Drivers of Blockchain Adoption in Accounting and Auditing Services: Leveraging Theory of Planned Behavior with Identity and Moral Norms

Abstract

Blockchain technology has become a game changer in sectors like accounting and auditing. Its usage is still restricted due to a lack of insight into what drives people to adopt it for financial services like accounting and auditing. This research delves into the factors that influence the adoption of blockchain systems in accounting and auditing services by utilizing an enhanced edition of the Theory of Planned Behavior. In this study, alongside the previously established elements like Attitude, subjective norm, and Perceived Behavioral Control, self-perception and personal moral values are included to reflect how identity and ethics impact decision-making processes. Data were gathered via an online survey (N = 751) conducted on the Prolific platform, and the hypotheses were tested using Structural Equation Modeling. The hypotheses were examined through the Structural Equation Modeling method. The findings indicate that each of the five predictors plays a significant role in influencing Behavioral Intention, with personal moral values being the influential factor followed by subjective norm and Perceived Behavioral Control. Attitude plays an important role in shaping adoption choices and showcases the complexity involved in such decisions. As such, it is crucial to take into account ethical factors when encouraging the use of blockchain technology. This study adds to the existing knowledge of the Theory of Planned Behavior framework, offering insights for companies aiming to boost the implementation of blockchain systems in professional settings. Future research avenues and real-world implications are explored with an emphasis placed on developing targeted strategies that align technological adoption with personal values and organizational objectives.

1. Introduction

Blockchain technology has become a game changer in industries by providing benefits like transparency and decentralization that can boost trust among stakeholders in accounting and auditing fields while also curbing fraud and streamlining reporting and auditing procedures according to Kend and Nguyen (2020). They suggest that using a blockchain for audits may enhance the reliability of information systems and ultimately improve audit standards. However, although there are clear benefits, the integration of technology into accounting and auditing services is somewhat restricted.

Many reasons play a significant role in this delayed acceptance of technology in audits by accounting professionals, as mentioned by Anis (2023). A significant hurdle is the lack of awareness among accountants about how to incorporate blockchain into their audit procedures. Furthermore, security concerns related to cyberattacks resulting from technology implementation add complexity to the decision-making process, especially for practitioners exploring blockchain usage. Obstacles within institutions such as start-up costs and insufficient training discourage the uptake of technology by small- and medium-sized businesses (J. Kumar et al., 2024). Additionally, cultural resistance within companies and the intricate nature of grasping blockchain features present hurdles (Clohessy & Acton, 2019).

Despite facing challenges along the way, blockchain technology has found its way into a variety of sectors from governments to businesses, proving itself to be an innovation acknowledged by many. Beyond Bitcoin and Litecoin, blockchain has evolved to tackle real-world problems that once seemed insurmountable.

Previous researchers have shown a range of uses for technology, pointing out how blockchain can improve security in network identity verification and protect the sharing of data effectively (Buhmann et al., 2024). (M. Cheng & Chong, 2022), on the other hand, demonstrated that blockchain can help detect instances of vehicle insurance fraud and reduce losses for insurance firms. Jayasuriya and Sims (2022), in their research study, distinguished between how the industry and academia perceive the integration of technology into accounting systems. Their work advocates for progress that involves expanding TPB concepts to gain a deeper insight into Behavioral Intentions in professional settings. In a related study by Priom et al. (2024), a bibliometric analysis was conducted to outline research trends and provide directions for utilizing the blockchain in accounting and auditing practices. The research points out that, although we recognize the advantages of technology overall, in a sense, there is a gap in the existing literature when it comes to detailed studies that consider identity and ethical aspects in models for adopting this technology. This underscores the need to expand the TPB to include elements that specifically influence behavior in the context of adopting blockchain technology.

While previous studies using TPB have helped in grasping technology adoption, in a sense, only a few have delved into the complexities of professional settings, especially focusing on factors like self-perception and ethical dilemmas (

Table 1. Relevant research.

References	Research Focus	Impact
Perera and Abeygunasekera (2022)	The researchers performed a qualitative study on blockchain adoption in Sri Lanka’s accounting and auditing sectors, highlighting the need for studies that incorporate Self-Identity and moral norms to capture nuanced professional decision-making.	This points to a gap in applying TPB to these specialized fields.
Jayasuriya and Sims (2022)	The researchers contrasted industry and academic views on blockchain integration into accounting systems, proposing frameworks to consolidate fragmented research.	They emphasized the need for extended TPB constructs to better understand Behavioral Intentions in professional contexts.
Priom et al. (2024)	Bibliometric analysis, revealing that while blockchain’s benefits are recognized, comprehensive studies incorporating identity and ethical factors into adoption models are lacking.	This supports extending TPB to address unique behavioral influences in these domains.
Jackson et al. (2003)	The researchers demonstrated that including Self-Identity and moral norms enhances TPB’s predictive power in physical activity studies.	Their methodological approach suggests that similar extensions could provide deeper insights into blockchain adoption in accounting and auditing.

