Journal of Islamic Monetary Economics and Finance, Vol. 9, No. 3 (2023), pp. 533 - 558 p-ISSN: 2460-6146, e-ISSN: 2460-6618 THE ISLAMIC BANKING CUSTOMERS’ INTENTION TO USE DIGITAL BANKING SERVICES: AN INDONESIAN STUDY Darwis Harahap1, Ahmad Afandi2 and Try Mahendra Siregar3 1 Syahada State Islamic University Padangsidimpuan, Indonesia, darwisharahap@uinsyahada.ac.id Syahada State Islamic University Padangsidimpuan, Indonesia, ahmadafandi@uinsyahada.ac.id 3 Yogyakarta State University, Indonesia, trymahendrasiregar@gmail.com 2 ABSTRACT This study examines factors that influence Indonesian Islamic banking customers’ behavioral intention to utilize digital banking services using the Unified Theory of Acceptance and Use of Technology (UTAUT 2). The factors examined include effort and performance expectations, social influence, facilitating conditions, price value, hedonic motivation, habits, trialability, and spiritual motivation. The study also examines whether Islamic lifestyle moderates the roles of social influence, habits, and spiritual motivation in the tendency to utilize Islamic digital banking. Gathering data from 195 Indonesian millennials and utilizing the partial least squares structural equation modeling (PLS-SEM) method, we find that not all factors have a positive effect on the propensity to utilize Islamic digital banking services. The performance expectations, social influences, price values, habits, and Islamic lifestyles all have a strong favorable effect on the desire to use digital banking. Meanwhile, the facilitating condition, hedonic motivation, trialability, and spiritual motivation only slightly affect the intention to use digital banking. Finally, the paper notes that absence of Islamic lifestyle’s moderating role. Keywords: UTAUT2, Trialability, Spiritual motivation, Islamic lifestyle, Digital banking. JEL classification: G40; G10; 010. Article history: Received : January 11, 2023 Revised : April 19, 2023 Accepted : August 31, 2023 Available online : September 29, 2023 https://doi.org/10.21098/jimf.v9i3.1673 534 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study I. INTRODUCTION The advancement of technology and information in the banking industry has had a significant impact on banking, leading to the introduction of various new financial services such as SMS banking, phone banking, internet banking, mobile banking, and other payment systems known as digital banking (Riza & Hafizi, 2019). Bank Indonesia (BI) notes that digital banking transactions in 2022 increased by 28.72% compared to the previous year to IDR 52,545.8 trillion. The BI further has projected the increase in digital banking transactions in 2023 by 22.13% to Rp. 64,175.1 trillion. Following the increasing users of digital banking, banks’ financial performance contributed by digitalization also improves (Azman & Zabri, 2022; Mosallamy & Metawie, 2022). Sharia banking still accounts for 5.99% of the total banking industry in Indonesia. Given that Indonesia has the world’s biggest population of Muslims, there are both possibilities and obstacles for Islamic banking to grow its market share (Nasuha, 2020). Despite those possibilities, utilizing information technology to provide customers with services is one approach to offer (Sahu & Deshmukh, 2020). The success of digital banking depends not only on the provision of applications by banks but also on persuading customers to embrace them as an alternative to in-person bank encounters (Shaikh & Karjaluoto, 2015). Meuter et al. (2005) emphasize that the challenge is not managing technology but convincing consumers to try it. The increased usage of digital banking suggests a shift in consumer banking behavior (Cuesta et al., 2015). The rapidly increasing demand for technologybased financial services and competition in the banking sector has compelled banks to digitize services in order to avoid falling behind (Beckett, Hewer, & Howcroft, 2000). Dasho et al. (2016) state that banking must go digital, embracing a technological revolution and innovation in order to respond to changes in customer dynamics caused by the internet. However, requiring customers to change their behavior from conducting traditional transactions to using digital banking channels is not an easy process, mainly due to the lack of understanding of customers about this phenomenon (Curran & Matthew, 2007). Previously, not much literature discusses the digital banking adoption in Islamic banking. Most previous studies focus mainly on mobile banking (Nawaz et al., 2020; Susilowati et al., 2021; Win et al., 2021) health care device (Wang et al., 2020), online shopping or purchases (Sun, 2022), and e-commerce mobile applications (Alamanda et al., 2021). In light of this, this study examines factors that influence Indonesian Islamic banking customers’ behavioral intention to utilize digital banking services using the Unified Theory of Acceptance and Use of Technology (UTAUT 2) as proposed by Venkatesh et al. (2012). In the literature on technology adoption, the unified theory of acceptance and use of technology (UTAUT) (Akhtar et al., 2019; Merhi et al., 2019; Soomro, 2019) is normally applied to examine the perceived usefulness, an intention to use an information technology and willingness to embrace technological advances in individual (Venkatesh et al., 2003). Then, Venkatesh et al. (2012) extends the UTAUT, which focuses only on consumer behavior (Purwanto & Loisa, 2020; Soomro, 2019), to other constructs, namely; effort expectations, performance expectations, social factors, hedonic motivation, values, and habits, Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 535 known as UTAUT2. Hence, applying the UTAUT2, this study examines the behavioral intentions of Islamic banking customers to digital banking services for the case of Indonesia. II. LITERATURE REVIEW AND RESEARCH HYPOTHESIS Customers’ acceptance of technology has attracted a great deal of attention in the literature. In this regard, the unified theory of acceptance and use of technology or UTAUT developed by