The Effect of Lifestyle, Conformity, and E-Money on Online Shopping Consumptive Behavior in Generation Z in the City of Mataram

: The purpose of this study was to determine the effect of lifestyle, conformity, and e-money on online shopping consumptive behavior in generation z in Mataram City. The type of research used is quantitative research. The population of this study is generation Z with the birth year 1997-2012 in Mataram City. The sample used in this study consisted of 120 people who were identified using purposive sampling technique. Data collection in this study used a questionnaire. The data in this study were analyzed using SEM-PLS analysis with the help of SmartPLS 4.0 software. Based on data analysis, the following results are obtained: (1) lifestyle has a positive and significant effect on online shopping consumptive behavior. (2) conformity has a positive and significant effect on online shopping consumptive behavior. Meanwhile, (3) E-Money has a positive but insignificant effect on the consumptive behavior of online shopping.


Introduction
The payment system is the most important part of the economy, especially in ensuring the fulfillment of payment transactions made between people and businesses.In addition, the payment system also plays an important role in maintaining a stable financial system and implementing monetary policy.Bank Indonesia focuses on four key areas to ensure that payment processes run smoothly and safely: improving the usability, security, and effectiveness of payment systems, as well as customer safety.With the development of technology and the increasing value of transactions and risks, a safe and smooth payment system is becoming increasingly important (Vera Intanie, 2006).The increased innovation in payment systems that is currently being created has led to new innovations in the monetary framework, particularly monetary innovation (fintech).Fintech is a new model of providing financial services created through advances in information technology (Yang et al., 2017).
The increased innovation in the payment system that is currently being created has led to new innovations in the monetary framework, particularly monetary innovation (fintech).Fintech is a new model of providing financial services created through advances in information technology (D' Alimonte et al., 2014).According to Bank Indonesia (2017) in (Marginingsih, 2021) Financial technology is the use of technology in the financial system to create new service products, technology, business models, and/or payment system reliability.This can have an impact on monetary stability, financial system stability, and the efficiency, smoothness, security, and reliability of the payment system.(Giglio, 2021) explains that Fintech refers to the relationship that exists between businesses that provide financial services such as loans, payments, and other banking, and technologies such as mobile internet and public computing The proliferation of online stores into the lives of individuals has led to the emergence of a new phenomenon: online shopping.Online shopping has now become a lifestyle for everyone, one of which is generation Z which develops and grows very complex and related to the web.According to the Ministry of Finance of the Republic of Indonesia (Saputra et al., 2023) Generation Z was born between 1997 and 2012, so they grew up in the midst of rapid technological advances that forced them to live a digital lifestyle.Easier access makes it easier for Generation Z to investigate the virtual world.Generation Z prefers instant gratification, lacks patience, and dislikes process (Rini & Sukanti, 2016).The large number of online shoppers in the midst of the digital era results in individuals who are part of a culture of consumerism that does not exclusively fulfill basic individual needs.
Consumptive behavior is the act of buying desired goods or services without considering their benefits, known as consumerism (Angelia et al., 2022).Consumptive actions are inseparable from the features in e-commerce applications in the form of e-payments and e-wallets.These features help Generation Z to do online shopping easily.A person's lifestyle is determined by the activities (how they spend their time) that they consider important to their environment and how they feel about themselves and their environment.Every activity that a person does, online shopping is the talk of most of generation Z (Parmini* & Hernowo, 2023).Factors that influence lifestyle are values, activities, personality traits, and environment.Since most social media users are the younger generation, they will inevitably be influenced to make motivational purchases due to the strong appeal.Consumptive behavior will arise from unplanned spending or shopping.Those who live a luxurious lifestyle tend to have a high consumptive level.This is supported (Pulungan & Febriaty, 2018) and (Tinggi et al., 2022) owing the results of data analysis that Lifestyle has a positive and significant effect on Consumptive Behavior.However, the findings of research conducted by (Risnawati et al., 2018) concluded that lifestyle has no direct effect on consumptive behavior.
The consumptive behavior of Generation Z online shopping can be caused by several factors, one of which is conformity.Conformity is a situation where a person changes his or her attitude and behavior to conform to the social norms prevailing in society.Adolescents rely heavily on their peers or reference group.Friendships with peers are strong as they are seen as a source of fun and provide a variety of information (Yuliantari & Herdiyanto, 2015).They have a better chance of being accepted by popular groups if they behave and look like them.This is supported by (Hayati et al., 2020) and (Fitriyani et al., 2013) shows that conformity has a significant effect on consumptive behavior, but in contrast to the results of research by (Suminar, 2013) which states that conformity is not significantly related to consumptive behavior.
The existence of e-money or electronic money can also influence Gen Z in online shopping consumptive behavior.Electronic money is money whose value is stored in electronic-based media, electronic money is an innovative instrument in payment transactions.The ease of purchasing goods is very valuable for all people, especially for generation Z, which is often referred to as the tech-savvy generation, because they are a generation that grew up with innovations that provide a lot of convenience.Generation Z will definitely make sudden purchases, which can trigger consumptive behavior.This is supported by research from (Mujahidin, 2020) and (Insana & Johan, 2021a) shows that electronic money has a positive and significant effect on consumptive behavior in online shopping.However, it is not supported by (Yahya, 2021) that Electroni money has a negative and insignificant effect on Consumptive Behavior.Based on the understanding described above, the researcher aims to identify how generation Z, the largest consumer group in the world today continues to spend money independently, the desire to buy goods and services via the internet is a major trend in modern consumptive behavior.It is important to know the reasons for Generation Z's online shopping consumptive behavior in Mataram City, especially those related to lifestyle, conformity, and electronic money.

