THE FACTORS INFLUENCING BEHAVIOURAL INTENTION FINTECH LENDING (PAYLATER) AMONG GENERATION Z INDONESIAN MUSLIMS AND ISLAMIC CONSUMPTION ETHICS VIEWS

This study seeks to investigate and analyze the factors that influence Generation Z’s use of fintech lending (paylater) in Jakarta, West Java, East Java, Central Java, and North Sumatra. This study employs a descriptive quantitative methodology and questionnaire distribution. The study employed purposive sampling. This study included 200 Generation Z respondents who have utilized fintech lending (paylater) as respondents. The method of data analysis employs Partial Least Square-Structural Equation Modeling (PLS-SEM) and SmartPLS version 3.2.9 software. The variables performance expectation, social influence, hedonic motivation, and habit have a positive and significant effect on behavioral intention, whereas effort expectation, facilitating conditions, and price value do not. In addition to testing the UTAUT 2 model, this research was conducted on Generation Z, where few research results are discussing the use of fintech lending (paylater). Generation Z is the generation that currently dominates the population in Indonesia and will be the next generation of Indonesians; therefore, it is essential to determine what factors play a role in encouraging the use of fintech lending (paylater) among Generation Z.


INTRODUCTION
Each generation has its own characteristics.Andrea Bencsik in her article entitled "Y and Z Generation at Workplaces", explains some of the fundamental differences between each generation; Generation Z (Gen Z) or iGeneration (iGen).They have almost the same similarities with the millennial generation, namely born and growing up during the rapid development of communication technology and the internet.In fact, this generation has a habit of applying technology in various daily activities.The use of smartphones has become a common thing in their activities.Gen Z is very spoiled by the ease of technology today.Discussing the generation in Indonesia, currently, Gen Z is the generation that dominates the population in Indonesia.According to the results of the 2020 population census conducted by BPS, there are 270.20 million Indonesians, or 27.94% or 75.49 million people.The generation born between 1997 and 2012 is known as Gen Z.When this study was conducted, Gen Z in Indonesia was at the age of 25 years -age 10 years (Rakhmah, 2021) Various literacy and expert views say that Gen Z is currently the key generation for its role in developing Indonesia's growth now and in the future.The creativity of Gen Z is very dominant; even according to the results of a survey conducted by Harris Poll in 2020, which shows that Gen Z is interested in creative activities.(Sakitri, 2018) The creativity of Gen Z in creating and producing the economy was also accompanied by the consumptive nature that emerged (Puteri et al., 2022).Consumer risk is caused by various variables, including peer pressure based on community or circle of friends, environment, and other elements, according to digital lifestyle observer Ben Soebiakto.The main factor influencing the consumptive behavior of Gen Z is the environment, further influenced by social media and technology (CNN Indonnesia, 2018).The ease of financial technology, such as digital wallets, mobile banking, online loans, and peer-to-peer (P2P) lending, can now be said to be one of the drivers of the emergence of consumptive lifestyles in Gen Z.
One type of fintech, specifically P2P lending services, consists of lending and lending operations.Fintech lending, also known as P2P lending, is a method of borrowing and borrowing between debtors and creditors directly in rupiah currency supported by information technology.
Fintech lending in Indonesia is divided into two, namely conventional fintech lending and sharia fintech lending.Basically, there is no difference between Sharia fintech lending and conventional fintech lending.However, the rules and regulations stipulated by the National Sharia Council-Indonesian Ulema Council in Fatwa DSN-MUI No. 117/DSN-MUI/II/2018 concerning Technology-Based Financing Services Based on Sharia Principles (Wulandari & Nasik, 2021).Conventional fintech lending and sharia fintech lending must at least adhere to three sharia principles: no maisir (betting), no gharar (uncertainty), and no riba (interest above the terms).The availability of Sharia P2P financing is expected to facilitate the public in carrying out economic activities and transactions in accordance with Sharia principles.
For the public, P2P lending is better known as online loans (pinjol).Especially among Gen Z, which is a generation born in the midst of technological developments, including financial technology; this term is known as paylater.Paylater is an installment payment scheme when someone buys something to buy now and paylater.With the paylater scheme, consumers can make purchases online or offline.P2P lending, particularly paylater, is rapidly growing in Indonesia.The research and market institute predicts paylater growth in Indonesia in 2022 will reach 68.4% on an annual basis or worth US $ 4,674.1 million.The high interest of Gen Z in the paylater payment system and the encouragement of consumptive nature have been proven by several previous studies.The high number of loan recipients or people who make loans from the data provided by OJK (Otoritas Jasa Keuangan -Financial Services Authority) as of June 2022 shows an increase in the number of borrowers under the age of 19 years as many as 532,499 borrower accounts from the previous 73,935 borrower accounts as of May 2022.Based on research with 405 respondents consisting of the age range of 18-21 years in the Jabodetabek area, 58.4% of respondents became more consumptive than the existence of e-wallets.In fact, according to data submitted by Sunu Widyatmoko, Secretary General of AFPBI, 60 percent of borrowers in the fintech (financial technology) sector are aged 19-34 years, which is the age of the millennial generation and generation Z.Based on these data, the majority of borrowers come from Java, namely 82%, while 18% comes from the area of Java Island (Ikhsan, 2022).
According to previous research conducted by Suyanto and Kurniawan (2019), it is stated that in addition to offering various conveniences, P2P lending also has several risks that can endanger its users.Among these risks are 1) Consumer protection including protection of lender funds and protection of borrower data; 2) National interests, such as financial system stability initiatives and AML-CFT.As discussed and data above previously which shows that Gen Z does a lot of lending activities through P2P lending, making it easy to apply for loans through P2P lending is not so much an obstacle for Gen Z in making online loans.Gen Z's lack of understanding of the importance of managing finances can lead them to extravagant and consumptive behavior so that the income they get from work or pocket money from their parents is not used for productive things.This will have an impact on the instability of the Gen Z financial system itself.The data explains that there is a significant increase in the accounts of borrowers who belong to Gen Z.It raises the question of why Gen Z makes online loans, and what drives Gen Z to make online loans.Are online loans made Gen Z allocated to productive needs or activities or just to meet a consumptive lifestyle?
Research on the use of fintech lending has been carried out by previous researchers.However, the majority of research is still limited to examining how generation X and Y behave towards fintech lending.Such as the research of Priskila G (Walangitan et al., 2020) focusing on Gen X and Y in Manado.Likewise, the research of Ni Luh Putu Puspta Dew i (Dewi & Gorda, 2021) on research Gen Y. Although, both of these studies used the foundation of the UTAUT model, only a few variables in UTAUT were used.The research of Henny Triyana Hasibuan is also friends, aiming to see the factors influencing the interest of users of Sharia P2P lending services using the UTAUT 2 model.However, the study did not explain to which generation the research was conducted.Research by Ayman Abdalmajeed Alsmad (Alsmadi et al., 2023) explains the adoption of Islamic fintech lending in Malaysia using the theoretical approaches of TPB, TAM, and several UTAUT variables.However, this study was also conducted on respondents aged 28-48 years, which does not include the age of the current generation Z.
Based on the OJK data, where there is a large growth in the number of borrowers under the age of 19, Gen Z is beginning to actively use fintech lending.However, there has been no research that focuses on examining Gen Z's attitudes toward fintech loans.
As a result, academics believe that literature is scarce on past study studies on Generation Z, hence they believe that this research is necessary.Furthermore, experts believe that the usage of P2P lending in Gen Z is related to spending patterns that must be examined to establish whether these consumption patterns are in conformity with demands in terms of Islamic consumption ethics.