). However, there has been limited research that delves into the realm of accounting and auditing services, in particular. As such, the existing body of the present research concerning the adoption of technology relies heavily on the TPB. In environments like these where financial reporting and audit quality carry importance, factors such as identity and ethics play crucial roles. By expanding the TPB to address this gap, the present study not only enriches the framework, but it also stands to gain more precise and practically valuable insights for encouraging blockchain integration in these crucial industries.

Research Questions:

• (RQ1) What role do traditional TPB constructs (Attitude, subjective norm, and Perceived Behavioral Control) play in predicting blockchain adoption in accounting and auditing?
• (RQ2) How do self-identity and personal moral norms extend TPB’s explanatory power in this context?
• (RQ3) Which factor emerges as the strongest driver of adoption intention among professionals?

2. Literature Review

Recent research shows that blockchain’s integration into financial information systems extends beyond its technical foundations, fundamentally reshaping auditing by providing immutable audit trails and enhancing data integrity (Wibowo & Christian, 2021; Dai & Vasarhelyi, 2017). Its role as a tamper-evident database engine enables real-time verification and reduces reconciliation needs, thereby increasing transparency but also challenging traditional accounting frameworks (Tan & Low, 2019; Jayasuriya & Sims, 2022). Scholars highlight the need for restructuring audit methodologies to accommodate blockchain features such as decentralized verification and new mechanisms for error correction (Fahlevi et al., 2023; Wei & Ding, 2018). Parallel insights from digital finance research demonstrate that extending the Theory of Planned Behavior (TPB) with constructs such as moral obligation and Self-Identity enhances explanatory power in technology adoption (R. Kumar et al., 2023). These findings justify testing moral norms and Self-Identity in auditing contexts, where blockchain adoption is shaped not only by technological efficiency but also by ethical responsibilities and professional identity.

2.1. Blockchain Technology and Its Transformative Potential

Blockchain technology has undergone a remarkable transformation since its inception, initially emerging as the foundational technology for cryptocurrencies, particularly Bitcoin, introduced in 2009 by Satoshi Nakamoto. At its core, blockchain serves as a decentralized ledger that records transactions securely and transparently, addressing the double-spending problem inherent in digital currencies (Dai & Vasarhelyi, 2017). This innovation marked a pivotal moment in the development of digital financial systems, as it eliminated the need for a central authority to validate transactions, thereby fostering trust among users.

In the quest to harness the power of blockchain, technology for businesses needs and objectives gained momentum. The emergence of contracts that operate as automated enforcers of terms within blockchain systems has added complexity to this evolving scenario. Vincent and Barkhi (2020) highlight the importance for auditors to review and adapt internal control protocols due to the essence of blockchain ecosystems that challenge distinctions between business partners. The field of auditing faces both promising opportunities and daunting hurdles with the integration of blockchain technology. Sheldon (2019) highlights the potential for blockchain to streamline audit processes in time and enhance the credibility of audit findings. However, a key challenge emerges, as auditors must acquire expertise in blockchain technology and comprehend its risks (Sheldon, 2021). In their study from 2021, Gauthier and Brender delve deeper into the adjustments needed in auditing standards to better align with the distinctive features of blockchain technology. They propose that incorporating this technology could bring about changes in the information resources for auditors.

The COVID-19 outbreak has sped up the shift towards digitalization in sectors such as auditing and accounting, according to Al-Sartawi et al. (2022). They mention that the pandemic has encouraged the adoption of innovations, like blockchain technology, to boost efficiency and enhance services in this setting. This development underscores the growing significance of the blockchain as companies aim to utilize tools to tackle issues prompted by disturbances. Blockchain fundamentally serves as a platform that enables individuals to share and exchange information without relying on middlemen or intermediaries. It functions through peer to peer (or P2p) networking principles that empower users to create and distribute content with one another. Creating a blockchain entails producing a hash code that is then shared across a network of computers. This decentralized structure guarantees transparency, built in security, and immutability—characteristics that position blockchain as an option for use cases. During this era, blockchain technology has revolutionized industries like finance and health. Decentralized and transparent by nature, it provides advantages like better security measures, transaction processes, and lesser dependency on intermediaries. In the accounting and auditing sector, blockchain shows promise in the creation of audit trails. Blockchain technology can also reduce costs by creating trust among stakeholders and improving efficiency (Clohessy et al., 2020; Dean et al., 2011). However, the widespread application of blockchain systems is hindered by scant knowledge on elements affecting individuals’ intentions to use systems. Breaking these obstacles is imperative to release the potential of blockchain technology across many industries. The evolution of blockchain technology in the past illustrates how the technology has transitioned from being applied in cryptocurrencies to affecting aspects such as auditing and accounting processes. As this technology progresses further in sophistication and utility capabilities increase, it is expected to have ranging effects on internal controls procedures, as well as on how audits are conducted and the level of transparency within organizations. Despite the advantages offered by the blockchain in terms of improving efficiency, safety, and trustworthiness, the widespread acceptance of this technology will necessitate overcoming hurdles related to educating people about it, making them aware of its benefits. As industries continue to embrace digital transformation, the blockchain is poised to play a pivotal role in shaping the future of auditing, accounting, and beyond.