Theoretical Basis, Hypothesis And Theoretical Framework 2.1. Theoretical basis Consumptive Behavior
According to Effendi (2016) consumptive behavior is the behavior of buying goods or services that are not needed and consuming excessively.As a result, when a person uses products that prioritize wants over needs, they engage in individual consumptive behavior.Consumptive attitudes develop as a result of the many goods consumed, thus requiring a wide range of concepts, mass media electronically and directly mass or instantly (Putri et al., 2022) There are four factors that influence the way of consumptive behavior, namely: (1) Cultural factors, including social class, subculture, and behavior and preferences.2) Social factors, including family, role, and status, and reference groups 3) Individual factors, including age and stage of life, profession and financial situation, way of life, personality, and self-perception.4) Psychological factors, including learning, motivation, perception, and attitudes and beliefs.Indicators of consumptive behavior according to Sumartono, namely: 1) Buying products because of prize draws; (2) Buying products because of attractive packaging; (3) Buying products because of self-confidence and excellence; (4) Buying products because of price considerations (not because of their usefulness); (5) Buying products because they follow trends; (6) Wearing products with the aim of following models seen on social media; (7) Forming the belief that buying expensive products will increase one's self-esteem; (8) Trying several of the same or similar products (brands) (Wahyuni et al., 2019).

Lifestyle
According to (Richter et al., n.d.) lifestyle is defined as the way individuals spend their time (activities), their interests and interests that are valued in their environment and opinions and observations about their own lives and the surrounding world.According to Mowen and Minor (2008) in (Tinggi et al., 2022) that lifestyle describes a person's time and financial allocation.Therefore, lifestyle can be understood as an individual's pattern reflected in interests, activities, routines, habits, and time allocation for financial expenditure.Thus, we can see how students live on campus, which shapes their way of life and highlights the socio-cultural changes that occur there.
Lifestyle indicators are as follows: i) Activities (activities) ask consumers to describe their activities; ii) A person's interests can have an impact on decision making.Understanding consumer needs and preferences is essential for any business; (iii) assessment looks at people's opinions and perspectives on current issues and world events.Each consumer's point of view is unique (Sari et al., 2023)

Confomity
According to Rusich (2008) in (Wardhani & Wibowo, 2018) Conformity is several situations of feeling under pressure to comply with rules -both written and unwritten, which determine acceptable behavior.One believes that their group members are hedonistic, spontaneously rewarding, and happy to make impulse purchases.When one goes shopping with their friends, they can feel that it is important to get together and act and think in a way that matches the expectations of others (Wu & Huan, 2010).
According to (Baron, Byrne, & Branscombe, 2008) in (Khrishananto & Adriansyah, 2021) Factors that influence adolescent change are group cohesiveness (aspects of cooperation in meetings), group size, and ultimately, societal norms and accepted practices.Adolescents must adhere to a common set of customs in order to be accepted as normal in social settings, as accepted normal practices are evident in every setting

