Readiness and Acceptance of Accounting Information Systems for Financial Reporting in Indonesian Village-Owned Enterprises: A TRAM Approach

Abstract

KEYWORDS technology readiness and acceptance model; accounting information systems; bumdes; village -owned enterprises; digital accounting adoption .

Introduction

Digital transformation has increasingly influenced administrative and economic practices in rural Indonesia. Alongside the growing role of village -based development,

Village-Owned Enterprises or Badan Usaha Milik Desa (BUMDES) and Joint Village-Owned

Enterprises or Badan Usaha Milik Desa Bersama (BUMDESMA) have become important institutional mechanisms for strengthening local economic activities and improving community welfare (Izzalqurny et al., 2022 ). Beyond their economic function, these institutions are expected to support better village governance, expand local services, and encourage more sustainable development at the grassroots level. Achieving these objectives requires reliable financial management practices supported by transparent and accountable financial reporting. As village enterprises manage public resources and community-based economic activities, stakeholders increasingly demand financial

Despite the growing adoption of digital accounting applications, there is limited evidence on how technology readiness influences the acceptance of accounting information systems within village -owned enterprises. This study examines the readiness and accep tance of accounting information systems used for financial reporting in Indonesian village-owned enterprises, using the Technology Readiness and Acceptance Model (TRAM). Data were collected through an online survey of personnel from village -owned enterpris es involved in financial reporting and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that perceived usefulness is the strongest determinant of intention to use accounting information systems. Optimism positiv ely influences perceived usefulness, while innovativeness positively affects perceived ease of use.

Interestingly, insecurity also positively affects perceived usefulness, suggesting that concerns about data security, transaction reliability, and information accuracy may increase users’ appreciation of accounting applications. In contrast, perceived ease of use does not significantly influence intention to use. These findings indicate that technology adoption in village -owned enterprises is driven primarily by perceived practical benefits rather than operational simplicity. The study extends the application of TRAM to village-owned enterprises and suggests that technology readiness may operate differently in accountability -oriented rural organizations.

Practically, adoption initiatives should emphasize the benefits of accounting applications for reporting quality, efficiency, and accountability.

Hadi et al. 10.61194/ijtc.v7i4.2394 information to evaluate performance, monitor accountability, and strengthen public trust. Consequently, the adoption of accounting information systems becomes increasingly important because it can improve the quality, consistency, and timeliness of financi al reporting while supporting good governance practices within BUMDES and BUMDESMA (Fitriani, 2024 ; Handayani & Windriyati, 2023 ; Hapsari, 2020).

Despite this strategic role, many BUMDES still face managerial and operational constraints that affect their institutional sustainability. Several studies have reported that some BUMDES become inactive after establishment due to weak governance practices, limited managerial capacity, and inadequate financial administration systems (Handajani et al., 2021 ; Marsono et al., 2023 ). In financial management, one of the most persistent issues is the continued reliance on manual record -keeping, which may lead to inconsistent reporting, weak transparency, and reduced accountability to stakeholders (Rosari et al., 2022).

Human resource capability also remains a central challenge in BUMDES management. Although many village administrators are aware of the importance of accountable financial reporting, not all operators have sufficient accounting knowledge or technological sk ills to prepare standardized financial statements and use digital applications effectively. This problem has also been highlighted in previous studies, which found that limited managerial competence and weak financial reporting capacity can hinder the perf ormance and accountability of

BUMDES (Anowta, 2023; Sofyani et al., 2020).

In response to these challenges, accounting information systems are increasingly viewed as practical tools for improving financial transparency, reporting efficiency, and administrative accountability in BUMDES. Digital applications may help simplify trans action recording, reduce reporting errors, improve data accessibility, and support more timely financial monitoring. This is consistent with studies suggesting that the use of information technology can strengthen efficiency and accountability in public and village- based financial management (Sagala & Siregar, 2023 ;

Syarwani & Ermansyah, 2020).

Digitalization in village institutions also involves changes in work habits, managerial mindset, institutional capacity, and user readiness. Empirical studies have shown that the implementation of digital systems in BUMDES is frequently constrained by limi ted internet infrastructure, insufficient training opportunities, varying levels of accounting competence, and uneven managerial support across villages (Izzalqurny et al., 2022 ; Ra’is & Rini, 2024 ). In many cases,

BUMDES administrators are required to adopt digital financial reporting systems despite having limited experience with accounting procedures and information technology. Such conditions may reduce users’ confidence in operating accounting i nformation systems (AIS), increase perceived complexity, and create concerns regarding system reliability.

These challenges are closely related to the TRAM dimensions of discomfort and insecurity. At the same time, the availability of training, leadership support, and digital capacity development may strengthen optimism and innovativeness toward technology adoption. Consequently, successful digital transformation in BUMDES requires not only the provision of accounting information systems but also continuous efforts to improve human resource capability, digital literacy, and organizational readiness (Sulistiarini et al., 2025).

To obtain a deeper understanding of this phenomenon, the present study adopts the Technology Readiness and

Acceptance Model (TRAM), a framework that combines individuals’ technological readiness with their acceptance of digital applications (Lin et al., 2007). Through this approach, the study examines how optimism, innovativeness, discomfort, and insecurity shape users’ evaluations of system usefulness, perceived ease of use, and their willingness to continue utilizing accounting information systems. The acceptance aspect of the framework is derived from the

Technology Acceptance Mo del, which emphasizes that users’ perceptions regarding usefulness and ease of use play central roles in influencing technology adoption decisions (Davis, 1989; Venkatesh et al., 2003).

This study focuses on the readiness and acceptance of accounting information systems used in financial reporting activities within BUMDES and BUMDESMA. Although the

Technology Readiness and Acceptance Model (TRAM) has been widely applied to explain technol ogy adoption behavior, prior studies have predominantly examined commercial organizations, educational environments, e -commerce platforms, and various digital service applications (Bhati et al., 2023; Kampa, 2023; Lin et al., 2007 ). Consequently, limited evidence exists on how technology readiness influences the acceptance of accounting information systems in village-based enterprises.