Venkatesh et al. (2003) has gained popularity for understanding customers’ behavior toward technology, see inter alia Akhtar et al., (2019), Merhi et al., (2019) and Soomro, (2019). The UTAUT is based on four major factors that drive behavioral intention to use information technology. These are performance expectations, social variables, business expectations, and facilitating conditions. In their subsequent work, Venkatesh et al. (2012) incorporate additional three major variables, i.e. hedonic motivation, price value, and habits in the model, which is known as UTAUT2. The UTAUT and its extension or UTAUT 2 have been applied in different contexts, which mobile-banking (Nawaz et al., 2020; Susilowati et al., 2021; Win et al., 2021) health care device (Wang et al., 2020), online purchases (Sun, 2022), and e-commerce mobile applications (Alamanda et al., 2021). As far as the digital banking in Islamic banking is concerned, however, the application of these models in particular the UTAUT2 remains sparse. Thus, the understanding of how the main constructs of UTAUT2, namely performance expectations, effort expectations, social factors, and conditions that facilitate hedonic motivation, habits, and price values influence the adoption of Islamic digital banking is limited. Farzin et al. (2021) conduct a trialability study and discover that it has an effect on the intention to use mobile banking. In this research, together with spiritual motivation, trialability is added as a new construct. The reason for adding spiritual motivation is to complement hedonic motivation, which is a construct in UTAUT2. If the hedonic motivation variable sees a person’s tendency in terms of happiness (Chang et al., 2019; Nawaz et al., 2020; H. Wang et al., 2020), the spiritual motivation views motivation in the context of worship. So it can be concluded that spiritual motivation is the opposite of material motivation (Wadi & Nurzaman, 2020). Then, we add an Islamic lifestyle as a moderating variable. The Islamic lifestyle is one of the habits of a person to live a daily life in accordance with the values ​​and principles of the Islamic religion (Ebrahimi & Yusoff, 2017). In line with previous research, Islamic lifestyle moderates social influences, habits and spiritual motivations. Parsamehr et al. (2014) state in their research results that the Islamic lifestyle has a direct relationship to social adaptation. Then Sukardani et al. (2018) find that social activities play an active role in creating lifestyle trends that are in accordance with Islamic teachings or better known as the halal lifestyle. Asghari & Safara (2015) find that Islamic lifestyle has a significant positive relationship with happiness. Aryadi & Rahmawati (2019) find positive causality between spiritual motivation and religious performance. 536 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study 2.1. Performance Expectation The point to which an individual agrees using the system will benefit her/him in task execution is defined as performance expectation (Venkatesh et al., 2003). Users will be more encouraged to adopt specific mobile technologies if they feel that adopting them would improve their standard of living and offer them with new purposes (Ashraf et al., 2014; Azman & Zabri, 2022; Baabdullah, 2018). Consequently, performance expectation is the most likely predictive factor impacting technology adoption intention (Afshan & Sharif, 2016). Previous studies reveal that performance expectation influences the inclination for using a technology (Akhtar et al., 2019; Baabdullah, 2018; Intarot & Beokhaimook, 2018; Sun, 2022). Based on these, the hypothesis to be tested is: H1: Performance Expectation Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks. 2.2. Effort Expectation Effort expectation reflects how much a person believes in the ease of usage (Venkatesh et al., 2003). The variable of effort expectation is generated based on prior theory’s three key components, namely the TAM model’s perceived ease of use. The effort expectation is also an important factor in determining whether or not someone is interested in using technology (Kasri & Sosianti, 2023). The simpler an application, the more inclined people will be in using technology. Previous studies have discovered that effort expectation affects the intention to utilize technology (Ahmad et al., 2021; Akhtar et al., 2019; Cooperman et al., 2011). Based on the description above, the hypothesis is: H2: Effort Expectation has a Positive Effect on the Intention to Use Digital Banking in Islamic Banking 2.3. Social Influence In this context, social influence occurs when individuals believe that their peers assume they should utilize digital banking or electronic payments (Afshan & Sharif, 2016). A person’s behavior is shaped by his social impact because they can preserve peace or harmony in groups and maintain reciprocal relationships (Soomro, 2019). The findings of previous studies show that technology adoption is influenced by social influences (Al-okaily et al., 2022; Chang et al., 2019). From the description above, the hypotheses is : H3: Social Influence Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks 2.4. Facilitating Condition The facilitating condition refers to a person’s assessment of the system’s existing technical and organizational infrastructure (Venkatesh et al., 2003). This condition Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 537 implies the portability and accessibility of resources that result in the adoption of particular behaviors (Siddik et al., 2014). This condition additionally affords the individual a sense of psychological control over his propensity to accept particular actions, and it is mostly influenced by a person’s social, cultural, and technological background (Farzin et al., 2021). Researches by Al-okaily et al. (2022), Chang et al. (2019), Li et al. (2018), and Purwanto & Loisa (2020) show that facilitating conditions influence user intention, so the hypothesis is as follow: H4: Facilitating Condition Has a Positive Effect on