E-Money
According to the definition given by the Bank for International Settlements (BIS) in October 1996, electronic money is a device that allows users to store certain qualities or payments on their own electronic media.Unlike phone cards, which are single-use prepaid cards, e-cash is a payment method that supports multiple uses and multi-purpose installments (Shobri et al., 2022).According to (BI, 2020) in (Sudiro & Asandimitra, 2022) electronic money can be used as a financial instrument by utilizing chip-based media or cash stored on a server.This framework is managed by the media or issuer in a way that allows cash to be stored without being categorized as a reserve fund (savings).The purpose of electronic money is to provide cashless financial tools as a substitute for cash through computerized monetary instruments.

EM-2024-6478
Based on Bank Indonesia policy, article 1 number 3 of Bank Indonesia regulation number 16 article 18 of 2014 regarding renewal, as well as Bank Indonesia regulation number 11 article 12 of 2009 regarding electronic money.According to these regulations, electronic money is considered a payment instrument that has the following characteristics (Situngkir, 2018): 1. Issued in accordance with the amount of money that has been deposited by the electronic money user to the previous electronic money company.
2. Can be used as payment for goods from sellers who do not use electronic money suppliers 3. The amount of balance kept by the owner of the e-money will be monitored by the e-money supply organization not a store as stipulated in the banking regulations.
Thus, it can be concluded that the use of electronic money facilitates the process of purchasing goods or services from vendors.

Hypothesis
From a marketing standpoint, it is clear that consumers with similar interests will be categorized into specific groups according to how they spend their money and where they want to focus their leisure time.Generation Z today tends to engage in consumptive behavior, driven by technological advancements and the ease of shopping via the internet.Consumptive behavior is caused by a luxurious lifestyle without clear reasons to buy it.Various research results regarding lifestyle have certainly been carried out by many researchers (Melina & Wulandari, 2018) shows that lifestyle has a significant influence of 0.899% on the consumptive behavior of economic education students of STKIP YPM Bangko.This shows that a person's consumption behavior increases along with his lifestyle.This is also supported by (Ittaqullah et al., 2020) shows that the buyer's lifestyle significantly affects their consumptive behavior when shopping online by 35.1%.Furthermore, research by (Fungky et al., 2021) hows that Generation Z's consumptive behavior is positively and significantly influenced by their lifestyle.This shows that Generation Z's lifestyle increases along with their consumptive behavior.Also, (Sari et al., 2023) concluded that consumptive consumptive behavior is significantly influenced by lifestyle.

H1: Lifestyle affects the consumptive behavior of generation Z online shopping in Mataram City.
Research conducted by these findings shows a strong 23.9% commitment of the conformity variable to online shopping consumptive behavior, which indicates a positive correlation between students' intention to buy online and peer conformity And research by (Badawi et al., 2021) concluded that conformity affects purchase intention in web-based or online shopping.Furthermore, research (Ou et al., 2022) he results showed that online shopping consumptive behavior was significantly influenced by conformity.As well as research by (Lorenza & Lestari, 2023) concluded that students' online shopping consumptive behavior is influenced by conformity .

H2: Conformity affects the consumptive behavior of generation Z online shopping in Mataram City.
Research conducted (Fauziah & Nurhasanah, 2020)shows that electronic money has a positive and significant influence on the consumptive behavior of STEI SEBI students, students who use more electronic money will behave more consumptively.This is supported (Dewi et al., 2021) The findings of this study indicate that electronic money affects the consumptive behavior of consumer online shopping.And research by (Bilal Abdillah Rasyid & Fahrullah, 2022) shows that e-money partially and simultaneously has a positive and simultaneous effect on student consumptive behavior.Furthermore, (Insana & Johan, 2021b) concluded that partially or simultaneously the consumptive behavior of students can be influenced by electronic money, either partially or completely.And research (Oktarina & Iskandar, 2023) The findings of the analysis show that the consumptive behavior of students is influenced by the use of electronic money by 3.33%.The use of electronic money can also cause wasteful behavior, such as not considering its potential or usefulness, buying goods excessively, prioritizing needs over wants, and not having a priority system.
H3: E-Money affects the consumptive behavior of generation Z online shopping in Mataram City.