From an empirical perspective, previous studies on

BUMDES have largely focused on governance, managerial competence, financial reporting quality, organizational performance, financial reporting quality, and accountability of village-owned enterprises (Handayani & Windriyati, 2023 ;

Hapsari, 2020 ; Indrawanto et al., 2025 ; Putra et al., 2024 ;

Rosari et al., 2022 ). While these studies emphasize the importance of digitalization and sound financial management, relatively few have examined how users’ technology readiness influences their acceptance of accounting information systems.

Existing technology acceptance studies in the BUMDes context, such as Asqolani & Hadi (2024), provide valuable insights but remain limited to a single local setting, namely Jombang

Regency, leaving broader evidence across different BUMDES and BUMDESMA environments relatively scarce.

Furthermore, prior TRAM studies have reported inconsistent findings regarding the effects of technology readiness dimensions on technology acceptance. Several studies found that optimism and innovativeness positively influence users’ perceptions and technology adoption, whereas others reported weaker or insignificant relationships depending on the technological and organizational context (Bhati et al., 2023; Chotijah & Retrialisca, 2020). Similarly, findings related to insecurity remain inconclusive. While both Pambudi &

Dwinata JS (2023) and Bhati et al. (2023) found that insecurity did not significantly influence perceived usefulness, they reported different results regarding perceived ease of use.

Pambudi & Dwinata JS (2023 ) found a significant relationship between insecurity and perceived ease of use, whereas Bhati et al. (2023) reported no significant effect. These inconsistent findings suggest that the role of insecurity in technology acceptance may vary across organizational and technological contexts.

The context of BUMDES and BUMDESMA provides a particularly relevant setting for such an investigation. Village - owned enterprises operate under heterogeneous technological conditions, limited organizational resources, varying accounting capabilities, and ac countability-oriented reporting responsibilities. Consequently, technology readiness dimensions may influence acceptance of accounting information systems differently from the relationships commonly observed in commercial organizations, educational institutions, and other digital service environments. In addition,

BUMDES and BUMDESMA operate within a governance framework that emphasizes financial accountability, transparency, and reporting responsibilities, which may shape technology acceptance differently from contexts commonly examined in prior TRAM studies.

Accordingly, this study contributes to the literature in three ways. First, it extends the application of TRAM to the

Hadi et al. 10.61194/ijtc.v7i4.2394

Figure 1. Technology Readiness and Acceptance Model (TRAM)

Source: Compernolle et al. (2018) context of village-owned enterprises and accounting information system adoption. Second, it provides empirical evidence on the relationships between technology readiness dimensions and accounting information system acceptance among BUMDES and BUMDESMA users across mu ltiple regions in Indonesia. Third, it enriches the understanding of technology adoption in village -owned enterprises, where organizational conditions, digital capabilities, and financial reporting responsibilities differ from those commonly examined in previous TRAM studies.

Based on these theoretical, empirical, and contextual gaps, this study examines how optimism, innovativeness, discomfort, and insecurity influence perceived usefulness, perceived ease of use, and intention to use accounting information systems among BUMDES and BUMDESMA financial administrators. Specifically, this study seeks to determine whether technology readiness dimensions significantly affect users’ perceptions of usefulness, ease of use, and their intention to continue using accounting information systems for financial reporting activities.

Literature Review and Hypothesis Development

The growing use of digital systems in organizational activities has encouraged many institutions to adopt technology-based administrative processes, including financial management and reporting systems. In rural institutions such as BUMDES and BUMDESMA, ac counting information systems are increasingly expected to support more transparent, accountable, and efficient financial administration. Nevertheless, the adoption of digital technology within village organizations remains uneven because users’ technologic al readiness, managerial capability, and institutional support differ substantially across regions (Sagala & Siregar, 2023; Tangi et al., 2021).

To better understand technology adoption behavior in this context, the present study applies the TRAM model, which integrates the Technology Readiness Index (TRI) and the

Technology Acceptance Model (TAM) (Lin et al., 2007 ) (see

Figure 1). TRAM is considered relevant because the model not only focuses on system acceptance but also considers users’ psychological readiness toward technology. This perspective is particularly important in village -based institutions, where digital transformatio n often takes place in environments characterized by uneven digital literacy, limited technical assistance, and varying organizational capacities.

Technology readiness describes an individual’s tendency to embrace and utilize technology in completing work-related activities (Parasuraman & Colby, 2015 ). Within the TRAM framework, readiness toward technology is reflected through four dimensions: optimism, innovativeness, discomfort, and insecurity. Optimism and innovativeness generally represent positive drivers of technology adoption because they encourage users to view digital systems as beneficial and manageable. In contrast, discomfort and insecurity may create hesitation, anxiety, or distrust when interacting with technological applications.

The acceptance component of TRAM is derived from the

Technology Acceptance Model, which explains that users’ willingness to adopt technology is closely related to their perceptions regarding usefulness and ease of use (Davis, 1989). In practical settings, individuals are more likely to continue using digital systems when they perceive clear benefits for their work activities and experience fewer operational difficulties during system interaction (Venkatesh et al., 2003).

Within the BUMDES environment, optimistic users may perceive accounting information systems (AIS) as tools capable of improving administrative efficiency and strengthening financial accountability (Afiana et al., 2022 ). Likewise, individuals with higher innovativeness tend to adapt more easily to technological changes and may experience fewer obstacles when using accounting systems (Bhati et al., 2023).

Conversely, users experiencing discomfort or insecurity may demonstrate lower confidence in operating digital applications, particularly when technological familiarity and technical support remain limited (Jeong & Kim, 2023; Kampa, 2023).

