p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 4, No. 10 October 2023 http://jist.publikasiindonesia.id/
Doi: 10.59141/jist.v4i10.757 1646
THE INFLUENCE OF LIFESTYLE, BRAND IMAGE, AND PRODUCT
DESIGN ON SMARTPHONE PURCHASE DECISIONS (STUDY ON
STUDENTS IN DKI JAKARTA)
Harits Abyan Aufa
Veteran National Development University Jakarta, Indonesia
Email: [email protected]
*Correspondence
ABSTRACT
Keywords: lifestyle; brand
image; product design;
smartphone top brand 2023;
purchase decision.
This study uses a quantitative method to prove the influence of Lifestyle,
Brand Image, and Product Design directly and indirectly on Purchase
Decisions. This study used 150 respondents from students of
Smartphone Top Brand 2023 in DKI Jakarta as primary data, and
secondary data researchers obtained through various references related
to the research. Data were collected using purposive sampling techniques
and analyzed using descriptive and inferential analysis techniques with
the help of SmartPLS software. So data processing obtains the results
that (1) Lifestyle has a positive and significant effect on Purchase
Decision, (2) Brand Image has a positive and significant effect on
Purchase Decision, (3) Product Design has a positive and significant
effect on Purchase Decision, 4) Lifestyle, Brand Image, and Product
Design both have a positive effect on Purchase Decision.
Introduction
In this day and age, the development of Science and Technology, or what we often
hear with science and technology has been increasingly advanced and sophisticated in its
use. The rapid development of science and technology has produced the latest
innovations. In its development, science and technology gave rise to many of the latest
inventions one of them is now in Japan there is a new technological tool, namely the
Human Washing Machine. This is due to a factor that greatly helps the development of
science and technology itself is growing faster, namely Globalization. Globalization is a
condition in which many people realize that they participate in receiving a part in a world
that continues to change without control according to (Giddens, 2022) by Hesri
Mintawati. Its development, technology in the world of communication is also developing
rapidly, today humans no longer have difficulty communicating with each other between
places and even between continents. The technology is a Smartphone.
One of the needs of today's society to support its activities is a smartphone. Electronics
manufacturers noticed this need, which led to the emergence of various brands of
smartphones. There are more and more demands from the public for high-quality services
and goods as a result of the development of information technology and people's standard
of living. Some members of today's modern culture now consider having a smartphone
necessary for their lifestyle. This situation encourages the development of several
smartphones that provide goods to meet consumer needs for communication technology.
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In Indonesia, there is competition between several smartphone manufacturers,
including Samsung, Apple, Vivo and others. Competitors in the telecommunications
industry are involved in fierce competition due to this smartphone market. According to
the analysis of smartphone sales projections worldwide in 2022 (Figure 2) quoted from
(www.bhineka.com, 2023) found that the Samsung brand is the brand that makes the
largest sales with a percentage of 21.6%, followed by the Apple brand (iPhone
manufacturer) with a percentage of selling 18.8% million units, Xiaomi as much as
12.7%, OPPO 8.6%, Vivo 8.2%, and other brands by 30%.
Lifestyle is how a person lives their life, including the products they acquire, how
they use them, and their thoughts and feelings after use, as well as their lifestyle about
how they respond to purchases made by customers (Alsabiyah, 2019) Lifestyle will
determine the decisions that will be taken by consumers including smartphone purchase
decisions.
Many studies on lifestyle have revealed that it is a more accurate indicator of
customers' changing interests and values and that these values may ultimately influence
their behavior. Research conducted (by Wulansari &; Setiawan, 2023) shows that brand
image variables have a positive influence on purchasing decisions, while lifestyle
variables have a negative influence on purchasing decisions. In contrast to the results of
research conducted by (Sobandi & Somantri, 2020) where in the study the results say that
lifestyle variables have a positive influence on purchasing decisions and brand image
variables have a positive influence on purchasing decisions. This research is also in line
with research conducted by (Handayani & Kurnianingsih, 2021) where in the study it is
said that lifestyle variables have a significant influence on smartphone purchase decisions
and product design variables also affect purchase decisions. In addition, the results of this
research are also in line with the research conducted (Andi & Ali, 2019) and (Clyde,
Hanifah, & Muchlish, 2022).
