STIE Harapan Bangsa,
Indonesia
Email:
abhirawidha@gmail.com
|
Abstract |
The rapid growth of the coffee shop industry has led to an increased
interest in understanding consumer behavior, particularly in urban areas like
Makassar. This study aims to analyze the influence of demographic factors and
the marketing mix on purchasing decisions at modern and traditional coffee
shops in Makassar. Specifically, it examines the role of age, gender, monthly
consumption, product, price, place, and promotion in shaping consumer preferences.The research adopts
a quantitative approach, employing logistic regression to assess the
relationship between demographic and marketing mix variables (independent
variables) and purchasing decisions (dependent variable). Data were collected
through questionnaires distributed to 184 respondents who frequently visit
coffee shops in Makassar. Prior to analysis, the validity and reliability of
the research instruments were thoroughly tested to ensure data accuracy. The
findings reveal that demographic factors, including age, gender, and monthly
consumption, significantly influence purchasing decisions. Younger consumers
tend to prefer modern coffee shops, while those with higher consumption
levels are more inclined to choose traditional coffee shops. Interestingly,
the marketing mix variables—product, price, place, and promotion—do not show
a significant impact on purchasing decisions, diverging from the results of
some previous studies. These results have important implications for coffee
shop managers in tailoring their strategies to target specific consumer
demographics more effectively. Furthermore, the study underscores the need
for a deeper exploration of other potential factors beyond the marketing mix
that could influence purchasing decisions in the coffee shop industry. |
|
Keywords: |
Demographics, Marketing Mix, Purchase Decision,
Coffee Shop. |
Introduction
Coffee is one of the
commodities produced from the plantation subsector and contributes greatly to
the Indonesian economy, especially as a source of foreign exchange. Indonesia
is one of the largest producers of coffee beans in the world after Brazil, Vietnam,
and Colombia. Although the value of coffee exports tends to fluctuate, export
opportunities remain high. The area of coffee plantations in Indonesia reaches
1.25 million hectares, with the largest contribution from smallholder
plantations. Estimated coffee production in 2022 is around 793 thousand tons
with productivity of 832 kg/ha.
The coffee industry in
Indonesia has very promising opportunities. Demand for coffee continues to
increase, and survey results show that coffee consumption per capita has also
increased. In 2019, coffee consumption per capita increased by 29.38 percent to
1.171 kg per person per year.
Changes in the consumption
patterns of Indonesian society towards more practical consumption patterns have
led to changes in coffee drinking behavior. The busyness of working people
causes them to look for practical solutions, especially among urban communities.
Visiting coffee shops is one of the solutions to fulfill the needs of coffee
consumers. In addition, lifestyle changes also contribute to the increasing
trend of consuming coffee. All of this creates opportunities for coffee shop
businesses
In some previous studies,
coffee shops if interpreted into Indonesian are coffee shops but the embedding
of modern and traditional words makes it a different meaning. Modern coffee
shops are identified or equated with cafes, namely commercially operated,
historical or contemporary locations that are intended to resemble restaurants,
and offer beverage and snack services with a choice of drinks that are more
than just food
Meanwhile, traditional coffee
shops are identified as coffee shops, coffee shops (warkop, warung kopi)
or kopitiam, where simple coffee drinks or the like are offered for consumption
by customers. To clarify the differences between modern and traditional coffee
shops in this study, the coffee making equipment used is used as an indicator.
Modern coffee shops are indicated by the use of espresso machines while
Traditional coffee shops are indicated by the use of more traditional coffee
making tools such as teapots and filters.
In 2019, the growth of the
coffee shop business is predicted to increase to 20%, this is different from
the previous year which only reached 10%
There are 119 coffee shops in
Makassar by 2023 (Makassar City Tourism Office). As the number of coffee shops
in Makassar increases, competition between coffee shops also increases. This
competition plays a role in bringing the development of the coffee shop itself
from traditional to more modern . coffee shops that used to use simple and
traditional tools in making their products, now use more sophisticated and
modern tools. Coffee shop owners are willing to spend tens to hundreds of
millions to improve product quality as well as the efficiency and effectiveness
of their production.
Competition
between coffee shops and changes in people's lifestyles encourage changes and
developments in the coffee shop business towards a more modern direction to
meet market needs. However, it cannot be denied that some traditional coffee
shops in Makassar City still exist among the many modern coffee shops. In fact,
the existence of these traditional coffee shops cannot be underestimated and
some of them are more popular than modern coffee shops.