Drawing upon the theoretical framework and prior empirical studies, this research formulates ten hypotheses to examine the relationships among the proposed variables. The hypotheses are developed based on the Technology Readiness and Acceptance Model (TRAM ), which links technology readiness dimensions —optimism, innovativeness, discomfort, and insecurity—to perceived usefulness, perceived ease of use, and intention to use accounting information systems. The theoretical rationale for each proposed relationshi p is discussed in the following sections.

Based on the TRAM framework, optimism and innovativeness are expected to positively influence perceived usefulness and perceived ease of use, whereas discomfort and insecurity are expected to negatively influence both constructs.

Furthermore, perceived usefulness and perceived ease of use are expected to positively influence users’ intention to use accounting information systems. The following hypotheses are therefore proposed.

Optimism, Innovativeness, and Technology Acceptance

Optimism reflects an individual's positive belief that

Hadi et al. 10.61194/ijtc.v7i4.2394

Figure 2.

Research Framework

technology can improve work performance, efficiency, and productivity (Parasuraman & Colby, 2015 ). Users who are more optimistic about technology tend to perceive digital systems as useful tools for supporting their work. In the context of accounting information systems, optimism may encourage users to recognize the benefits of technology in improving financial reporting quality, administrative efficiency, and accountability. Previous studies have reported a positive relationship between optimism and perceived usefulness (Afiana et al., 2024 ; Bhati et al., 2023 ; Lin et al., 2007). Similarly, optimistic users are more likely to perceive technology as easier to learn and operate because they generally approach technological change with confidence and positive expectations (Chotijah & Retrialisca, 2020 ; Kampa, 2023; Pambudi & Dwinata JS, 2023).

Innovativeness refers to an individual's tendency to experiment with and adopt new technologies earlier than others (Parasuraman & Colby, 2015 ). Users with higher innovativeness are generally more willing to explore system features and adapt to technological change. As a result, they may perceive accounting information systems as more useful and easier to use. Prior studies have generally found positive relationships between innovativeness and technology acceptance, although some inconsistent findings have also been reported across different organizational contexts (Asqolani & Hadi, 2024 ; Bhati et al., 2023 ; Chotijah &

Retrialisca, 2020). Based on these arguments, the following hypotheses are proposed: H1. Optimism positively influences perceived usefulness. H2. Innovativeness positively influences perceived usefulness. H3. Optimism positively influences perceived ease of use. H4. Innovativeness positively influences perceived ease of use.

Discomfort, Insecurity, and Technology Acceptance

Discomfort reflects a perceived lack of control over technology and feelings of being overwhelmed when using technological systems (Parasuraman & Colby, 2015 ).

Individuals experiencing discomfort may perceive accounting information systems (accounting applications) as less useful and more difficult to use, as operational complexity can reduce confidence in their use. Previous studies have reported that discomfort may negatively affect perceived usefulness and perceived ea se of use, although the strength of these relationships varies across contexts (Bhati et al., 2023 ; Lin et al., 2007; Pambudi & Dwinata JS, 2023).

Insecurity refers to distrust of technology and concerns regarding system reliability, data security, and potential risks associated with technology use (Parasuraman & Colby, 2015).

Users with higher levels of insecurity may be less confident in their ability to rely on accounting applications and therefore perceive them as less useful and easier to use. However, prior studies have reported mixed findings regarding the influence of insecurity on technology acceptance (Bhati et al., 2023 ;

Pambudi & Dwinata JS, 2023). Based on these arguments, the following hypotheses are proposed: H5. Discomfort negatively influences perceived usefulness. H6. Insecurity negatively influences perceived usefulness. H7. Discomfort negatively influences perceived ease of use. H8. Insecurity negatively influences perceived ease of use.

Perceived Usefulness, Perceived Ease of Use, and Intention to

Use

According to the Technology Acceptance Model (TAM), perceived usefulness and perceived ease of use are the primary determinants of technology acceptance (Davis, 1989).

Perceived usefulness reflects the extent to which users believe that a system enhances their job performance. In contrast, perceived ease of use refers to the degree to which a system is perceived as effortless to operate. Users who perceive accounting a pplications as beneficial and easy to use are generally more likely to continue using them in their daily work activities. Numerous studies have confirmed the positive influence of perceived usefulness and perceived ease of use on behavioral intention to u se technology (Afiana et al., 2022;

Bhati et al., 2023 ; Venkatesh et al., 2003 ). Based on these arguments, the following hypotheses are proposed: H9. Perceived usefulness positively influences intention to use. H10. Perceived ease of use positively influences intention to

Hadi et al. 10.61194/ijtc.v7i4.2394 use.

Research Framework

This study is grounded in the Technology Readiness and

Acceptance Model (TRAM), which combines technology readiness dimensions (optimism, innovativeness, discomfort, and insecurity) with technology acceptance constructs, namely perceived usefulness, percei ved ease of use, and intention to use. Based on the theoretical arguments and hypotheses developed in the previous section, the proposed research framework is presented in Figure 2.

Methods

This research adopted a quantitative approach to analyze the relationships among the variables proposed in the study model. Primary data were collected via an online questionnaire administered to BUMDES and BUMDESMA personnel directly involved in financial recording and reporting. Data collection was conducted between November 2025 and January 2026 using incidental sampling. This approach was considered appropriate because a comprehensive national database of BUMDES personnel involved in financial reporting activities was unavailable, and potential respondents were geographically dispersed across

Indonesia's provinces.

The questionnaire was distributed via WhatsApp through several regional BUMDES and BUMDESMA groups. Eligible respondents were individuals actively engaged in financial recording and reporting processes. Participation in the survey was voluntary. Only indiv iduals directly involved in financial recording and reporting activities within BUMDES or

BUMDESMA were considered eligible to complete the questionnaire. Group administrators and participants were encouraged to share the survey link with other eligible respondents. To improve data quality and minimize duplicate responses, the online survey was configured to allow only one submission per participant. Although incidental sampling enabled access to geographically dispersed respondents, the findings should be interpreted as exploratory rather than nationally representative.