Teoretical Framework
From the results of the theoretical studies that have been carried out above, to determine the effect of lifestyle, conformity, and e-money on the consumptive behavior of online shopping on generation z in the city of Mataram, the theoretical framework can be seen in Figure 1 below.Type of Research This research uses quantitative research.Quantitative research is a research technique that uses many numbers for data collection, analysis, and presentation of findings (Arikunto, 2019).The variable in this study is a single variable, namely online shopping consumptive behavior.

Population and Sample
The population of this study is generation Z with the birth year 1997 -2012 in Mataram City.The sample in this study used purposive sampling technique.The purposive sampling technique is a sampling technique that aims to describe a sampling strategy that emphasizes certain objectives, not irregular things, regions, or strata (Arikunto, 2019).The sample criteria in this study are having an e-commerce application and making at least two online purchases.birth year 1997 -2012 and domiciled in Mataram City.Determination of the number of samples using quota sampling and the number of samples obtained was 120 people with 20 people each in 6 sub-districts in Mataram City.

3.3.
Data Collection Technique Data collection in this study used a questionnaire.The questionnaire is a data collection method that involves asking respondents to answer a series of questions or provide organized explanations, namely for lifestyle instruments, conformity, use of e-money and consumptive behavior.The questionnaire is structured using a Likert scale (six) points that move from 1 to 5. Statement items are given a score, strongly disagree (1), to strongly agree (5).The questionnaire was created using the google form application.

Data Analysis Technique
The data analysis used is SEM-PLS analysis.Structural Equation Modeling (SEM) is a multivariate analysis method that can be used to show synchronous direct relationships between known factors (indicators) and factors that cannot be estimated directly (latent variables).Partial Least Square (PLS) is an effective analysis technique because PLS does not depend on the measurement scale (such as interval or ratio scale), sample size, and distribution of residuals Indicators in PLS can be formed with reflexive or formative types (Sholiha & Salamah, 2015).This study uses SEM-PLS structural model analysis with the help of SmartPLS 4.0.software.

4.1.
Respondent Identity The identity of respondents in this study can be seen in table 1.This study analyzed data with a total of 120 respondents, consisting of 50 people (41.7%) male and 70 people (58.3%) female, with a birth year of 1997 -2012 aged 12 to 27 years and domiciled in Mataram City.70 people (58.3%) female, with the birth year 1997 -2012 aged 12 to 27 years and domiciled in Mataram City.There are 6 sub-districts in Mataram city, namely ampenan sub-district, mataram sub-district, selaparang sub-district, sekarbela sub-district, cakranegara sub-district, sandubaya sub-district, each of these sub-districts obtained 20 people (16.7%) respondents.Based on the dominating occupation is Student / Student of 90 people (75%).Then the ecommerce used is dominated by shopee e-commerce by 73 people (60.8%).Based on the e-money used, it is dominated by M-Banking by 32 people (26.7%).Then in the period of using e-money, 62 people (51.7%) have used e-money for more than 1 year.The composite reliability (cr), Cronbach alpha (ca), and average variance extracted (ave) measures are used to confirm how well the model is measured by the specified indicators.However, the interpretation of composite reliability and Cronbach alpha scores is the same.Composite reliability is a measure used to check how well the model is estimated by a predetermined indicator.Cronbach alpha is the coefficient used to measure the reliability of the measurement scale If the Cronbach alpha value is> 0.60, the variable is considered consistent / reliable.Based on table 2, it is known that almost all indicators are consistent / reliable in measuring latent variables (ca value ≥ 0.6).While the ave value is obtained greater than 0.5, this explains that the latent variable is able to describe an average of at least 50% of the variance of the indicators that measure it.