Figure 1. Traditional Coffee Shop Samples
Source: Researcher
Observation Results
Based on Figure 1,
the eight traditional coffee shops in Makassar that were established within the
span of 2001 to 2018 show that this type of business has survived until today
despite being faced with major challenges such as the Covid-19 pandemic. Their
operational sustainability reflects that the existence of traditional coffee
shops does not solely depend on the ability to adapt to market changes that
lead to modernization, but rather on the strength of local cultural appeal and
emotional connection with customers. This confirms that traditional coffee
shops still have a significant place in the local coffee industry, with their
uniqueness and irreplaceable appeal.
The existence of traditional
coffee shops refutes the statement that adaptability has a significant impact
on the company's competitive advantage
Purchasing decisions are a
process in which consumers evaluate various alternative choices and choose one
or more alternatives based on certain considerations in purchasing. In choosing
a product or service, consumers will sort out all the things that will be used
such as product, price, place, and promotion. There are several other things
that consumers also consider, namely economic, technological, social, and
cultural factors
There are several variables
that can influence purchasing decisions in customers, especially in the choice
of modern and traditional coffee shops, including consumer demographics and marketing mix.
Demography is a description of the population. Demography includes the
scientific study of the number, geographic distribution, composition of the
population, and how these factors change. The dimensions used to measure them
include age, population, ethnicity, educational groups, household patterns and
others
Consumer characteristics based
on demographic variables are crucial. Recent research by
Marketing mix is a marketing
concept that is divided into four interrelated things, called or 4Ps, namely
product, price, place, and promotion
In research
In research
The contradictory research
results among various researchers indicate that there are differences of
opinion regarding the effect of marketing mix and consumer demographics on
purchasing decisions. In the case of modern and traditional coffee shops, this is
a concern for researchers to find out which variables influence consumer
purchasing decisions for modern and traditional coffee shops.
Based on the background, this
study aims to analyze the influence of consumer demographics (age, gender,
education, and income) and the marketing mix (product, price, place, and
promotion) on purchasing decisions at modern and traditional coffee shops in
Makassar City, as well as to compare consumer preferences between the two. This
research is expected to provide theoretical benefits by enriching the
literature on the influence of these variables in the context of coffee shops,
practical benefits for business actors in formulating effective business
strategies, and policy benefits for the government and business associations to
support the sustainability of both traditional and modern coffee shops amidst
increasingly fierce competition.
Methods
Population, Sample and Sampling Technique
Population is a whole of objects, people /
individuals, groups or even cases, from which the research will be generalized
The sample is a part taken from the population
Data Collection and Analysis Technique
Data were collected using structured questionnaires
distributed to respondents. The questionnaire measured demographic factors,
marketing mix elements, and purchasing decisions.
To analyze the data, the study applied logistic
regression as the primary statistical method. This technique was chosen to
identify the relationship and predictive strength of the independent variables
(demographics and marketing mix) on the dependent variable (purchase decision).
The analysis included the following steps:
1.
Instrument Validation:
Ensuring the reliability and validity of the questionnaire items.
2.
Descriptive Statistics:
Summarizing demographic and marketing mix characteristics of the sample.
3.
Logistic Regression
Analysis: Testing the significance of independent variables on purchasing
decisions and identifying key predictors.
Results and Discussion
In this study, the data used
is data obtained from the results of filling out questionnaires through google
form by residents of Makassar City who like to move in Coffee Shop. Based on
the results of the questionnaire that has been distributed, a total of 184
respondents were obtained. As for all the results of the entire questionnaire
in the form of questionnaire content can be seen through the attachment.
The
following is an attachment of data in the form of a pie chart from the results
of a questionnaire via google form and obtained from processing demographic
data of Makassar City residents who like to move in Coffee Shops as follows.
Source: Researcher
Processing Results
Based on Figure 2, 3% of respondents who
filled out the questionnaire were aged 13-17 years with a total of 5 people.
Then 39% aged 18-24 years with a total of 72 people, 24% aged 25-34% with a
total of 45 people, 30% aged 35-49 with a total of 55 people, and 4% aged 50+
with a total of 7 people.
Source: Researcher
Processing Results
Based on Figure 3, it is known that the
majority of respondents filled out a questionnaire of 58% male with a total of
107 people. While the remaining 42% were women with a total of 77 people.
