Behavioral intentions in embracing cloud-based accounting information systems

In facing the digital era and a more competitive environment, every organization is required to increasingly implement information systems that can facilitate various organizational needs. Cloud Based Accounting Information Systems (CBAIS), as part of information systems (IS), have also gained attention of organizations. This research was conducted to obtain empirical evidence of the interest in using CBAIS in various medium-sized companies in Indonesia measured using Institutional Theory. The data analysis tool used was SEM-PLS. The respondents in this study were accounting and finance departments employees working for logistics companies that still use conventional accounting information systems (non-cloud-based). A total of 89 responses were collected from 5 logistics companies in Indonesia. The research results indicated that mimetic pressure positively influenced the interest in using CBAIS, coercive pressure does not positively influence the interest in using CBAIS, and normative pressure positively influenced the interest in using CBAIS. An interesting aspect of this study is the absence of regulation or even demand in Indonesia that obligates the use of CBAIS. Hence, the use of CBAIS has not become a commonly adopted best practice in logistics companies.


Introduction
At the onset of the fourth industrial revolution, the adoption of Information Technology (IT) has represented a substantial advancement across diverse sectors.The use of IT has led to the creation of new business models conducted digitally.This pattern also applies to the realm of accounting, where IT plays a vital role.An approach that can assist in elevating information precision and enhancing decision-making in organizational operations is the implementation of Accounting Information Systems (AIS).AIS has evolved into a crucial strategic instrument for reaching organizational objectives.Numerous organizations adopt AIS with the aim of achieving efficiency, increasing productivity, and improving overall performance (Haleem, 2021).Furthermore, AIS stands out as a pivotal technology-driven asset for all organizations; leveraging the information it produces, organizations can make well-informed strategic decisions (Tajvidi & Ahmadi, 2021).
In contrast to conventional AIS, a Cloud-Based Accounting Information System (CBAIS) presents a competitive edge by enhancing services tailored to client requirements, demanding lower capital investment, facilitating superior cost control, and offering improved accessibility (Asatiani et al., 2019), and offering the capability to enhance combination within the supply chain (Oliveira et al., 2014).Cloud refers to internet-based data storage that can be accessed from any location with an internet connection.Cloud accounting involves the online processing and accessibility of data through a web browser.
Information is stored on remote servers rather than on-site at the organization's premises.
Unlike traditional accounting systems, cloud accounting is a service that eliminates the need for installing and maintaining software on individual desktop computers.It entails minimal maintenance, automates backups, updates financial data automatically, and offers real-time financial reports (Modi, 2018).CBAIS, classified as a contemporary concept within cloud-based technology, is characterized by the processing of accounting data through a suite of information distribution systems and applications.This occurs within the framework of the cloud information concept, eliminating the need for users to be aware of the physical position and structure of the system (Mihalache, 2011).Furthermore, it is a type of accounting software that runs on cloud infrastructure, such as servers hosted through cloud service providers such as Microsoft Azure, Amazon Web Services (AWS), and Google Cloud (Dimitriu & Matei, 2015), harnesses its capabilities within the cloud-based technology framework, or other cloud providers.This system allows companies to efficiently manage financial data, record transactions, and generate financial reports without operating and maintaining their physical servers.
In Indonesia, the Alibaba Cloud survey conducted in 2023 revealed that 94% of cloud service users aspire to increase their investments in cloud technology while 92% (compared to 84% in Asia) of other businesses plan for a complete cloud migration within two years.Some of these trends are driven by new needs emerging during the pandemic.Despite the high business interest in adopting cloud technology in Indonesia, 71% of businesses still perceive "difficulty in making management recognize the value of adopting new technology" as the most significant challenge.In 2019, research finding by Kaspersky revealed that 19.4% of companies had started adopting cloud services while 32.1% of companies planned to adopt cloud services in the next 12 years.This underscores that cloud services are increasingly becoming the choice for future-oriented companies.In addition, the development of e-commerce, marked by the increase in transactions, compels companies to streamline their supply chains.This is certainly viewed positively by logistics companies, with their enhancement of existing information systems to capitalize on growth opportunities in technology-based marketplaces (Yati, 2021).
Literature has shown that CBAIS represents the latest tool in the field of IT offering various benefits for organizations (Christauskas & Miseviciene, 2012) compared to traditional Information Systems (IS) (Alshirah et al., 2021).Essentially, adopting CBAIS will also impact the accounting configuration.Giving precedence to CBAIS is crucial within efforts aimed at improving business productivity and competitiveness (Al-Okaily et al., 2023).Although much literature generally examines the risks and benefits of CBAIS (Alshirah et al., 2021), to date, only a few studies have focused on the factors playing a crucial role on the intention to use CBAIS.Therefore, this research attempts to provide a description and empirical evidence of the intention to use CBAIS in Indonesia.As suggested by Jackson and Allen (2023) that organizations must recognize the pivotal role of its staff in technology adoption, this research aims to investigate individuals' inclination to adopt CBAIS through Institutional Theory.
The study aims to broaden the comprehension of CBAIS by exploring the categorization of influential factors that contribute to the inclination to adopt CBAIS within Indonesian companies.Institutional theory and CBAIS have a close relationship, primarily because institutional theory can be used to understand and explain the influence of acceptance and implementation of CBAIS.Institutional Theory moderates whether the intention to use CBAIS is influenced by normative pressure (NP), mimetic pressure (MP), and coercive pressure (CP).Berger and Luckmann (1967) initially introduced the Institutional Theory, and it has since found extensive application in examining the dissemination and adoption of technology within organizational contexts (Olivera et al., 2014;Li & Wang, 2018).According to Scott and Christensen (1995), this theory underscores that at its core, the choices and decisions made by organizations are influenced by external environmental factors and the imperative for legitimacy.It posits that within a specific industry, organizational decision-making transcends rational approaches.Organizations seek to bolster legitimacy in their decision-making by aligning with their institutional environment, acting in anticipation, and justifying their decisions (Al-Okaily et al, 2023).This theory delineates three principal dimensions of institutional pressure that compel and shape the extent of technology adoption.These dimensions include coercive pressure, exerted by institutions crucial to organizational dependence, encompassing formal forces like government regulations and informal forces such as industry persuasion; mimetic pressure, arising from the tendency to imitate others in comparable industries, such as leading companies or competitors; and normative pressure, stemming from social forces on the company and its members to conform to specific norms.Earlier empirical studies conducted by Ahmadi et al. (2017), utilizing institutional theory, tested the adoption of IT/Hospital IS M-Commerce, and Asatiani et al. (2019) found that institutional theory influences the acquisition of information systems/technology, especially on technologies like CBAIS.