This study adapted the research instrument from previously validated measures of the Technology Readiness and Acceptance Model (TRAM) and technology acceptance.

Specifically, the study adopted the technology -readiness constructs—optimism, innovativeness, i nsecurity, and discomfort—proposed by Parasuraman & Colby (2015 ). In contrast, the technology acceptance constructs were adapted from Parasuraman & Colby (2015 ), Kampa (2023 ),

Aripradono (2021), and Compernolle et al. (2018). The initial questionnaire comprised 39 measurement items representing seven latent constructs: optimism (5 items), innovativeness (6 items), insecurity (6 items), discomfort (6 items), perceived usefulness (6 items), perceived ease of use (6 items), and intention to use (4 items). All items used a five- point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). The study slightly modified the wording of several items to fit the context of accounting information systems used in BUMDES and BUMDESMA. Appendix A provides the complete list of measurement items and their corresponding sources. A total of 125 valid responses were analyzed using Partial

Least Squares Structural Equation Modeling (PLS -SEM) with

SmartPLS 4 software. SEM -PLS was considered appropriate because the study emphasizes prediction and exploratory analysis involving multiple latent variables and relatively complex relationships (Hair et al., 2021 ). The sample size of 125 respondents satisfies the minimum requirements for

PLS-SEM analysis. Following the ten -times rule and the recommendations of Hair et al. (2021 ), the sample was deemed adequate to estimate the proposed model comprising seven constructs and 10 hypothesized relationships.

Prior to evaluating the measurement and structural models, common method bias (CMB) was assessed because all data were collected using a single self -administered questionnaire.

Following the variance inflation factor (VIF) criterion proposed by Kock (2015 ), and consistent with its application in recent

SmartPLS studies (Borjigin et al., 2024 ; Zuhroh et al., 2025 ), collinearity among the latent constructs was examined.

According to Kock (2015), VIF values below 3.3 indicate that common method bias is unlikely to pose a serious threat because excessive collinearity attributable to a common measurement source is absent. The VIF values obtained in this study ranged from 1.619 to 2.050, all below the recommended threshold of 3.3. Therefore, common method bias was not considered a significant concern in this study.

The data analysis consisted of five sequential stages: (1) common method bias assessment, (2) measurement model assessment, (3) structural model assessment, (4) model fit evaluation, and (5) hypothesis testing. Following the common method bias assessment, the measurement model was evaluated using factor loadings, Average Variance Extracted (AVE), Cronbach's Alpha (CA), Composite Reliability (CR), and the Heterotrait–Monotrait Ratio (HTMT). The structural model was assessed using the coefficient of determina tion (R²) and predictive relevance (Q²). Model fit was primarily evaluated using the Standardized Root Mean Square Residual (SRMR), while the Normed Fit Index (NFI) was reported as a complementary fit index. Finally, hypothesis testing was performed using bootstrapping procedures based on path coefficients, t-statistics, and p-values (Hair et al., 2021).

Result and Discussion

Descriptive Statistics of Respondents

Table 1 presents the demographic characteristics of the respondents. Of the 125 respondents, 55.2% were male, and 44.8% were female, indicating a relatively balanced gender distribution with a slight male predominance. Most respondents were Generation Y (60.0%), followed by Generation Z (25.6%) and Generation X (12.0%), while Baby Boomers and Generation

Alpha accounted for only a small proportion of the sample.

Regarding business activities, many BUMDES/BUMDESMA operated multiple business units simultaneously. Acc ordingly, respondents were classified based on their business -sector combinations. The largest group operated exclusively in the service sector (30.4%), followed by service and trade (21.6%), trade (20.8%), and trade and manufacturing (10.4%), indicating that service and trading activities constitute the dominant business portfolios of the surveyed BUMDES/BUMDESMA.

Geographically, the respondents represented 17 provinces across Indonesia. The largest proportions originated from West

Java (28.8%), East Java (19.2%), Central Java (16.8%), South

Sumatra (9.6%), and North Maluku (6.4%), while the remaining 19.2% were distributed across twelve other provinces. This distribution suggests that the study captured perspectives from diverse regional settings, although respondents were primarily concentrated in provinces on Java Island.

Descriptive Statistics of Research Variables

The descriptive statistical results show that all variables measured on a 1–5 Likert scale have mean values ranging from 3.157 to 4.590, indicating that respondents tended to give fairly high to very high ratings for the use of technology, with low to moderate levels of variation in answers (standard deviation 0.744–1.311). The variables of optimism (OPT) and perceived usefulness (PU) had the highest average values, indicating respondents' high confidence in the benefits and role of

Hadi et al. 10.61194/ijtc.v7i4.2394

Table 1. Respondent Characteristics

Characteristic Category Frequen cy

Percenta ge (%)

Gender

Male 69 55.2

Female 56 44.8

Total 125 100.0

Generation

Baby

Boomers 1 0.8

Generation X 15 12.0

Generation Y (Millennials) 75 60.0

Generation Z 32 25.6

Generation

Alpha 2 1.6

Total 125 100.0

Business

Sector

Service 38 30.4

Trade 26 20.8

Manufacturin g 11 8.8

Service and

Trade 27 21.6

Service and

Manufacturin g 3 2.4

Trade and

Manufacturin g 13 10.4

Service,

Trade, and

Manufacturin g 7 5.6

Total 125 100.0

Province

West Java 36 28.8

East Java 24 19.2

Central Java 21 16.8

South

Sumatra 12 9.6

North Maluku 8 6.4

Other provinces (12 provinces) 24 19.2

Total 125 100.0

Table 2. Descriptive Statistics of Research Variables

Name Mean Min Max Std Dev

OPT 4.590 1 5 0.765

INN 4.088 1 5 1.019

INS 3.827 1 5 1.147

DIS 3.157 1 5 1.311

PU 4.585 1 5 0.744

PEU 4.217 1 5 0.974

ITU 4.445 1 5 0.898 technology in improving performance. In contrast, discomfort (DIS) had the lowest average but the highest variation, indicating differences in comfort levels in using technology.