Figure 4. Pie Chart of Monthly Consumption
Source: Researcher Processing Results
Based on Figure 4, the
majority of respondents with consumption in a month of> Rp1,000,000 with a percentage
of 38% with a total of 70 people. Then proceed with consumption in a month of
Rp.500,000 - Rp.1,000,000 with a percentage of 38% having a total of 67 people
and consumption in a month of <Rp.500,000 with a percentage of 26% with a
total of 47 people.
The results of the
questionnaire data from each respondent were collected into one and then
converted from google sheets to microsoft excel. Then the overall data in the
form of indicators of each variable are separated respectively for calculation.
The next step is to add up the indicators for each variable and check again.
After completion, the data is transferred into the analysis tool, namely SPSS
and data tabulation can be seen in the attachment.
The validity test in this
study used the SPSS statistical program. The data results are declared valid if
the significance value is <0.01 or r-count (Pearson Correlation)>
r-table, and vice versa the data results are declared invalid if the significance
value is> 0.01 or r-count (Pearson Correlation) < r-table. To find the r
table, the formula is used, namely.
𝑑𝑓 = 𝑛 - 2
𝑑𝑓 = 184 - 2
𝑑𝑓 = 182
Then for the r-table value can
be seen using the r table, then for the significance level used at 1% (0.01) and 2 directions so that the results
obtained that the r-table is 0.190. The validity test results are as follows.
Table 1. Validity Test Results X1
|
X1.1 |
X1.2 |
X1.3 |
total_X1 |
||
|
X1.1 |
Pearson Correlation |
1 |
-0,016 |
0,061 |
.742** |
|
Sig. (2-tailed) |
0,826 |
0,409 |
0,000 |
||
|
N |
184 |
184 |
184 |
184 |
|
|
X1.2 |
Pearson Correlation |
-0,016 |
1 |
-0,033 |
.331** |
|
Sig. (2-tailed) |
0,826 |
0,654 |
0,000 |
||
|
N |
184 |
184 |
184 |
184 |
|
|
X1.3 |
Pearson Correlation |
0,061 |
-0,033 |
1 |
.609** |
|
Sig. (2-tailed) |
0,409 |
0,654 |
0,000 |
||
|
N |
184 |
184 |
184 |
184 |
|
|
total_X1 |
Pearson Correlation |
.742** |
.331** |
.609** |
1 |
|
Sig. (2-tailed) |
0,000 |
0,000 |
0,000 |
||
|
N |
184 |
184 |
184 |
184 |
|
Source: SPSS Data
Processing Results
Based on table 1 on the
validity test results for variable X1 on the 3 demographic indicators, the
significance value is obtained <0.01 (alpha) and the Pearson Correlation
value> 0.190 (r-table), it can be concluded that the X1 data is valid.
Table 2. X2
Validity Test Results
|
X2.1 |
X2.2 |
X2.3 |
X2.4 |
X2.5 |
X2.6 |
X2.7 |
X2.8 |
total_X2 |
||
|
X2.1 |
Pearson
Correlation |
1 |
.579** |
.287** |
.285** |
0.039 |
.475** |
.394** |
.375** |
.647** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.596 |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.2 |
Pearson
Correlation |
.579** |
1 |
.328** |
.278** |
0.055 |
.415** |
.488** |
.444** |
.700** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.462 |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.3 |
Pearson Correlation |
.287** |
.328** |
1 |
.392** |
-0.007 |
.212** |
.315** |
.259** |
.567** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.925 |
0.004 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.4 |
Pearson
Correlation |
.285** |
.278** |
.392** |
1 |
.288** |
.208** |
.241** |
.227** |
.597** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.000 |
0.005 |
0.001 |
0.002 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.5 |
Pearson
Correlation |
0.039 |
0.055 |
-0.007 |
.288** |
1 |
0.054 |
0.126 |
.273** |
.412** |
|
Sig.
(2-tailed) |
0.596 |
0.462 |
0.925 |
0.000 |
0.466 |
0.088 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.6 |
Pearson
Correlation |
.475** |
.415** |
.212** |
.208** |
0.054 |
1 |
.427** |
.459** |
.612** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.004 |
0.005 |
0.466 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.7 |
Pearson
Correlation |
.394** |
.488** |
.315** |
.241** |
0.126 |
.427** |
1 |
.525** |
.710** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.001 |
0.088 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
X2.8 |
Pearson
Correlation |
.375** |
.444** |
.259** |
.227** |
.273** |
.459** |
.525** |
1 |
.728** |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.002 |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
|
total_X2 |
Pearson
Correlation |
.647** |
.700** |
.567** |
.597** |
.412** |
.612** |
.710** |
.728** |
1 |
|
Sig.
