ2) was applied to test sets of categorical data to evaluate how likely
it is that any observed difference between the sets arose by chance.
The econometric analysis was done by using the marginal effect of Multinomial Logit regression for
demographic characteristics of consumers, beer quality and price; advertisement, situational influence; and
social and peer groups influence effects on consumers beer brand preference.
Moreover; demographic characteristics of consumers, beer quality and price; advertisement,
situational influence; and social and peer groups influence as independent variables and beer brand
preference as dependent variable were exhaustively tested to meet model specification assumptions. This
model helped us to see the direction of the effect and hidden characteristics of the data. Therefore; validity
of the regression model was carefully tested for independence of irrelevant alternative (IIA),
heteroscedasticity, multicollinearity, autocorrelation, and also for specification errors.
3. RESULTS AND DISCUSSION

3.1 Demographic Characteristics of Respondents'
This sub-section presents the demographic features of 261 sample respondents. These features are
found to be of great help in terms of clearly depicting the diverse background of the respondents on beer
brand preference and the impact this diversity has had on the descriptive and statistical results.
Table 3.1: Respondents Demographic characteristics Inferential and Descriptive Analysis Result
Inferential and Descriptive Analysis of Demographic Characterstics of Sampled Respondents
Bartlett's test for

F-Test Pearson chi2 Test
SN Variable Observation Percent Freq. Mean Std. Dev. equal variances
F Prob > F chi2(3) Prob>chi2 chi2 Pr

Male 216 83%
1 Sex 261 0.828 0.378 0.600 0.618 3.051 0.384 1.804 0.614
Female 45 17%
2 Age 261 38.456 9.757 11.310 0.000 7.171 0.067
Single 58 22%
3 Maerital Status Married 194 74% 261 0.812 0.471 4.790 0.003 31.607 0.000 24.102 0.001
Divorce 9 3%
4 Family Size 261 2.935 1.657 4.860 0.003 19.310 0.000 86.956 0.000
No Formal Education 4 2%
Primary to Secondary Edu 69 26%
5 Educational level 261 2.241 0.898 0.840 0.476 0.068 0.995 31.593 0.000
College Diploma 48 18%
First Degree & Above 140 54%
Source: Own computation
The statistical summary provided in Table 4.1 shows that male respondents 82% (216) is higher than
that of female-headed households 18% (45). The mean age of a typical respondents is about 38 years with
the youngest being 24 and the oldest 60 years old. Majority of respondent attained first degree and above
54% (140), 26% (69) attained primary to secondary education, 18% (48) have attained college diploma and
only 2% (4) have not attained formal education. On average, each respondent has a family size of three;
however the range varies from one to a maximum of nine.

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The summary of one-way ANOVA result above shows that age, family size and marital status of
respondents are statistically significant which means a change in their variance significantly explain the
respondents preferred beer brand variance as a whole. Whereas; respondents' educational status and sex are
statistically insignificant in explaining respondents beer brand preference. Moreover; the Pearson chi2 test
showed that marital status, family size, and educational status are found to significantly affect respondents
beer brand preference. Whereas, sex of the respondent is found to be statistically insignificant.
3.2 Variables that Determine Respondents' Beer Brand Preference

The one-way ANOVA summary test result in the table below shows that respondents perceived beer
quality, perceived beer price, perceived social benefit, peer influence, and exposure to advertisements
tends to have significant different effect on respondents beer brand preference. Whereas; situational
influence tend to have insignificant effect on respondents beer brand preference. Moreover; the Pearson
chi2 test result revealed that perceived beer quality, perceived beer price, perceived social benefit, peer
influence, situational influence, and exposure to advertisements are found to significantly affect
respondents beer brand preference. Summarized test output of each variable was presented below.
Table 3-2: Inferential and Descriptive Analysis Result for Variables that Determine Respondents' Beer
Brand Preference
Descriptive Analysis and Non-Parameteric Tests By Using One-ANOVA and Pearson chi2 Test for Determinants Variables of Beer Brand Preference
Bartlett's test for

Pearson chi2 Test
SN Variable Observation Percent Freq. Mean Std. Dev. F Prob > F equal variances
chi2(3) Prob>chi2 chi2 Pr

Poor Quality Beer 6 2%
Normal Quality Beer 66 25%
1 Percieved Beer Quality 261 3.881 0.716 3.460 0.017 2.269 0.519 16.611 0.055
Good Quality Beer 142 54%
Best Quality Beer 47 18%
cheap 13 5%
Low 39 15%
2 Beer Price Normal 135 52% 261 3.100 0.906 3.340 0.020 30.207 0.000 43.239 0.000
Fair 57 22%
Expensive 17 7%
Bad Social Benefit 46 18%
No Social Benefit 69 26%
3 Percieved Social Benefit 261 2.483 0.897 13.170 0.000 27.319 0.000 66.034 0.000
Normal Social Benefit 120 46%
Fair Social Benefit 26 10%
Poor 19 7%
Low 59 23%
4 Percieved Advertisment Effect Normal 109 42% 261 2.954 0.964 3.540 0.015 16.592 0.001 48.868 0.000
Medium 63 24%
High 11 4%
Very Unlikely 4 2%
Unlikely 7 3%
5 Situational Influence Maybe 97 37% 261 3.625 0.758 1.570 0.198 8.737 0.033 35.537 0.000
Likely 128 49%
Very Likely 25 10%
Very Unlikely 36 14%
Unlikely 49 19%
6 Peer Influence 261 2.640 0.846 5.750 0.000 23.818 0.000 42.224 0.000
Maybe 149 57%
Likely 27 10%
The descriptive result shows that majority of 54% (142) respondents enjoyed good quality beer and
18% (47) enjoy best while only 25% (66) of the respondents perceive their preferred beer is of normal
quality, thus benefited. The remaining 2% (6) of the respondents perceive the beer they consume is of
inferior quality, thus not benefited. The Pearson chi2 and one-way ANOVA test for the perceived beer

