Digital readiness of Islamic rural banks in Indonesia: Lesson from the COVID-19 pandemic

Abstract

The goal of this research is to investigate how various variables, including ease of use, usefulness, and social influence, competencies affect a specific phenomenon, and COVID-19 on digital readiness and examine the role of attitude as mediating variables. This study used a quantitative research method that gathers the data through questionnaires to employees at Islamic rural banks in Java Islands, Indonesia. Three hundred and seventy-eight respondents from Java and outside Java islands across Indonesia were collected and the data were analyzed by SEM-PLS. The result shows that perceived ease of use and perceived usefulness drive the attitude of employee at Islamic rural banks which also affect their readiness for digital transformation. Further, COVID-19 and competency also found to have positive effect on digital readiness. The originality of this study is to provide new perspective that COVID-19 drive the emergence of digital transformation in Islamic rural banks. Moreover, by analyzing the attitudes and competencies of employee and management, this study fills the gap to uncover the critical factors that shape the outcome of digital transformation in Islamic rural banks in Indonesia.

Keywords:

• digital readiness
• covid-19 pandemic
• Islamic rural banks
• employee’s competency
• perception

1. Introduction

The velocity of digital transformation in Islamic banks unquestionably accelerated since the COVID-19 pandemic. The substantial alterations are apparent from how people shift from traditional to online services, such as opening new accounts and managing financial transactions through mobile banking. However, compared to Islamic rural banks, digital transformation creates major challenges. There are few numbers of Islamic rural banks that have implemented mobile banking, such as Fajar Mobile initiated by BPR Syariah Fajar Sejahtera Bali and Dinar Mobile initiated by BPR Syariah Dinas Ashri, while the shift in people’s behavior which increasingly relies on technology requires Islamic rural banks to be able to provide digital-based banking products and services that are innovative and varied, cheap, safe, and easily accessible anywhere and at any time. The emergence of fintech and bank digital also create fierce competition for providing financing to the micro or retail segment. It can be seen from the percentage of financing given to SMEs and informal sector where 38.39% of them used online loan and peer to peer lending platform to fulfill their basic needs and business expansion (Irawati, 2023). It is supported by the increased trend of internet users in rural areas from 19.87% in 2019 to 49.30% in 2022, as well as the increased trend of financial inclusion from 68.49% to 82.7% (Financial Service Authority, 2022).

As Islamic Rural Banks provide financing and saving services to Micro, Small and Medium Enterprises (MSMEs), farmers, fisherman, workers, retirees, and other societal groups with medium to low income, Islamic rural banks are recognizing the importance of digitalization in improving their efficiency, customer experience, and overall competitiveness (Nurfadilah et al., 2022). Arjun et al. (2021) added that operational banking activities may be impacted by the existence of machine learning, artificial intelligence, big data, and the internet of things. The high number of tellers and back office would be replaced by applications and many branches would be switched to digital bank. It is necessary for the companies to acquire digital that has capability to manage the business process in an agile and responsive way. Otherwise, the investment in digital technology will not provide a better return in the long run. However, recent technology advancement triggers much discussion into its impact on the employee’s digital readiness. The remaining question is what factors drive the employee’s digital readiness?

From a theoretical perspective, digital readiness refers to the intention and ability to adopt digital technology, in addition to a readiness to utilize this technology, there is also a desire to generate novel innovative opportunities that can aid individuals, organizations, industries, or countries in achieving their objectives more quickly and with better outcomes. According to Westerman et al. (2019), organizations that possess strong digital readiness experience significantly higher levels of revenue and profitability compared to those with a lower level of digital readiness. Digital readiness encompasses two perspectives. The first pertains to the attitude towards digital technology, which is perceived as a distinct object that can be universally recognized (as an independent object). Particularly in light of current problems, banks need to reconsider their client contacts and recast their operations as a fully digital organization (Gomber et al., 2017). However, not all banks have adequate digitalization readiness (Berghaus & Back, 2017). More specifically, they struggle to transition from a traditional bank to a digital bank, where processes are automated, customer interactions are supported by robo-advisors, and banking primarily takes place online, on mobile devices, and in other social media channels. Banks must plan for and be ready for such a transition in order to master it. When a bank is said to be “digitally ready,” it refers to both its employees’ readiness to manage the required transformation in regard to their optimistic attitudes, proficiency, and expertise, and taking into account the organization’s preparedness, including factors such as financial limitations, organizational capabilities, endorsement from leaders, and culture of innovation (Arsawan et al., 2022). Evidence suggests that being digitally prepared affects business success positively, and that businesses, as well as their management and people, must be prepared. For the necessary organizational change to be successfully guided and carried out, a deeper knowledge of the perceptional disparities between managers and employees as well as among management levels is essential.

