THE INFLUENCE OF LIFESTYLE, BRAND IMAGE, AND PRODUCT DESIGN ON SMARTPHONE PURCHASE DECISIONS (STUDY ON STUDENTS IN DKI JAKARTA)

ABSTRACT


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.
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 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
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.

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.

Convergent Validity Test
Suryo Hartoko Minarwanto, Didik Supriyanto, Deden Faturohman 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) 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.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) 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.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.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 crossloading 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.

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: 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.

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.

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 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%.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
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.
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 ttable 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.

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 &; 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.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.
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.

Table 3
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.

Table 8 R -Square
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.