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quality or performance benefits on respondents beer brand preference in the table:4-2 shows statistically
significant difference among each categories. Whereas, Bartelet test for equal variance shows statistically
insignificant connection.
The descriptive result shows that the majority of 74% (192) respondents enjoyed normal to fair price
while only 20% (52) of the respondents perceive that they are enjoying cheap to low beer price. The
remaining 7% (17) of the respondents perceive that they are affected by expensive beer price. The Pearson
chi2 and one-way ANOVA test for the perceived beer price on respondents beer brand preference in the
table: 4-2 shows statistically significant difference among each categories.
The descriptive result shows that 46% (120) of the respondents have expressed their agreement to
normal social benefit; whereas 26% (69) of the respondents perceived no benefit at all and 18% (46)
perceived bad social outcomes. The remaining 10% (26) of the respondents perceive fair social benefit.
The Pearson chi2 and one-way ANOVA test for the perceived social benefits on respondents beer brand
preference in the table:4-2 shows statistically significant difference among each categories. Respondents
beer social benefit as a result consuming preferred beer are acceptability, good impression from others,
increased social approval, and emotional reliefs.
The result shows that 42% (109) of the respondents have said do have normal effect, 24% (63)
medium effect, 22% (59) low effect, 7% (19) poor effect and only 4% (11) have high effect. Medium and
high effect of advertisement is seen on St. George 11% (29) and on Habesha 12%(31). Poor and low
advertisement effect is observed on St. George 13% (34) on Habesha 7%(18), on walia 6%(16) and Others
4%(10). As can be seen on the Pearson chi2 test respondents beer brand preference response to
advertisement is statistically significant (Pearson chi2> Pr = 0.000). The one way ANOVA test also
revealed that there is a statistically significant difference with respondents beer preference outcome among
the five degree of advertisement categories (Prob >F= 0.015). Though advertisement is not a sufficient
condition by itself. Advertisement quality is a critical factor too its quality refers to message content,
famous personality involved, and visual effect. These composition can either boost output sales and thus
production or restrain such a capability.
The majority of respondents 58.5% (153) are very likely or likely shift preferred beer on different
events; whereas only 5% (11) of respondents are very unlikely or unlikely to shift beer preference on
different events. Moreover; 37% (97) of the respondents may or may not be affect their beer preference on
different events. Though the one-way ANOVA for the effects situational factors on respondents beer brand
preference is only statistically significant at 80% confidence interval, Pearson chi2 test in the table below
shows statistically significant difference (Pearson chi2> Pr = 0.000). Basically situational factors were
defined as places, events etc... on which beer is consumed for different purposes.
The descriptive result shows that 57% (149) of the respondents may or may not shift their beer
preference by peer influence, 33% (85) of respondents are unlikely to be affected their beer preference by
peer influence, and only 10% (27) of the respondents are likely to affect their beer preference by peer
influence. The Pearson chi2 test and one-way ANOVA for the situational factors on respondents beer
brand preference in the table below shows statistically significant difference among each categories.
3.3 Consumption Volume, Consumption Year and Beer Brand Preference

The table below shows that the summarized analysis result for beer preference, consumption volume
and year of consumption.

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Table: 3-3 Inferential and Descriptive analysis of Beer Preference, Consumption Volume and
Consumption Year
Descriptive Analysis and Non-Parameteric Tests By Using One-ANOVA and Pearson chi2 Test
Bartlett's test for

Pearson chi2 Test
SN Variable Observation Percent Freq. Mean Std. Dev. F Prob > F equal variances
chi2(3) Prob>chi2 chi2 Pr

St. George 104 40%
Habesha 74 28%
1 Beer Brand Preference 261 2.889 1.133
Walia 33 13%
Others 50 19%
1 to 4 Beer at a Time 184 71%
2 Consumption Volume 5 to 10 Beer at a Time 63 24% 261 1.349 0.579 1.910 0.128 9.171 0.027 14.091 0.029
Above 10 Beer at a Time 14 5%
3 Consumption Year 261 8.119 9.062 59.720 0.000 263.127 0.000
The graph below depicted that respondents percentage beer preference for St. George, Habesha,
Others (Meta, Bedele, Harar & Dashen), and Walia is 39.85% (104) , 28.35% (74), 19.16% (50), and
12.64% (33) respectively.
Fig: 3-1 Respondents Beer Preference
19.16%
39.85%
12.64%
28.35%
Others(DashenHararBedeleMeta) Waliya
Habasha StGeorge
The result from these study is comparable with beers previous market share. Data collected by
Fortune in 2014 indicates 38% market share hold by BGI (St George), Heineken which owns Walia, Harar
and Bedele breweries holds 35% of the market and Diageo owner of Meta Abo Brwery, and Dashen
Brewery S.C takes third stage with 27% market share.
The graph below depicted that respondents consumption volume for 1 to 4, 5 to 10 and above 10
beers at a time is 70.5%, 24.14%, and 5.36% respectively. the Person chi2 test result shows that
respondents consumption volume level have statistically significant effect on preferred beer. Whereas, the

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F-test of one-way ANOVA only significant at 13% level of significance. These result seems to have deep
impact on expansion scheme of beer production.
Fig: 3-2 Respondents consumption volume
5.364%
24.14%
70.5%
1 to 4 Beer at a Time 5 to 10 Beer at a Time

Above 10 Beer at a Time
The graph below depicted that respondents mean consumption year for St. George, Others (Meta,
Bedele, Harar & Dashen), Habesha and Walia is is 15, 6.56, 2.27, and 2 respectively. Moreover; the mean
consumption year of a typical respondents is about 8 years with the shortest period of consumption being 1
and the longest period 43 years. Moreover; the one-way ANOVA test result showed consumption year do
have statistically significant effect on respondents beer preference.
Fig: 3-3 Respondents consumption experience
3.4 Multinomial Logit Estimation Result for Determinants of Beer Brand Preference
The likelihood ratio statistics as indicated by chi2 statistics are highly significant (P <0.0000),
suggesting the model has a strong explanatory power. We tested whether the assumption of IIA holds in
our model using the Hausman tests. The result consistently indicates that the assumption is not violated
and hence application of multinomial logit model is appropriate. The Pseudo R2 is 0.68, indicating the
specification fits the data well the variables included in the model explain 68% of the variation in the
respondents beer brand preference. The maximum likelihood estimate for the multinomial logistic