Theoretical Foundation
The adoption of fintech lending technology, which is a technology product in this study, will be analysed using the Unified Theory of Acceptance and Use of Technology (UTAUT) 2 model.The UTAUT 2 model is considered more effective and flexible because it is a combination of several previous theories, namely the Theory of Reasoned Action (TRA), the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), a combination of TAM and TPB, the Social Cognitive Theory (SCT), The Dual-Factor Theory of Perceived Usefulness (DTPU), and the Predictive Control Model (MPC).(Hamrul et al., 2018) The UTAUT 2 model is the result of the development of the UTAUT 1 model, where the UTAUT 2 model has added three new constructs, namely hedonic motivation, price, and habits.The UTAUT 2 model (Hamrul et al., 2018) aims to find three main research constructs related to the acceptance and use of technology by society and consumers, change some of the existing relationships in the concept of the UTAUT 1 model, and add new relationships.The UTAUT 2 model is considered effective in explaining and understanding the factors that encourage the use of technology and how these factors affect the behavioral intention and use behaviour of users of the technology.(Venkatesh et al., 2003) Based on previous research, four main constructs play a role in encouraging behavioural intention to use paylater, namely performance expectancy, effort expectancy, and facilitating conditions.Research conducted by Nugraha (Soegesty et al., 2020) states that performance expectancy, effort expectancy, social influence, and hedonic motivation factors significantly affect the intention to use P2P lending services.Research conducted by Gidion (Adirinekso, 2021) also explained that it affects the intensity of paylater use, but social influence factors have no effect.Another study related to paylater acceptance conducted by Windy (Pratiwi et al., 2020) proved that the previous factor had an effect on the behavioural intention of using the OVO Paylater type of paylater, while effort expectancy had no effect because the level of ease in using OVO Paylater was still considered low.
Furthermore, other studies prove that there is an influence of paylater on impulse buying attitudes, or in this study, consumptive attitudes.Research conducted by Luqman (Hilmi & Pratika, 2021) proves that payback and hedonic motivation have a significant effect on impulse buying.Paylater is also a significant positive factor in impulsive buying.Paylater users tend to often do impulse buying when doing online shopping using e-commerce.
Based on studies of previous studies, the model used in this study is specifically designed to know the factors driving the use or behavioural intention of fintech lending or paylater in generation Z, namely: 1) performance expectation; 2) effort expectation; 3) facilitating condition; 4) social influence; 5) hedonic motivation; 6) price value; and 6) habit.
A review of previous studies was conducted on research related to the use of technology through UTAUT 2 model analysis.The main research comes from the Unified Theory of Acceptance and Use Behaviour model.Performance expectations, effort expectations, enabling circumstances, social influences, hedonic incentives, price values, and habits have a positive and substantial influence on technology utilization, according to the model made by (Venkatesh et al., 2012) Performance expectancy can be interpreted as the trust of technology users in a system or technology used to help achieve profits, and the extent of performance that can be generated from the use of technology explains that performance expectancy or performance expectations are factors that can affect people's intentions to use technology.In addition, Ni Wayan (Pertiwi & Ariyanto, 2021) also explains that performance expectancy is considered to have a positive influence on the intention to use financial technology.In addition, performance expectancy has a significant influence on the use of fintech lending in MSMEs.(Soegesty et al., 2020) From the description above, the hypothesis is H1: Performance Expectancy Positively Affects Behaviour Intention.
Furthermore, the variable effort expectancy is the extent of the ease that individuals feel when using a system or technology.The use of technology is expected to facilitate business.Preeti Tak explained that effort expectancy affects behavioural intention in the use of technology.(Tak & Panwar, 2017) In fact, Simon Megadewandanu stated that effort expectancy is the strongest factor influencing the behavioural intentions of mobile wallet users in Indonesia.(Megadewandanu et al., 2016) Effort expectancy in Amirul Mukminin's research is proven to have a positive and significant influence on influencing the intensity of Traveloka Paylater usage .(Mukminin & Wahyudi, 2019) Therefore, based on a literature review of the effort expectancy variable, a hypothesis can be proposed H2: Effort Expectancy Positively Affects Behaviour and Intention.