Companies can create a positive perception of their brand and attract more
customers to their products by making a good first impression on consumers (Firmansyah,
2019a). As we know, a good impression of a product will tend to give more positive
results for the company, as well as the Toyota Innova car which has the impression of
being a family car, which indicates that the car is comfortable for the family.
Research conducted (Frandika, 2018) found results where brand image variables
have a positive influence on purchasing decisions, and lifestyle variables also have a
positive influence on purchasing decisions. While in research conducted by (Bin-Tahir,
Saidah, Mufidah, & Bugis, 2018) said that brand image variables do not have a significant
influence on smartphone purchase decisions. In another study, (Ramadani &
Rachmawati, 2022), it was also found that brand image variables did not have a
significant influence on smartphone purchase decisions.
To encourage consumer interest in buying a product, product design is an object
that is very closely related to a product that may be felt by users (Maslikha, 2019)
purchasing decisions are influenced by attractive product designs. (Abral et al., 2020) Of
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course, in this case, a product that has an attractive product design will be very capable
of increasing sales of a company's products.
Research conducted by (Anisyah, Hernawaty, & El-Fikti, 2021) found that product
design variables have a positive effect on purchasing decisions. This is in line with
research conducted by (Akbar, Violinda, Setiawati, & Rizwan, 2021) where in the journal
product design variables affect the purchase decision of Smartphone products.
Meanwhile, in the research presented by (Anisyah et al., 2021) stated that product design
variables do not affect smartphone purchase decisions.
According to (Asti & Ayuningtyas, 2020) a purchase decision is a choice to shop
for the brands that are most in demand made by consumers, but two things can happen
between purchase intent and actual decision-making. Purchasing decisions, on the other
hand, are the steps customers take to decide which product or service they want to acquire,
(Fatihudin & Firmansyah, 2019). Tanady & Fuad (2020) assert that the way the purchase
decision-making process is implemented influences consumer purchasing decisions.
(Yusuf, 2021) claims that purchasing decisions are thought processes in which people
consider many options and assign a product from a variety of choices.
Based on these expert statements, it can be concluded that purchasing decisions are
one of the stages of consumer behavior that precede post-purchase behavior and how
people choose, buy, utilize, and satisfy their needs and desires for products and services.
This applies to individuals, groups, and organizations.
The results of this research can enrich the author's experience and knowledge about
lifestyle, brand image, product design as well and customer purchasing decisions in the
future. For UPNVJ, it is intended that the results of this research can be useful as reference
material for the literature of the University of National Development "Veteran" Jakarta
and can be a reference for further research.
Research Methods
An operational definition is a definition based on what can be observed to indicate
what the researcher should do when testing a hypothesis or providing an answer. A
variable to be used in research can be determined, evaluated, or measured by the
operational definition itself. In addition, it can be a guideline for researchers who want to
measure, ascertain, or assess a variable using operational language. This study using four
variables studied, namely lifestyle (X1), brand image (X2), and product design (X3) as
independent variables. As well as purchasing decisions as a dependent variable.
Data Collection Techniques
Data collection techniques are using data collection strategies, it is possible to
obtain the data needed for a study that utilizes certain technologies. According to
(Sugiyono, 2022: 137) there are several places, sources, and various methods for
collecting data. When viewed from data collection methods and procedures, it can be
done by interviewing, filling out questionnaires, making observations, or using a
combination of the three.
Data Type
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The type of data used in this study is quantitative and uses the Likert scale.
According to (Sugiyono, 2022: 13) quantitative data is research data in the form of
numbers that can be measured using statistics as a mathematical test tool related to the
problem being studied to get a conclusion. Quantitative data is a research design based
on concrete data. The numbers are obtained from questionnaires that will later be
distributed.
Data Sources
In this study, the data source used in this study is the primary data source. Sourced
from (Sugiyono, 2022: 456) primary data is data that can be accessed directly by data
collectors. The reviewers themselves collect the first source of data or the site where the
research takes place. The primary data in this study was by using the G-Form
Questionnaire. In addition to primary data, secondary data is also used. According to
(Sugiyono, 2022: 456) secondary data is a source of information that indirectly provides
information to data reviewers through intermediaries such as other people or newspapers.