Second, attitude toward interaction with digital technology. Individuals who perceive digital technology as an integrated object should be prepared to engage with it. The emotional responses that arise due to the presence of digital technology and the possibility of alterations in work processes or activities resulting from engagement with digital technology are significant implications to consider, are important to be included in these two components of digital readiness. Consequently, when digital technology is perceived as an independent object with its outcomes, it is known as attitudinal readiness. On the other hand, when digital technology is perceived as an integrated object with its effects, it is referred to as action readiness (Nasution et al., 2021).

From the empirical perspective, there has been much discussion about digital readiness. Kunaifi and Ubaidillah (2021) stated that BPR Syariah Bakti Sumekar used e-banking, namely BBS Mobile, by developing this service to boost the number of customers. Currently, the number of customers is 278,426. Moreover, this service has already been used in 31 BPRS Bakti Sumekar branches throughout Indonesia, including the ATM owned by BPRS Bakti Sumekar which reached 31 (Husna, 2023). Adhiatma et al. (2023) examined the digital transformation in SMEs in Indonesia by looking into readiness, agile leadership, dynamic capability, and digital ecosystem. The study found that SMEs in Semarang, Indonesia, those three criteria influence the development of digital readiness. Abdi et al. (2022) conducted similar studies for MSMEs in Indonesia and found that intrinsic motivation and information technology knowledge. However, there is a scarcity of research that examines digital readiness within Islamic financial institutions or even rural Islamic banks. Majority of previous studies in this field focused on the relation about digital transformation and banking process which spurred the growth of blockchain, artificial intelligence, and cryptocurrency. This study aims to bridge the gap between theory and practice by expanding the technology acceptance model with two objectives: (1) to examine the relationship between perceived ease of use, perceived usefulness, perceived social influence, and competency towards attitude, and (2) to explore the impact of attitude and COVID-19 on digital readiness.

This study provides three significant contributions. Firstly, it builds upon previous research and used industry 4.0 as the phenomenon of their study (Pirola et al., 2020), while this study used COVID-19 as a new variable to examine its impact on digital readiness. COVID-19 pandemic is somehow unique compared to other crises where it is an unprecedented crisis from health care and socio-economic development (Fung & Liu, 2021). Thus, it may provide different findings that contribute to the field of business and management. Second, many previous studies conducted a study about digital readiness in regards to MSMEs (Abdi et al., 2022; Pirola et al., 2020), while this study aims to address the gap in the existing literature of digital readiness in Islamic rural banks which has not been explored by previous scholars. Islamic rural banks hold a crucial significance for the economic development in Indonesia because they provide financial inclusion among MSMEs and other societal groups that have no access to commercial banks. Third, it provides managerial implications for practitioners in Islamic rural banks that need to have an insight about their employee’s perceptions and competencies toward digital readiness, while previous studies discussed about the digital readiness from user’s perspective (Khanboubi & Boulmakoul, 2019; Ly & Ly, 2022). The need to conduct this study also comes from an issue faced by Islamic rural banks where they need to adapt quickly with digitalization, but they face a barrier from regulators which limit their innovation due to security risks and traditional business models.

This paper is organized into five sections. First, it discusses the background of study together with the objectives. Second, it reviews the literature. Third, it presents the methodology. Next, it discusses the research findings. Finally, it outlines the research results and offers recommendations for managers and theories.

2. Literature review

2.1. Development of Islamic rural banks

To facilitate the advancement of the national economy, banking institutions that are able to provide broad services to the public are needed. The community’s need for Islamic banking institutions is considered quite high. To meet the needs of the community, Nurfadilah et al. (2018) suggests that the national banking system allows for the creation of a sharia bank, such as Islamic rural banks, which can provide simple, easy, and efficient banking services to communities, particularly to small and medium-sized enterprises in both urban and rural areas. As can be seen from Table 1, there is an increased in the number of Islamic rural banks from 167 in 2018 to 171 in April 2023 (Financial Service Authority, 2023). The assets and number of banks increased for 64.9% and 51.5% respectively, while the number of employees increased for 69.4% within the same period. The western area continues to dominate this distribution.

Table 1. Islamic rural banks growth in Indonesia from 2018 to April 2023

Years	Asset	Islamic rural banks in Indonesia
		Number of Banks	Number of Offices	Number of Employees
2018	IDR 12.3 T	167	446	4,565
2019	IDR 13.7 T	164	617	6,620
2020	IDR 14.9 T	163	627	6,750
2021	IDR 17.05 T	164	659	6,964
2022	IDR 20.1 T	167	668	7,491
April 2023	IDR 20.29 T	171	676	7,735

**Data per April 2023 (source: Financial Service Authority, 2023)

2.2. The readiness for digital technology

Companies must shift digitally in order to respond to change in the age of Industry 4.0 and stay competitive. The success of a company’s transformation directly depends on how prepared they are for such a change. Method for determining whether a transport firm is ready for digital transformation. The following tasks were completed as part of the readiness assessment: evaluation of the maturity of management processes, analysis of processes according to the readiness level for automation, and evaluation of the competencies and skills of the company’s staff to use contemporary digital technologies and solutions. Neither industry nor organization is thought to be secured to the effects of new digital technology, making its exploration, integration, and exploitation one of the major challenges for corporations and society today.