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regression for the probability of preferring St. George, Habesha, Walia and Others as base outcome is
presented in Table 3.4. The result of the MNL regression showed that most of the variables tested for the
probability of respondents beer brand preference had expected sign.
Thus; age, perceived beer quality, perceived social benefit, situational influence and peer influence
had positive sign and significantly affect the probability of preferring St. George. Whereas; family size had
sign and significantly affect the probability of preferring St. George. Nevertheless; sex, age, marital status,
educational level and advertisement had positive sign, but they are statistically insignificant while
perceived beer price of the respondent had negative sign and have statistically insignificant effect on the
probability of preferring St. George.
Advertisement, situational and peer influence had positive sign and significantly affect the
probability of preferring Habesha. Whereas family size had negative sign and significantly affect the
probability of preferring Habesh. Nevertheless; sex, age, marital status, and perceived beer price had
negative sign, but they are statistically insignificant while educational level, perceived beer quality and
perceived social benefit of the respondent had positive sign but they have statistically insignificant effect
on the probability of preferring Habesha.
Advertisement and situational influence had positive sign and significantly affect the probability of
preferring Walia. Whereas sex and marital status had negative sign and significantly affect the probability
of preferring Walia. Nevertheless; age, and peer influence had negative sign, but they are statistically
insignificant while family size, educational level, perceived beer quality and perceived social benefit of the
respondent had positive sign but they have statistically insignificant effect on the probability of preferring
Walia.
Family size, marital status, perceived social benefit and situational influence had positive sign and
significantly affect the probability of preferring Other beers (Harar, Dashen, Meta & Bedele). Whereas age
and peer influence had negative sign and significantly affect the probability of preferring Other beers
(Harar, Dashen, Meta & Bedele). Nevertheless; educational level, perceived beer price, and advertisement
had negative sign, but they are statistically insignificant while sex and perceived beer quality had positive
sign but they have statistically insignificant effect on the probability of preferring Other beers (Harar,
Dashen, Meta & Bedele).

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Table: 3-4 Multinomial Logit Estimates of Respondents' Beer Brand Preference
Multinomial logistic regression Number of obs = 261
LR chi2(33) = 143.61
Prob > chi2 = 0.0000
Log likelihood = -268.03097 Pseudo R2 = 0.6813
St. George
Variables prefered [95% Conf.
Std. Err. z P>Z
beer brand Interval]
Base Outcome Other (Bedele, Meta, Dashen & Harar)
St. George
Sex 0.0885 0.5414 0.1600 0.8700 -1.1496 0.9726
Age 0.0841 0.0269 3.1300 0.0020 0.0314 0.1368
Familysize -1.7363 0.5680 -3.0600 0.0020 -2.8494 -0.6231
Marital Status 0.1307 0.1449 0.9000 0.3670 -0.4146 0.1532
Educational level 0.2854 0.2357 1.2100 0.2260 -0.1765 0.7473
Percieved Beer Quality 0.5992 0.3086 1.9400 0.0520 -1.2041 0.0057
Percieved Beer Price -0.2793 0.2839 -0.9800 0.3250 -0.2770 0.8357
Percieved Social Benefit 1.0782 0.3055 3.5300 0.0000 1.6769 -0.4795
Advertisment Effect 0.2675 0.2228 1.2000 0.2300 -0.1691 0.7042
Situational Influence 0.5019 0.2781 1.8000 0.0710 1.0470 0.0432
Peer Influence 0.5795 0.2584 2.2400 0.0250 0.0730 1.0859
_cons 2.4432 2.2636 0.8800 0.3280 -1.9935 6.8798
Habesha
Sex -0.6105 0.5628 -1.0800 0.2780 -1.7135 0.4925
Age 0.0160 0.0287 0.5600 0.5770 0.0403 0.0724
Familysize -1.7073 0.5831 -2.9300 0.0030 -2.8501 -0.5644
Marital Status -0.1894 0.1742 -1.0900 0.2770 -0.5307 0.1520
Educational level 0.2763 0.2376 1.1600 0.2450 0.1894 0.7421
Percieved Beer Quality -0.0991 0.3341 -0.3000 0.7670 -0.7539 0.5558
Percieved Beer Price 0.1248 0.2930 0.4300 0.6700 0.4495 0.6992
Percieved Social Benefit 0.1029 0.3152 0.3300 0.7440 -0.7206 0.5148
Advertisment Effect 0.2909 0.2380 1.8200 0.1020 0.1756 0.7574
Situational Influence 0.7612 0.3004 2.5300 0.0110 1.3500 -0.1724
Peer Influence 0.8572 0.3089 2.7800 0.0060 0.2518 1.4626
_cons 1.4674 2.3738 0.6200 0.5360 -3.1852 6.1200
Walia
Sex -1.2660 0.7858 -1.6100 0.1070 -2.8061 0.2741
Age -0.0309 0.0337 -0.9200 0.3590 -0.0970 0.0351
Familysize 0.2488 0.6583 0.3800 0.7050 -1.0414 1.5391
Marital Status -1.6916 0.3982 -4.2500 0.0000 -2.4722 -0.9111
Educational level 0.5437 0.3608 1.5100 0.1320 -0.1634 1.2507
Percieved Beer Quality 0.6248 0.5028 1.2400 0.2140 -0.3606 1.6103
Percieved Beer Price -0.2710 0.3897 -0.7000 0.4870 -1.0348 0.4927
Percieved Social Benefit -0.4201 0.3885 -1.0800 0.2800 -1.1814 0.3413
Advertisment Effect 0.8693 0.3352 0.5900 0.0510 1.5264 -0.2123
Situational Influence 0.8471 0.3831 2.2100 0.0270 -1.5980 -0.0962
Peer Influence -0.7411 0.3591 -0.5600 0.2390 -1.4449 -0.0374
_cons 11.1636 3.2916 0.3900 0.7010 4.7121 17.6151
As indicated earlier, the parameter estimates of the MNL model provide only the direction of the
effect of the independent variables on the dependent variable: estimates do not represent actual magnitude
of change or probabilities. Thus, the marginal effects from the MNL, which measure the expected change
in probability of a particular category with respect to a unit change in an independent variable, are reported
and discussed. In all cases the estimated coefficients should be compared with the base category. Table 3.5
presents the marginal effects along with the levels of statistical significance.