Journals and papers related to the research topic serve as secondary data sources.
Data Collection
1. Questionnaire
A questionnaire is a way of building and compiling a detailed list of questions for
data collection. Respondents were given questionnaires to fill out on their own and
without the intervention of researchers. According to (Sugiyono, 2022: 142)
questionnaire is a technique by asks respondents to answer written statements or
questions, and data collection techniques are used. When researchers are confident in the
variables to be tested as well as know what might be expected from respondents,
questionnaires make the data collection approach more effective.
2. Literature Study
Data collection techniques by studying reviews of books, documents, publications,
and reports related to the subject stored. In this literature method, the author collects data
from journals, literature books, and related studies relevant to the title he is researching.
Data Analysis Techniques
Data analysis according to (Sugiyono, 2022: 482) is a method of collecting
information in an organized manner from interviews, direct notes, and archiving by
categorizing information into several categories, deciphering it in detail, synthesizing it,
and organizing it into patterns. This information is then used to build detailed conclusions
for researchers and others.
Descriptive Statistical Analysis
Descriptive statistical analysis explained by (Sugiyono, 2022: 169) aims to examine
the data collected through data description with no intention to conclude generalizations.
In the sense that this analysis only provides an overview of data which is usually in the
form of charts and tables.
Results and Discussion
1. Convergent Validity Test
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The results obtained from the SmartPLS application found that the value of the
loading factor on each instrument from the indicators on the variables of this study is as
follows:
Purchase Decision (Y)
Table 1.
Purchasing Decision
Outer loading
KEP1
0.943
KEP2
0.959
KEP3
0.931
KEP4
0.947
KEP5
0.926
KEP6
0.942
KEP7
0.696
KEP8
0.825
KEP10
0.702
KEP11
0.669
KEP12
0.875
Based on Table 1 above, there is an outer loading factor value from the purchase
decision variable which explains that each indicator has values above 0.6. This means
that all indicators on the purchase decision variable have a high influence on shaping the
purchase decision variable. The lowest outer loading factor value is KEP 11 with a value
of 0.669 which indicates smartphone products to accept product payments in cash or cash.
Then the highest outer loading factor value is found in KEP 2 with a value of 0.959 which
indicates that smartphone products have various variants or types of products.
Lifestyle (X1)
Table 2
Lifestyle
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Outer Loading
GH1
0.872
GH2
0.914
GH3
0.863
GH4
0.914
GH5
0.867
GH6
0.770
Based on table 2, there is an outer loading factor value from lifestyle variables
which explains that each indicator all have values above 0.7. This means that all indicators
on lifestyle variables have a high influence in shaping these lifestyle variables. The lowest
outer loading factor value is GH 6 with a value of 0.770 which indicates smartphone
products are products that will always develop in the future. Then the highest outer
loading factor value is found in GH 2 and GH 4 with a value of 0.914 which indicates
that smartphone products can help in supporting my hobby and social media influences
in choosing smartphone products.
Brand Image (X2)
Table 3
Brand Image
Outer Loading
CM1
0.864
CM2
0.859
CM3
0.860
CM4
0.860
CM5
0.798
CM6
0.857
Based on table 3, there is an outer loading factor value from the brand image
variable which explains that each indicator all have a value above 0.7. This means that all
indicators on the brand image variable have a high influence in shaping the brand image
variable. The lowest outer loading factor value is CM5 with a value of 0.798 which
indicates the smartphone product has a name that is easy to remember. Then the highest
outer loading factor value is found in CM1 with a value of 0.864 which indicates that the
smartphone product has an attractive physical appearance or design.
Product Design (X3)
Tabel 4
Desain Produk
Outer Loading
DP1
0.874
DP2
0.851
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DP3
0.860
DP4
0.794
DP5
0.763
DP6
0.780
DP7
0.823
DP8
0.873
Based on table 4 there is an outer loading factor value from the product design
variable which explains that each indicator all have a value above 0.7. This means that all
indicators on product design variables have a high influence in shaping the product design
variables. The lowest outer loading factor value is DP5 with a value of 0.763 which
indicates that smartphone products have product quality in accordance with the price paid.