The phrase “condition of being both psychologically and behaviorally prepared to take action” (i.e., capable and willing) is used to describe the readiness concept (Jafari-Sadeghi et al., 2021). More practically, measuring or assessing readiness is described as the methodical investigation of an organization’s capacity to manage and implement a transformative process or change. When changes are introduced within a practical setting of an organization, including new processes, procedures, and organizational structures, risks, opportunities, and potential obstacles may materialize. Furthermore, conducting a readiness evaluation provides a chance to identify and address any deficiencies in the current organizational setup before or during the execution of planned modifications (Pirola et al., 2020). In order for the organization to address any potential success hurdles prior to starting the change project, a readiness assessment also aims to detect any current ones.

2.3. Technology Acceptance Model (TAM)

Technology acceptance is the voluntary decision made by an individual adopting new technology. The willingness of users to integrate and use technology successfully is a key component (Granić & Marangunić, 2019). According to Selvi (2023), the successful implementation of electronic banking initiated by BPR Syariah Fajar Sejahtera for Fajar Mobile, BPR Syariah Dinas Ashri for Bali Dinar Mobile, and BPR Syariah Bakti Sumekar for BBS Mobile. The service has already been used in 31 BPRS Bakti Sumekar branches throughout Indonesia, including the ATM owned by BPRS Bakti Sumekar which reached 31 (Husna, 2023). Researchers have created a number of models over the last few decades to comprehend the characteristics of user adoption of technology. These models’ efficacy for numerous information technology-based applications has been repeatedly proven (Salloum et al., 2019). However, the most solid and proven basis for technology adoption to date is represented by Davis’ Technology Acceptance Model (TAM) (Kamal et al., 2020). TAM, which has roots in sociology and psychology, is the model that is most frequently utilized in a variety of research investigations. The main objective of TAM is to anticipate user adoption of new technology and to draw attention to information system design flaws before widespread use (Rafique et al., 2020). TAM is made up of two major components that are applied in a variety of technology contexts: perceived utility and perceived usability (Estriegana et al., 2019).

In this study, perceived ease of use, perceived usefulness, and perceived social influence are important factors that can impact an individual’s attitude and competencies towards digital readiness in Islamic rural banks. In addition, their attitude and competencies can influence their readiness to adapt with digital, although COVID-19 might be one of the triggers. Thus, the theoretical framework for this study can be seen in Figure 1.

Figure 1. Theoretical framework.

Modified from Pham & Vu (2022).

2.4. Perceived ease of use

Perceived ease of use, employed in the UTAUT model (Dwivedi et al., 2019), effort expectancy is an important component of TAM and refers to the perceived level of ease associated with using a new system. The perception of usability has a big impact on adoption (Wu et al., 2020). To put it differently, users are more likely to want to use a system when they perceive it as easy to use. Employee desire to adopt digital systems will also increase if they believe that using these is simple. When a system is made to be easy to use, it may be considered to be of high quality (Malik & Annuar, 2021). This includes making it simple for users to acquire the knowledge and skills required to operate and benefit from the system. It also makes it simple for users to complete a task or job (Bui et al., 2022; Latifah et al., 2021; Nguyen et al., 2020). The ease in this context refers to whether using a digital system or platform makes an employee’s daily tasks and activities in a company easier compared to traditional

With the advancement of the internet, several gadgets such as laptops, tablets, and smartphones have emerged and are extensively utilized by organizations (Dasgupta & Gupta, 2019). To remain competitive, businesses need to adapt to this trend (Gobble, 2018). As habits and work procedures are altered to suit the potential efficiency increases, digitalization is thought to deliver considerable efficiency (Kuusisto, 2017). The typical work patterns and methods, on the other hand, will undoubtedly change as a result of digitization strategies. Workers must adjust to the technology as part of this process, and this will have a variety of effects on them. Some workers may perceive these changes as positives, while others may need more time to grasp and cope with them (Nurfadilah & Samidi, 2021). The objective of this study is to examine the significance of ease of use in the adoption of digital technology by employees of Islamic Rural Bank in Indonesia. Thus, the hypothesis can be formulated as follows:

H1:

Attitude is significantly and positively influenced by the perceived ease of use.

2.5. Perceived usefulness

The most important element in user acceptance of a system is perceived usefulness. The productivity, effectiveness, and overall advantages of the system in terms of enhancing user performance are all factors that influence how useful people consider it to be.