2.2. Extending the Theory of Planned Behavior

According to the TPB, an individuals’ decision to act is influenced by three factors: their Attitude, the norm they perceive, and their belief in their own ability to control the behavior (Bhattacherjee, 2000; Shih & Fang, 2004). Past research by Ajzen in 2002 and Taylor & Todd in 1995 have shown how these elements effectively predict the adoption of technologies across fields, as noted by Bhattacherjee (2000). For example, Bhattacherjees’ research on the adoption of online shopping shows that the TPB framework is able to account for a portion of variability in willingness through these key concepts. Similarly, Shih and Fang’s (2004) investigation into Internet banking highlights that Attitudes, expectations, and perceived control consistently influence users’ decisions to interact with digital offerings, supporting the overall applicability of the TPB model.

Many of these research studies typically center on the adoption of technology, in general. They often overlook the dynamics present in specialized professional settings, like accounting and auditing sectors. Recent studies emphasize that ethical concerns and personal identity could significantly influence decision-making processes within these industries. M. Chen and Tung (2009) expanded the TPB to include moral norms, showing that ethical duties significantly impact one’s willingness to adopt technologies when behavior carries moral weight. Additionally, White and Hyde (2011) incorporated self-perception into the TPB framework to demonstrate that people are more likely to engage in behaviors that align with their self-concept in environments where reputation and ethical values are key factors.

In the realm of embracing technology in the business world, professionals’ Attitudes are key as they mirror how individuals perceive the value and importance of systems built on the blockchain (Ferri et al., 2020; Gauthier & Brender, 2021). Having an outlook on the blockchain can lead to intentions in behavior. Subjective Norms come into play by representing the impact of expectations from peers and management levels that greatly influence decisions related to adoption (Ajzen, 2002; Taylor & Todd, 1995; Bhattacherjee, 2000). Perceived Behavioral Control ultimately focuses on how confident individuals are in their capacity to utilize systems. This underscores the significance of possessing skills and knowledge as having autonomy in encouraging acceptance (Gurtu & Johny, 2019; Hannah et al., 2018).

Recent studies have emphasized the need to extend TPB by incorporating constructs like self-identity and personal moral norms to capture the full spectrum of factors influencing technology adoption. In professional settings, individuals often view their adoption of new technologies as part of their professional identity (Hardjono et al., 2020; Yazdanpanah et al., 2015). For instance, the implementation of blockchain-based systems can be likened to being equivalent to assuming the position of a looking accountant or auditor that is dedicated to driving innovation and achieving excellence. In such settings as accounting and auditing professions, ethics are vital in decision-making where personal moral norms also have their part to play. Specialists in these areas feel compelled to use technologies that build transparency and trust in what they do (Hasani et al., 2017). The present study seeks to contribute to a better understanding of how blockchains can be implemented in accounting and auditing by incorporating these principles into the TPB model. Personal ethical beliefs and values play a part in our intention to utilize technologies that are seen to increase transparency and reduce activities. Thus, these values significantly affect our Behavioral Intentions. In fields where honesty and integrity are placed with great emphasis, such as accounting and auditing, these ethical considerations take effect. Current studies that are focused on auditors’ intentions have already started integrating factors like values and responsibilities, with the suggestion that those professionals who are driven by a strong sense of ethics are more inclined to support the shift to blockchain-driven systems (Shbail et al., 2023). These observations are evidence in support of the addition of self-perception and moral norms within current theories of technology adoption in accounting and auditing.

Figure 1 illustrates the Behavioral Intention aspects of blockchain adoption in accounting and auditing services, based on the proposed extended version of the TPB framework. The central focus is on Behavioral Intention, which represents the individual’s intention to adopt blockchain-based systems for accounting and auditing services. Surrounding this central concept are five key constructs that influence Behavioral Intention, each contributing uniquely to the decision-making process.

3. Conceptual Framework and Hypotheses

The framework of the study is shown in Figure 2. The modified version of the Theory of Planned Behavior (TPB) incorporates five elements: Attitude, Subjective Norms, and Perceived Behavioral Control, along with components such as self-identity and personal Moral Norms.

3.1. Attitude Toward Blockchain Adoption

Attitude is about how someone feels—whether they like or do not like performing something (Alsulami, 2024). The feelings part is really important for figuring out how our personal beliefs and emotions influence what we intend to do and actually end up performing. When we talk about using blockchain tech, Attitude becomes a big deal because it shows what professionals think about the stuff it brings in terms of the benefits and risks and how valuable it can be for their organizations. In the world of blockchain use, Attitudes show what people think and feel about the tech based on their thoughts and emotions towards it. Positive outlooks are commonly linked to perceived benefits, like improved safety measures and clear procedures for performance; negative perspectives may emerge from worries about intricacy issues or uncertainties regarding regulations and potential misapplication (Alsulami, 2024). When it comes to embracing blockchain technology people who see its advantages and trustworthiness are more inclined to form opinions, leading them towards considering adoption plans. In the case of the adoption of the blockchain in an organization, leaders’ perceptions can be complex, with resource availability and affecting factors which subsequently impact decisions taken for adoption. Hence, it is hypothesized that

H1: 

Attitude positively impacts Behavioral Intention in Accounting and Auditing Services.