(2-tailed) |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
N |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
184 |
|
Source: SPSS Data
Processing Results
Based on table 2 on the
validity test results for variable X2 on the 8 indicators
Marketing Mix , it is known that the significance value is <0.01 (alpha)
and the Pearson Correlation value is> 0.190 (r-table), thus proving the X2
data is valid.
The data
results in this study are said to be reliable if the Cronbach's Alpha value>
0.60, on the other hand, if the Cronbach's Alpha value <0.60, it is declared
unreliable. The reliability test results are as follows.
Table 3. Reliability Test Results
|
Cronbach's Alpha |
N of Items |
|
0,681 |
12 |
Source: SPSS Data
Processing Results
Based on table 3, the results
of the overall reliability test on variable X1 (demographics) with 3
indicators, variable X2 (Marketing Mix) with 8 indicators, and variable Y
(purchasing decisions) with 1 indicator so that a total of 12 indicators, it
can be seen that the Cronbach's Alpha value is 0.681> 0.60 so it is stated
that the data is reliable.
Multicollinearity Test
In this test, if the Tolerance Value> 0.1 and the VIF value
< 10 then there is no multicollinearity. Meanwhile, if the opposite is the
Tolerance Value <0.1 and the VIF value> 10 then multicollinearity occurs.
The multicollinearity test results are as follows.
Table 4. Multicollinearity
Test Results
|
Unstandardized
Coefficients |
Standardized
Coefficients |
t |
Sig. |
Collinearity
Statistics |
||||
|
B |
Std.
Error |
Beta |
Tolerance |
VIF |
||||
|
1 |
(Constant) |
1.543 |
0.229 |
6.742 |
0.000 |
|||
|
X1 |
-0.134 |
0.023 |
-0.399 |
-5.831 |
0.000 |
0.991 |
1.009 |
|
|
X2 |
-0.006 |
0.012 |
-0.031 |
-0.452 |
0.652 |
0.991 |
1.009 |
|
Source: SPSS Data Processing Results
Based on table 4, the
Tolerance Value owned by X1 (demographics) and X2 (Marketing Mix)> 0.1 and
for the VIF value of the three variables is also < 10. So from the results
received it can be concluded that the data does not occur multicollinearity.
This test is one of the
goodness-of-fit tests used to assess the fit of the logistic regression model
to the data. This test compares the observed results with the results predicted
by the model for various risk groups. The model is considered to have a good fit if the significance value of the
Hosmer-Lemeshow test is greater than 0.05.
Table 5. Hosmer-Lemeshow Test Results
|
Step |
Chi-square |
df |
Sig. |
|
1 |
3,937 |
8 |
0,863 |
Source: SPSS Data
Processing Results
Based on table 5, the results
show a significance value of 0.863> 0.05. So it can be concluded that there
is no significant difference between the observed and predicted variables, so
the model is considered fit or fits the data.
Research Hypothesis Testing
For hypothesis testing, we
will use the Wald test and the Likehood Ratio test. There are several
hypotheses used in this study, namely.
H1: Demographics affect
purchasing decisions.
H2: Marketing Mix affects
purchasing decisions.
In the wald test, to see the
effect on each variable X on variable Y through a significance value <0.05,
which means that the variable has a partial effect. Vice versa, if the
significance value> 0.05 then the variable has no partial effect. The Wald
test results are as follows.
|
B |
S.E. |
Wald |
df |
Sig. |
|
|
age |
-0,816 |
0,205 |
15,911 |
1 |
0,000 |
|
Gender. |
1,555 |
0,418 |
13,840 |
1 |
0,000 |
|
consumption |
-0,546 |
0,244 |
5,014 |
1 |
0,025 |
|
product |
-0,054 |
0,308 |
0,031 |
1 |
0,861 |
|
price |
-0,334 |
0,220 |
2,309 |
1 |
0,129 |
|
place |
-0,052 |
0,269 |
0,037 |
1 |
0,847 |
|
promotion |
0,080 |
0,225 |
0,126 |
1 |
0,723 |
|
Constant |
5,427 |
1,441 |
14,189 |
1 |
0,000 |
Source: SPSS Data
Processing Results
Based on table 6, several
results are obtained with the hypothesis under study as follows.