the Intention to Use Digital Banking in Islamic Banks 2.5. Hedonistic Motivation Venkatesh et al. (2012) include the hedonistic motivation as an additional variable in their extension of UTATUT into UTAUT-2. Hedonistic motivation refers to a person’s enjoyment in leveraging the technology. Hedonic motivation, according to Zia & Alzahrani (2022), is defined as intrinsic motivation, such as pleasure, happiness, or the enjoyment of using and leveraging technology. This means that consumers will be more likely to rely on technology that appears interesting and has unique and imaginative skills and functionalities (Merhi et al., 2019; Sahu & Deshmukh, 2020). Previous studies find that hedonic incentive influences usage intention (Ahmad et al., 2021; Alamanda et al., 2021; Farzin et al., 2021). The hypothesis based on the given description then is: H5: Hedonistic Motivation Has a Positive Effect on Intention to Use Digital Banking in Islamic Banks 2.6. Value Price Venkatesh et al. (2012) depict the price value as a tug of war between advantages and payments of using technology, such as internet fees, bank service fees, and transaction fees (Raza et al., 2019). A good pricing value implies that the advantages surpass the monetary expenses (Baptista & Oliveira, 2015). Existing studies show that the price value positively influences the intention to use technology (Yoga & Triami, 2021; Zia & Alzahrani, 2022). So, based on this finding, the hypothesis is: H6: Price Value Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks 2.7. Habit Venkatesh et al. (2012) relate habitual characteristics to the degree to which a person tends to perform behaviors automatically based on learning. Habits explain how individuals behave towards technology and will use it automatically after learning. It is also related to experiences, in which the experiences can form different levels of habits, or in other words, experiences can reflect the results of a habit. The habits can influence the intention to use technology (Alamanda et al., 2021; Susilowati et al., 2021). Owing to this, the hypothesis is: 538 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study H7: Habits Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks 2.8. Trialability Trialability of an innovation is the level to which it can be tested on a small scale (Koksal, 2016). The trialability to try is often assumed to affect a person’s willingness to adopt a technology. The trialability to test reduces potential users’ uncertainties and boosts their faith (Wang, 2014). As a result, novel products and services that might be assessed before they fully are fully integrated are more likely to be approved (Alam et al., 2022). Farzin et al. (2021) conduct a research on the trialability and discover that it affects the intent to embrace mobile banking technology. Another study by Chen (2013) has also shown that the trialability is positively correlated with the technology adoption rate. Therefore, the hypothesis is: H8: Trialability Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks 2.9. Spiritual Motivation Sheldrake (2005) defines spirituality as the consciousness of a personal connection with God for those who believe. Then, the spirituality is interpreted as a factor of the needs that the individual wants as a goal to find the meaning of life (King et al., 2006; Monod et al., 2011). In this research, spiritual motivation is a sense of benefit to society and an enduring reward for the intention to use technology. Previous studies point out a connection between spirituality and economic or financial behaviors. Thus, the hypothesis is: H9: Spiritual Motivation Has a Positive Effect on The Intention to Use Digital Banking in Islamic Banks 2.10. Behavioral Intentions Behavioral intentions are ones in which an individuals’ conduct affects how they use technology (Venkatesh et al., 2003). Numerous studies have stated that behavioral intentions influence banking usage behavior. Behavioral intent represents a predictor of the behavior of banking customers’ use. These findings align with previous studies showing that behavioral intentions positively impact usage behavior (Parsamehr et al., 2014; Raza et al., 2019; Win et al., 2021). By the description above, the hypothesis will be: H10: Intention to Use Has a Positive Effect on The Behavior of Use Digital Banking in Islamic Banks Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 539 2.11. Islamic Lifestyle Islamic lifestyle is a tendency to consume and utilize products and services carried out in everyday life, standardized with the teachings of the Islam (Azizibabani et al., 2022). It relates the philosophy of life from an Islamic perspectives. The Islamic lifestyle has a direct and important association with social adaptation, hence the more Islamic a person’s lifestyle, the more social adaptation he or she will have (Parsamehr et al., 2014). Asghari & Safara (2015) conclude that the Islamic lifestyle has a positive connection with happiness. In addition, Alamanda et al. (2021) also discover that habits have a significant and favorable impact on the intention to utilize technology. Spiritual motivation is related to the fulfillment in spiritual needs such as self-actualization and the individual’s propensity for a certain religion, and it will modify his behavioral patterns (King et al., 2006). Aryadi & Rahmawati (2019) document a positive causality between spiritual motivation and religious performance. The hypotheses developed in this study are as follows: H11: Islamic Lifestyle Has a Positive Effect on the Intention to Use Digital Banking in Islamic Banks H12: Social Influence Significantly Effects the Intention to Use Digital Banking in Islamic Banks Through an Islamic Lifestyle H13: Habits Significantly Effects the Intention to Use Digital Banking in Islamic Banks Through an Islamic Lifestyle H14: Spiritual Motivation Has a Significant Effects on The Intention to Use Digital Banking an Islamic Banks Through an Islamic Lifestyle III. METHODOLOGY 3.1. Data This study takes Indonesia as a