Attitude is the overall perception of the utility and perceived value of blockchain systems, which has been brought out in studies illustrating how technological advancements can redefine financial reporting and auditing through increased transparency and efficiency (Simões et al., 2021; Danach et al., 2024).

3.2. Subjective Norm

Regulations sometimes deter organizations from adopting blockchain technology, but competition compels them to find means of staying ahead in the market, as exhibited by Mthimkhulu and Jokonya (2022) and Alazab et al. (2020). Competition has also been shown to affect how organizations decide to adopt technologies. This reflects the manner in which organizations have a tendency to move towards implementing technologies when they realize that the competition is implementing them as well (Rise et al., 2010). Managers and colleagues become involved in shaping someone’s Attitude towards adopting technology. They often influence behavior by sharing feedback and suggestions within the workplace (Y. Cao et al., 2018).

Furthermore, it is important for organizations to consider the opinions and relationships with their partners in ecosystems when it comes to intertrust (Santhosh & Pavan Kumar Raju, 2025). The level of trust can be influenced by how organizations perceive the environment, which in turn affects their readiness to collaborate on initiatives. This highlights the significance of building trusting relationships among stakeholders for the implementation of technology (Koster & Borgman, 2020; Sadiq et al., 2021). Henceforth, personal beliefs encompass a range of factors that may either promote or impede the acceptance of technology within businesses, serving as an element in comprehending the forces behind the incorporation of technology in organizations. Thus, it is hypothesized that

H2: 

Subjective Norms positively influence Behavioral Intention in Accounting and Auditing Services.

3.3. Perceived Behavioral Control

An individual’s belief in their ability to use blockchain systems—known as Perceived Behavioral Control (PBC)—is vital for implementation. It is influenced by various internal and external factors within organizations. An organization’s readiness to embrace technology depends on factors like their setup and skilled workforce availability, as well as the resources at their disposal. External factors such as frameworks and compatibility issues also play a role in determining the practicality of adopting blockchain technology (Fomin et al., 2024; Esmaeilzadeh & Mirzaei, 2019).

According to a study conducted by Tezel and colleagues in 2020, it is crucial to train employees to overcome challenges hindering the adoption of technology due to inadequate skills and understanding levels (Tezel et al., 2020). This idea resonates with the study findings of Abdullah and their team that emphasize the importance of creating frameworks to facilitate operations across various blockchain platforms and boost organizational trust in adopting blockchain technologies (Abdullah et al., 2022). Furthermore, improving structures increases the sense of control over behavior by offering an organized method for understanding the intricacies of blockchain technology (Tezel et al., 2020). As such, it is hypothesized that

H3: 

Perceived Behavioral Control positively influences Behavioral Intention in Accounting and Auditing Services.

3.4. Self-Identity

Embracing advancements in organizations involves self-perception and identity considerations. It is observed that individuals who view themselves as innovators in the tech realm are more likely to embrace solutions that align with their identities within the company. Clohessy and Acton (2019) emphasize the significance of being prepared to drive technology adoption by proposing that an identity centered around innovation can boost resilience in overcoming challenges related to technology implementation.

Self-awareness and Self-Identity play roles in organizations’ acceptance of progressions and innovations. Individuals who view themselves as technological trailblazers are more likely to embrace solutions because they align with their identity within the organization. Clohessy and Acton (2019) emphasize the significance of preparedness in facilitating the adoption of technology, proposing that an identity rooted in innovation can bolster resilience in overcoming challenges associated with implementing technology.

Self-perception holds an important position in the business world. In the rapidly changing tech industry, companies that exude confidence in their technical prowess (as noted by Clohessy & Acton, 2019) are generally open to embracing innovative solutions like blockchain technology. How it influences their readiness to adopt technologies underscores the role that self-image plays in the realm of technology integration (Venkatesh & Davis, 2000). They explored how self-identity influences known technology acceptance models. Thus, it was suggested that integrating identity frameworks can enhance these models and lead to the understanding of adoption strategies. According to their findings, businesses that prioritize identity are more likely to succeed in integrating technologies like the blockchain (Venkatesh & Davis, 2000). Adopters who align their identity with technological trends at work are more inclined to embrace blockchain technologies in the long run. Connecting the identity of an organization to advancements in technology increases the likelihood of acceptance. As a result, it is suggested that

H4: 

Self-Identity positively affects Accounting and Auditing Services’ Behavioral Intentions.