Meanwhile, innovativeness (INN), insecurity (INS), and perceived ease of use (PEU) were in the high category with moderate variation, and intention to use (ITU) indicated a strong intention to use. In general, these findings indicate that respondents hold favorable views of technology and are strongly inclined to adopt and use it. The descriptive statistical results for each variable are presented in Table 2.

Measurement Model and Structural Model, Model Fit

Assessment

Following the assessment of common method bias, the data analysis proceeded in four subsequent stages: (1) measurement model assessment, (2) structural model assessment, (3) model fit evaluation, and (4) hypothesis testing.

The measurement model was first evaluated by examining indicator loadings, Average Variance Extracted (AVE), Composite

Reliability (CR), Cronbach’s Alpha (CA), and discriminant validity using cross-loadings and the Heterotrait–Monotrait ratio (HTMT).

After the measurement model satisfied the recommended criteria, the structural model was assessed using the coefficient of determination (R²) and predictive relevance (Q²). Model fit was subsequently evaluated using the Standardized Root Mean

Square Residual (SRMR) and Normed Fit Index (NFI). Finally, the proposed hypotheses were tested using the bootstrapping procedure to estimate path coefficients, t -statistics, and p - values. The evaluation criteria adopted in this study followed the recommendations of Hair et al. (2021).

Measurement Model Assessment

During the measurement model assessment, three indicators (one from insecurity, one from discomfort, and one from intention to use) were removed because they did not satisfy the recommended validity and reliability criteria. Consequently, the final model c onsisted of 36 indicators that met the recommended thresholds for convergent validity and construct reliability.

The convergent validity assessment, shown in Table 3 , indicates that most indicators achieved loadings above the recommended threshold of 0.70 (Ghozali & Latan, 2016 ; Hair et al., 2021; Sholihin & Ratmono, 2020). Although one indicator of the insecurity construct (INS5) showed a loading of 0.645, it was retained because the construct maintained adequate convergent validity and reliability, with AVE values ranging from 0.599 to 0.936, Cronbach's Alpha ranging from 0.853 to 0.958, and Composite Reliability ranging from 0.880 to 0.966, all exceeding the recommended thresholds (Hair et al., 2021 ).

Furthermore, Hair et al. (2021 ) suggest that indicators with loadings between 0.40 and 0.70 may be retained when their removal does not substantially improve the measurement model and when supported by theoretical considerations. Overall, these results indicate that all constructs posse ss satisfactory convergent validity and internal consistency.

Discriminant validity was subsequently assessed using cross- loadings, the Fornell–Larcker criterion, and HTMT. All indicators exhibited higher loadings on their intended constructs than on other constructs. In addition, the square root of AVE for each construct exceeded its inter -construct correlations, while all

HTMT values remained below 0.90. Therefore, the discriminant validity requirements were fully satisfied. These results suggest that the indicators were capable of representing their respective latent constructs appropriately, as in Table 4, Table 5, Table 6.

Overall, the measurement model satisfied the criteria for convergent validity, discriminant validity, and construct reliability, indicating that it was appropriate for subsequent structural model analysis.

Structural Model Assessment

The structural model assessment indicates that the proposed model possesses moderate explanatory and predictive capability. As shown in Table 7, the R² values were 0.529 for perceived usefulness (PU), 0.584 for perceived ease of use (PEU), and 0.658 for intention to use (ITU). These results indicate that the exogenous variables explain 52.9% of the variance in PU, 58.4% in PEU, and 65.8% in ITU, suggesting moderate explanatory power.

The Q² values for PU (0.413), PEU (0.435), and ITU (0.532) were all substantially above zero, indicating that the model was adequately predictive. In particular, the highest Q² value was observed for ITU, suggesting that the model has strong predictive capability in explaining users’ intention to use accounting information systems. Overall, these findings support the

Hadi et al. 10.61194/ijtc.v7i4.2394 adequacy of the structural model for hypothesis testing.

Table 3. Outer Loading, AVE, CA, and CR Values

Constructs Items Loading AVE CA CR

OPT

OPT1 0.911 0.818 0.944 0.957

OPT2 0.873

OPT3 0.949

OPT4 0.901

OPT5 0.886

INN

INN1 0.796 0.660 0.897 0.921

INN2 0.752

INN3 0.837

INN4 0.822

INN5 0.826

INN6 0.839

INS

INS1 0.702 0.599 0.853 0.880

INS2 0.706

INS3 0.884

INS4 0.898

INS5 0.645

DIS

DIS1 0.738 0.636 0.859 0.897

DIS2 0.800

DIS3 0.808

DIS4 0.781

DIS5 0.857

PU

PU1 0.889 0.828 0.958 0.966

PU2 0.904

PU3 0.950

PU4 0.942

PU5 0.866

PU6 0.905

PEU

PEU1 0.788 0.783 0.944 0.956

PEU2 0.887

PEU3 0.895

PEU4 0.926

PEU5 0.884

PEU6 0.921

ITU

ITU1 0.943 0.936 0.896 0.830 ITU2 0.936

ITU3 0.852

Model Fit Assessment

Model fit evaluation produced mixed results. The SRMR value of 0.096 was below the recommended threshold of 0.10, indicating acceptable approximate model fit (Hair et al., 2021).

However, the NFI value of 0.666 did not reach the conventional benchmark of 0.90 (Hu & Bentler, 1999) and is therefore acknowledged as a limitation of the overall model fit assessment. Nevertheless, this result should be interpreted within the context of PLS -SEM, which primarily emphasizes prediction and explanation rather than exact model fit.