The acceptance of technology by individuals is influenced by two cognitive factors, namely perceived usefulness (PU) and perceived ease-of-use (PEOU)—mediates how people adopt new technologies (Brandon-Jones & Kauppi, 2018). As per Malik and Annuar (2021), perceived usefulness refers to the personal probability of the user that the technology would enhance the performance of the individual or team from an organizational perspective. A person’s assessment of how technology is positioned to enhance their jobs or duties in regards to efficacy and productivity is known as perceived usefulness.

A concept known as “perceived usefulness” demonstrates how changing people’s behavior might be a particular aspect of repeated usage (Kong et al., 2021). Al-Hattami and Gomez Corona (2021) suggests that five separate indicators of magnitude of increased efficiency, advantageous, productivity, speedier trade, and efficacy of an activity should be used to measure or analyze the perceived usefulness variable. The major goal of this research is to ascertain how employee attitudes and performance in the Islamic Rural Bank in Indonesia are impacted by the perceived usefulness of digitalization in order to bridge the digital gap. Thus, the hypothesis can be formulated as follows:

H2:

Attitude is significantly and positively influenced by the Perceived Usefulness.

2.6. Perceived social influence

Most individuals who participate in online social activities are primarily consumers of forum content blog post searchers, or viewers of images or other media (Holt et al., 2022). The impact of social influence can be associated with various aspects of the social network, such as families and organizations, certain behaviors such as obtaining emotional or informational assistance, or our perception of the availability of resources for support (Singh et al., 2020). An exchange of resources between two people that is understood by either the supplier or the intended recipient to improve the wellbeing of the recipient is another way to define social influence. It comes in the forms of inspiration, drive, knowledge, and experience. Other research has examined the impact of cultural and social factors on technology adoption, highlighting the importance of social influences. For example, Hao et al. (2017) found that users’ decisions to adopt technology are shaped by a combination of social factors, including social image and subjective norms. According to perceived social influence, employees at an Islamic rural bank feel that their attitudes and behaviors regarding digital technology may be altered, either consciously or unconsciously, to accommodate social pressures.

Understanding what factors affect people’s decisions to adopt and use information and communication technologies (ICTs) is important as these technologies permeate more and more facets of our life. Social influence may become more crucial in determining whether technologies thrive as more and more technologies, particularly social technologies, are developed (Popkova & Zmiyak, 2019; Upadhyay et al., 2021). Social influence can be seen from the intensity of employees towards digital changes in Islamic rural banks. Intention to use is considered a behavioral construct that is indicative of attitude, behavior, and actual usage being acceptable. This might happen as a result of the fact that the behavior of a person is a reflection of their intention to use a certain technology. The purpose of use in this context is mainly focused on measuring employee interest in viewing and monitoring their performance review results, work-progress reports, and updates on the evolution of daily information made digitally accessible (Purwanto & Loisa, 2020). Examining this as a measure of acceptance of digitalization will reveal the level of eagerness among employees and its importance to them. It is possible that each employee has unique intentions when using applications and websites that demonstrate variations in performance value and rewards earned. As a result, the hypothesis can be formulated as follows:

H3:

Attitude is significantly and positively influenced by the Perceived Social Influence.

2.7. Attitude

Attitude is considered one of the fundamental elements of human psychology, which is a feature of the mind since it reflects a response to interactions with the outside world and the body. The extensive body of study on this topic demonstrates the practical use of this trait in the fields of psychology, sociology, political science, and other related fields Hien and Nhu (2022) have an impact on their actions. Positive attitudes among employees, which have been thoroughly documented in the literature to have an impact on both individual and organizational performance (Mwesigwa et al., 2020), may significantly affect both. Positively, though, if management demonstrates a desire to engage with employees and make changes as needed, that attitude in and of itself can significantly raise morale. Thus, the hypothesis can be formulated as follows:

H4:

Attitude is significantly and positively influenced by the Digital Readiness.

2.8. Competencies

Although research on digitalization and related fields has explored its effects at the employee level, including smart manufacturing (also known as Industry 4.0) and servitization, there is a research gap regarding competency (Kohtamäki et al., 2020; Szalavetz, 2019; Van Melle et al., 2019). There is currently no academic framework that identifies employee competencies in the context of digital transformation, despite inquiries into the overall implications of digitalization on staff competencies. While some general frameworks have been proposed (e.g., Carretero et al., 2017; Myovella et al., 2020; Vuorikari et al., 2020), these frameworks were developed from a societal perspective and do not focus on the business context. Thus, further research is necessary to understand the importance of integrating competencies into digital transformation strategies, with particular attention paid to the competencies required for the transformation process (Kohtamäki et al., 2020). Alam et al. (2023a) mentioned that there is a positive correlation between the absence of technological devices and digital literacy, which had a negative impact on academic achievement as a result of e-learning.