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Table 3.5 Marginal effects of the explanatory variables on the probability of beer brand preference
St. George Habesha Walia Others
Variables Margenal Std. Margenal Std. Margenal Std. Margenal Std.

P>Z P>Z P>Z P>Z
Effect Err. Effect Err. Effect Err. Effect Err.
Sex 0.0936 0.5414 0.8700 -0.0983 0.5628 0.2780 -0.0521 0.7858 *0.107 0.0567 0.0661 0.3910
Age 0.0193 0.0269 ***0.002 -0.0078 0.0287 0.5770 -0.0028 0.0337 0.3590 -0.0087 0.0039 **0.028
Familysize -0.2033 0.5680 ***0.002 -0.1213 0.5831 ***0.003 0.0595 0.6583 0.7050 0.2651 0.8019 ***0.001
Marital Status 0.0234 0.1449 0.3670 -0.0023 0.1742 0.2770 -0.0582 0.3982 ***0.000 0.0371 0.0221 *0.093
Educational level 0.0236 0.2357 0.2260 0.0124 0.2376 0.2450 0.0119 0.3608 0.1320 -0.0479 0.0343 0.1620
Percieved Beer Quality 0.1465 0.3086 *0.052 0.0540 0.3341 0.7670 0.0349 0.5028 0.2140 0.0577 0.0458 0.2080
Percieved Beer Price -0.0572 0.2839 0.3250 -0.0090 0.2930 0.6700 -0.0164 0.3897 0.4870 -0.0318 0.0413 0.4410
Percieved Social Benefit 0.2465 0.3055 ***0.000 0.1303 0.3152 0.7440 0.0048 0.3885 0.2800 0.1114 0.0442 **0.012
Advertisment Effect 0.0423 0.2228 0.2300 0.0339 0.2380 *0.102 0.0403 0.3352 *0.051 -0.0360 0.0337 0.2850
Situational Influence 0.0859 0.2781 *0.071 0.0803 0.3004 **0.011 0.0138 0.3831 **0.027 0.1000 0.0405 **0.014
Peer Influence 0.0404 0.2584 **0.025 0.1078 0.3089 ***0.006 -0.0475 0.3591 0.2390 -0.1007 0.0397 **0.011
Source: Own computation from own Survey
Note: ***1% significance level, **5% significance level, *10% significance level
The result indicated that respondents sex decreases the probability of preferring Walia and have no
statistically significant effect on St. George, Habesha and Others (Meta, Bedele, Harar & Dashen)
preference. Thus being female decrease the probability of preferring Walia by 0.05. The result is consistent
with Hartford et al., (1983) finding which involving demographics and drinking behaviors, males tend to
drink in larger quantities in same sex groups, whereas women drink with mixed crowds or with a male.
Moreover; an increase in age by one year significantly increases the probability of preferring St.
George 0.02 where as it decreases the probability of preferring Habesha by 0.03 and Others (Meta, Bedele,
Harar & Dashen) 0.01. According to Blackwell, Miniard & Engal (2006), understanding consumers‟ needs
in marketing analysis is related to age. For instance, Bennett, (2002) study group between ages 25 and 34
prefer to drink standard domestic beer drinkers whereas 35 to 44 year old choose light beer. Older people
drink more than younger people (Midanik et al., 1994).
The result also revealed that being married decrease the probability of preferring Walia. Whereas it
increase the probability of preferring Other beers (Meta, Bedele, Harar & Dashen); and have no
statistically significant effect on St. George and Habesha preference. Thus being married increases the
probability of preferring Others beer (Meta, Bedele, Harar & Dashen) by 0.04 and it decrease the
probability of preferring Walia by 0.06. On the other hand, a change in respondents family size by one
significantly decrease the probability of preferring St. George by 0.2, Habesha by 0.12 where as it
increases the probability of preferring Others (Meta, Bedele, Harar & Dashen) by 0.27.
Educational status of respondents increases the probability of preferring Walia at 15% of
significancy level; and have no statistically significant effect on St. George, Habesha and Others beer
(Meta, Bedele, Harar & Dashen) preference. Thus; educational status increases the probability of
preferring Walia beer by 0.012. This result shows that the educated segment of respondents preferred
Walia more than other. The finding is consistent with Michman, (2003) in which educational achievement
explained purchasing decisions and it was also closely associated with occupation and economic
circumstance. Moreover; Wells & Prensky (1996) claimed that education and occupation might affect the
consumer behavior process of evaluating and choosing of products. For instance, the working class will
choose products based on function and comfort rather than what is trendy, also most of them will not take
risks to try new products. Therefore; the more marketers understand the consumer demographics, the more
they can build the attitude to their brand in order to response the specific requirements of consumers.
Perceived beer quality increase the probability of preferring St. George only and a change in
perceived beer quality scale increases the probability of preferring St. George by 0.15. Perceived beer