case study, focusing specifically on Muslim millennials born between 1980 and 2000 who are technologically adept and familiar with Islamic bank digital banking. According to Hair et al. (2010), a sample size be between 100-200 respondents should prove adequate for the application of the Structural Equation Model (SEM). Bhattacherjee (2012) suggests multiplying the number of variables included in the study by 5 to set the minimum number of respondents. Using purposive sample technique, we gather data from 195 respondents, which meet the recommendations by Hair et al. (2010) and Bhattarcherjee (2012). In the study, we adopt the PLS-SEM data analysis technique due to the data’s tendency to be non-normal, the model’s complexity, and the low sample size of 200 respondents (Hair et al., 2017). The questionnaires are distributed using Google Form and they have 39 questions on a Likert scale, which are sent out to respondents who use digital banking from Indonesian Islamic banks. A total of 267 responses were received; however, after filtering, only 195 are chosen. Respondents were asked four demographic questions, ranging from gender, age, and employment to how long they have used digital banking in Islamic institutions, which are presented in Table 1 below. The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study 540 Table 1. Respondent Demographics Characteristic Gender Man Woman Total Age 20-30 31-40 41-50 Above 50 Total Work Civil Service Entrepreneurial Self-employed Student Other work Total Domicile Province Aceh North Sumatera West Sumatera Riau Jambi South Sumatera Bengkulu Lampung Bangka Belitung Islands Riau Islands Special Capital Region of Jakarta West Java Central Java Banten East Java Special Region of Yogyakarta Bali East Nusa Tenggara West Nusa Tenggara West Kalimantan South Kalimantan Central Kalimantan East Kalimantan North Kalimantan South Sulawesi North Sulawesi Frequency Percentage (%) 86 109 195 44.11 55,89 100 74 56 43 22 195 37.95 28.72 22,05 11,28 100 56 29 35 37 38 195 28.72 14,87 17.95 18,97 19.49 100 16 24 11 3 2 9 9 4 4 8 15 8 12 6 7 15 4 1 2 2 3 2 2 1 2 4 8,21 12,31 5,64 1,54 1,03 4,62 4,62 2,05 2,05 4,10 7,69 4,10 6,15 3,08 3,59 7,69 2,05 0,51 1,03 1,03 1,54 1,03 1,03 0,51 1,03 2,05 541 Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 Table 1. Respondent Demographics (Continued) Characteristic Central Sulawesi South East Sulawesi West Sulawesi Gorontalo North Maluku Maluku West Papua Papua Total Duration of use (in years) Less than 1 1-2 2-4 Above 4 Total Frequency Percentage (%) 3 1 2 3 2 2 2 4 195 1,54 0,51 1,03 1,54 1,03 1,03 1,03 2,05 100 47 49 65 34 195 24.11 25.13 33,33 17.43 100 3.2. Method To test the research hypotheses, the PLS-SEM method is used (Ascarya & Indra, 2022; Hair et al., 2017). Table 2 contains information on latent variables along with indicators. The SMARTPLS 3.0 software is used (Hair et al., 2017) as follows: 1) Evaluation of the outer (measurement) model: Individual item reliability, internal consistency (construct reliability), average variance extracted (AVE), and discriminant validity; 2) Evaluation of the inner (structural) model: path coefficient, collinearity, effect size (f2), coefficient of determination (R2 value), and predictive relevance (Q2). Table 2. Research Variable Variable Performance Expectation Effort Expectation Social Influence Facilitating Conditions Indicators Promote productivity Increase opportunities Usefulness in daily life More efficient Easy to learn User friendly Fair and understandable Easy to master The influence of significant people Social factors Participation of others Presence of resources Existence of knowledge Assistance/infrastructure Source (Venkatesh et al., 2012) (Venkatesh et al., 2012) (Venkatesh et al., 2012) (Venkatesh et al., 2012) 542 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study Table 2. Research Variable (Continued) Variable Hedonistic Motivation Value Price Habit Trialability Spiritual Motivation Islamic Lifestyle Intention to Use Use Behavior Indicators Fun Entertaining Pull Affordability Price conformity to benefits Provides great value Habit. Addiction to use. Must use Naturalness Can try Easy to use Opportunity to try Faith motivation Worship motivation Muamalah motivation. Activity Opinion Interest Intention to try Plan to use Intention to behave Intention to continue using Satisfaction of use Recommend use Source (Venkatesh et al., 2012) (Venkatesh et al., 2012) (Venkatesh et al., 2012) (Wang, 2014) (Aryadi & Rahmawati, 2019) (Azizibabani et al., 2022) (Venkatesh et al., 2012) (Venkatesh et al., 2012) 3.3. Model Development The model for this study is derived from UTAUT2 by Venkatesh et al., (2012) with Trialability (T), Spiritual Motivation (SM), as exogenous variables, and Islamic Lifestyle (IL) as the moderating variable. Figure 1 shows an illustration of the research model. 543 Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 Performance Expectancy Effort Expectancy Social Influence Facilitating Condition Intention to Use Digital Banking Hedonic Motivation Price Value Use Behavior Habits Trialability Spiritual Motivation Islamic Lifestyle Figure 1. Research Models Notes: EE= Effort Expectancy, PE = Performance Expectancy, SI= Social Influence, FC= Facilitating Condition PV= Price Value, HM= Hedonic Motivation, H= Habit, SM= Spiritual Motivation, T= Trialability, IL= Islamic Lifestyle, UB= Use Behavior, and IB= Intention to Use. IV. RESULTS AND DISCUSSION 4.1. Results 4.1.1. Evaluation of the Measurement (Outer) Model The external model for a measurement within the theoretical framework determines the association between indicators and their supports. PLS pathway modeling is used to measure Cronbach’s alpha, composite reliability (CR), discriminant validity, Average Variance Extracted (AVE), and convergent validity. Cronbach’s alpha values range from 0.748 to 0.910, while the CR values range from 0.882 to 0.937. Based on Hair et al. (2017) for internal construction consistency reliability, it must be above 0.70 (α and CR > 0.70). Table 3 displays