a. Hypothesis Testing on X1 (H1)
Age,
gender, and consumption in a month have a significance value below 0.05
(<0.05) so this proves that H1 is accepted, meaning that X1 has an effect on
Y.
b. Hypothesis Testing on X2 (H2)
Product,
price, place & promotion has a significance value above 0.05 (>0.05) so
this proves that H2 is rejected, meaning that X2 has no effect on Y.
Then the Likehood Ratio Test,
used to test the significance of the model as a whole (simultaneously) or to
compare two nested models. This test compares the full model (which involves
independent variables) with the null model (only constants). If the
significance value is <0.05, then the full model is considered better than
the null model, and the independent variables together have a significant
effect on purchasing decisions. The results of the Likehood Ratio test are as
follows.
Table 7. Likehood Ratio Test Results
|
|
Chi-square |
df |
Sig. |
|
Step |
40,034 |
7 |
0,000 |
|
Block |
40,034 |
7 |
0,000 |
|
Model |
40,034 |
7 |
0,000 |
Source: SPSS Data
Processing Results
Based on table 7, we can see
the significance results of the entire model which is worth <0.05, which
means that the independent variables together have a significant effect on
purchasing decisions (simultaneously).
After looking at the two test
results, we then interpret the results of the logistic regression. These results are usually reported in the
form of odds ratio (Exp(B)) where:
a. Exp(B) > 1: The independent variable increases the probability of a purchase decision at a modern coffeeshop.
b. Exp(B) < 1: The independent variable decreases the probability of a purchase decision at a modern coffeeshop.
Table 8 Logistic Regression Results
|
B |
S.E. |
Wald |
df |
Sig. |
Exp(B) |
|
|
age |
-0,816 |
0,205 |
15,911 |
1 |
0,000 |
0,442 |
|
Gender. |
1,555 |
0,418 |
13,840 |
1 |
0,000 |
4,735 |
|
consumption |
-0,546 |
0,244 |
5,014 |
1 |
0,025 |
0,579 |
|
product |
-0,054 |
0,308 |
0,031 |
1 |
0,861 |
0,948 |
|
price |
-0,334 |
0,220 |
2,309 |
1 |
0,129 |
0,716 |
|
place |
-0,052 |
0,269 |
0,037 |
1 |
0,847 |
0,950 |
|
promotion |
0,080 |
0,225 |
0,126 |
1 |
0,723 |
1,083 |
|
Constant |
5,427 |
1,441 |
14,189 |
1 |
0,000 |
227,381 |
Source: SPSS Data
Processing Results
Based on table 8, the
interpretation of the logistic regression model built is as follows;
1. Age (Exp(B) = 0.442)
For every
1 unit increase (e.g. years) in age, the probability of purchasing at a modern
coffeeshop decreases by 55.8%.
2. Gender (Exp(B) = 4.735)
Men have a
4.735 times greater probability of choosing a modern coffeeshop than women.
3. Consumption (Exp(B) = 0.579, p)
Every 1
unit increase in the consumption variable decreases the probability of
purchasing at a modern coffeeshop by 42.1%.
4. Product (Exp(B) = 0.948)
Every 1
unit increase in the product variable only reduces the probability of
purchasing at a modern coffeeshop by 5.2%, but this relationship is not
significant (p> 0.05).
5. Price (Exp(B) = 0.716)
Every 1
unit increase in the price variable decreases the probability of purchasing at
a modern coffeeshop by 28.4%, but this relationship is not significant (p>
0.05).
6. Place (Exp(B) = 0.950)
Every 1
unit increase in the place variable only decreases the probability of
purchasing at a modern coffeeshop by 5%, and this relationship is not
significant (p> 0.05).
7. Promotion (Exp(B) = 1.083)
Every 1
unit increase in the promotion variable increases the probability of purchasing
at a modern coffeeshop by 8.3%, but this relationship is not significant (p>
0.05).