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quality include test, production process, health and social outcome from the way it is defined, it is expected
that the beer quality variable is positively related to beer brand preference. Consistent with studies
conducted by Warui & Ngugi, (2013) quality of products, quality of price, and quality of service were all
fundamental influencers of customer satisfaction. Poor quality products for instance, precipitate low
satisfaction levels, with customers preferring to go for other substitute products with higher quality.
Vadlamudi, (2010) also indicated that customers are always looking for value for their money in both the
services and products that they purchase.
As it is expected respondents perceived beer price don't have statistically significant effect on any of
the beer categories' presented. These is basically because; the four categories' of beer under study typically
don't compute on sales price sphere. Ethiopian beer market exhibits similarity of price irrespective of
production cost and product quality. The result deviated from many previous researches. According to Kuo
et al., (2003) study; lowering the price of beer increases drinking rates, but limiting advertising in the area
decreases the rate of binge-drinking overall.
Respondents perceived social benefit has a significant positive effect on the probability of preferring
St. George and Others beer (Meta, Bedele, Harar & Dashen). Thus a change in perceived social benefit
response scale increases the probability of preferring St. George by 0.25 and Others (Meta, Bedele, Harar
& Dashen) by 0.11.
Advertisement significantly increases the probability of preferring Habesha and Walia. Table: 3-5
indicates a change in respondents response scale for advertisement impact revealed that the probability to
prefer Habesha and Walia increases by 0.03 and 0.04 respectively. The result is consistent with the
findings from Kuo et al (2003), Graffe (1997), Dolich, (1969). Katke, (2007) and Mackenzie, (2004)
findings that advertisements inform consumers about the existence and benefits of products and services,
and helps to persuade consumers to buy them. Moreover, Kotler et al., (2005) claim that advertising aim at
attaining target consumers to either think or react to the product or brand. Though, as a method of
achieving advertisement goals, advertisements as well as their content play a vital role in the process of
commercial communication. Homer, (2001) further stated that liking advertising message and content
increases the tendency to like the product. It is clear that consumer may associate characteristics of the
celebrity with attributes of the product which coincide with their needs or desire.
Situational factor has a significant positive effect on the probability of preferring all beer categories.
Thus; a change in respondents situation response scale increase the probability of preferring St. George by
0.09, Habesha by 0.08, Walia by 0.014 and Others beer (Meta, Bedele, Harar & Dashen) by 0.11. In line
with Quester and Smart (1998), Orth (2005), Miller and Ginter (1979) studies involving situational factors
which demonstrated significance based on impacting brand choice. Moreover; areas that have been studied
with situational drivers include product involvement, brand choice, and product attributes.
According to Yang et al., (2002) high product involvement was considered as a factor that influences
behaviors with the interaction of situational drivers. Product factors have different levels of importance to
consumers based on situation. Brand choice has been found to be impacted significantly by situational
factors. Moreover; Yang et al., (2002) finding consider drinking beer as an activity that may occur in
distinct situations so that there should be a clear variance according to their changing environment.
Peer influence has a significant positive effect on the probability of preferring St. George, Habesha;
but it has a significant negative effect on preferring Others beer (Meta, Bedele, Harar & Dashen). Thus; a
change in respondents peer influence increases the probability of preferring St. George by 0.04, Habesha
by 0.11 but it decrease the probability of preferring Others beer (Meta, Bedele, Harar & Dashen) by 0.1.
The result is consistent with previous research findings (Collins et al., (2003); Hoyer and Macinnis,
(2004); Jessor, (1981), Kandel, (1980); Bandura, (1977) and Iyanga, (1998)).
According to Collins et al., (2003) peer influences consist of influential factors determined by family
and friends. In addition, his study indicated adolescents are exposed to peer-pressure and group-think
mentalities, which lead them to consuming brands that their friends and peers consume. Hoyer and
Macinnis, (2004) in their study revealed also that opinion from leaders, family/friend influence, reference
groups, social class, culture, and sub-culture can affect the brands that a consumer purchases. As a result a

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consumer may purchase a higher priced, upscale brand in order to identify and be accepted by a higher
social class. Moreover; according to Jessor, (1981) and Kandel, (1980) peer influence stems from
persuasion by attitudes and behaviors of fellow peers. In addition, Bandura, (1977) revealed that the
behavior of others might remind the individual that alternatives to their own behavior are available.
Therefore, normative influences can have an effect on brand choice for the beer product category.
Throughout research on social behavior, other individuals‟ behaviors may serve as cues which could
increase the potential for behavior. There is a social risk associated with every purchase decision a
consumer makes. This social risk is often associated with what the consumer believes are acceptable
brands based on the brand perceptions in the individual‟s social group. According to Iyanga, (1998) study
it is a group real or imaginary that one looks for guidance in structuring his or her behavior pattern.
4. CONCLUSIONS AND RECOMMENDATION

4.1 Conclusions
Ethiopia with a population closer to 100 million, the per capita consumption of beer stands at eight
liters and is expected to reach nine or 10 by the end of 2016/17, which is very small compared to Kenya‟s
above 15 liters and South Africa and around 60 liters. One of the major actor for the growth of the beer
industry came in the past few years when the government of Ethiopian transferred all state-owned
breweries to private.
These study tried to assess determinants of beer brand preference in Addis Ababa, Ethiopia based on
primary data collected from 261 sampled civil servant respondents. Consumers beer brand preference was
justified on the basis of utility maximization. The study reviewed empirical evidences on factors which
determines beer brand preference in developing countries. The evidence shows that peer influence,
situational factors, advertisements are among the major determinants which affect beer brand preference in
developing countries including Africa. In Ethiopia empirical works show that weak brand loyalty or
inconsistent beer preference due to weak market segmentation and product differentiation.
The respondents in the study area were characterized by a relatively average living standard and
respondents covered in this study were civil servants. Thus, the result revealed that out of a total 261
respondents, beer brand preference result was St. George 40% (104), Habesha 28% (74), Others (Meta,
Bedele, Harar & Dashen) 19% (50) and Walia 13% (33).
The statistical findings from one-way ANOVA and Pearson chi2 showed that age, marital status,
family size, perceived beer quality, perceived beer price, perceived social benefit, advertisement situational
influence and peer influence have statistically significant association with the beer brand preference.
The finding from the multinomial logistic regression revealed what factors determine the probability
attached to respondents beer brand preference. Accordingly; age, perceived beer quality, perceived social
benefit, situational influence and peer influence had positive sign and significantly affect the probability of
preferring St. George. Whereas; family size had sign and significantly affect the probability of preferring
St. George.
Moreover advertisement, situational and peer influence had positive sign and significantly affect the
probability of preferring Habesha. Whereas family size had negative sign and significantly affect the
probability of preferring Habesh.
Finally, advertisement and situational influence had positive sign and significantly affect the
probability of preferring Walia. Whereas sex and marital status had negative sign and significantly affect
the probability of preferring Walia.
4.2 Recommendations
Based on the findings discussed above the following recommendation forwarded:
The company can take a market segmentation strategy and design their products in a manner that
make the products appeal to different categories of individuals. The managers should appreciate the
influence of personal factors on customer satisfaction. In so doing, they should implement a product design
strategy that appeals to greater number of customers.