composite reliability (CR) and Cronbach’s alpha (α) values. Convergent validity and discriminant validity are tested using average variance extract (AVE) and outer loadings values. Convergent validity is demonstrated by the loading factor value, which is considered to be acceptable if it is more than 0.7 (Hair et al., 2017). The Average Variance Extracted (AVE) number is likewise unaffected because it is more than 0.50, as proposed by Henseler et al. (2009). The degree to which one construct differs from another is shown by the discriminant validity. This assures that a construct gets an uncommon occurrence that other constructs do not describe (Hair et al., 2011). To assess discriminant 544 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study validity, the Fornell-Larcker criterion is used (Hair et al., 2017). Investigating the Fornell-Larcker criteria reveals that the AVE square root value for each AVE construct is more than the construct with the highest relations with the others, see the following table 4. Table 3. Measurement Model Output Variable Performance Expectations (α=0,867, CR=0,906 and AVE=0,708) The use of digital banking in Islamic banks can improve my performance The use of digital banking in Islamic banks can save me time I use digital banking in Islamic banks in every activity I think digital banking of Islamic banks is beneficial and increase the effectiveness Effort Expectations (α=0,910, CR=0,937 and AVE=0,788) I find it easier to learn to use digital banking in Islamic banks I am more skilled in using digital banking in Islamic banks I think Islamic bank digital banking is easy to use Connecting with digital banking Islamic banks is easy for me Social influence (α=0,895, CR=0,934 and AVE=0,826) People whose opinions I value advocate using digital banking in Islamic banks I was advised to use digital banking in Islamic bank because I feel it is important People are essential to me in suggesting the use of digital banking in Islamic banks Facilitating conditions (α=0,748, CR=0,855 and AVE=0,663) My residence supports using digital banking in Islamic banks I have sufficient knowledge about digital banking in Islamic banks Using digital banking in Islamic banks according to my needs Hedonistic motivation (α=0,799, CR=0,882 and AVE=0,713) I think using digital banking in Islamic banks is fun I feel entertained when using digital banking in Islamic banks I think digital banking in Islamic banks is interesting Price Value (α=0,793, CR=0,878 and AVE=0,707) I think using digital banking in Islamic banks is very cheap I think digital banking in Islamic banks is very affordable The fees set on Islamic bank digital banking are commensurate with the benefits provided Habit (α=0,837, CR=0,892 and AVE=0,674) I am used to using digital banking in Islamic banks For any payment, I have to use digital banking in an Islamic bank I feel more effective and dependent on using digital banking in Islamic banks In my opinion, digital banking of Islamic banks has become a trend and commonplace among the public Code Loadings Weight PE.1 0,874 0,276 PE.2 PE.3 0,876 0,823 0,287 0,268 PE.4 0,777 0,369 EE.1 EE.2 EE.3 EE.4 0,884 0,920 0,891 0,855 0,304 0,276 0,233 0,274 SI.1 0,931 0,369 SI.2 0,937 0,434 SI.2 0,856 0,423 FC.1 FC.2 FC.3 0,742 0,850 0,847 0,369 0,434 0,423 HM.1 HM.2 HM.3 0,806 0,861 0,866 0,437 0,392 0,385 PV.1 PV.2 0,818 0,828 0,424 0,342 PV.3 0,875 0,279 H.1 H.2 0,723 0,804 0,262 0,316 H.3 0,873 0,333 H.4 0,874 0,377 545 Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 Table 3. Measurement Model Output (Continued) Variable Code Loadings Weight T.1 T.2 0,867 0,902 0,331 0,380 T.3 0,859 0,440 SM.1 0,888 0,397 SM.2 SM.3 0,875 0,876 0,365 0,279 IL.1 0,831 0,321 IL.2 0,862 0,342 IL.3 0,851 0,326 BI.1 0,773 0,329 BI.2 0,875 0,366 BI.3 BI.4 0,839 0,793 0,265 0,321 UB.1 0,904 0,431 UB.2 0,887 0,398 Trialability (α=0,849, CR=0,908 and AVE=0,768) I tried correctly before deciding to use digital banking in Islamic bank I use digital banking in Islamic bank as a test to see what it can do I have many opportunities to try various digital banking capabilities of Islamic banks Spiritual motivation (α=0,855, CR=0,911 and AVE=0,774) I am sure that when using digital banking in Islamic banks will facilitate activities I use digital banking in Islamic bank based on worship Digital banking in Islamic bank is here according to my needs Islamic lifestyle (α=0,805, CR=0,885 and AVE=0,719) Digital banking from Islamic banks makes me more confident in my daily activities I use digital banking in Islamic banks because it is under the sharia system Using digital banking in Islamic banks provides a sense of security and peace of mind during transactions Intent to use (α=0,838, CR=0,892 and AVE=0,674) I intend to continue using Islamic bank digital banking in the future I will always try to use digital banking in Islamic banks in my daily life I plan to use digital banking in Islamic banks frequently In the future, I will continue to use digital banking in Islamic banks Usage behavior (α=0,745, CR=0,890 and AVE=0,802) I feel satisfaction when using digital banking in Islamic banks I am willing to recommend the use of digital banking in Islamic banks to others Table 4. Fornell-Larcker Criterion Output BI EE FC H HM IL PE PV THE BC T UB BI EE FC H HM IL PE PV THE BC T 0,821 0,559 0,562 0,797 0,660 0,682 0,482 0,599 0,623 0,618 0,689 0,665 UB 0,888 0,741 0,613 0,571 0,566 0,769 0,569 0,462 0,582 0,556 0,561 0,814 0,599 0,584 0,532 0,654 0,610 0,402 0,530 0,510 0,501 0,821 0,715 0,641 0,625 0,755 0,703 0,619 0,773 0,711 0,845 0,545 0,575 0,694 0,639 0,540 0,618 0,584 0,848 0,576 0,668 0,352 0,866 0,701 0,791 0,842 0,619 0,487 0,605 0,569 0,542 0,841 0,488 0,656 0,636 0,610 0,909 0,353 0,520 0,523 0,880 0,673 0,622 0,876 0,710 0,896 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study 546 4.1.2. Evaluation of the Structural (Inner) Model To determine the path coefficient of the suggested links and the coefficients of determination of the innate variables, the PLS algorithm step is used. The