Variable facilitating conditions can be interpreted as the extent to which an individual's trust in existing infrastructure and resources can support him in using technology.Facilitating conditions in using fintech lending (paylater) can mean such things as the availability of gadgets, internet networks, and professional services from fintech lending provider companies.The more complete the facilities available, the higher the level of technology use.Other studies have shown that there is a significant effect of facilitating conditions on behavioral intention.Amirul Mukminin (Mukminin & Wahyudi, 2019)also explains that facilitating conditions have a positive and significant influence on behavioral intention.However, research from Mia Audina (Audina et al., 2021) mentioning that facilitating conditions are not a driving factor for technology utilization.From that explanation, hypotheses can be proposed H3: Facilitating Condition Positively Affects Behaviour Intentions.
The next variation in UTAUT 2 is social influence.Social influence in technology adoption is often interpreted as how far individuals think others are important and influential in the process of adopting the technology.Intan Novirani (Rahmatillah, 2018) shows that social influence drives the use of technology.Usually, the use of technology is influenced by family, friends, and co-workers.In the use of fintech lending (paylater), as conveyed by Windy Pratiwi, social influence has a significant positive effect.(Pratiwi et al., 2020) Thus, this study proposes the fourth hypothesis: H4: Social Influence Positively Affects Behaviour and Intention.
The fifth variable is hedonic motivation, which is a modified variable in UTAUT 2 from the previous UTAUT 1. Hedonic motivation can be interpreted as a sense of pleasure and joy obtained when using technology.Hedonic motivation is considered a powerful variable and driver of the use of technology.Wan Rung Lin (Lin et al., 2020) found that hedonic motivation had a positive and significant influence on the intensity of mobile payment users in Taiwan.In addition, Gideon explained that hedonic motivation is the driving force behind using Traveloka Paylater and Gojek Paylater.(Adirinekso, 2021) Then, Luqman Dzul Hilmi explained that hedonic motivation can encourage impulse buying behaviour in Indonesia.(Hilmi & Pratika, 2021) Thus, this study proposes a hypothesis: H5: Hedonic Motivation Positively Affects Behaviour and Intention.
The sixth variable is price alue.This variable is an additional variable in the modification to the UTAUT 2 model.Price value, according to Venkatesh (Venkatesh et al., 2012) has a beneficial impact on intentions when customers believe that using technology is more profitable than expensive.According to the findings of this study, the costs involved in the use of technology, such as administrative costs, interest, and installments that must be returned, can have an impact on the usage of fintech lending (paylater).Gioliano Putra research (Putra & Ariyanti, 2017) explained that the price value significantly affects behavioural intention.Relevant to that, Henny (Hasibuan, 2021) research also explains that price value affects the use of P2P lending.Thus, the sixth hypothesis was proposed in this study, H6: Price Value Positively Affects Behavior Intention.
The last variable used in this study is the habit.The habit of using technology is an activity that is formed based on experience using technology.Kim and Malhotra(Kim & Malhotra, 2005) says that habit is the same as automation.The habits formed can be observed in the frequency of technology use.The higher the frequency of using technology, the greater the habit formed.Habit is also often expressed by a sense of addiction to using technology.Setiawan explained that habits significantly affect behavioral intention in the use of technology.(Kurniabudi & Assegaff, 2016) Gidion's research is contradictory, where the habits formed cannot encourage behavioural intention, as evidenced by the lack of an increase in the frequency in using technology.(Adirinekso, 2021) Here is the seventh hypothesis proposed in the study: H7: Habit Positively Affects Behavior Intention.
Based on the literature review and hypotheses proposed, the conceptual framework compiled in this study is:

METHOD
This research was conducted from July 2022 -October 2022 with students (generation Z) who are Muslims from the provinces of Jakarta, North Sumatra, West Java, East Java and Central Java with a total of 200 respondents as the object of research.The sampling technique used is purposive sampling where only respondents who have used fintech lending or paylater can become respondents in this study.All respondents were given a questionnaire with a total of 40 questions consisting of 1 screening question where this question became a requirement in filling out the questionnaire, namely: Have you ever used a Fintech Lending or PayLater application?If the answer is Yes, the respondent can fill in the continuation of this questionnaire, but if the answer is No, it means that the respondent cannot continue filling out this questionnaire.The other 7 questions are respondent profile questions.While the other 32 questions are questions that are arranged based on the variables in the UTAUT2 model.This study did not reach the testing of the moderating effects of age, gender and experience.Age, gender and experience are sufficiently described in descriptive analysis where the data is obtained from the respondent's profile.
The results of the respondents' answer were analysed using Structural equation Modelling (SEM) through the SmartPLS application version 3.2.9.In addition to not testing the moderation effect of the UTAUT 2 variable, the limitation in this study is also not testing the use behaviour variable because it is considered sufficient to reach behaviour intention.
The outer model test is used to test the construct validity and reliability of the instrument.The validity test was carried out through loading factor parameters with a result indicator of ≥ 0.5 (Hair et al., 2010) and Average Variance Extracted (AVE) with a result indicator of ≥ 0.5 (Ghozali, 2016).Reliability tests were conducted through Cronbach's Alpha with a result indicator of ≥ 0.6 parameters and Composite Reliability with a result indicator of ≥ 0.7 In measuring the fit of the model, we used crossloading and Fornell-Larcker assessments.
Habibullah (Habibullah, 2018) Citing Imam Syatibi's reasoning in the book al-Muwafaqot, it is said that consuming serves the aim of maslahah, which is to bring benefits and prevent damage that can be done.Needs-satisfaction goes beyond simply wanting to use Islamic economics.As a result, when it comes to consumption, humans must prioritise what is a need, what is only a desire, and what is an extravagant lifestyle that eventually leads to consumptive behaviour.
In the Islamic view, consumptive behaviour shows redundant behaviour, which in Islam is strictly prohibited.As the verse of Allah Subhanahu Wata'ala Surah Al-Isra Verse 27 says, Verily, those who are wasteful are brothers of Satan, and Satan is very disobedient to his God.(QS.Al Isra: 27) In addition, the Prophet Muhammad (peace be upon him) said, "Eat and drink, give alms, and dress in moderation."Other Hadiths narrated by Imam Ahmad Matan: An-Nasa'i (2512), Ibn Majah (3595), al-Hakim, and instigated in Sahih al-Jami ash Shagir (4505) in the view of Islamic economics, the principles of moderation and balance should be maintained, whereas waste should be avoided.
Furthermore, Islam has sharia guidelines for consumption (Lubis, 2022) 1) The benefits of what is consumed physically and spiritually must be in accordance with the values of sharia maqashid, namely halal and thoyyib.2) The existence of the principle of independence that emphasizes planning in consumption, having savings, and having debt activities is despicable and must be shunned.3) The existence of the principle of simplicity is qanaah and not redundant.4) The existence of social principles, namely the encouragement of infaq and mutual help.