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A potentially successful strategy can be that which provides products that correspond to and
appreciate customers‟ social status and age. Design a product that appeal to different genders is also a
potentially effective strategy given that women also consume beer.
The advertisement should encourage group purchasing and the positive effect of such purchase
(security, acceptability of choice, championship etc.) and depict friendship situation. The advertisement
should emphasize the situation in which the consumer may find his/herself such as parties and dining out.
Based on the finding it is advised that any advertisement for beer brands should convey information about
the advantages which the brand being advertised would offer over other brands.
Since situational influence was found to be significantly relevant to brand preference of beer,
producers should in their advertisement emphasis social groups. They should exploit this further through
segmenting the market into distinctive social classes.
Managers in the industry should implement policies that will address the external factors that affect
customer satisfaction and should control strategically and use environmental factors such as competition
and market saturation to ensure that they maintain customers‟ loyalty to their products and have a
competitive advantage than their competitors.
Future researchers should conduct more experimental research on customer dynamics in the
breweries industry, principally on how customers perceive satisfaction. Such studies can facilitate the
understanding of customers behavior in the breweries industry.
5. REFERENCE
Aaker, D. (1991& 1996) Managing Brand Equity (New York, NY: The Free Press).
Ali, M. J. (2014). Factors Influencing Marketing of Alcoholic Beverages In Kenya: A Case Study of East African
Breweries. European Journal of Business and Social Sciences. Vol. 3 (2), 122 – 153.
Allison, Ralph I., and Kenneth P. Uhl (1964), “Influence of Beer Brand Identification on Taste Perception,” Journal
of Marketing Research, 1(3), 33-39.
Assmus, Gert, John U. Farley, and Donald R. Lehmann (1984), “How Advertising Affects Sales: Meta- Analysis of
Econometric Results,” Journal of Marketing Research, 21(1), 65-74.
Ayanwale, A.B, Alimini, T and Ayalambe, M.A (2005). The influence of advertising on consumer brand preference.
Journal of Social Science 10(1), 9-16
Babor, T. F., and Mendelson, J. H., Greenberg, I., and Kuehnle, J. (1978), Experimental analysis of the „happy hour:
effects of purchase price on alcohol consumption‟, Psychopharmocology, Vol. 58, pp. 35-41.
Bagwell, Kyle (2007), “The Economic Analysis of Advertising,” Handbook of Industrial Organization, 3, 1701-
1844.
Bain, Joe S. (1950), “Workable Competition in Oligopoly: Theoretical Considerations and Some Empirical
Evidence,” American Economic Review, 40(2), 35-47.
Bandura, A. (1977). Social Learning Theory. New York: Prentice Hall.
Bearden, W. O. and Etzel, M. J. (1982), Reference group influence on product and brand purchase decisions,
Journal of Consumer Research, Vol. 9, No. 2, pp. 183-194.
Becker, Gary S., and Kevin M. Murphy (1988), “A Theory of Rational Addiction,” Journal of Political Economy,
96(4), 675-700.
Belk, R. (1974), An exploratory assessment of situational effects in buyer behavior, Journal of Marketing Research,
Vol. 11, pp. 156-163.
Berkman, Harold W., Jay D. Lindquist, and M. Joseph Sirgy (1997), Consumer Behavior: Concepts and Marketing
Strategy, NTC Business Books, Lincolnwood, IL.
Bovee, L.C, Thill, V.J, Dovel, G.P and Wood, M.B (1995) Advertising Excellence Boston:
Bruijin, B. (2011). Alcohol Marketing Practice In Africa: Findings From the Gambia, Ghana, Nigeria and Uganda.
Utretch, NE: World Health Organization
Casswell, S. (2004, November/December). Alcohol brands in young peoples' everyday lives: New developments in
marketing. Alcohol and Alcoholism, 39(6), 471-476. Retrieved September 15, 2007, from EBSCOhost
database.