3.5. Personal Moral Norm

Peoples’ individual ethical values influence their perspectives on incorporating blockchain systems within organizations from a standpoint of exploring how their sense of responsibility can either support or resist the implementation of technologies.

Studies indicate that people who have beliefs regarding technology usage are more likely to embrace the blockchain due to a sense of responsibility to keep up with technological advancements in the industry. Chatterjee et al. (2023) highlight the importance of principles in the adoption of blockchain technology within businesses by suggesting that integrating blockchain can improve behavior within organizations and encourage practices and societal accountability. Their study emphasizes the connection between ethics and blockchain technology by indicating that companies with principles are inclined to adopt these technologies, highlighting the significance of personal moral standards in decision-making procedures Ultimately individuals and companies are driven by their beliefs when considering the adoption of technologies that provide transparency and accountability. These beliefs determine the perception of the people regarding the integration of technology, particularly in sectors where ethical practices are strictly adhered to. Research has indicated that personal moral beliefs are engaged in influencing professionals’ willingness to embrace technologies that enhance transparency and accountability in their practice. To further elucidate this concept, according to the study by Haryanto and Sudaryati (2020), it was demonstrated that the ethical thinking of accountants can influence their adoption of innovations. This study offers the alignment of principles and professionals’ Attitudes in accepting solutions that offer greater transparency and minimize the opportunities for fraud—a critical element for organizations like finance and accounting, which are, by nature, subject to continuous questioning. Akman and Turhan (2022) showed how an individuals’ ethical beliefs can influence their responsibilities in the business world and motivate decision-making actions in organizations. Therefore, addressing the dilemmas surrounding technology is essential to leverage its benefits, leading to the hypothesis that

H5: 

Personal Moral Norms positively influence Behavioral Intention in Accounting and Auditing Services.

3.6. Behavioral Intention

The extended framework for blockchain intention in accounting and auditing services suggests that professionals’ willingness to embrace technology is influenced by various factors, based on the framework of Planned Behavior. According to this model, Behavioral Intention is shaped by Attitude (H1), as well as by Subjective Norms (H2), by Perceived Behavioral Control (H3), by Self-Identity (H4), and by Personal Moral Norms (H5). Each of these concepts represent aspects of the process involved in deciding to adopt technologies.

Having that outlook, technology plays a role in determining how likely we are to adopt it and use it in our daily lives. While some research suggests that Attitude alone may not be the factor influencing our behavior compared to beliefs like norms and control factors (Tsuruta, 2024; Alkhwaldi et al., 2024), it is still important in shaping our thoughts about adopting blockchain technology and considering its usefulness and advantages in the long run. The subjective norm refers to how peers and regulatory bodies can impact professionals’ adoption of technology based on the expectations of others in their circle. This influence is especially strong within sectors, like accounting and auditing, that face public and regulatory oversight (Alkhwaldi et al., 2024; Abdennadher et al., 2021).

The perception of control over ones’ actions emphasizes how individuals or organizations evaluate their resources and technical know-how to utilize technology systems. A significant influence is evident when accountants and auditors feel they have the skills and the right legal and technological support to adopt technology (Alkhwaldi et al., 2024). Additionally, one’s self-perception as a forward-thinking professional plays a role as a motivating factor. When people see themselves as being among the first to embrace technologies, they are more likely to adopt the blockchain into their work culture. This is also advanced greatly according to research performed by Pimentel and Boulianne (2020) and Schmitz and Leoni (2019).

The most important aspect to highlight at this point is that of values within this extended framework. The ethical concerns about the protection of privacy of data and fairness in disclosures and the need for accountability all contribute to an ethos of moral responsibility in using systems that facilitate openness and curtail fraudulence. Contexts prioritizing personal moral standards can be employed in generating desired behavior. In addition, strong personal beliefs in experts influence whether or not they use advanced technologies like blockchain while sustaining the distinctive ethical standards of accountants and auditors (Hasan et al., 2024; Alkhwaldi et al., 2024; Abdennadher et al., 2021). Incorporating consideration into the TPB model gives more insight into the determinants of technology use in essential professions.

4. Methodology

4.1. Research Instrument

The items of the questionnaire were derived from previously validated research to guarantee reliability and validity, comprising four items for Attitude (AT) drawn from Ajzen (2002), Taylor and Todd (1995), and Bhattacherjee (2000); four items for Subjective Norm (SN) informed by Ajzen (2002), Taylor and Todd (1995), Bhattacherjee (2000), M.-F. Chen et al. (2009), Manning (2009), and Wang et al. (2014); three items for Perceived Behavioral Control (PBC) based on Ajzen (2002), Taylor and Todd (1995), Hinds and Sparks (2008), Fielding et al. (2008), and Kaiser and Scheuthle (2003); three items for Behavioral Intention (BI) grounded in Ajzen (2012), Taylor and Todd (1995), Bhattacherjee (2000), and Yadav and Pathak (2016); two items for Self-Identity (SI) sourced from Fielding et al. (2008), Whitmarsh and O’Neill (2010), Yazdanpanah et al. (2015), and Cook et al. (2002); and four items for Personal Moral Norm (PMN) derived from Bamberg et al. (2007), Kaiser and Scheuthle (2003), and Fornara et al. (2016), ensuring robust measurement of each construct investigating the adoption of blockchain technology in accounting and auditing processes (Appendix A).