Research Results
According to the data processing on the gathered questionnaires, up to 200 respondents have given answers and have been considered valid as respondents.The following is a descriptive profile of respondent data from this survey.It can be explained that the majority of respondents in this study were female, as many as 152 (76%).Furthermore, based on monthly income or pocket money, Gen Z in this study had pocket money between Rp 1,000,000 and Rp 2,000,000 (57% of respondents).The majority of respondents came from Jakarta (48%), and only 6% came from Central Java province.The fintech lending applications or paylater services that are often used by respondents are Shopee Paylater (41%), and at least 2% of respondents have used Ammana Paylater.
The intensity of the use of fintech lending or paylater by generation Z is to shop for fashion (26%), then for gadgets (21%), and only 6% use fintech lending or paylater for business capital.The average respondent (46%) has only used 1 fintech lending or paylater application, which has been used more than 5 times, or about 7% of the total respondents.

Outer Model Test (Measurement Model)
The outer model test is carried out to test whether the research model used is reliable (can be used several times) and valid (shows correct and consistent results).Outer model testing is carried out by testing validity and reliability with several methods and references, including convergent validity, discriminant validity, and reliability.The test was conducted with the help of SmartPls software version 3.2.9.The results of outer model testing from the study show that all question indicators in this study have a loading factor value of > 0.5, where, based on the standard indicator of the loading factor, it is 0.5-0.6 to be declared according to convergent validity requirement (Ghozali, 2018).Thus, all statement items in this study are considered feasible and valid for use in research and subsequent data analysis.
Convergent validity can also be measured from the value of average variance extracted (AVE), so an indicator declared valid must have a value above 0.5.That is, based on Table 8.It can be proven that all variables in this study are valid and in accordance with convergent validity requirements based on AVE values.Furthermore, data analysis was carried out by assessing the discriminatory validity, which can be assessed based on the cross-loading value and Fornell Larcker value.The recapitulation of discriminant validity is found in Table 9.
It is known from Table 9 that each statement item has a correlation value on its construct and a correlation value with another construct.Until then, it can be stated that discriminant validity testing through the cross-loading method is in accordance with the requirements.Then, based on the Fornell-Larcker value, it is admitted that the Fornell-Larcker value of each variable exceeds the correlation between the two variables in the model (Table 10).As a result, it can be said that the research variable meets the requirements of discriminant validity.
Next, data testing is done to test reality.The assessment methods are Cronbach's Alpha and Composite Realibility.Cronbach's alpha, while Composite dependency knows the true value of its construct dependency, assessing the lower bound of the item's reliability value.
Based on the two reliability test methods in Table 11 is known that all variables in this study are reliable because they have a value of ≥ 0.60 for Cronbach's alpha test and ≥ 0.70 for composite reliability testing.Therefore, data testing is continued by testing the structural model (inner model.