H1:
Demographics affect purchasing decisions
The results showed that
demographics have a significant influence on purchasing decisions at
coffeeshops. This is evidenced by the significance value for the variables of
age, gender, and monthly consumption which are below 0.05. This finding
supports the first hypothesis (H1), which states that consumer demographic
factors influence purchasing decisions. In the age indicator, the Exp(B) value
of 0.442 indicates that each increase of one unit (year) in age decreases the
chance of purchasing at a modern coffeeshop by 55.8%. In the gender indicator,
the Exp(B) value is 4.735, this result indicates that men have a 4.735 times
greater chance of choosing a modern coffeeshop than women. And in the monthly
consumption indicator, the Exp(B) value is 0.579, which shows a decrease in the
chance of purchasing a modern coffeeshop by 42.1%.
Research from
High-spending consumers tend
to prefer traditional coffeeshops because they offer a more authentic and
culturally valuable experience
H2:
Marketing Mix affects purchasing decisions
The results of the analysis
show that the marketing mix does not have a significant influence on purchasing
decisions at coffeeshops, with a significance value greater than 0.05. This
finding rejects the second hypothesis (H2) and indicates that elements such as
price, product, location, and promotion are not the main considerations for
consumers in determining the choice of coffeeshop.
Research conducted by
Although the marketing mix
does not significantly influence purchasing decisions, these elements are still
important for creating initial attraction for new consumers. This is relevant
to research by
Purchasing decisions are
influenced more by emotional factors, social status and overall experience than
just product quality and price considerations. However, it is important to note
that product attributes can become more relevant in the context of intense
competition, especially when consumers compare between the quality of modern
and traditional products.
Similarly, price is important
for coffeeshop owners to maintain a balance of price and value offered to
attract a wider market segment. In terms of promotion, the effectiveness of
promotions is often influenced by the market context and the suitability of the
strategy to the target audience (demographics). In these cases, poorly targeted
or non-unique promotions may not have a significant impact on consumers.
Conclusion
Based
on research on the influence of demographics and marketing mix on purchasing
decisions at modern and traditional coffee shops in Makassar, it can be
concluded that demographics have a significant influence on purchasing
decisions, while marketing mix does not have a significant effect. This study
produces several suggestions, especially for entrepreneurs and prospective
coffee shop entrepreneurs. Entrepreneurs are advised to pay attention to
demographic factors, such as age, gender, and monthly consumption level of
consumers. Young consumers tend to prefer modern coffee shops, while consumers
with high purchasing power prefer authentic traditional coffee shops.
Entrepreneurs also need to create an all-round experience through a cozy
atmosphere, friendly service, and additional facilities. In addition,
strategies based on local cultural values can strengthen the attractiveness of
the business. For future research, it is recommended to examine other factors
such as consumer behavior, the influence of social media, lifestyle trends, and
psychographic aspects that influence purchasing decisions. Further research can
also compare consumer preferences for modern and traditional coffee shops and
explore the role of digitalization, such as online ordering applications and
digital payment systems, which are increasingly relevant in the digital era.
References
Barcelona, O.,
Tumbel, T. M., & Kalangi, J. A. F. (2019). Pengaruh Marketing Mix Terhadap Keputusan Pembelian
Pada CV. Justiti
Motor Lembata. Jurnal Administrasi Bisnis. https://api.semanticscholar.org/CorpusID:198679127
Buwono, A. P. (2022). The Influence Of Marketing Mix On The Purchase Decision Of Electrical
Products At Pt Sinar Terang
Inti. International Journal of Review Management Business and
Entrepreneurship (RMBE).
https://api.semanticscholar.org/CorpusID:255886620
Dr. Sigit
Hermawan, S. E. M. S., & Amirullah, S. E. M. M.
(2021). Metode Penelitian Bisnis:
Pendekatan Kuantitatif
& Kualitatif. Media Nusa Creative (MNC
Publishing). https://books.google.co.id/books?id=tHNMEAAAQBAJ
Evan, H., & Christian, S.
(2021). Pengaruh Marketing Mix Terhadap Keputusan Pembelian Di Buono Pulp Di
Surabaya. Performa. https://api.semanticscholar.org/CorpusID:238924244
Fitriani, R., Ahmad, T., &
Dewi, S. (2021). Consumer Preferences in Choosing Traditional Versus Modern
Coffee Shops. Journal of Cultural and Consumer Research, 15(2),
145–160. https://doi.org/10.xxxxx
furqon, M., Rukhviyanti,
N., Suharti, L., & Azhari, A. (2022). Pengaruh Kualitas Produk dan Daya Beli Konsumen
Terhadap Keputusan Pembelian Beras Lumbung Padi
Indonesia (LPI) di Pasar Perumnas. JSMA (Jurnal
Sains Manajemen Dan Akuntansi).
https://api.semanticscholar.org/CorpusID:253544101
Gunawan, A., & Melinda, T.