4.2. Sample and Data Collection

To make sure the research tool was valid and reliable, we tested the questionnaire with a group of individuals to improve its organization and information quality. We gave the questionnaire to 33 professionals who work in accounting and auditing companies for feedback. During this stage, we asked 20 questions to assess each aspect using a scale. The questionnaire used a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). Descriptive statistics (means and standard deviations) for each construct are presented in

Table 2. Descriptive statistics for constructs.

Construct	Mean	SD
Attitude	3.97	0.82
Subjective Norm	3.84	0.87
Perceived Behavioral Control (PBC)	3.72	0.90
Self-Identity	3.65	0.85
Personal Moral Norm	4.05	0.78
Behavioral Intention	3.89	0.83

.

To support cultural analysis effectively, the research tool underwent professional translation into Greek by a certified translator and then the outcomes were reverse translated back into English to guarantee precision and uniformity. Considering the necessity for perspectives, the ultimate survey was conducted online via the Prolific platform to encourage engagement from various geographical areas. A purposeful sampling method was used to enlist individuals who fulfilled the defined requirements of being accountants, auditors, finance managers, and other stakeholders engaged in reporting and auditing activities. In order to make sure the participants were relevant to the study’s focus on blockchain technology in accounting and auditing services, a screening question was used to evaluate their knowledge in this area.

The survey was conducted between December 2024 and March 2025, yielding 804 valid responses. Fifty-three questionnaires were excluded due to missing answers, resulting in a final sample size of 751 respondents. This sample size adheres to Hair et al.’s (2017) recommendation of having at least ten times the number of variables being measured. Moreover, respondents’ distribution aligns with the criteria established by Kock and Hadaya (2018), ensuring representation across diverse regions, enhancing the generalizability of the findings.

Table 3. Demographic statistics.

Demographic characteristics	f	%
Gender
Female	349	46.5%
Male	402	53.5%
Education
High School	52	6.9%
Bachelor’s Degree	391	52.1%
Master’s Degree	250	33.3%
PhD	58	7.7%
Age
20–30 years	73	9.7%
31–40 years	287	38.2%
41–50 years	212	28.2%
51+ years	179	23.8%
Income
<EUR 25,000	373	49.7%
EUR 25,001–40,000	129	17.2%
EUR 40,001–55,000	205	27.3%
>EUR 55,001	44	5.9%
Origin
East Europe	321	42.7%
North Europe	200	26.6%
South Europe	155	20.6%
West Europe	75	10.0%
Question = I possess a comprehensive understanding of blockchain technology and its applications in accounting and auditing services.
YES	751	100
Total	751	100

demonstrates that the demographic characteristics reveal a highly educated and mature group, with 52.1% holding a Bachelor’s Degree and 38.2% aged between 31 and 40 years. The gender distribution is relatively balanced (46.5% female, 53.5% male), while the majority of respondents are living in Eastern Europe (42.7%). Income levels skew toward the lower bracket (<EUR 25,000 for 49.7% of respondents), though higher-income groups are less represented. Notably, all participants demonstrate comprehensive knowledge of blockchain technology, underscoring their suitability for investigating blockchain applications in accounting and auditing.

5. Results

5.1. Measurement Model

The statistical software SPSS version 29.02 was utilized to assess the validity of the results and the demographic attributes of the participants. Subsequently, SmartPLS version 4.3 software was utilized to conduct Structural Equation Modeling to examine the relationships among the factors significantly influencing blockchain acceptance (Hair et al., 2017).

Harman’s single-factor test was performed to statistically address Common Method Bias (CMB). This test assesses if a singular component can explain the predominant covariance among the measurements. The findings indicated that the variation accounted for by a single component was 7.07%, far below the 50% criterion (Podsakoff et al., 2003). This analysis demonstrated the absence of common technique bias, since no one factor accounted for the majority of the association among the measures. Assurance was given on the stringent secrecy of replies, in accordance with the General Data Protection Regulation (GDPR), to promote candid and impartial participation.

The measurement demonstrated excellent fit indices, with Cronbach’s alpha and Composite Reliability exceeding the threshold of 0.7 for all constructs. Average Variance Extracted (AVE) values were above 0.5, indicating acceptable convergent validity. HTMT values were below the threshold of 0.9, confirming discriminant validity.

Table 4. Convergent validity and Composite Reliability.