Inner Model Test (Structural Model)
Through the bootstrapping method on the menu in the SmartPLS 3.2.9application, a mesh coefficient based on each variable is obtained.The inner model test is used in assessing R2 (R-Square value) and Q2 (predictive relevance value) as well as the path coefficient for testing hypotheses.The table of R2 value test results shows that the Behaviour Intention (BI) variable construct has an R2 value of 90.3%.This percentage is considered very good, meaning that the percentage of Behaviour Intention (BI) in this study can be explained as much as 90.3% by independent variables, namely PE, EE, FC, SI, HM, PV, and HBT, but the other 9.7% is exposed to other factors that are not studied this time.As for the Q2 analysis value on Table 11, which is used to evaluate how well the parameter estimation and observation values are produced by the model, the model is said to have a useful predictive value if the Q2 value is greater than zero.It can be interpreted that the behaviour intention variable has a good predictive relevance value because the Q2 value is > 0. Next, the hypothesis is tested through the path coefficient, t-value, and p-value analysis tests.The hypothesis is accepted if the t-statistic or tvalue is > 1.97 (two-tailed test), and the hypothesis test table can be seen in the table below; then his hypothesis was accepted.If the p-value is 0.05 (two-tailed test), then the hypothesis is accepted The confirmation of the hypothesis that has been proposed with the following description: 1.The performance expectancy variable H1 is acceptable in this study because the calculated t value is 2.846 > t table is 1.97 and the p value is 0.004 0.05.In other words, the intention to behave is significantly influenced by performance expectations.2. It can be concluded that H2 was rejected because the effort expectation variable in this study had a calculated value of 0.257 t table 1.97 and a p value of 0.567 > 0.05.That is, there is no visible relationship between behavioral intentions and business expectations.3. H3 can be ruled out because the variable of possible conditions in this study has a calculated value of 0.844 > t table 1.97 and a p value of 0.399 0.05.In other words, the state of the supporter has no visible impact on behavioral intentions.4. It can be assumed that H4 is accepted because the social impact variable in this study has a calculated value of 2.165 > table 1.97 and a p value of 0.030 0.05.In other words, social influence has a huge impact on what people want to do. 5. H5 is accepted because the hedonic motivation variable in this study has a calculated value of 4.757 > Table 1.97 and a p value of 0.000 0.05.In other words, hedonic motivation has a significant effect on behavioural intentions.6. H6 can be ruled out because the price value variable in this study has a calculated value of 0.793 > table 1.97 and a p value of 0.428 0.05.Therefore, there is no visible relationship between price value and behavioral intention.7. It is concluded that H7 is accepted because the habitual variable in this study has a calculated value of 13.617 > Table 1.97 and a p value of 0.000 0.05.This suggests that habits have a major impact on behavioural intentions.