As Sousa and Rocha (2019) noted, digitalization has only recently become a topic of discussion in management literature, despite a significant body of knowledge in IS research (Eller et al., 2020; Legner et al., 2017; Parviainen et al., 2017; Vial, 2019). However, research has yet to establish a connection between digitalization and employees. The term “digital competencies” refers to a broad variety of skills that are essential for carrying out tasks that are part of daily routine and require the use of digital media, such as using technology, analyzing, and assessing data, or networking online. Our study concentrated on two types of competencies, namely digital communication competencies and digital collaboration abilities, and we based our research on a comprehensive digital competencies model recently introduced by Oberländer et al. (2020). As a result, the hypothesis can be formulated as follows:

H5:

Competencies have a significant and positive impact on digital readiness.

2.9. Digital readiness amidst covid-19 pandemic

The outbreak of COVID-19 has created challenges for companies operating in various sectors. Many of these firms have encountered intense pressure to offer goods or services through digital channels as well as to embrace new internal working patterns. Due to the need for remote work and social isolation amidst the COVID-19 pandemic, there has been a considerable increase in the adoption and utilization of digital technology. Due to this, business owners have to improve their digital skills to compete in the worldwide market. Digital platform corporations, according to Gawer (2021), “create value by facilitating connections across numerous sides, subject to cross-side network effects,” in order to leverage and control digital resources that are located beyond the company’s purview. The main benefit of digital platforms is their ability to reduce transaction expenses and make transactions easier, according to Arfi et al. (2021). As a result, it is feasible to rely on customer-driven entrepreneurship on digital platforms that prioritize user-centered innovation, as noted by Park et al. (2021).

Everyone has to adapt to the changes in Covid-19, which makes everyone have to follow existing regulations. With the existence of digital technology, it is mandatory for everyone to learn how to use it for the continuity of work carried out remotely. The COVID-19 pandemic has highlighted the potential risks associated with working in-person, as it increases one’s exposure to and risk of contracting the virus. Telecommuting, on the other hand, has become a viable option for many workers (Sostero et al., 2020). However, those who lack access to technology or digital literacy are disadvantaged and may be limited to in-person jobs that increase their risk of exposure. Additionally, some activities such as doctor appointments cannot be fully replaced by digital alternatives, increasing the risk of transmission. As a result, the hypothesis can be formulated as follows:

H6:

COVID-19 has a positive and significant impact on the readiness for digital transformation.

3. Research methodology

3.1. Population and sampling

The objective of this study is to examine the relationship between perceived ease of use, perceived usefulness, perceived social influence, and competency towards attitude, and to explore the impact of attitude and COVID-19 on digital readiness. In order to answering this question, this study used quantitative research method through survey. The sampling technique used in this study is convenience sampling method through Indonesian Sharia Bank Association. The sample of this study is employees of Islamic rural banks in Java and outside Java Islands for junior staff to senior executive level. By using the ten thumbs rule (Sarstedt et al., 2022), the minimum size of this sample is 280 data.

3.2. Data collection

The researchers gathered primary data using questionnaires that utilized a five-point Likert scale, where the responses ranged from strongly disagree (1) to strongly agree (5). The questionnaire is divided into three parts, such as screening questions “Are you currently working in a BPRS company in Indonesia?”, “Do you have at least 2 years’ work experience?”, “Do you have status as a full-time employee?”, respondents profiles that consist of 14 questions; and 28 main questions that consist of exogenous latent variables (perceived ease of use, perceived usefulness, perceived social influence, covid, competencies, attitude) and endogenous latent variables (digital readiness).

In order to get valid and reliable data, the process of data collection consists of two stages. Firstly, this study conducted the pilot project to 50 respondents through an online survey. Out of 28 questions, we removed 6 indicators. Secondly, the questionnaires were distributed to more respondents through Indonesian Sharia Bank Association, including junior staff to senior executive level with an online survey. Three hundred and ninety data were collected and 12 invalid data were removed. Thus, this study uses 378 data for further analysis, including employees of Islamic rural banks in Java and outside Java Islands.

3.3. Data analysis

Once the data is collected, the data would be analyzed using SEM-PLS. This is a statistical technique that relies on variance to analyze the relationships among variables and determine how they contribute to the overall structure of the model that can be used in both predictive and explanatory research (Sarstedt et al., 2022). This method accommodates a small sample size in addition to its capacity to manage non-normality and formative structures of the data. This method has been previously utilized by researchers studying digital readiness (Yusif et al., 2020);. talent management (Abdullahi et al., 2021; Younas & Waseem Bari, 2020); fintech (Agustiningsih et al., 2021).