Accordingly, the model remains appropriate for hypothesis testing because it demonstrates satisfactory explanatory power (R²), predictive relevance (Q²), and statistically significant structural relationships (Hair et al., 2021).

Hypothesis Testing and Discussion

The hypothesis testing results reveal several important findings regarding technology readiness and technology acceptance within BUMDES and BUMDESMA financial management contexts. Hypothesis testing was conducted using bootstrapping with 5,000 subsamples and a significance level of 0.05. The results of the structural model analysis are presented in Table 8.

First, optimism was found to positively and significantly influence perceived usefulness (H1). This result indicates that users with stronger confidence in technology are more likely to recognize the practical value of accounting applications in supporting fina ncial reporting activities. This finding is consistent with the optimism profile of the respondents. The optimism indicators show that respondents generally believe that technology can improve work efficiency (OPT3; mean = 4.648), enhance work quality (OPT1; mean = 4.640), support financial recording and reporting activities (OPT4; mean = 4.640), increase productivity (OPT5; mean = 4.552), and provide greater flexibility in completing tasks (OPT2; mean = 4.472).

These perceptions suggest that BUMDES an d BUMDESMA personnel recognize the practical benefits of accounting applications in facilitating transaction recording, report preparation, and accountability monitoring, which in turn strengthens perceived usefulness. Within the BUMDES environment, optimistic users may perceive digital systems as tools capable of improving efficiency, simplifying administrative processes, and strengthening accountability practices. A similar tendency has also been identified in previous studies emphasizing the role of posi tive technological attitudes in shaping users’ perceptions regarding system usefulness (Afiana et al., 2022; Bhati et al., 2023; Handoko et al., 2024). However, optimism did not significantly influence perceived ease of use (H3). One possible interpretation is that positive attitudes toward technology do not automatically reduce operational complexity or technical difficulties experienced during system interaction.

Although users may recognize the importance of accounting applications, they may still encounter challenges related to system navigation, feature utilization, or technical adaptation.

This pattern is relatively consistent with findings reporte d by (Noviaristanti & Nugroho, 2024).

Hadi et al. 10.61194/ijtc.v7i4.2394

Table 4. Cross Loading Values

OPT INN INS DIS PU PEU ITU

OPT

OPT1 0.911 0.550 0.382 0.128 0.613 0.455 0.518

OPT2 0.873 0.590 0.475 0.199 0.560 0.465 0.489

OPT3 0.949 0.630 0.370 0.108 0.679 0.523 0.550

OPT4 0.901 0.582 0.326 0.133 0.655 0.498 0.571

OPT5 0.886 0.669 0.414 0.130 0.609 0.543 0.591

INN

INN1 0.623 0.796 0.317 0.122 0.528 0.672 0.494

INN2 0.316 0.752 0.028 0.043 0.237 0.536 0.158

INN3 0.521 0.837 0.258 0.052 0.386 0.617 0.380

INN4 0.685 0.822 0.343 0.062 0.540 0.588 0.481

INN5 0.567 0.826 0.214 0.054 0.441 0.573 0.382

INN6 0.489 0.839 0.187 -0.075 0.461 0.699 0.421

INS

INS1 0.239 0.165 0.702 0.643 0.224 0.117 0.118

INS2 0.235 0.089 0.706 0.622 0.186 0.035 0.151

INS3 0.399 0.315 0.884 0.369 0.462 0.232 0.411

INS4 0.450 0.300 0.898 0.433 0.510 0.252 0.405

INS5 0.212 0.073 0.645 0.642 0.216 0.045 0.228

DIS

DIS1 0.124 0.109 0.413 0.738 0.094 0.125 0.046

DIS2 0.144 0.002 0.487 0.800 0.100 -0.019 0.049

DIS3 0.128 0.084 0.581 0.808 0.152 0.047 0.118

DIS4 0.126 0.001 0.446 0.781 0.175 -0.071 0.135

DIS5 0.088 0.022 0.457 0.857 0.126 -0.006 0.072

PU

PU1 0.625 0.500 0.433 0.125 0.889 0.557 0.824

PU2 0.600 0.445 0.438 0.212 0.904 0.560 0.733

PU3 0.640 0.513 0.396 0.124 0.950 0.605 0.742

PU4 0.663 0.563 0.469 0.137 0.942 0.626 0.738

PU5 0.601 0.540 0.394 0.131 0.866 0.637 0.596

PU6 0.639 0.416 0.439 0.202 0.905 0.521 0.761

PEU

PEU1 0.606 0.679 0.362 0.095 0.762 0.788 0.684

PEU2 0.437 0.621 0.131 -0.024 0.529 0.887 0.474

PEU3 0.439 0.641 0.139 -0.024 0.501 0.895 0.483

PEU4 0.464 0.683 0.190 -0.014 0.529 0.926 0.436

PEU5 0.487 0.714 0.148 0.008 0.489 0.884 0.417

PEU6 0.451 0.680 0.150 -0.008 0.539 0.921 0.454

ITU

ITU1 0.561 0.424 0.383 0.103 0.754 0.506 0.943

ITU2 0.533 0.413 0.303 0.048 0.716 0.488 0.936

ITU3 0.550 0.500 0.372 0.160 0.737 0.545 0.852

Table 5. HTMT Matrix

DIS INN INS ITU OPT PEU PU

DIS

INN 0.119

INS 0.791 0.276

ITU 0.122 0.529 0.377

OPT 0.171 0.713 0.434 0.653

PEU 0.099 0.817 0.188 0.604 0.575

PU 0.178 0.574 0.445 0.868 0.724 0.666

Table 6. Fornell–Larcker Matrix

DIS INN INS ITU OPT PEU PU

DIS 0.798

INN 0.052 0.812

INS 0.603 0.288 0.774

ITU 0.115 0.490 0.389 0.911

OPT 0.152 0.669 0.433 0.603 0.904

PEU 0.010 0.761 0.218 0.564 0.551 0.885

PU 0.170 0.545 0.471 0.809 0.691 0.641 0.910

Table 7. R², R² adjusted and Q² values R² R2 adjusted Q²

PU 0.529 0.513 0.413

PEU 0.584 0.571 0.435

ITU 0.658 0.652 0.532

Second, innovativeness was found to have a significant effect on perceived ease of use (H4). This result suggests that users who are more receptive to new technologies tend to adapt more easily when interacting with accounting applications. Their willingness to explore system features and experiment with unfamiliar functions may reduce perceived complexity and facilitate system use. This finding is consistent with previous studies indicating that innovative individuals generally experience fewer difficulties when adopting new technologies