DISCUSSION
The study's first hypothetical finding suggests that performance expectation factors have a positive and substantial impact on behavioral intention.In other words, the finding of the first hypothesis in this study is in accordance with the UTAUT 2 theory which states that there is a positive and substantial relationship between behavioral intentions and performance expectations.Gen Z in this study adopts fintech lending technology (paylater) because they believe that its performance suits their wishes.As many as 53% of Gen Z respondents in this study agree and 17% strongly agree that fintech lending (paylater) can provide convenience in meeting their needs, can save time to obtain their needs (45% strongly agree and 19% agree).Fintech lending (paylater) is considered by the majority of Gen Z in this study (41% agree and 20% strongly agree) to be a fast payment alternative so that the shopping process becomes more efficient.
The results of this research are relevant to the results of research on the theme of fintech lending conducted by Nugraha, where performance expectancy also has a positive and significant relationship.Another study that supports the results of this study is a study with the theme of using paylater in Traveloka conducted by Amirul Mukminin that explains that performance expectancy has a significant effect on behavioural intention.(Mukminin & Wahyudi, 2019) The second hypothesis in this study explains that there is no significant effect of the effort expectancy variable on the behavioural intention variable.The second hypothesis in this study is rejected and does not support the UTAUT 2 model, which states that the higher the effort that must be done by individuals when using technology, the more encouraging the adoption of technology.That is, in this study, although the majority of respondents (more than 50% of respondents) consider that fintech lending (paylater) applications are easy to use and the administrative process is easy to fulfil, it is not enough reason for the majority of Gen Z in this study to use applications or services from fintech lending (paylater).
This can happen because Gen Z is a generation that is very adaptive to technological developments, including financial technology such as fintech lending (paylater).Thus, the use of pay-later technology is a common thing for Gen Z.The results of this study are relevant to the results of the study Audina (Audina et al., 2021) which also explain that effort expectancy has no effect on behavioural intention.However, it is different from the results of research from Nugraha, where effort expectancy turned out to have a positive and significant relationship with behavioural intention towards the use of fintech lending.In contrast to the results of the study , where the result is that effort expectancy has a significant effect on behavioural intention.
The third hypothesis in this study was also rejected; facilitating conditions did not have a significant effect on behavioural intention.The third hypothesis in this study is also not in accordance with UTAUT 2 Venkatesh, which proves that individual intentions to use technology are influenced by the conditions and completeness of facilities that can support the use of technology.
The results of this study are relevant to Mia Audina's research, which also explains that there is no significant relationship between facilitating conditions and the intention to use technology.In contrast to the results of Gideon's research, the study explains that it is precisely facilitating conditions that are an important factor in the use of fintech lending through Paylater, Traveloka, and Gojek, meaning that the study explains that facilitating conditions affect the intention to use technology.While this study is seen based on the average score of respondents' answers to question items on the facilitating condition variable, the results show that the majority of respondents answer that they have facilities and infrastructure (58% agree and 20% strongly agree) such as mobile phones or gadgets, internet access, knowledge in using fintech lending (paylater), can ask for help from others if they experience obstacles in using fintech lending (paylater), and have confidence that this fintech lending (paylater) application is equipped with complete features and supported by professionals, but it has not been the main reason they use fintech lending (paylater).As in the previous analysis, because everyday today it can be said that the majority of Gen Z now already has these facilities and Gen Z is a generation that is responsive to learning technology including fintech lending technology (paylater) .
The fourth hypothesis in this study is that the positive and significant influence of social influence on behavioral intention is proven and acceptable.Based on the average answers of respondents in the study, it can be seen that the influence of the social environment of respondents is very large on the adoption process of using fintech lending (paylater).The results of this research are certainly relevant to the theory of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2).This research is also relevant to the research results of Mia Audina, Nugraha, Windy Pratiwi and Amirul Mukminin1 Which also explains that there is a significant influence of social influence variables on behavioral intention of using technology.
It means that the environment where Gen Z is usually located, such as the environment of friends on campus or school and the family environment, has a considerable influence on the intention to use fintech lending technology (paylater).Based on a descriptive analysis of respondents' answers, 69% of respondents stated that the people around them influenced them to use fintech lending.Positive references from the social environment of Gen Z to the use of fintech lending technology (Paylater) can encourage them to also decide to use fintech lending applications (Paylater).In fact, in the system run by fintech lending (Paylater) service providers, it is known that there is a referral code programme where someone who has used the fintech lending application (Paylater) will get a unique code to be distributed to others so that other people who use it will get attractive promotions, and people who share the unique code also get attractive promotions.This is what then drives the rapid spread of fintech lending technology (paylater) adoption by people around.