Then the highest outer loading factor value is found in DP1 with a value of 0.874 which
indicates that smartphone products have a model form that continues to experience
updates
Discriminant Validity Test
Furthermore, there is another test, namely by testing the validity of the discriminant
which can be considered from the AVE value on each indicator statement instrument used
in the study. That suggested value should exceed 0.5. Here is the SmartPLS 4.0 output
that gets the following AVE result.
Table 5
Avarege Variand Extrtacted (AVE)
Average variance extracted (AVE)
Lifestyle
0.753
Brand Image
0.723
Product Design
0.686
Purchasing Decision
0.744
In table 5, that good AVE value is one that exceeds 0.5 (Ghozali, 2014, p. 39).
Lifestyle earns 0.753, Brand Image earns 0.723, Product Design earns 0.686, and
Purchasing Decision has a payoff of 0.744. So, from the data above, it is concluded that
every instrument of the indicators in this research variable can be said to be valid so that
it can be continued to the next stage. There is another way for discriminant validity to be
seen from cross loading. Here is the software output of cross loading in SmartPLS 3.0 as
follows.
Table 6.
Cross Loading
Lifestyle
Brand Image
Product Design
Purchasing Decision
GH1
0.872
GH2
0.914
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GH3
0.863
GH4
0.914
GH5
0.867
GH6
0.770
CM1
0.864
CM2
0.859
CM3
0.860
CM4
0.860
CM5
0.798
CM6
0.857
DP1
0.874
DP2
0.851
DP3
0.860
DP4
0.794
DP5
0.763
DP6
0.780
DP7
0.823
DP8
0.873
KEP1
0.943
KEP2
0.959
KEP3
0.931
KEP4
0.947
KEP5
0.926
KEP6
0.942
KEP7
0.696
KEP8
0.825
KEP10
0.702
KEP11
0.669
KEP12
0.875
Based on table 6, it can be seen that all statements from each indicator on the
variables of service quality, customer satisfaction and customer loyalty have a high cross-
loading value according to the variables formed compared to other variables. According
to (Ghozali, 2014, p.43) have an expectation that each latent variable has a higher loading
on each indicator block compared to other hidden variables. So, from these data, it is
concluded that each instrument of the indicators in this research variable has been said to
be valid so that it can proceed to the next stage. The statements that arise from the previous
loading factor are reinforced by the findings of AVE and Cross loading because each
statement item of each indicator on the variable has a value that is considered valid. Due
to the ability of indicators to measure lifestyle characteristics, brand image, product
design, and purchasing decisions, it can be inferred from the findings of convergent and
discriminant validity calculations that all statement items of the indicator are said to be
valid.
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Reliability Test
After conducting tests with validity, then conduct an analysis by testing reliability
tests. Reliability tests are used to look for evidence of instrument stability, accuracy, and
precision to measure structures (Ghozali &; Latan, 2020, p. 75). Seeing reliability can be
seen from the output results in the SmartPLS application, which is obtained from the
Croobach Alpha and Composite Reliability values of each variable. Reliability testing of
indicators on variables of service quality, brand image, customer satisfaction, and
purchasing decisions. It can be done in 2 ways, namely composite reliability and
cronbach's alpha (Ghozali, 2014, p. 64). Here are the Composite Reliabilty values of the
Smart Pls 3.0 output as follows:
Table 7
Composite Reliability
Composite Reliability
Lifestyle
0.948
Brand Image
0.940
Product Design
0.946
Purchasing Decision
0.969
In table 7, it can be seen that the composite reliability of the variables lifestyle,
brand image, product design, and purchasing decision obtained a value of > 0.70, meaning
that every statement made by each indication meets the established standards. The
recommended limit value for composite reliability is greater than 0.70, according to
Ghozali (2014, p. 65). The highest value of composite reliability. It is in the lifestyle
variable with a value of 0.948 and the lowest value is in the product design variable with
a value of 0.937. These results conclude that the instruments on each indicator of this
research variable have good reliability because of the consistency and accuracy to
measure well, so that the data used can be trusted to continue to the next research.