Hadi et al. 10.61194/ijtc.v7i4.2394

Table 8. Summary of Hypothesis Test Results

Hypothesis Relationship Between Variables Coefficient T-statistic P-value Decision H1 Optimism → Perceived Usefulness 0.494 2.737 0.006 Accepted H2 Innovativeness → Perceived Usefulness 0.144 1.660 0.097 Rejected H3 Optimism → Perceived Ease of Use 0.082 0.593 0.553 Rejected H4 Innovativeness → Perceived Ease of Use 0.707 6.823 0.000 Accepted H5 Discomfort → Perceived Usefulness -0.067 0.885 0.376 Rejected H6 Insecurity → Perceived Usefulness 0.257 1.996 0.046 Rejected H7 Discomfort → Perceived Ease of Use -0.043 0.452 0.652 Rejected H8 Insecurity → Perceived Ease of Use 0.005 0.055 0.956 Rejected H9 Perceived Usefulness → Intention to Use 0.759 8.714 0.000 Accepted H10 Perceived Ease of Use → Intention to Use 0.078 0.950 0.342 Rejected (Bhati et al., 2023 ; Chotijah & Retrialisca, 2020 ; Nugroho, 2022).

However, innovativeness did not significantly influence perceived usefulness (H2). This finding contrasts with previous studies that reported a positive relationship between innovativeness and perceived usefulness, suggesting that individuals with stronger innovative tendencies are more likely to recognize the benefits of new technologies (Afiana et al., 2024; Bhati et al., 2023). A possible explanation is that, within the

BUMDES/BUMDESMA context, users may be willing to experiment with accounting applications and learn their functionalities. However, their assessment of usefulness depends more on the system’s ability to support financial reporting, accountability requiremen ts, and routine administrative tasks than on their personal inclination toward innovation. Nevertheless, this result is consistent with the findings of Chotijah & Retrialisca (2020 ) and Kampa (2023), who likewise found no significant relationship between innovativeness and perceived usefulness.

The results also show that discomfort did not significantly affect perceived usefulness (H5) or perceived ease of use (H7).

This finding suggests that although some users may experience operational difficulties or uncertainty when using accounting applications, such discomfort does not necessarily reduce their perception regarding the importance or utility of the system.

One possible explanation is that users continue utilizing digital systems because financial reporting requirements increasingly demand tec hnological adaptation regardless of individual comfort levels. This outcome aligns with studies demonstrating that even discomforting technological interfaces might still be perceived as useful if their functionalities offer significant utility (Kampa, 2023).

Similarly, insecurity was not found to significantly influence perceived ease of use (H8). This result is consistent with Bhati et al. (2023), who also found that insecurity did not significantly influence perceived ease of use. However, it differs from the findings of Pambudi & Dwinata JS (2023 ), who reported a significant relationship between the two constructs. A possible explanation lies in the distinction between system security and system usability. The insecurity indicators in this study primarily capture concerns related to data security, information misuse, transaction safety, and system reliability. In contrast, perceived ease of use reflects users’ ability to learn, understand, and operate the accounting application. Therefore, concerns regarding security and reliability do not necessari ly reduce users’ perceptions that the application is easy to learn, understand, and use for routine financial reporting activities.

Contrary to the proposed hypothesis, insecurity showed a significant positive relationship with perceived usefulness; therefore, H6 was not supported. Although this finding differs from the original TRAM proposition, it may reflect the accountability-oriented nature of financial reporting activities within BUMDES/BUMDESMA. The insecurity indicators in this study primarily capture concerns regarding data security, transaction reliability, information accuracy, and the need to verify system outputs. Rather than discouraging technology use, such concerns may increase users’ awareness of the importance of reliable accounting applications. Users who are more cautious about potential risks may place greater value on systems that help improve reporting quality, enhance transaction traceability, support accountability, and facilitate compliance with financial reporting requirements. Consequently, insecurity may not merely represent technological anxiety but may also reflect a heightened awareness of financial account ability and risk management responsibilities. In the context of BUMDES/BUMDESMA, concerns about technological risks may prompt users to pay closer attention to the practical benefits of accounting applications, particularly when these systems support mandatory reporting and accountability processes. This unexpected finding is broadly consistent with Nugroho (2022) and Wardayanti et al. (2022). However, it contrasts with the theoretical expectation of the TRAM framework and previous findings reported Asqolani &

Hadi (2024) and Bhati et al. (2023). Future studies may employ qualitative methods to explore further the mechanisms underlying this relationship and determine whether insecurity reflects technological anxiety, accountability awareness, or other institutional factors that influence technology acceptance.

The strongest relationship identified in this study was between perceived usefulness and intention to use (H9). This finding indicates that perceived usefulness plays a central role in encouraging the continued use of accounting applications among BUMDES/BUMDESMA users. This result is in line with

Alfarizi (2022) and Kampa (2023) but differs from Afiana et al. (2024), who found that perceived usefulness did not significantly influence intention to use. A possible explanation is that accounting applications in BUMDES/BUMDESMA are closely associated with financial reporting responsibilities and accountability requirements. Consequently, users may place greater emphasis on the practical benefits of the system, particularly its ability to support reporting efficiency, accuracy, and compliance with administrative obligations.