Furthermore, the fifth hypothesis in the study was accepted.The hedonic motivation variable has a positive and significant effect on the behavioural intention variable, according to the fifth hypothesis in this study.The results of this study are in line with the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2), which emphasises pleasure or satisfaction obtained from the use of technology.While a person's tendency to use technology increases along with his level of happiness.(Venkatesh et al., 2012) This research is in line with the research of Adirinekso and Nugrahadan Rahmatillah, and the results of these studies also show that hedonic desires have a considerable impact on behavioural intentions.The findings of this study are contrary to the findings of Henny Triyana and Ratna Dzulhaida, who stated that hedonic motivation has little influence on behavioural intentions.Some differences in research results may occur.However, in this study, based on the analysis of respondents' answer scores for each item of hedonic motivation questions with an average value of 70.5%, it can be explained that the majority of Gen Z in this study feel happy and comfortable making purchases supported by fintech lending (paylater) applications.So that the fun and comfort of using the fintech lending application (Paylater) can encourage them to continue using this fintech lending (Paylater) application.
The sixth hypothesis in the study was rejected.It was not shown in the study that changes in price values had a significant influence on behavioural intentions.Therefore, UTAUT 2 does not support this study.However, this study is consistent with Nugraha's research, where explaining monetary value has no impact on behavioural intentions.(Nugraha, 2018) That is, although the perception of Gen Z in this study on administrative costs that are quite affordable is that the majority answered in the affirmative and there is no need to guarantee something to make a loan, the majority of respondents also answered in agreement, and promotions from fintech lending (paylater) that were considered attractive were not enough to dominate other perceptions in the price value question item.The perception of Gen Z respondents turned out to be greater on the belief that loan interest in fintech lending applications (paylater) is greater than loans at banks, and the installments to be paid are also greater than the nominal loan.Thus, the difference in perception in the price value variable is not able to encourage the behavior of using fintech lending applications (paylater).
The seventh and final hypothesis of the study is that habit variables have a positive and substantial impact on behavioural intention variables, supporting the UTAUT 2 model for the Unified Theory of Acceptance and Use of Technology.Habit is seen as a habit obtained from the experience of using a technology, which then encourages a sense of wanting to continue using the technology and even addiction to the technology.The results of the descriptive analysis of respondents' answers to each statement on the habit variable had an average score of 69.68% (high).In this study, it is proven that the use of fintech lending (paylater) applications in Gen Z has become a new habit, especially in supporting online shopping activities.
The results of this study are different from Nugraha's research, where he explained that habit does not have a significant influence on behavioural intention.(Nugraha, 2018) This may happen because the object in (Soegesty et al., 2020)research is MSMEs that make loans in fintech lending for business capital needs.Usually, the need for business capital is greater than the habit of Gen Z who make loans to buy fashion, gadgets and others.So, naturally there is an element of caution that is more from MSMEs when compared to Gen Z.
Finally, based on descriptive analysis of the average score of behavioural intention variables, it is known that the average percentage of behavioural intention variables is 71.08%, which means that it is high enough that it can be concluded that factors that influence behavioural intention can encourage the tendency to use fintech lending (paylater) applications by Gen Z in the future.Gen Z in this study has also planned to use fintech lending (paylater) to meet the needs of online shopping and will invite others to use fintech lending (paylater).
On the other hand, the author also observed how the adoption of fintech lending in Gen Z in this study was dominated by respondents with income or pocket money of IDR 1-2 million per month.In this study, Gen Z made loans through fintech lending for consumptive needs such as purchasing fashion and gadgets.Several studies mention that the presence of fintech lending should provide great benefits for economic development if used for productive things.Researchers assess that fashion and gadget spending carried out by Gen Z is only a consumptive activity that is driven by lifestyle.Only 2% of the total Gen Z respondents in this study use loans through fintech lending for business capital.
The ease of the loan application process through fintech lending such as ShopeePay is a strong encouragement for Gen Z to continue to consume things that are not priorities.Another problem is that Gen Z in this study is made up of Muslims.However, based on the results of data collection, it is known that the majority of fintech lendingbased loan service providers that they often use are not sharia fintech lending companies.So, it is likely that the transactions they make have elements of usury.In Islam, riba is clearly forbidden as written in the Qur'an Surah Al-Imron, verse 130, which means: "O believers!Do not eat usury in one fold and fear Allah so that you may be lucky.(QS.Al-Imron-130)" Therefore, this should be a common concern and a reminder that, as Muslims, there are obligations and responsibilities that must be carried out regarding consumption.As Muslims, they must be more careful in their daily consumption patterns in the midst of rapid technological developments today.

Table 5 .
Category Shopping

Table 6 .
Frequency of Use of Fintech Lending

Table 7 .
Factor Loading Test Results

Table . 8
AVE Test Results

Table . 9
Recapitulation of Discriminant Validity Assessment

Table . 10
Recapitulation of Discriminant Validity Assessment

Table 11 .
Recapitulation of Discriminant Validity Assessment

Table 11 .
Hypothesis Test Based on Path Coefficient *Source: Processed Research Data 2022