Mimetic Pressure (MP) and Intention to Use CBAIS
Mimetic pressure is one of the institutional factors that can lead companies to leverage the successful experiences of their competitors (Mitra & Singhal, 2008).Companies might consider emulating the success of their competitors as a strategic choice, imitating the behaviors and actions of these successful rivals through the adoption of comparable practices (Li & Wang, 2018).Upon discovering the advantages that competitors derive from CBAIS, companies experience MP, compelling them to emulate and adopt the practices of these successful rival firms (Olivera et al., 2014).As recognized in existing literature, organizations encounter heightened pressure when observing numerous counterparts within the industry and shared environment successfully employing innovation.Consequently, they sense the need to adapt in order to uphold their competitiveness (Chang et al., 2006).
In accordance with institutional theory, numerous prior studies have indicated that the MP exerted by competitors significantly impacts the adoption of technology within companies.
For instance, Ahmadi et al. (2017) found that MP from competitors significantly and positively influences the intention to adopt technology.In previous research on CBAIS that did not explicitly apply institutional theory, some studies have indicated that the adoption of cloudbased technology is strongly influenced by CP (Chen et al., 2023;Alipour et al., 2021), equivalent to the MP exerted by competitors.Studies on ERP adoption have reported that companies, upon witnessing other entities or competitors within the same supply chain incorporating ERP into their operations, experience pressure to similarly adopt ERP system (Lutfi, 2020).MP exerts the most substantial influence on the decision to embrace innovative IS (Al-ma'aitah, 2017).Thus, this study posits that: MP positively influences the intention to use CBAIS.