Zambrut
Casswell, S., & Zhang, J.-F. (1998). Impact of liking for advertising and brand allegiance on drinking and alcohol-
related aggression: A longitudinal study. Addiction, 93(8), 1209- 1217. Retrieved September 15, 2007, from
Blackwell-Synergy database.
Chalotte, S. (1999) Brand asset management- how business can profit from the power of brand journal of consumer
marketing 19(4), 551-538.
Charlton, P. and Ehrenberg, A. S. C. (1973), McConnell‟s experimental brand choice data, Journal of Marketing
Research, Vol. X, pp. 302-307.
Clare, K., Ramatapa, E. & Currin, B. (2004). Study of the Liquor Industry in South Africa. Study conducted by
Reality Research Africa for the Department of Trade and Industry.
Collins, R. L., Schell, T., Ellickson, P. L., and McCaffrey, D. (2003), Predictors of beer advertising awareness
among eighth graders, Addiction, Vol. 98, pp. 1297-1306.
Dekimpe, Marnik G., Jan-Benedict E. M. Steenkamp, Martin Mellens, and Piet Vanden Abeele (1997), “Decline and
Variability in Brand Loyalty,” International Journal of Research in Marketing, 14(5), 405-420.
Doraszelski, Ulrich, and Sarit Markovich (2007), “Advertising Dynamics and Competitive Advantage,” Rand
Journal of Economics, 38(3), 557-92.29
Dovaliene, A., Gadeikiene, A. & Piligrimiene, Z. (2007). Customer Satisfaction and Its Importance for Long-Term
Relationships with Service Provider: The Case of Odontology Services. Engineering of Economics. Vol. 5
(55), 59 -67.
Ellison, Glenn, and Drew Fudenberg (1995), “Word-of-Mouth Communication and Social Learning,” Quarterly
Journal of Economics, 110(1), 93-125.
Engel, J.F., Blackwell, R.D., and Kollart, D.T (1978) Consumer behavior Illinois: The Dryden press.
Farquhar, P. H. (1989) „Managing Brand Equity‟, Marketing Research, pp. 24 33.Marketing‟, Journal of Marketing,
56 (January), pp. 55–68.
Gianforte, G. (2003). Proactive Customer Service: Seizing Initiative to Exceed Customer Expectations, Cut Cost and
Out-Service The Competition. New York, NY: RightNow Technologies Inc.
Green, C. A., Perrin, N. A., and Polen, M. R. (2004), Gender differences in the relationships between multiple
measures of alcohol consumption and physical and mental health, Alcohol Clin Exp Res, Vol. 28, pp. 754-
764.
Graeff, T. R. (1997, January). Consumption situations and the effects of brand image on consumers' brand
evaluations. Psychology and Marketing, 14(1), 49-70. Retrieved September 16, 2007, from EBSCOhost
database
Hartford, T. C., Weschsler, H., and Rohman, M. (1983), „The structural context of college drinking‟, Journal of
Studies on Alcohol, Vol. 44, pp. 722-732.
Hawkins, D.I., Best, R.J. and Coney, K.A. (2001) Consumer behavior: Building strategy Chicago:
Henning-Thurau, T. & Klee, A. (2010). Customer Satisfaction and Relationship Quality on Customer Retention: A
Critical Reassessment and Modal Development. Oxford, UK: Oxford University Press.
Hoyer, W. D. and MacInnis, D. J. (2004), Consumer Behavior, 3rd Edition, Boston: Houghton Mifflin Company.
Inyanga, J. (2008), Group influence on consumer behavior. Journal of business and Social Sciences 3(1), 69-83.
Jean-Noëlkapferer (2012) the new strategic brand management
Jessor, R. (1981), The perceived treatment environment in psychological theory and Research. In D. Magnusson
(ed.), Toward a Psychology of Situations: An Interactionist Perspective, Hillsdale, NJ: Lawrence Erlbaum
Associates.
Kapferer J.N. (2012) _Brand Marketing_ New Strategic Brand Management
Katke, (2007). The impact of television advertising on child health and family spending. Internation marketing
conference on marketing and society. Retrieved on http://www.itul
Keller, K. (2000) „The Brand Report Card‟, Harvard Business Review, Jan–Feb
Keller, K. (2003) Strategic Brand Management: Building, Measuring, and Managing
Klemperer, Paul (1987), “Markets with Consumer Switching Costs,” Quarterly Journal of Economics, 102(2), 375-
394.
Knibbe, R. A., Oostveen, T., and Van de Goor, I. (1991), Young people‟s alcohol consumption in public places:
Reasoned behavior or related to the situation? British Journal of Addiction, Vol. 86, pp. 1425- 1433.
Kotler (2004), Marketing management: Analyses, planning, implementation and control. New- Delhi: Prentice
hall

Zambrut
Kotler, P. & Keller, K.L. (2011). Marketing Management. 14th edition. Upper Saddle River, NJ: Pearson. Nb 2011
doc.
Kotler, P., & Armstrong, G. (2007). Marketing: An Introduction. (8th Ed.). New York, NY: Pearson Prentice Hall.
Kotler, P., Wong, V., Sanders, J and Armstrong. G. (2005). Principles of Marketing Harlow: Pearson Education
Limited.
Kuo, M., Wechsler, H., Greenberg, P., and Lee, H. (2003), The marketing of alcohol to college students: The role of
low prices and special promotions, American Journal of Preventive Medicine, Vol. 25, No. 3, pp. 204-211.
Lai, A. (1991), Consumption situation and product knowledge in the adoption of a new product, European Journal of
Marketing, Vol. 25, No. 10, pp. 55-67.
Lee,Yang ,Mizerski and Lambert-2015 , on the Strategy of Global Branding and
Ling, Davina C., Ernst R. Berndt, and Margaret K. Kyle (2002), “Deregulating Direct-to- Consumer
Lodish, Leonard M., Magid Abraham, Stuart Kalmenson, Jeanne Livelsberger, Beth Lubetkin, Bruce Richardson,
and Mary Ellen Stevens (1995), “How T.V. Advertising Works: A Meta-Analysis of 389
Mackenzie, (2004). English for business studies and Economics students. Cambridge: Cambridge University Press.
Mason, C. H. (1990). New product enteries and product class demand Marketing science, 3(4), 58-73
Melewar T.C and Elif Karaosmanoglu (2008) Contemporary Thoughts on Corporate Brand and Corporate Identity
ManagementEngland Palgrave MacmillanMurray, Brian H.,‟
Miller, K. E. and Ginter, J. L. (1979), An investigation of situational variation in brand choice behavior and attitude,
Journal of Marketing Research, Vol. XVI, pp. 111-123.
Mordern, A.R. (1991). Elements of marketing. London: D.P publication limited
Musia, Z. M. (2013). Factors Influencing Competitive Advantage By East African Breweries LTD within Beer
Manufacturing Sector in Kenya. Thesis. Project Thesis Submitted to the Nairobi Business School in Partial
Fulfillment of the Requirements for a Masters of Business Administration.
Nderitu, K. M & Ngugi, K. (2014). Effects Of Green Procurement Practices On An Organization Performance In
Manufacturing Industry: Case Study Of East African Breweries Limited. European Journal of Business
Management, 2 (1), 341-352.
Oh, H. (2007). Service Quality, Customer Satisfaction, and Customer Value: A Holistic Perspective. Hospitality
Management. Vol. 18, 67 – 82.
Orth, U. R. (2005), Consumer personality and other factors in situational brand choice variation, Brand
Management, Vol. 13, No. 2, pp. 115-133.
Panchayat, D. (2001), Advertising exposure, loyalty and brand purchase. A two stage model for choice Journal of
marketing research 5(8), 134-144.
Quester, P. G. and Smart, J. (1998), The influence of consumption situation and product involvement over
consumers‟ use of product attributes, Journal of Consumer Marketing, Vol. 15, No. 3, pp. 220-238.
Raju, P. S. (1980), Optimum stimulation level: Its relationship to personality, demographics, and exploratory
behavior, Journal of Consumer Research, Vol. 7, No. 3, pp. 272-282.
Ram, S. and Jung, H. (1989), The link between involvement, use innovativeness and product usage, Advances in
Consumer Research, Vol. 16, pp. 160-166.
Redman, S., Sanson-Fisher, R. W., Wilkinson, C. Fahey, P., and Gibberd, R. W. (1987), Agreement between two
measures of alcohol consumption, Journal of Studies on Alcohol, Vol. 48, pp. 104-108. 127
Rogers, E.M. (1995), Diffusion of innovation New – Jersey: Prentice Hall.
Royo-vela, M(2005). Emotional and informational content of commercials: Visual and Auditory circumplex spaces,
product information and their effects on audience evaluation. Journal of cultural issues and research in
advertising 27(9), 13-38.
Schiffman, L.G and Kanuk, L.L (2009). Consumer behaviour. New Delhi: Prentice hall of India. European Journal
of Business and Management www.iiste.org ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online) Vol.5, No.17,
2013
Schmalensee, R. (1983). Advertising and entering deterrence: An exploratory model Journal of political economy
91(4), 636-653.
Schmalensee, Richard (1982), “Product Differentiation Advantages of Pioneering Brands,” American Economic
Review, 72(3), 349-365.
Schwartz, R. H., Farrow, J. A., Banks, B., and Giesel, A. E. (1998), Use of false ID cards and other deceptive
methods to purchase alcoholic beverages during high school, Journal of Addictive Diseases, Vol. 17, No. 3,
pp. 25-33.