Bootstrap is used to determine the results relevancy. As proposed by Kleinbaum et al. (1988), one of the most effective steps is to deploy an evaluation of the variance inflation factor (VIF), which can also be utilized to assess the multicollinearity presence among the independent variables. The regression analysis reveals that the VIF approximately ranges from 1.016 to 4.148. Owing to Hair et al. (2014), the variance inflation factor below 5 indicates no multicollinearity issue. Further, the analysis includes an examination at the Effect Size (f2). Cohen (1988) divide f2 values of 0.02 (small), 0.15 (medium), and 0.35 (large), and these can be used to predict the size of the predictor effect. As shown in Table 5, the overall output f2 ranges from 0.001 to 0.803. Table 5. Effect Size and Multicollinearity Output Construct Relationship f² VIF PE -> BI EE -> BI SI -> BI FC -> BI HM -> BI PV -> BI H -> BI T -> BI SM -> BI BI -> UB IL -> BI 0,067 0,022 0,035 0,005 0,011 0,061 0,231 0,009 0,001 0,803 0,035 3,715 4,148 3,980 2,896 3,684 2,370 2,899 1,016 2,836 3,490 2,189 The value of the coefficient of determination (R2) shows the accuracy of construct predictions in the suggested model. The R2 value of the dependent variable is maximized in PLS-SEM. According to Hair et al. (2017), The cutoff values for Weak, Medium, and Strong R2 are 0.25, 0.50, and 0.75, respectively. The purpose construct’s coefficient of determination is moderate (R2 = 0.745, R2 adjusted = 0.738). As a result, all independent variables have a 74.5% influence on the intention to use, with the remaining 25.5% influenced by other variables not investigated in this study. Similarly, intention to use has a 44.2% effect on using behavior, with the remaining 55.8% affected by variables not investigated in this study. The Q2 value can be used to predict the importance of the independent variable to the dependent variable (Hair et al., 2017). The Q2 value of the intention to use variable is 0.738, and the usage behavior is 0.439, both of which are greater than the minimal threshold value of 0. It shows that the values are correctly recreated, allowing the model to be predictive. 547 Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 Table 6. R-Square (R2) and R Square Adjusted (Q²) Output Variable BI UB R Square R Square Adjusted 0,745 0,442 0,738 0,439 The testing for the hypothesis is done by Smart PLS application, bootstrapping innovative PLS re-sampling method (Hair et al., 2017). The hypothesis’s significance value is tested under the assumption that the main sample has a positive or negative influence as the t-statistics value is greater than 1.65 and the p-value is less than 0.05. The inner model results in this investigation are also shown in figure 2 below. PE2 PE3 PE4 32.897 26.875 24.194 38.145 PE1 EE1 EE2 EE3 PE 29.961 42.927 39.543 28.155 EE EE4 SI1 SI2 SI3 FC1 FC2 FC3 HM1 HM2 HM3 PV1 PV2 PV3 H1 H2 H3 59.296 53.248 26.885 10.246 27.292 27.588 T2 T3 SM1 SM2 SM3 1.160 FC 19.776 33.193 24.952 2.362 1.850 HM 23.410 19.867 30.909 BI1 BI2 BI3 BI4 18.769 36.786 27.764 15.307 1.108 2.796 PV 14.749 26.042 45.156 35.722 12.700 0.310 4.962 0.777 [+] 0.298 H H4 T1 2.811 SI BI 0.695 [+] 36.364 UB1 28.337 UB2 UB [+] IL*SM 0.186 IL*SI 2.632 IL*H 21.269 40.620 28.458 T 43.003 26.697 44.227 IL1 IL2 IL3 SM 22.770 31.550 30.519 IL Figure 2. Inner Model Research Model 4.2. Robustness Check Researchers commonly assume that the relationships between the constructs are linear when developing trending route models. While the linear relationship is often a good approximation, it may not be the case (Ahrholdt et al., 2019). Sarstedt et al. (2020) recommend non-linearity criteria to enhance robustness. As a result, we 548 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study also look at a quadratic effect. The quadratic effect output reveals that the results are insignificant to all pathways. To summarize, the interaction is insignificant, demonstrating the robustness of the linear impact (Sarstedt et al., 2020). Table 7. Output of Quadratic Effect Variable PE -> BI EE -> BI SI -> BI FC -> BI HM -> BI PV -> BI H -> BI T -> BI SM -> BI BI -> UB IL -> BI Quadratic Effect PE -> BI Quadratic Effect EE -> BI Quadratic Effect SI -> BI Quadratic Effect FC -> BI Quadratic Effect HM -> BI Quadratic Effect PV -> BI Quadratic Effect H -> BI Quadratic Effect T -> BI Quadratic Effect SM -> BI Quadratic Effect BI -> UB Quadratic Effect IL -> IB IL*SI -> BI IL*H -> BI IL*SM -> BI Β p-values f² 0,229 0,140 0,171 0,064 0,104 0,231 0,554 0,091 0,028 0,673 0,236 -0,049 0,043 0,014 -0,031 -0,018 -0,028 0,101 0,068 -0,198 0,043 -0,206 0,033 -0,045 0,441 0,005 0,247 0,019 0,065 0,268 0,005 0,000 0,766 0,853 0,000 0,009 0,601 0,662 0,845 0,926 0,788 0,646 0,569 0,459 0,348 0,843 0,352 0,487 0,757 0,757 0,803 0,022 0,005 0,231 0,011 0,035 0,002 0,002 0,041 0,067 0,061 0,007 0,007 0,004 0,016 0,002 0,052 0,011 0,004 0,001 0,035 0,028 0,035 0,001 0,009 4.3. Discussions 4.3.1. Performance Expectation Toward Intent Use The results show that the expectation performance has a substantial positive effect on the intention to utilize digital banking of Islamic banks. It is thus in accordance to the theory of Venkatesh et al. (2012), which emphasizes the performance expectation as the strongest predictor of intention for the use of technology. This study uses the UTAUT by Venkatesh et al.(2012), which concentrates on using and utilizing technology. The results thus are in line with previous studies that state that the performance expectation can influence the intention of using technology (Afshan & Sharif, 2016; Akhtar et al., 2019; Baabdullah, 2018; Intarot & Beokhaimook, 2018; Sun, 2022). Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 549 4.3.2. Effort Expectation Toward Intent Use Intent to Use According to the results, effort expectation positively affects the reasons to use digital banking in Islamic banks. So, the second hypothesis is rejected and not supported by the data. The level of convenience associated with using technology is represented by effort expectation (Venkatesh et al., 2003). Usually, the use of technology will make a person’s life easier, simpler, flexible, and not dependent on others and thereby leading to interest or adoption of technology. However, this study finds that the effort does not encourage the use of digital banking. The results of this study are similar to the work by Susilowati et al. (2021), which finds that effort expectation is not a supporting variable for one’s desire to use technology in various contexts. However, other researches (Ahmad et al., 2021; Akhtar et al., 2019; Cooperman et al., 2011) find that effort expectation affects the intention to use technology. 4.3.3. Social Influence on Intention to Use According to the results, social influence had a favorable effect on the intention to use digital banking. As a result, the third hypothesis in this study is supported. Social influence refers to how far a person pays attention to the importance of other people’s beliefs for consideration in using new technologies (Venkatesh et al., 2003). Furthermore, when using technological services, society tends to listen to the recommendations provided by its social surroundings (Kasri & Sosianti, 2023). Previous research show that technology adoption is influenced by social influences (Al-okaily et al., 2022; Chang et al., 2019). 4.3.4. Facilitating Condition Toward the Intention to Use It is noted that facilitating condition has a positive but minor effect on the intention to adopt digital banking. The facilitating condition refers to how much organizational and technological infrastructure is perceived to exist to enable system utilization (Venkatesh et al., 2012). The findings suggest that digital banking users should pay particular attention to the facilities, resources, and skills required to deploy digital banking properly and effectively. This is in line with the findings of Alamanda et al. (2021), which indicate that the facilitating conditions are not supportive of one’s intention to use technology. This however contradicts other works, which discover that facilitating conditions influence the propensity to utilize technology, (Al-okaily et al., 2022; Chang et al., 2019; Li et al., 2018; Purwanto & Loisa, 2020). 4.3.5. Hedonistic Motivation Toward Intention to Use According to the results, hedonic incentive has no effect on the intention to utilize digital banking. The hypothesis of hedonic motivation is rejected and not supported. The concept of hedonic motivation here is intrinsic because excitement, curiosity, and muscular control can influence a person to adopt a technology or system. This is evidenced in previous studies noting that hedonic motivation affects the intention to use (Ahmad et al., 2021; Alamanda et al., 2021; Farzin et al., 2021). However, this finding is in line with Merhi et al. (2019) who show that hedonic motivation does not influence the intention to use technology. 550 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study 4.3.6. Price Value Toward Intention to Use The hypothesis is accepted in that the price value has a positive impact on the intention to use digital banking. Venkatesh et al. (2012) define the price value as a tug-of-war between the benefits and costs that exist in the use of technology. (Raza et al., 2019). The results of this study are consistent with earlier research (Yoga & Triami, 2021; Zia & Alzahrani, 2022), which reveals that the variable price value is factor that affects a person’s intention to use digital banking. 4.3.7. Habits Toward Intention to Use The hypothesis that habits have a positive effect on the intention to use digital banking of Islamic banks is accepted or supported. This condition makes habit a supporting variable in forming one’s intention to use digital banking in Islamic banks. Habit is defined as how far a person goes to perform a behavior repeatedly due to learning (Venkatesh et al., 2012). A person familiar with trusted technologies and systems will be more likely to adopt new technologies even before using those technologies (Chang et al., 2019). These results are consistent with the research conducted by Alamanda et al. (2021) and Susilowati et al. (2021), which shows that habits affect a person’s intentions to use technology. 4.3.8. Trialability Toward Intention to Use The results show that the millennial generation using digital Islamic banking is not typically based on the trialability factor. So, the hypothesis that trialability has a significant positive effect on the frequency of using digital banking of Islamic banks is rejected or, in other words, not supported. At the same time, Koksal (2016) states that trying is often assumed to affect a person’s willingness to adopt a technology. Studies have shown that users using digital banking are not inclined to embrace new technologies when they completely understand them; these findings also give the idea that users are likely to only test the platform after adopting the relevant technology. In contrast, Farzin et al. (2021) conduct a study on the ability to try and find that it influences the intention to adopt mobile banking technology. Then some studies have shown that the ability to try positively correlates with the technology adoption rate (Chen, 2013). 4.3.9. Spiritual Motivation Toward Intention to Use The spiritual motivation is found to have no effect the intention to use digital banking. Sheldrake (2005) defines spiritual motivation as awareness of the relationship with God for those who believe in it. In this research, spiritual motivation is not shown as a sense of benefit to the society and an enduring reward for the intention of using technology. 4.3.10. Use Intent Toward Usage Behavior. According to this study, the intention to use has a positive effect on Islamic digital banking activity (behaviors). Individual behavior affects the behavior of the actual Journal of Islamic Monetary Economics and Finance, Vol. 9, Number 3, 2023 551 usage of one’s technology in behavioral intentions (Venkatesh et al., 2003). Usage behavior is the intensity of the user in using new technologies. The behavior of using information technology is the intensity or frequency of users’ utilization of information technology (Venkatesh et al., 2012). These findings are in line with Parsamehr et al. (2014), Raza et al. (2019) and Win et al. (2021). They state that behavioral intentions influence the behavior of using technology. 