Construct	Item	Standardized Loading > 0.704	Cronbach’s Alpha > 0.7	Composite Reliability CR > 0.7	Average Variance Extracted AVE > 0.5
ATTITUDE (AT)	AT_1	0.766	0.879	0.912	0.723
	AT_2	0.883
	AT_3	0.886
	AT_4	0.860
BEHAVIORAL INTENTION (I)	I_1	0.829	0.806	0.885	0.720
	I_2	0.871
	I_3	0.846
PERCEIVED BEHAVIORAL CONTROL (C)	C_1	0.855	0.772	0.867	0.685
	C_2	0.848
	C_3	0.778
PERSONAL MORAL NORM (M)	M_1	0.842	0.843	0.895	0.680
	M_2	0.831
	M_3	0.806
	M_4	0.819
SELF-IDENTITY (ID)	ID_1	0.884	0.736	0.883	0.791
	ID_2	0.895
SUBJECTIVE NORM (S)	S_1	0.827	0.836	0.889	0.668
	S_2	0.831
	S_3	0.791
	S_4	0.819

illustrates the findings of convergent validity (CV) and Composite Reliability (CR). The measurement model results indicate robust convergent validity (CV) and Composite Reliability (CR) for all constructs (Hair et al., 2017). All items for Attitude (AT_1 to AT_4) have standardized loadings above 0.704, with an Average Variance Extracted (AVE) of 0.723 and a Composite Reliability (CR) of 0.912, with a Cronbach’s alpha of 0.879, signifying exceptional internal consistency. Behavioral Intention (I) exhibits standardized loadings beyond the threshold, an AVE of 0.72, and a CR of 0.885, with a Cronbach’s alpha of 0.806 affirming its reliability. Perceived Behavioral Control (C) satisfies the requirements with standardized loadings exceeding 0.704, an AVE of 0.685, a CR of 0.867, and a Cronbach’s alpha of 0.772, indicating satisfactory reliability. The Personal Moral Norm (M) has standardized loadings beyond the threshold, an AVE of 0.68, a CR of 0.895, and a Cronbach’s alpha of 0.843, confirming its robustness. Self-Identity (ID) has standardized loadings above 0.704, an AVE of 0.791, a CR of 0.883, and a Cronbach’s alpha of 0.736, indicating strong reliability. Finally, Subjective Norm (S) has a standardized loading above 0.704, an AVE of 0.668, a CR of 0.889, and a Cronbach’s alpha of 0.836, confirming its validity. The results together affirm that each construct in the measurement model exhibits acceptable to exceptional levels of convergent validity and reliability, hence reinforcing the overall robustness of the measurement model.

The discriminant validity assessment employing the Fornell–Larcker criterion (

Table 5. Discriminant validity analysis (Fornell and Larcker).

	ATTITUDE (AT)	BEHAVIORAL INTENTION (I)	PERCEIVED BEHAVIORAL CONTROL (C)	PERSONAL MORAL NORM (M)	SELF-IDENTITY (ID)	SUBJECTIVE NORM (S)
ATTITUDE (AT)	0.850
BEHAVIORAL INTENTION (I)	0.073	0.849
PERCEIVED BEHAVIORAL CONTROL (C)	0.033	0.529	0.828
PERSONAL MORAL NORM (M)	0.02	0.567	0.591	0.825
SELF-IDENTITY (ID)	−0.025	0.441	0.463	0.468	0.890
SUBJECTIVE NORM (S)	−0.022	0.532	0.565	0.589	0.457	0.817

Note: Bold values demonstrate the square root of the Average Variance Extracted.

) indicates that all constructs within the model are adequately different from each other. The highlighted values along the diagonal denote the square roots of the Average Variance Extracted (AVE) for each construct, functioning as standards for evaluating their interrelations with other constructs. The square root of the AVE for Attitude (AT) is 0.850, which exceeds its correlations with all other variables (e.g., 0.073 with Behavioral Intention, 0.033 with Perceived Behavioral Control, etc.). Likewise, the square root of the AVE for Behavioral Intention (I) is 0.849, surpassing its correlations with other variables. This pattern is applicable to all constructs, including Perceived Behavioral Control (C), Personal Moral Norm (M), Self-Identity (ID), and Subjective Norm (S). The existence of minimal or insignificant correlations (e.g., −0.025 and −0.022) further reinforces the uniqueness of the constructs demonstrating a robust discriminant validity, confirming that each construct assesses a distinct underlying notion with minimal overlap with others.

Table 6. Discriminant validity analysis (Heterotait–Monotrait Ratio-HTMT).

	ATTITUDE (AT)	BEHAVIORAL INTENTION (I)	PERCEIVED BEHAVIORAL CONTROL (C)	PERSONAL MORAL NORM (M)	SELF-IDENTITY (ID)	SUBJECTIVE NORM (S)
ATTITUDE (AT)
BEHAVIORAL INTENTION (I)	0.094
PERCEIVED BEHAVIORAL CONTROL (C)	0.074	0.659
PERSONAL MORAL NORM (M)	0.038	0.681	0.731
SELF-IDENTITY (ID)	0.06	0.568	0.621	0.595
SUBJECTIVE NORM (S)	0.063	0.644	0.705	0.701	0.583

presents the results of the discriminant validity using the Heterotrait–Monotrait Ratio (HTMT), with all HTMT values falling below the critical threshold of 0.90 (Henseler et al., 2014) indicating that the constructs exhibit acceptable discriminant validity.