Coercive Pressure (CP) and Intention to Use CBAIS
Coercive pressure originates from companies or other authorities that have power over the target company (Olivera et al., 2014).It may emanate from various sources, including, industry associations, government regulators, as well as suppliers or customers.For example, an industry association may have significant influence on a company.Customers may demand new features that could be more cost-effective when executed through CBAIS.Moreover, companies might also be susceptible to the influence of holding companies or shareholders (Li & Wang, 2018).Lutfi et al. (2017) examined the role of policy determinant in the use and adoption of IS among SMEs.A noteworthy determinant identified within the domain of IS was government policies.In accordance with institutional theory and consistent with prior research, government policies emerge as substantial and positively associated external influence on CBAIS (Alsharari et al., 2020).Furthermore, the government establishes regulations and policies that encompass various promotional programs or rules to pursue the institutional adoption of CBAIS (Ahmadi et al., 2017).Thus, this research argues that: CP positively influences the intention to use CBAIS.

Normative Pressure (NP) and Intention to Use CBAIS
Normative pressure refers to the impact exerted by professional standards and the influence of the professional community on a company.This influence stems from adherence to established norms, ethical guidelines, and expectations within a particular professional  1983).NP occurs when a company adheres to the structure and policies of its central company as a model that promotes the homogenization of structures.The majority of previous research has found the importance of NP in the adoption of IT and IS within organizations or institutions (Olivera et al., 2014).It is a crucial factor influencing the adoption of information technology (Ahmadi et al., 2018;Lin et al., 2020).Thus, this research hypothesizes that: NP positively influences the intention to use CBAIS.
From the arguments discussed, the research framework is shown in figure 1.

Methodology
This research is an explanatory study that examined the validity of several hypotheses testing their relationships.The data utilized were primary data collected using a closed questionnaire instrument, distributed directly to the study sample and disseminated online.The population for this study consisted of employees using AIS in logistics companies registered with the Indonesian Logistics Association (https://www.ali.web.id/web2/).The population in this study consists of 23 companies selected through convenience sampling based on location in Bandung -Indonesia.Respondents in this study were from the accounting and finance departments of logistics companies that still use conventional SIA (non-cloud-based).
The measurement of research variables in this study was adopted from Alshirah et al. (2021) as illustrated in table 1. -Customers are increasingly integrating CBAIS into their operations.
-Government influences are encouraging the company to adopt CBAIS..

Mimetic Pressure
-Our competitors hold a positive perception of CBAIS adoption.
-The adoption of CBAIS is widely perceived as highly advantageous for our company.
-Customers and suppliers alike hold a positive view of CBAIS adoption..
The data analysis in this research is carried out through the application of Structural Equation Modeling (SEM) with a focus on Partial Least Squares (PLS).

Results and Discussion
The population for this study comprises employees in the accounting and finance departments of logistics companies still utilizing conventional AIS.Data were collected through questionnaires, and a total of 89 data points were successfully gathered from 5 logistics companies.On average, each company filled out 15-20 questionnaires.
This research incorporated unobserved variables, necessitating the utilization of SEM analysis.This approach evaluated the degree of influence exerted by independent variables on dependent variables and tested the hypotheses put forth in the study.The testing was conducted using the SmartPLS 3 application.

Measurement Model Evaluation
During the measurement model evaluation phase, the outcomes of data processing using the SmartPLS 3 application are outlined.Convergent validity testing, including assessments of indicator reliability and average variance extracted, is performed to ascertain the effectiveness of the measurement instruments in fulfilling their respective functions.Validity refers to the extent to which a measurement accurately represents the intended concept.In SmartPLS, the assessment of validity involves examining loading factors for each indicator, as revealed in the results of convergent validity.Indicators and variables are deemed valid if their correlation values exceed 0.7, indicating a strong relationship with the underlying construct being measured (Hair et al., 2017).Table 2 displays the outcomes of the loading factor testing and convergent validity assessment.