Structural Model (Inner Model)
The output results of the SmartPLS application represented by the R-Square value
can be seen after measurements on the outer model and testing on the structural model or
inner model. SmartPLS software can directly assess statistical T values and P values as
cut off values used to measure accepted or rejected hypotheses in addition to determining
indirect effects.
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Figure 1 Inner Model
R Square
The determinant coefficient (R-Squere) assesses how well the model contributes to
variations in the dependent variable. The values of the coefficient of determination are 0
and 1. Explain that the variance of the independent variable provides almost all the
information necessary to make predictions about the dependent variable if it is asked to
have a small value (Ghozali, 2014, p.183). If the result has R2 values of 0.67 (good), 0.33
(medium), and 0.19 (weak), then (Ghozali, 2014, p. 42) is correct. The output results of
the SmartPLS application are as follows.
Table 8
R – Square
R - Square
R – Square Adjusted
Purchasing Decision
0.571
0.562
Based on table 8, R-Square for purchasing decision variables that get a value of
0.571 means that lifestyle, brand image, and product design are able to explain purchase
decisions by 57.1% and the remaining 42.9% are due to other variables that are not used
in this study such as product quality, price, and others.
T-Statistical Test
To determine whether the presented claims are statistically correct and to
determine whether the findings of the hypothesis are acceptable or rejected, hypothesis
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testing is performed. The purpose of hypothesis testing is to provide a foundation so that
it can use evidence from data to produce an assessment of whether to accept or reject the
correctness of the hypothesis compiled (Sugiyono, 2022, p. 160). Thus, a statistical t test
is used to measure it. SmartPLS 4.0 software output produces path coefficient values,
indirect influences, and the presence or absence of influence on lifestyle variables (X1),
brand image (X2), product design (X3), and purchase decisions (Y). These values are
used to understand how much influence the relationship between variables has.
Hypothesis testing is done by a joint significance test or t test which will explain
how far the influence of an independent variable partially or together to explain the
variation of the dependent variable. In this study to determine the relationship of no or
influence on lifestyle variables (X1), brand image (X2), product design (X3) and
purchasing decisions (Y). Finding the value of t table can be seen from the significance
level of 0.05 which is obtained from the value df = number of samples - number of
variables. After doing the calculation, the table t value is 1.976 which is obtained from
the formula df = 150 – 4 = 146 which is then connected with a significance level of 0.05
or 5%.
Table 9
Uji T
Original
sample (O)
Sample
mean (M)
Standard deviation
(STDEV)
T statistics
(|O/STDEV|)
P values
CM > KP
0.290
0.289
0.137
2.121
0.034
DP > KP
0.298
0.307
0.115
2.590
0.010
GH > KP
0.247
0.243
0.103
2.393
0.017
Based on table 9 it can be seen in the original sample value that, the lifestyle variable
on purchasing decisions produces a value with 0.247 or 24.7% meaning that it has a
positive influence of lifestyle on purchasing decisions and results that, t count 2.393 is
higher than t table 1.976 and has a significant value of 0.017 below 0.05. This shows that
lifestyle has a significant influence through purchasing decisions. So, the result obtains
that H1 is acceptable. Brand image on purchasing decisions gets a value of 0.290 or 29%,
meaning that it has a positive influence of brand image on purchasing decisions. Then,
the results of the brand image variable test on purchasing decisions found that, t count
2.121 is greater than t data table 1.976 and has a significant value of 0.034 below 0.05.
This means that brand image has a significant influence on purchasing decisions. So, the
result obtains that H2 is acceptable. Product design on purchasing decisions results in a
value of 0.298 or 29.8%, meaning that it has a positive influence of product design on
purchasing decisions. Then, the results of testing product design variables on purchasing
decisions resulted in that, t count 2.590 is greater than data t table 1.976 and has a
significant value of 0.010 below 0.05. This means that product design has a significant
influence on purchasing decisions. So, the result obtains that H3 is acceptable.