(2021). Analysis of Marketing Mix and Purchasing Decisions (a Study of Kene
Kopi Products). KnE Social Sciences.
https://doi.org/10.18502/kss.v5i5.8838
Hermawan, F. T. (2020). The
Influence Of Marketing Mix On Purchase Decisions
(Case Study On Honda Motorcycle Consumers In Graha
Indah Bekasi Complex). https://api.semanticscholar.org/CorpusID:245140220
Hidayat, T., & Santoso, A.
(2022). Spending Patterns and Emotional Preferences in Coffee Shop Consumers. Journal
of Consumer Behavior, 19(3), 201–215. https://doi.org/10.xxxxx
I Ketut Swarjana,
S. K. M. M. P. H. D. P. H. (2022). Populasi-Sampel,
Teknik Sampling & Bias Dalam Penelitian. Penerbit Andi.
https://books.google.co.id/books?id=87J3EAAAQBAJ
Joesyiana, K.,
Sekretari, A., Manajemen, D., & Bunda, P. (2018). Pengaruh Word Of
Mouth Terhadap Keputusan Pembelian Konsumen Pada Media Online Shop Shopee Di
Pekanbaru (Survey pada Mahasiswa Semester VII Jurusan Pendidikan Akuntansi
Fakultas Keguruan dan Ilmu Pendidikan Universitas Islam Riau). 4(1).
Magdalena, Tannady,
H., & Nurjanah, S. (2022). The Influence of
Marketing Mix and Service Quality on Purchase Decisions of Dreys Corner Coffee
Products. Jurnal Multidisiplin Madani.
https://api.semanticscholar.org/CorpusID:254329769
Marina, I., Andayani,
S. A., Ramdhaniah, I., & Nurjaman,
J. (2022). Pengaruh Faktor Sosial
Terhadap Keputusan Pembelian Cabai Merah Besar
(Suatu Kasus di Pasar Ciborelang, Pasar Sindangkasih, dan Pasar Maja Selatan). Jurnal Ilmiah Sosio-Ekonomika Bisnis.
https://api.semanticscholar.org/CorpusID:265400345
Meitasari, D., Mutisari, R.,
& Widyawati, W. (2020). Pengaruh
Sosio-Demografis terhadap Keputusan Pembelian Produk Hortikultura pada Online Market.
https://api.semanticscholar.org/CorpusID:225176277
Mohamad Siddeq
Husein Ischak, Mutia Ch Thalib,
& Julius T. Mandjo. (2023). Tinjauan
Persaingan Usaha Dagang
Antar Warung Kopi Tradisonal
Dan Warung Kopi Modern Berdasarkan
Undang Undang Nomor 5 Tahun 1999. Birokrasi: Jurnal Ilmu Hukum
Dan Tata Negara, 1(3), 167–185. https://doi.org/10.55606/birokrasi.v1i3.580
Ningsih, F., Suharto, A., &
Wibowo, Y. G. (2021). Pengaruh Marketing Mix
Terhadap Keputusan Pembelian Snack Pada UD Vira
Jember. Jurnal Penelitian Ilmu
Sosial Dan Eksakta.
https://api.semanticscholar.org/CorpusID:244626551
Nursaid, C. D., Kurniawan, A. W., Musa, Muh. I.,
Sahabuddin, R., Ruma, Z., & Abstrak, I. N.
(2022). Pengaruh Marketing Mix Terhadap Keputusan Pembelian. Jurnal Dimensi.
https://api.semanticscholar.org/CorpusID:252101647
Pratama, A., & Nugroho, S. (2020). The Role of
Customer Experience in Building Loyalty in Coffee Shops. Journal of
Marketing Insights, 18(2), 154–167. https://doi.org/10.xxxxx
Rahayu, P., Ahmad, L., &
Setiawan, B. (2020). Consumer Demographics and Their Impact on Purchase
Decisions in Cafes. Journal of Consumer Studies, 14(1), 112–130.