Internal consistency (Cronbach's alpha, composite reliability)
The assessment of reliability involves two key criteria: Cronbach's alpha and composite reliability, extracted from the SmartPLS 3 algorithm results.To meet the recommended reliability standards for the measurement structure, values exceeding 0.7 are desirable, as suggested by Hair et al. (2017).Table 4 shows the results of Cronbach's alpha and composite reliability tests for each research variable.

Discriminant validity
Discriminant validity is used to examine correlation values.There are two tests for discriminant validity, the first one is Fornell-Larcker.Fornell-Larcker, which assesses the correlation between variables.The results of Fornell-Larcker can be seen in table 5.The Fornell-Larcker values are obtained by comparing the magnitude of the relationships between the variables with each other.To ensure valid results, it is crucial that the strength of the relationship between a variable and itself surpasses the relationships between those variable and other variables.The outcomes presented in table 5 reveal that the relationships of the variables with themselves (highlighted in yellow and bold) are indeed greater than the relationships between those variables and other variables.Consequently, it can be inferred that discriminant validity is established.
The second examination for discriminant validity involves cross-loading.This process aims to verify whether the indicators within a construct exhibit higher values on the construct they represent compared to values associated with other constructs.The outcomes of the crossloading analysis are displayed in the table 6.The cross-loading values are determined by comparing the strength of the relationship of each indicator with its respective variable against the strength of the relationship of each indicator with other variables.To ensure valid results, it is essential that the magnitude of the relationship of each indicator with its variable exceeds the magnitude of the relationship of each indicator with other variables.As per the information in table 7, the results indicate that the relationships between indicators and their variables are indeed greater than the relationships between the indicators themselves and other variables.Consequently, it can be concluded that discriminant validity is satisfied.
With the obtained test results, it can be asserted that the measurement model exhibits validity and reliability, meeting the necessary criteria for proceeding with further analysis, specifically the evaluation of the structural model and hypothesis testing.

Analysis of R Square (R 2 )
The R Square (R 2 ) analysis is conducted on each endogenous latent variable, providing insights into the degree to which the endogenous variable is influenced by its contributing exogenous variables.A higher R 2 value signifies a more substantial impact on the endogenous variable, as outlined by Hair et al. (2017).

Analysis
The Q Square value serves as an indicator for evaluating the goodness of the structural model.If Q 2 is greater than 0, it signifies that the model possesses predictive relevance.
Conversely, if Q 2 is less than 0, it suggests a lack of predictive relevance in the model.

Hypothesis Testing
Hypothesis testing is undertaken to scrutinize the influence of independent variables on the dependent variable.In order to assess the significance of path coefficients, a bootstrap method is utilized at a 5% significance level in SmartPLS 3. Table 10 shows the results of the calculations for testing the hypotheses.