Test F
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In this study there is simultaneous testing or better known as the f test. The point
is to see together the influence of the independent variable on the dependent variable. The
next step is to carry out a comparison process between f count and f table, where f count
must be higher than the value of f table so that the results are said to have a positive and
significant effect simultaneously following the test.
F Count =
F Count =
=
=
= 62.333
Based on the calculation results of the f test above shows the number 62,333 with
a probability of 0.05. For the F value of the table itself after calculations with the formula
f (K: n – K – 1) get the result (3:146). When compared the results f calculate 62,333 >
2,670 f table. So it is concluded that lifestyle variables, brand image, product design, on
purchasing decisions have a positive and significant effect simultaneously or together.
The Influence of Lifestyle on Purchasing Decisions
Based on the results of research that has been carried out, it can be explained that
lifestyle variables have a positive influence on purchasing decisions known from the
original sample results and a correlation of 0.245 or 24.5%. For the statistical t-test of
lifestyle variables, the results had a positive influence on purchasing decisions with t-
table values compared to t-counts of 2,511 > 1,976. This is also supported by the results
of P Values of 0.022 < 0.05 which shows that lifestyle has an influence and is significant
on purchasing decisions. In the first hypothesis, various lifestyle indicators such as
activities, interests, and opinions influence the purchase decision can be accepted. That
is, that any increase in Smartphone consumer purchasing decisions is influenced by
lifestyle variables.
This is in accordance with research by (Anisyah et al., 2021) in this study that
lifestyle variables have an influence on purchasing decisions. This result is supported by
research (Wulansari &; Setiawan, 2023) The results show that brand image variables have
a significant effect and have a positive effect on purchasing decisions. Lifestyle factors,
meanwhile, have a considerable but unfavorable impact on purchasing choices. In
addition, reference group variables have a positive relationship direction but do not have
a significant effect.
This is also supported by real conditions in the field. Where according to
Kompasiana (2023) Today, smartphones are very influential in a person's image and
identity. In essence, a person wants to pursue pleasure whenever he wants, which is
deeply tied to basic needs such as status, reflects who they are, and makes them feel more
confident. One way is to use a smartphone. Therefore, young people occasionally express
their self-image by buying trending products to fit their environment. Some young people
buy popular smartphones mainly for the purpose of improving their appearance and
confidence.
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The influence of brand image on purchasing decisions
Based on the results of research that has been carried out, it can be explained that
brand image variables have a positive influence on purchasing decisions known from the
original sample results and a correlation of 0.302 or 30.2%. For the brand image variable
statistical t test, the results had a positive influence on purchasing decisions with t-table
values compared to t-counts of 2,121 > 1,976. This is also supported by the results of P
Values of 0.028 < 0.05 which shows that brand ideals have an influence and are
significant on purchasing decisions. In the second hypothesis, various brand image
indicators such as strength, uniqueness, and liking influence on purchasing decisions are
acceptable. That is, that any increase in Smartphone consumer purchasing decisions is
influenced by brand image variables.
This is in accordance with (Wulansari &; Setiawan, 2023) in the study that brand
image variables have an influence on purchasing decisions. This result is supported by
research (Somantri et al., 2020) Based on the results of partial influence testing with t
test, that all independent variables, namely lifestyle and brand image, have a positive and
significant influence on purchasing decisions.
This is also in accordance with the real conditions that exist in society. According
to Liputan6 (2020) where there are several factors that influence consumers to choose a
product when they want to decide on a purchase decision. One of the things explained is
a good brand, in this case, it means that of course consumers tend to choose a product if
a product is well known by consumers and of course consumers will choose a brand that
already has a good name. Where this is in accordance with the results of research that the
brand image of a brand will greatly affect purchasing decisions.
The Influence of Product Design on Purchasing Decisions
Based on the results of research that has been carried out, it can be explained that
product design variables have a positive influence on purchasing decisions known from
the original sample value and correlation value of 0.283 or 28.3%. For the statistical t test
of product design variables, the results had a positive effect on purchasing decisions with
t-table values compared to t-counts of 2,606 > 1,976. This is also supported by the results
of P Values of 0.011 < 0.05 which shows that product design has an influential and
significant influence on purchasing decisions. In the second hypothesis, various product
design indicators such as shape, features, quality, and style affect purchasing decisions
are acceptable. That is, that any increase in Smartphone consumer purchasing decisions
is influenced by product design variables.