By contrast, perceived ease of use did not significantly influence intention to use (H10). This suggests that ease of operation may not be the primary consideration for BUMDES administrators when deciding whether to continue using accounting systems. Users may still be willing to use systems perceived as relatively complex as long as those systems provide meaningful practical advantages and support institutional accountability demands. This finding supports earlier studies suggesting that perceived usefulne ss tends to play a more dominant role in shaping users’ intention to adopt technology, even in situations where perceived ease of use does not significantly influence behavioral intention (Amara et al., 2024).

However, findings from other technological contexts have demonstrated different patterns. Studies on telemedicine and digital service platforms, for example, reported that perceived ease of use significantly affects users’ intention because intuitive system interfaces and operational simplicity become critical factors in encouraging continued technology adoption (Ricardianto et al., 2023).

From a practical perspective, the findings suggest that

Hadi et al. 10.61194/ijtc.v7i4.2394 improving system usability remains important, particularly for supporting day-to-day financial administration. However, efforts to increase adoption should not rely solely on simplifying system features or interfaces. Since perceived usefulness emerged as the strongest predictor of intention to use, training and implementation programs should emphasize how accounting applications improve reporting accuracy, support accountability, and reduce administrative workload. In addition, simplified reporting templates, technical guidance, helpdesk support, and leadership commitment may help users recognize the practical value of the system while minimizing operational barriers.

Overall, the findings indicate that technology adoption within BUMDES environments is influenced more strongly by perceived practical benefits than by operational simplicity alone. Psychological readiness factors such as optimism and innovativeness also play important roles, particularly in shaping users’ perceptions regarding system usefulness and ease of use. These results highlight the importance of strengthening not only technological infrastructure but also users’ adaptive capacity and institutional re adiness to support sustainable digital transformation in village financial governance.

For BUMDES and BUMDESMA managers, as well as local and central government agencies involved in village governance and development, implementation initiatives should focus not only on improving users’ technical skills but also on demonstrating the practical benefits of accounting applications for reporting quality, accountability, efficiency, and regulatory compliance. Continuous technical assistance, helpdesk support, and capacity-building programs may further strengthen users’ confidence and encourage the sustainable adoption of accounting information systems in village -owned enterprises.

Conclusion

This study examined the readiness and acceptance of accounting information systems used in financial reporting activities within BUMDES and BUMDESMA by applying the

Technology Readiness and Acceptance Model (TRAM). The findings indicate that technology acceptance is driven primarily by perceived usefulness rather than perceived ease of use.

Perceived usefulness emerged as the strongest determinant of intention to use, indicating that users are more likely to adopt accounting applications when they recognize clear benefits for reporting efficiency, administrative effectiveness, and financial accountability. Furthermore, optimism positively influenced perceived usefulness, while innovativeness significantly influenced perceived ease of use. These findings highlight the importance of technology readiness in supporting the acceptance of accounting information systems within BUMDES and BUMDESMA.

Interestingly, insecurity was found to influence perceived usefulness positively. Although this result differs from the original TRAM proposition, it may reflect the accountability - oriented nature of financial reporting activities within BUMDES and BUMDESMA. Users who are more concerned about data security, transaction reliability, and reporting accuracy may place greater value on accounting applications that support accountability and compliance requirements. In contrast, perceived ease of use did not significantly influence intention to use, suggesting that practical benefits are considered more important than operational simplicity in this context.

This study contributes to the application of the Technology

Readiness and Acceptance Model (TRAM) in village -owned enterprise settings. Unlike previous TRAM studies conducted primarily in commercial and educational contexts, this study demonstrates that technology readiness may operate differently in accountability -oriented village -owned enterprises. In particular, the positive effect of insecurity on perceived usefulness suggests that concerns regarding reliability, accountability, and reporting responsibilities may increase users' appreciation of accounting information systems. From a practical perspective, BUMDES/BUMDESMA managers and local governments should prioritize initiatives that emphasize the tangible benefits of accounting applications for reporting quality, accountability, and administrative efficiency. Training programs should focus not only on system operation but also on demonstrating how the applications support daily financial management tasks. In addition, simplified reporting templates, technical assistance, helpdesk support, and clear guidance on data security may help strengthen user confidence and encourage sustained system utilization.

Several limitations should be acknowledged when interpreting these findings. The use of incidental sampling and the uneven distribution of respondents across regions may limit the generalizability of the results. In particular, respondents were concentrated in several provinces, especially on Java Island, which may not fully capture variations in digital readiness and technology adoption among BUMDES and BUMDESMA in other regions. Therefore, the findings should be interpreted as exploratory rather than nationally representative.

Future studies are encouraged to employ probability-based, stratified, or province -based sampling approaches to improve representativeness and enable stronger comparisons across regions and types of BUMDES/BUMDESMA. Further research may also incorporate organizational factors such as leadership support, training quality, digital infrastructure, organizational culture, and regulatory support. Given the unexpected positive effect of insecurity on perceived usefulness, future qualitative studies are needed to explore whether insecurity reflects technological anxiety, accountability awareness, risk management considerations, or other institutional factors that influence technology adoption in village-owned enterprises.

Author contributions

Miftahul Hadi conceived the study, developed the theoretical framework, designed the research and analysis, supervised data collection, managed the overall study administration, interpreted the results, and led the writing of the initial manuscript and subsequent revisions. Rokhmat

Taufiq Hidayat contributed to the research design, data collection, analysis tools, data processing and analysis, interpretation of the results, and research administration.

Bagas Johantri contributed to the research design, data collection, analysis tools, data processing and analysis, methodology, and research administration. Joko Sustiyo contributed to the research design, data collection, the development of analysis tools, methodology, and research administration. Siti Khomsatun contr ibuted to the research design, data collection, interpretation of the results, and research administration.

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