Discussion
Based on the results of first hypothesis testing, it is evident that MP has a positive effect on the intention to use CBAIS.MP arises from the tendency or desire to imitate or follow the steps or decisions made by others or other organizations, especially when they are considered successful in the same industry.In the context of the intention to use CBAIS, MP can influence individuals or organizations to adopt the system in several ways.Firstly, when some competitors or large companies in the same industry have switched to cloud-based accounting information systems and successfully gained benefits or efficiency from the change, other competitors or companies are likely to be interested in imitating those steps to remain competitive.Moreover, the emergence of global or industry trends supporting the adoption of cloud technology, in general, can also create MP to adopt CBAIS (Serhan et al., 2020).
Companies or individuals may be interested in following the latest technology trends in an effort to stay relevant and up-to-date with industry developments (Handayani et al., 2021).
Based on the results of the second hypothesis testing, it is clearly indicated that CP does not have a positive effect on the intention to use CBAIS.This research aligned with the findings of Lin et al. (2020) that CP has no significant effect on perceived barriers (e-business) in agricultural firms.CP can be exerted by external parties, such as government regulations, industry norms, or demands from stakeholders, proven to drive individuals or organizations to adopt a particular technology or system (Chua & Goh, 2017).In Indonesian logistic companies, CP has not been proven to influence the use of CBAIS.This is reinforced by the fact that there is no regulation in Indonesia mandating the use of CBAIS.Additionally, the use of CBAIS has not become a widely adopted best practice by similar companies or competitors, causing logistics companies not to feel pressured to follow suit to stay relevant and competitive in the market (Poon & Tong, 2019).If stakeholders expect or desire the use of CBAIS to improve transparency, efficiency, or the reliability of financial reporting, individuals or organizations will feel compelled to adopt the system (Fathony, 2018).
Meanwhile, the third hypothesis testing states that NP has a positive effect on the intention to use CBAIS.This research aligned with the findings of Lin et al. (2020).NP, as a form of social pressure originating from company rules or policies.In this context, these rules or policies relate to the use of CBAIS in accounting and information management activities.
NP acts as a motivator for individuals to comply with the company's policies regarding the use of CBAIS.This may include rules related to financial reporting, data security, or system usage policies.Employees are more likely to follow rules or policies established by the company.In the context of using CBAIS, this means that employees are more likely to adopt or comply with guidelines set by the company regarding the use of the system.

Conclusion
The conducted tests have revealed several noteworthy findings.The outcomes of this study validate all three proposed hypotheses.The research indicates that MP, CP, and NP emerge as significant antecedents to the intention to adopt CBAIS.Among these, CP emerges as the most pertinent and crucial variable influencing the intention to adopt CBAIS, consistent with previous research.The obligatory nature of CP results in increased environmental engagement, significantly impacting the intention to adopt CBAIS.Moreover, in many developing countries, there is a notable dependence on government assistance and incentives to facilitate the adoption of IT/IS.Therefore, it is reasonable to consider that obtaining valuable and beneficial information from the government will facilitate logistics companies in better adopting CBAIS to support essential business needs.
MP is established as a significant factor, which encompasses the behavior of imitating and replicating actions observed in other structurally similar companies, including competitors.
Small and medium enterprises, in an effort to mitigate uncertainty and risk, rely on the experiences of competitors, resulting to increased engagement from the environmental context in fostering the intention to adopt CBAIS.Consequently, logistics companies are more likely to embrace CBAIS when they discern potential benefits and advantages, particularly in the context of heightened competition.
Similar to other environmental factors, NP is also determined to be significant.This discovery aligns with prior research emphasizing the crucial role of NP in the adoption of IT/IS-related applications.NP is exerted by various entities, including suppliers, government agencies, and other organizations that have effectively implemented CBAIS.These entities essentially share norms, values, and information with companies, contributing to increased involvement from the environmental context in fostering the intention to adopt CBAIS.
Through NP, logistics companies are expected to adhere to professional standards and embrace techniques and systems deemed best practices by relevant professional bodies.When NP is high, logistics companies adopt IT/IS not solely based on their evaluation of potential technological efficiency but due to the pressure exerted by the multitude of organizations that have adopted such technology.
the behavior and practices of the company in question(DiMaggio & Powell,

Figure 1
Figure 1Research model

Table 2
Convergent validity test result surpasses 0.5.In this study, all latent variables exhibited AVE values exceeding 0.5, signifying that all latent variable constructs possess strong validity.This suggests that the information encapsulated in each latent variable is effectively captured by its observable or manifest variables.

Table 3
Average variance extracted test result

Table 4
Cronbach's alpha and composite reliability test result demonstrate reliability and exhibit strong reliability as the results of both Cronbach's alpha and composite reliability tests for each variable surpass the threshold of 0.7.ISSN 2719-0617 (Print) 2719-0625 (Online) | 53

Table 7
Cross Loading (Discriminant Validity) test result

Table 8
Analysis of R Square (R 2 ) on endogenous variables