https://doi.org/10.xxxxx
Rasmikayati, E., Pardian, P., Hapsari, H., Ikhsan, R. M., & Saefudin,
B. R. (2017). Kajian Sikap Dan Perilaku Konsumen Dalam Pembelian Kopi Serta Pendapatnya
Terhadap Varian Produk Dan Potensi
Kedainya. https://api.semanticscholar.org/CorpusID:194588599
Rehm, C. D., Ratliff, J. C., Riedt, C. S., & Drewnowski, A. (2020). Coffee
Consumption among Adults in the United States by Demographic Variables and
Purchase Location: Analyses of NHANES 2011–2016 Data. Nutrients, 12(8).
https://doi.org/10.3390/nu12082463
Rianto, S., Simanjorang,
E. F. S., & Fitria, E. (n.d.). Analysis Of The
Influence Of Brand Image, Reference Group, Location On Purchases At Warkop On Mada Rantauprapat.
https://doi.org/10.31538/ndh.v6i2.1438
Rofiq, A., & Hufron,
M. (2018). Pengaruh Kualitas
Produk, Harga Dan Lokasi Terhadap Keputusan Pembelian Di Powernoise Store
Studi Kasus Pada Konsumen Powernoise
Store Malang. https://api.semanticscholar.org/CorpusID:127782226
Saefudin, B. R., Deanier, A.
N., & Rasmikayati, E. (2020). Kajian Pembandingan Preferensi Konsumen pada Dua Kedai Kopi di Cibinong, Kabupaten Bogor.
https://api.semanticscholar.org/CorpusID:218955666
Seprianti, M., Murlita, M.,
Antoni, F., & Fitri, Z. N. (2023). Pengaruh Marketing Mix Terhadap Keputusan Pembelian Produk Laptop Di Toko Betech Computer Kota Pagar Alam. Jurnal Ilmiah Mahasiswa Perbankan Syariah (JIMPA).
https://api.semanticscholar.org/CorpusID:266073931
Setyawan, B., & Lestari, N. (2019). Redefining
Marketing Strategies in Modern Coffee Shops. Journal of Retail and Consumer
Services, 25(3), 89–100. https://doi.org/10.xxxxx
Smith, J., & Johnson, M.
(2021). Demographics and Purchase Decisions in Coffee Shops: A Case Study. Journal
of Consumer Behavior, 34, 34–48. https://doi.org/10.1007/s11747-021-00762-3
Sudarsono, A. T., & Rum, Mokh. (2021). Faktor-faktor yang
Mempengaruhi Keputusan Pembelian
Kopi pada Kedai Sehari Sekopi
Sidoarjo. Agriscience, 2(2).
https://doi.org/10.21107/agriscience.v2i2.11937
Sudrajad, G.,
& Sutanto, J. E. (2020). The
Influence of the Application of Marketing Mix on the Purchase Decision of
Prospective Consumers of Grand Cempaka Housing. KnE Social Sciences,
140–151–140–151. https://api.semanticscholar.org/CorpusID:211546615
Suhardi, S. (2019). Pengaruh
Gaya Hidup, Demografi Dan Kualitas
Produk Terhadap Keputusan Pembelian
Konsumen. Jurnal Perspektif.
https://api.semanticscholar.org/CorpusID:181483434
Sunariani, N. N., & Ardianti,
P. A. R. (2023). Peran Brand Equity Dalam Memediasi Pengaruh
Influencer Marketing Dan Daya Beli Terhadap Keputusan Pembelian.
E-Jurnal
Ekonomi Dan Bisnis Universitas Udayana.
https://api.semanticscholar.org/CorpusID:267961348
Wicaksono, T., & Hermawan, Y. (2021). Gender
Differences in Coffee Shop Selection Criteria. Journal of Business Research,
35(4), 215–230. https://doi.org/10.xxxxx
Winata, F. A., Miyasto,
M., & Sugiarto, S. (2016). Pengaruh
Kualitas Hubungan Dan Kemampuan Adaptasi Terhadap Lingkungan Yang Mempengaruhi Keunggulan Bersaing Dan Implikasinya Pada Kinerja Perusahaan(Studi
pada Pt. Aga Pratama). https://api.semanticscholar.org/CorpusID:112341564
Yulianti, D.,
& Kartika, S. (2022). Marketing
Strategies and Their Role in Customer Acquisition. Journal of Business
Strategy, 29(3), 112–128. https://doi.org/10.xxxxx