According to Mehmetoglu and Venturini (2021), the SEM-PLS analysis is divided into two steps: the initial steps involve the measurement model, followed by the structural model. During the first step, the measurement model is required to evaluate the dependability and credibility of constructs, as well as detect multicollinearity. The factor loadings of the indicators and the average variance extracted (AVE) are linked with convergent validity, while the Fornell-Larcker criterion is connected with discriminant validity. According to Mehmetoglu and Venturini (2021), a reliable indicator should have factor loadings that are generally greater than 0.7, while the average variance extracted (AVE) should be at least 0.5. In addition, the Fornell-Larcker criterion recommends that the AVE of a construct should be larger than the squared correlation between that construct and other constructs in the model.

The second step of the analysis involves evaluating the structural model’s coefficient of determination (R2) and assessing whether there is any multicollinearity present. The coefficient of determination, often known as R2 or r-squared, is a statistical metric within a regression model that describes the variance percentage in the independent variable that used to explain the variation in the dependent variable. To put it another way, the coefficient of determination describes how well the data fits the model, often known as the goodness of fit. There are no specific and rigid criteria for estimating the size of R2, although there are some general guidelines: 0.19, 0.33, and 0.67, respectively, represent small, moderate, and large effects (Mehmetoglu & Venturini, 2021). In the last step, this study uses bootstrapping technique for path analysis.

4. Result and discussion

4.1. Result

4.1.1. Demographic respondents

Majority of respondents are male (53.5%) and the rest are female (46.7%) with most of them had more than 6 months to above working experiences. In relation to educational background, respondents are dominated by undergraduate degree (76,17%) and followed by master degree (16.7%), while the least respondents are high school (2.65%). Most of them earned below Rp5.000.000 per month (60%), followed by respondents with income level between Rp5.000.000 – Rp10.000.000 (16.7%), while the least respondents earned between Rp10.000.001 – Rp15.000.000 (6.7%) and Rp15.000.001 – Rp20.000.000 (6.7%).

4.1.2. Assessment of measurement model

Table 3 and Table 4 present an analysis of construct reliability, convergent validity, and determinant validity in relation to the measurement model shown in Figure 2. In convergent validity, it describes the extent to which a latent variable may account for the variation of indicators (Benitez et al., 2020). Table 2 shows that Factor loadings and AVE are indicators of convergent validity. Perceived ease of use is significantly explained by all measured variables (PEU1-PEU3), with PEU3 having a higher loading factor of 0.890 compared to PEU1. All measured variables (PU1-PU3) significantly explain perceived usefulness, with PU3 having the highest loading factor of 0.882, followed by PU1 with 0.878 and PU2 with 0.833. Additionally, all measured variables (PSI1-PSI3) significantly explain perceived social influence, with PSI3 having the highest loading factor of 0.877 compared to PSI1’s 0.819.

Figure 2. Outer loading.

Table 3. Measurement items

Construct	Code	Indicator	Loading
Perceived ease of use	PEU1	I suppose that it is easy for me to adapt with the digital technology, such as social media, application device, website, and etc	0.779
	PEU2	I believe that it is easy for me to competently use digital technology	0.856
	PEU3	I believe the use of digital technology will ease my work	0.890
Perceived usefulness	PU1	The digital technology helps me improve my performance of work	0.878
	PU2	The digital technology makes me more proactive in working	0.833
	PU3	The digital technology helps me absorb knowledge more effectively	0.882
Perceived social influence	PSI1	I have curiosity when others explain digital technology	0.819
	PSI2	I often follow the recommendations of others on digital technology	0.854
	PSI3	The influences from colleagues makes me want to try digital technology	0.877
Attitude	ATD1	I support the use of a digital technology in company	0.833
	ATD2	I aware that adaptation to digital technology is a must	0.858
	ATD3	I feel very excited when using digital technology	0.795
	ATD4	I always actively interact with the colleagues using digital technology (such as: social media, web, and application)	0.844
Competencies	COM1	I am able to generate new ideas and possibilities from my knowledge in using digital technology	0.896
	COM2	I can communicate and presents content using media such as website, application and etc	0.828
	COM3	I can consciously choose between different digital technologies based on their function	0.892
Covid-19	COV1	Covid-19 has helped me feel excited about the new digital technology method	0.848
	COV2	Covid-19 has helped me more proactive and self-disciplined in working	0.844
	COV3	Covid-19 has helped me adapt to the shift in digital technology method	0.837
Digital readiness	DR1	I have proactively absorbed knowledge through digital technology	0.850
	DR2	I believe with digital technology I can work more effectively and efficiently	0.844
	DR3	I am ready to use digital technology to complete various jobs in the company	0.822

Table 4. Construct validity and reliability

	Cronbach’s Alpha	rho_A	Composite Reliability	Average Variance Extracted (AVE)
ATD	0,853	0,853	0,901	0,694
COM	0,843	0,845	0,905	0,762
COV	0,796	0,797	0,880	0,710
DR	0,811	0,812	0,888	0,726
PEU	0,795	0,800	0,880	0,711
PSI	0,809	0,816	0,887	0,723
PU	0,831	0,832	0,899	0,747