4.3.11. Islamic Lifestyle Toward Intention to Use That Islamic lifestyle has a substantial beneficial impact on the urge to utilize Islamic banks’ digital banking is supported. The Islamic lifestyle is a tendency to consume and utilize products and services carried out in everyday life, standardized with the teachings of the Islamic religion (Azizibabani et al., 2022). The same can be said with the digital banking utilization in Islamic banks, which aligns with Sharia values. Religion plays an essential role in consumer behavior and attitudes, influencing the purpose for which technology is used. 4.3.12. Islamic Lifestyle Moderates Social Influence The Islamic lifestyle as a moderating variable for social influences and intention to use yields no significant results. Islamic lifestyle has a direct and meaningful relationship to social adaptation. That is, the more Islamic a person’s lifestyle is, the better is his social adaptation (Parsamehr et al., 2014). Social influence has major consequences on behavioral intention to use novel systems of information (Chang et al., 2019; Nawaz et al., 2020). However, in reality, Islam and social commitment are sometimes the essential variables in ensuring banking selection, in this case, the use of digital banking technology. 4.3.13. Islamic Lifestyle Moderate Habits The Islamic lifestyle is insignificant as a moderating variable in the relation between habits and the technology use intention. The Islamic lifestyle is one of a person’s daily habits to consume, utilize and use goods and services by the values and principles of the Islamic religion (Ebrahimi & Yusoff, 2017). Religion is a cultural aspect that is firmly on the value of habits and attitudes and the general public, which affects lifestyle and ultimately affects consumer decision-making. Asghari & Safara (2015) find that the Islamic lifestyle has a significant positive relationship with happiness levels. However, in reality, the Islamic lifestyle cannot be used as a moderating variable, as shown in our case. 4.3.14. Islamic Lifestyle Moderates Spiritual Motivation According to the results, the hypothesis that spiritual motivation has a substantial effect on the intention to use digital banking as part of an Islamic lifestyle is denied. The Islamic lifestyle is related to one’s life in all aspects, as seen in the two orientations of advice and prohibition. Implementing Islamic lifestyle values should encourage awareness to carry out activities according to Islamic guidance 552 The Islamic Banking Customers’ Intention to Use Digital Banking Services: An Indonesian Study (Aryadi & Rahmawati, 2019). However, the Islamic lifestyle is insignificant in being a moderator of spiritual motivation in the use of technology. V. CONCLUSION AND RECOMMENDATION The study has implications for practitioners and researchers. The UTAUT2 constructs are tested to have better understanding of the intention and the utilization of technology, namely digital banking of Islamic banks. This study evaluates the new constructs and the role of the Islamic lifestyle as a moderating variable in the use of digital banking. According to the findings, factors such as performance expectation, social influence, price values, Islamic habits, and lifestyles, as well as the reasons to use digital banking, have a significant effect on users’ behavior in Islamic banks. Other variables, such as effort expectation, condition facilities, hedonic motivation, and two new constructs, spiritual motivation, and trialability, do not significantly affect the intention to use. Furthermore, the Islamic lifestyle does not moderate the impacts of habits, social influence, and spiritual motivation on the intention. The findings of this study have practical implications including promoting Islamic bank digital banking services via performance expectation, social influence, price value, habits, and Islamic lifestyle as primary drivers. Respondents or users must be made aware that the digital banking features of Islamic banks are attractive and interesting to use. Islamic banks should focus on people who are used to using mobile devices and then promote the accompanying app features. Digital banking users must be given an understanding that using digital banking for financial transactions does not require extensive effort. In addition, the findings pave way for business collaboration to support growth of Islamic banking. Islamic banks may work with mobile data providers and mobile device providers and launch new promotional campaigns to provide basic services to customers, such as data packages at lower prices, with the aim of attracting more users. The digital banking design and functionality must then represent the positive impression and benefits that clients need. Moreover, the policy can also be carried out by Bank Indonesia by optimizing the role of digitization in banking to support and prepare well to face the new era of green and digital financial economy. Finally, the results of the study contribute to the knowledge regarding the millennial generation’s intention to use digital banking, which is influenced by factors such as performance expectation, price values, social influence, habits, and Islamic lifestyle. Future research can add new constructs. These may include culture and demographics, and educational attainment. In addition, a comparative analysis can also be conducted to compare Islamic and conventional digital banking adoption by the millennial generation. Future research also can explore alternative moderating variables given that we find no significant moderating role of the Islamic lifestyle. 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