Zambrut
Smith, Michael D., and Erik Brynjolfsson (2001), “Consumer Decision-Making at an Internet Shopbot
Srivastava, R. and A.D. Shocker (1991) „Brand Equity: a Perspective on its Meaning
Stanton, W. J (1981) fundamentals of marketing London: McGraw-Hill inc
Thumin, Frederick J. (1962), “Identification of Cola Beverages,” Journal of Applied Psychology, 36(5), 358-360.
Tornasky, L.O and Klein, K.J. (1982). Innovation characteristics and adoption. Implementation. A meta-analysis
findings IEEE Trans on Engineering Management, 29, 28-46.
Vadlamudi, S. (2010). Breweries Industry in Industry in Transition: Embracing New Markets, Products and
Consumers. White Paper. Tata Consultancy Services. 73
Van Trijp, H. C. M., Hoyer, W. D., and Inman, J. (1996), Why switch? Product category level explanations for true
variety-seeking behavior, Journal of Marketing Research, Vol. 33, No. 3, pp. 281-292.
Van Trijp, H. M. C. (1994), Product-related determinants of variety-seeking behavior for foods. Appetite, Vol. 22,
pp. 1-10.
Vazquez, R., Belen del Rio, R., and Iglesias, V. (2002), Consumer-based brand equity: Development and validation
of a measurement instrument, Journal of Marketing Management, Vol. 18, No. ½, pp. 27- 48.
Wahlers, R. G., Dunn, M. G., and Etzel, M. J. (1986), The congruence of alternative OSL measures with consumer
exploratory behavior tendencies, Advances in Consumer Research, Vol. 13, No. 1, pp. 398- 402.
Walsh, G. and Mitchell, V. (2005), Demographic characteristics to consumers who find it difficult to decide,
Marketing Intelligence and Planning, Vol. 23, No. 2/3, pp. 281-295. 129
Wilkie, W. L. (1986), Consumer Behavior, New York: John Wiley and Sons.
Wooldridge, J.M. (2002): Econometric Analysis of Cross Section and Panel Data. The MIT Press Cambridge,
Massachusetts London, England (page 453-550)
Yang, S., Allenby, M. G., and Fennell, G (2002), Modeling variation in brand preference: The roles of objective
environment and motivating conditions, Marketing Science, Vol. 21,No. 1, pp. 14-21.
Zaichkowsky, J. L. (1985), Familiarity: Product use, involvement or expertise? In E. C.
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Factors Determining Consumer Beer Brand Preference (Study in Addis Ababa,

Article in International Journal of Economics and Business Research · March 2019

Tsegaye Fereja Leykun Birhanu

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Factors Determining Consumer

Keywords: Factors Determining, Consumer, Beer Brand, Preference & Market.

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2. DATA AND METHOD

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2.2 Model Specification

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g ( X ,  )  1  h1 exp( X h ) .......................................................................................................(4)

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3. RESULTS AND DISCUSSION

Bartlett's test for

F Prob > F chi2(3) Prob>chi2 chi2 Pr

Source: Own computation

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3.2 Variables that Determine Respondents' Beer Brand Preference

Bartlett's test for

chi2(3) Prob>chi2 chi2 Pr

Source: Own computation

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3.3 Consumption Volume, Consumption Year and Beer Brand Preference

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Bartlett's test for

chi2(3) Prob>chi2 chi2 Pr

Fig: 3-1 Respondents Beer Preference

Source: Own computation

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Fig: 3-2 Respondents consumption volume

1 to 4 Beer at a Time 5 to 10 Beer at a Time

Source: Own computation

Fig: 3-3 Respondents consumption experience

Source: Own computation

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Source: Own computation

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Variables Margenal Std. Margenal Std. Margenal Std. Margenal Std.

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4. CONCLUSIONS AND RECOMMENDATION

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Zambrut Journal, Link Access;

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