Table 2. Respondent Profile

Demographic Variables		Frequency	Percentage
Gender	Male	201	53.3%
	Female	177	46.7%
Years of working	0–2 years	42	11.1%
	3–5 years	56	14.8%
	6–8 years	98	25. 9%
	9–11 years	70	18.5%
	>11 years	112	29.6%
Educational Background	High School	10	2.65%
	Undergraduate Degree	305	8.6%
	Master Degree	63	16.7%
	Doctoral	0	0
Income level per month	Below Rp 5.000.000	227	60%
	Rp 5..000 - Rp 1.000.000	63	16.7%
	Rp 1.000.001 - Rp 15..000	25	6.7%
	Rp 15..001 - Rp 2.000.000	25	6.7%
	> Rp 2.000.001	38	10%
Digital technology that you have known very well (can choose more than one)	Web development	25	6.7%
	Social media	290	76.7%
	Cloud computing	63	16.7%
	Microsoft office	315	83.3%
	Banking system/application	214	56.7%
	Blockchain	12	3.3%
	Dashboard	75	20%
Digital technology that you want to learn in the future (can choose more than one)	Web development	25	60%
	Social media	290	40%
	Cloud computing	63	36.7%
	Microsoft office	315	30%
	Banking system/application	214	50%
	Blockchain	12	43.3%
	Dashboard	75	26.7%

To explain attitude, all measured variables (ATD1-ATD4) significantly contribute, with ATD2 having the highest loading factor (0.858) compared to ATD3 (0.795). Similarly, for competencies, all measured variables (COM1-COM3) are significantly explained, with COM1 having the highest loading factor (0.896) compared to COM2 (0.828). For Covid-19, all measured variables (COV1-COV3) significantly explain, with COV1 having the highest loading factor (0.848) compared to COV2 (0.844). Finally, for digital readiness, all measured variables (DR1-DR3) are significantly explained, with DR1 having the highest loading factor (0.850) compared to DR2 (0.822).

In construct reliability, the obtained values for Cronbach’s Alpha and composite reliability are deemed satisfactory as they exceed the threshold of 0.7. Moreover, rho A and AVE also shows a good result with the value above 0.5.

4.1.3. Assessment of structural model

As can be seen from Table 5, R-square value for digital readiness is 0,801 which means the two latent variables (ATD, COV) moderately explain 80.1% of the variance in digital readiness. Furthermore, the conceptual model accounts for 83.5% of the variation in attitude. The multicollinearity test also shows that the VIF value is below 10 (Wielgos et al., 2021) and below 5 (Salmerón et al., 2020)as can be seen from Table 6.

Table 5. Coefficient determination

	R Square	R Square Adjusted
Attitude	0,835	0,833
Digital readiness	0,801	0,800

Table 6. VIF

	VIF
PEU1	1,438
PEU2	1,956
PEU3	2,161
PU1	2,326
PU2	1,576
PU3	2,387
PSI1	1,612
PSI2	1,883
PSI3	1,872
COM1	2,415
COM2	1,666
COM3	2,433
ATD1	1,931
ATD2	2,174
ATD3	1,714
ATD4	2,049
COV1	1,753
COV2	1,662
COV3	1,671
DR1	1,829
DR2	2,080
DR3	1,618

4.1.4. Hypothesis testing

All hypotheses are supported by data when the structural model assessments are finished. All the findings could also be seen as supporting the validity and dependability of the theoretical model.

H1:

Attitude is significantly and positively influenced by the Perceived Ease of Use.

Table 7 indicates that perceived ease of use and attitude have a significant positive effect with a p-value of 0.004, which is less than the alpha level of 0.05. Hence, H1 is supported.

Table 7. Hypothesis testing

	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDE V|)	P-Values	Result
PEU -> ATD	0,253	0,254	0,087	2,924	0,004	Accepted
PU -> ATD	0,281	0,272	0,121	2,318	0,021	Accepted
PSI -> ATD	0,161	0,161	0,096	1,674	0,095	Rejected
ATD -> DR	0,598	0,574	0,141	4,237	0,000	Accepted
COMP -> ATD	0,289	0,298	0,082	3,527	0,000	Accepted
COV -> DR	0,324	0,348	0,144	2,253	0,025	Accepted

H2:

Attitude is significantly and positively influenced by the Perceived Usefulness.

The result from Table 7 suggests a significant positive effect of perceived usefulness and attitude, with a p-value of 0.021, which is less than the alpha level of 0.05. Therefore, H2 is supported.

H3:

Attitude is significantly and positively influenced by the Perceived Social Influence.

According to Table 7, perceived social influence and attitude have a positive but insignificant effect, as the p-value of 0.095 is greater than the alpha level of 0.05. Hence, H3 is rejected.

H4:

Attitude is significantly and positively influenced by the Digital Readiness.