Aspects assessed
Original sample The path coefficient value between variables is said to be statistically significant, if the t-statistic value between latent variables shows a positive relationship with the t-statistic value compared to the t-table value and the result is greater.The t statistical value (critical ratio) is obtained from the bootstrapping results (resampling method) of the pls process.
Based on table 3, it is known that the highest path coefficient value is shown by the effect of conformity on consumptive behavior of 4.897.The lowest value is 1.658, which is the effect of e-money on consumptive behavior.Based on this value, the influence of the independent variable on the dependent variable is getting stronger the higher the path coefficient value.
Furthermore, testing the structural model is done by checking the results of the goodnes of fit test based on the coefficient of determination r2, the following r square value is obtained from the smartpls 4.0 ouput.

Aspects assessed R-square
Consumptive behavior (y) 0,668 Source: Data processed from SmartPLS 4.0 output The r-square (r2) value indicates the level of determination of exogenous variables on endogenous variables.According to Chin (1998) in the journal (Suntara et al., 2023) the r2 value can be categorized into three, 0.67 (substantial), 0.33 (moderate), or 0.19 (weak).Based on table 4, the r2 value of the consumptive behavior variable (y) is 0.668 (substantial).This shows that all independent variables (x1, x2, and x3) affect the consumptive behavior of online shopping by 66.8% and the remaining 33.2% is influenced by other indicators.
In the above model, a technique called hypothesis testing is used to identify the hypothesis or the beginning of a study.The bootstrapping output technique is used to obtain the t-statistic value for each.The hypothesis is accepted if the t-statistic value> t-table value.In this study, the significance (2-tailed) level of significance is 5%, with a t-table value of 1.96.To show the results of the bootstrapping output based on the t-statistic results, p-values, and hypothesis test results in Table 5.Source: Data processed from SmartPLS 4.0 output.
Table 5 shows that the hypothesis cannot be accepted or rejected because the t-statistic value of Emoney (x3) is smaller than 1.96, this indicates that the independent indicator e-money (x3) which is assumed to have a correlation and influence on online shopping consumptive behavior does not have a direct influence on consumptive behavior or is very small.For lifestyle (x1) and conformity (x2) have a direct influence on consumptive behavior.This is in accordance with research conducted by (Perdana Oskar et al., 2022) and (Lorenza & Lestari, 2023) that there is an influence between lifestyle and conformity on online shopping consumptive behavior based on the results of the analysis of the t value greater than the t table with 120 respondents (n = 120) and a significant level of 95%.

Discussion 4.3.1. The Effect of Lifestyle on Online Shopping Consumptive Behavior
Based on the results of statistical testing, it is known that lifestyle affects the consumptive behavior of online shopping.This can be seen from the results of the H1 hypothesis test, which shows a relationship between lifestyle variables and online shopping consumptive behavior.shows a path coefficient value of 0.549 and tcount (7.840) greater than t table (1.66).The p-value is 0.000.The p-value (0.001) < α = 5% (0.05).Thus, this study accepts hypothesis 1 (H1), which states that lifestyle has a positive and significant impact on online shopping consumptive behavior.The findings of this study indicate that there is a positive and significant correlation between the consumption habits of generation Z and lifestyle in Mataram City, meaning that the higher the lifestyle, the higher the consumptive behavior.
The lifestyle that has dominant value is the practice of shopping at several stores before making a purchase.Generation Z's consumptive behavior is closely correlated with their lifestyle, which can be determined by their activities, interests and opinions.One of the characteristics of this lifestyle is the habit of shopping before making a purchase.Generation Z's ideas, interests and activities shape their lifestyle, which is closely related to their consumption habits.In this study, respondents who shopped online said that shopping online is easy.When making purchase choices, consumers can easily compare prices and quality of multiple stores without having to travel far from home.Online marketplaces offer the latest products, and interactive information encourages purchases.Based on the results of this study, this is consistent with the findings of research (Fadhilah, 2023) states that lifestyle has a positive and significant influence on consumptive behavior.