This is in accordance with research (Akbar et al., 2021) in this study that design
variables have an influence on purchasing decisions. This result is supported by research
This study explains that product quality has a direct influence of 40.3% on purchasing
decisions. Product design also directly influences 32.6% of purchasing decisions, while
brand image does not influence purchasing decisions. Therefore, brand image cannot
mediate product quality and design against purchasing decisions. Product design has a
direct effect on brand image by 41.9%, and product quality has a direct effect on 32.2%.
Therefore, it is necessary to pay attention to these three things to increase sales.
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This is in accordance with the real conditions that exist in life. According to
Kompas (2020), not only beautiful, product design must also be functional. In this case,
it means that the design also immediately has an appropriate function, not just decoration.
Of course, this is in line with the results of research where product design has an influence
on purchasing decisions, especially smartphone purchases.
The influence of lifestyle, brand image, and product design on purchasing decisions
Based on the results of this study, an F test was obtained which showed that f count
62,333 > 2,670 f table which means lifestyle, brand image, and product design
simultaneously or thoroughly affect purchasing decisions on smartphone purchases. This
is supported by the results of R square adjusted where 56.2% of lifestyle, brand image,
product design have an influence on purchasing decisions. The remaining 43.8% was
influenced by several other factors that were not studied in this study.
This study runs in line with research conducted by (Handayani &; Kurnianingsih,
2021) Data processing uses classical assumption tests, model tests and influence tests
between x and y.The results of the study stated that lifestyle, design, features and product
quality obtained a Fcalculate value of 98.127 < from the Ftable value of 2.46 so that there
is an influence between lifestyle variables, design, features and product quality that
influence Samsung's smartphone purchase decision in Surakarta simultaneously.
Lifestyle variables obtained t-value 5.422 and p-value 0.000 > 0.05 which means lifestyle
has a significant positive effect on purchasing decisions. For the design, a regression value
of 5.190 and a p-value of 0.000 > 0.05 is obtained, meaning that the design has a positive
and significant effect on the purchase decision. While the feature variable obtained a
calculated value of 2.086 with a p-value of 0.000 > 0.40 which means that the feature
chooses a positive and significant influence on purchasing decisions, and the product
quality variable obtained a regression value t- calculation equation of 2.525 with a p-value
of 0.013 > 0.40 which means that product quality has a positive and significant influence
on the purchase decision of the Jakarta smartphone.
Conclusion
The following conclusions about how lifestyle affects smartphone purchases are
drawn from researched research and debates about smartphone purchases using the SEM-
PLS approach over SmartPLS. This shows the positive impact of lifestyle on purchasing
choices. Thus, a person's lifestyle can affect the smartphone they buy. The purchase of a
smartphone will not change if it is not motivated by lifestyle.
On smartphones, brand perception or brand image influences purchasing decisions.
It shows how brand image influences consumer purchasing choices. This indicates that a
stronger brand reputation will foster greater consumer trust when making smartphone
purchases. However, if the image is unattractive and confusing, the consumer may decide
not to buy the smartphone. On smartphones, product design influences purchasing
choices. It shows how product design affects consumer purchasing choices. This indicates
that better product design will increase consumer confidence when buying a smartphone.
However, smartphone purchase options can be reduced by an ugly design.
Suryo Hartoko Minarwanto, Didik Supriyanto, Deden Faturohman
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 10, October 2023 1660
Smartphone purchase decisions are directly influenced by lifestyle, brand image,
and device design. It shows how purchasing decisions are influenced by lifestyle, brand
image, and product design. This indicates that along with the increasing quality of
lifestyle, brand image, and product design offered, buyers will increase their purchases to
always use the latest mobile phones.
Implementation Of Development In Sudimoro Village, Bululawang Sub-District Towards
Socio-Economic Changes In The Community
Jurnal Indonesia Sosial Teknologi, Vol. 4, No. 10, October 2023 1661
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