The findings from Table 7 indicate that there is a significant and positive relationship between digital readiness and attitude, as evidenced by a p-value less than or equal to the alpha level of 0.05. Thus, H4 is confirmed.

H5:

Competencies have a significant and positive impact on digital readiness.

Table 7 also reveals a significant and positive relationship between competencies and digital readiness, with a p-value less than or equal to the alpha level of 0.05. Therefore, H5 is supported.

H6:

COVID-19 has a positive and significant impact on the readiness for digital transformation.

Based on Table 7, the results demonstrate that there is a significant and positive effect of COVID-19 and digital readiness, with a p-value less than or equal to the alpha level of 0.05. Thus, H6 is supported

5. Discussion

The purpose of this study is to examine the effect of perceived ease of use, perceived usefulness, perceived social influence, competencies, and COVID-19 on digital readiness in Islamic rural banks and examine the role of attitude as mediating variables. This study collected the data through online survey and distributed questionnaire to employees from Junior to senior executive level in Islamic rural banks located in Java and outside Java Islands. Based on the finding, perceived ease of use and perceived usefulness proved to have a significant effect on attitude. Perceived ease of use can significantly impact employee productivity and efficiency. If employees can navigate systems and technology without significant challenges, they can complete their tasks more quickly and accurately. This efficiency can lead to a sense of accomplishment and pride in their work, which, in turn, contributes to a positive attitude. It is in-line with the previous finding from Chen and Aklikokou (2020) when technology is perceived as easy to use, it reduced the time and resources required for training. Employees can quickly adapt to new systems or updates, making the transition smoother.

This can lead to a more positive attitude towards change and adaptability within the organization. It shows that the employees at Islamic rural banks perceive digital technology as beneficial tools/system that improve their work and assist them to be more effective and efficient at workplace (Barba-Sanchez et al., 2022).

The study also shows that the employee believes that digital technology is easy to use. It is also supported by Asbisindo that there are 97 out of 165 Islamic rural banks that have adopted digital technology in 2022. However, their perception toward social influence is found to have no significant on attitude. The investment in digital technology has to measure its impact on the company’s return, not only from the financial aspects, but also non-financial aspects, such as customer’s loyalty, trust, and company’s image.

Moreover, the employee’s competencies and COVID-19 are found to have positive effect on digital transformation. It shows that their skills are needed to help them absorb digital technology faster than others and the COVID-19 is also found to improve digital transformation in many sectors. Alam et al. (2023b) supported this study that competency to adopt digitalization remains a challenge. When the COVID-19 pandemic hit the world, the conventional methods of delivering education became obsolete and numerous countries adopted technology for education purposes. Since then, technology became a primary tool at different educational levels in diverse ways. The result is also in-line with the study conducted by Nurfadilah et al. (2022) that the implementation of advanced digital technologies must be accompanied by the readiness of the employees. Firms that have employees with higher degree of digital readiness are more likely to achieve greater productivity, leading to improved overall firm performance.

6. Conclusion and recommendation

6.1. Conclusion

The goal of this research is to examine the driver of digital readiness for Islamic rural bank’s employee in Indonesia. From the statistical significance tests, perceived ease of use, perceived usefulness, and competency has been shown to have a positive effect on attitude, while perceived social influence has no effect on attitude. Moreover, attitude plays a mediating role toward digital readiness together with COVID-19 as a significant variable. This research offers essential details that contribute to a more comprehensive comprehension of the connection.

6.2. Recommendation

The finding of this research provides contribution to the literature of Islamic financial institutions, particularly Islamic rural banks. It expands the theory of acceptance model by including COVID-19 as external variables and perceived social influence and competency as internal variables. This research can also serve as a valuable resource for professionals in the field to improve their talent management strategy in order to create a better talent that could adopt easily to the digital transformation. It contributes to the better understanding of the employee’s ability at Islamic rural banks to develop their skills and knowledge in adopting technology. This research has some limitations, including the small number of sample size that could not provide generalize result for Islamic rural banks in Indonesia. Future researchers are expected to expand the number of sample size across other provinces in Indonesia. Then, the study only focusses on COVID-19 as the phenomenon. This study may have different results for different situations; therefore, it is essential to expand the research for new normal or another crisis as another phenomenon.

Correction

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Acknowledgments

This research has been funded by a Research Grant awarded by the Keputusan Kuasa Pengguna Anggaran Direktorat Riset, Teknologi, dan Pengabdian Kepada Masyarakat under the reference number No: 1178/LL3/AL.04/2023. This grant is part of the 'Pendanaan Penelitian Program Kompetitif Nasional dan Penugasan,' sponsored by the Ministry of Education, Culture, Research, and Technology in Indonesia. Additionally, I would like to acknowledge the support I received from Sekolah Tinggi Manajemen IPMI.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Kementerian Riset Teknologi Dan Pendidikan Tinggi Republik Indonesia .