The Effect of Conformity on Online Shopping Consumptive Behavior
Based on the results of statistical testing, it is known that conformity affects online shopping consumptive behavior.This is shown in the results of the h2 hypothesis test conformity to online shopping consumptive behavior shows a path coefficient value of 0.313 and t-count (4.897) greater than t table (1.66).The p-value is 0.000.The p-value (0.000) < α = 5% (0.05).This means that it is concluded that conformity has a positive and significant effect on online shopping consumptive behavior, hypothesis h2 is accepted.This indicates that as the level of conformity increases in generation z in the city of Mataram, the consumptive behavior of generation z in the city of Mataram will also increase.
High levels of peer conformity can be seen in the way Generation Z individuals treat each other in their relationships.Based on the results of the questionnaire given, it was found that they always seek advice from their friends when making purchasing decisions, aspire to look like their friends, and adopt all social group fashions.In accordance with research (Azizah & Aryanti, 2023) states that conformity has a positive and significant influence on consumptive behavior.

The Effect of E-money on Online Shopping Consumptive Behavior
Based on the results of statistical testing, it is known that e-money affects the consumptive behavior of online shopping.The findings of the H3 hypothesis test show that e-money with online shopping consumptive behavior has a path coefficient of 0.087 and a t-count of 1.658, which is smaller than the t-table of 1.66.The p-value is 0.000, the p-value (0.000) < α = 5% (0.05).This means that e-money has a positive but insignificant effect on online shopping consumptive behavior, hypothesis H3 is rejected.So the third hypothesis (H3) in this study is rejected, which states that e-money has no effect on consumption behavior.The results of this study indicate that the consumptive behavior of generation z is not significantly influenced by e-money in Mataram city.Thus, the third hypothesis (H3) of this study is rejected, which states that e-money has no impact on online shopping consumptive behavior.The findings of this study indicate that e-money has no influence on the consumptive behavior of generation Z online shopping in Mataram City.
The research findings show that e-money has no effect on the consumptive behavior of generation Z online shopping in Mataram City, but instead this consumptive behavior will cause excessive spending by generation Z in Mataram City and increased consumption expenditure.The use of electronic money is one of the factors that influence Generation Z's consumption expenditure.The use of electronic money causes Generation Z's consumption expenditure to increase proportionally.Apart from being used to facilitate access to fast payment transactions, electronic money also encourages Generation Z to behave consumptively.The findings of this study are consistent with the results of research from (Alfinna et al., 2023) which states that e-money has no significant effect on consumptive behavior.

Conclusions And Suggestions
This research was conducted to analyze the influence of lifestyle, conformity, and e-money on online shopping consumptive behavior.The first assumption is that these variables affect the consumptive behavior of online shopping.Data were obtained from research subjects, namely generation Z with birth years 1997 -2012 in Mataram City in the form of a questionnaire instrument made using google form with several questions as indicators.The research method used is quantitative.The data analysis used for data processing is Smart-PLS software version 4.0.Based on the results of the study, it shows that lifestyle has a significant influence on online shopping consumptive behavior, so H1 is accepted.Conformity also has a positive and significant influence on online shopping consumptive behavior, so H2 is accepted.However, because this study does not show that e-money has an influence on online shopping consumptive behavior, H3 is rejected.Generation Z in Mataram City has consumption-driven online shopping behavior that is influenced by conformity and lifestyle.The better one's life is, the more likely one is to shop online extravagantly, and when one shops with friends, they may feel the need to congregate and follow the expectations of others.Therefore, it is expected that Generation Z in Mataram City will have better self-control and financial literacy to prevent problems related to excessive consumption.They will also be able to modify their lifestyle to suit their abilities while still meeting their needs and utilizing e-money wisely.

Figure 1
Figure 1.Research Model 3. Research methodology 3.1.Type of Research This research uses quantitative research.Quantitative research is a research technique that uses many numbers for data collection, analysis, and presentation of findings(Arikunto, 2019).The variable in this study is a single variable, namely online shopping consumptive behavior.

Figure 2
Figure 2 Outer model algorithm results, source: data analysis 2023Based on Figure2, the best pls model results are achieved when the loading factor value of each variable indicator is greater than 0.7 and has met convergent validity.

Table 1 . Respondent Identity
The initial model of correlation between variables can be seen in Figure2.This initial model is based on the markers or indicators identified in each questionnaire question.