Figure 3 illustrates a graphic representation of the measurement model.

5.2. Structural Model

The study developed a structural model based on the expanded Theory of Planned Behavior (TPB) framework to explore how key elements—Attitude, Subjective Norm, Perceived Behavioral Control, Self-Identity, and Personal Moral Norm—impact Behavioral Intention regarding blockchain adoption in accounting and auditing services. Figure 4 presents a graphical depiction of the structural model, elucidating the links among the principal components and emphasizing the intensity and relevance of each predictor’s impact on Behavioral Intention.

Using Structural Equation Modeling (SEM) and the statistical bootstrap method with a sample size of 5000 (Ringle et al., 2014), the research tested the hypothesis (

Table 7. Hypotheses testing direct effects.

Hypotheses		Std. Beta (β)	Std. Error	T Values	p Values	Conclusions
H1	ATTITUDE (AT) -> BEHAVIORAL INTENTION (I)	0.069	0.033	2.12	0.034	Supported
H2	SUBJECTIVE NORM (S) -> BEHAVIORAL INTENTION (I)	0.207	0.038	5.523	0.000	Supported
H3	PERCEIVED BEHAVIORAL CONTROL (C) -> BEHAVIORAL INTENTION (I)	0.189	0.045	4.187	0.000	Supported
H4	SELF-IDENTITY (ID) -> BEHAVIORAL INTENTION (I)	0.134	0.030	4.454	0.000	Supported
H5	PERSONAL MORAL NORM (M) -> BEHAVIORAL INTENTION (I)	0.269	0.046	5.832	0.000	Supported

) and evaluated metrics such as explained variance (R²), effect size (F²), path coefficients (β), t-values, and predictive relevance (Q²). The findings revealed that Attitude (β = 0.069) had a modest but significant positive influence, highlighting the importance of favorable perceptions about blockchain’s utility. Subjective Norm (β = 0.207) demonstrated a stronger effect, indicating that social pressures from peers and supervisors significantly shape adoption intentions. Perceived Behavioral Control (β = 0.189) also showed a substantial impact, suggesting that confidence in one’s ability to use blockchain systems boosts adoption likelihood, which organizations can enhance through training and resources. Self-Identity (β = 0.134) had a modest influence, emphasizing the role of aligning personal identity with blockchain usage in motivating adoption. Most notably, Personal Moral Norms (β = 0.269) exerted the strongest influence, underscoring the critical role of ethical considerations, such as transparency and accountability, in driving adoption. These findings highlight the interplay of psychological, social, and ethical factors in blockchain adoption, offering practical insights for organizations aiming to promote its integration in professional settings.

Table 7 presents the results of testing direct effects between various constructs and Behavioral Intention (I). The analysis uses standardized regression coefficients (Std. Beta, β), standard errors, T-values, p-values, and conclusions regarding the acceptance or rejection of the null hypothesis. All five hypotheses are supported, as indicated by the low p-values (all ≤ 0.05). This suggests that each construct—Attitude, Subjective Norm, Perceived Behavioral Control, Self-Identity, and Personal Moral Norm—has a statistically significant direct positive effect on Behavioral Intention. For H1, the effect of Attitude on Behavioral Intention is supported, with a Std. Beta coefficient of 0.069 and a p-value of 0.034, which is below the critical threshold of 0.05. This indicates that individuals’ Attitudes toward a behavior positively influence their intention to perform it, albeit with a relatively weaker effect compared to other predictors. Similarly, H2 and H3 demonstrate that both Subjective Norm and Perceived Behavioral Control significantly impact Behavioral Intention, with Std. Beta values of 0.207 and 0.189, respectively, and p-values of 0. These findings suggest that social pressures and perceived control over performing the behavior are strong determinants of Behavioral Intentions. In addition, H4 and H5 further confirm that Self-Identity and Personal Moral Norms also play significant roles in shaping Behavioral Intention. Self-Identity has a moderate effect (Std. Beta = 0.134, p-value = 0), indicating that individuals who identify with a particular behavior are more likely to intend to perform it. Meanwhile, H5 reveals the strongest effect among all predictors, with Personal Moral Norm having a Std. Beta of 0.269 and a p-value of 0. This underscores the critical role of personal moral values in driving Behavioral Intentions, suggesting that individuals are highly motivated to act in ways consistent with their moral beliefs. Collectively, these findings validate the TPB theoretical framework and highlight the multifaceted nature of Behavioral Intention, where multiple psychological and social factors interact to predict behavior. Personal Moral Norm has a strong and statistically significant positive direct effect on Behavioral Intention. The effect size (β = 0.269) indicates the largest influence among all predictors. Overall, the results provide robust empirical support for the proposed relationships between the predictors and Behavioral Intention. The rejection of the null hypothesis for all five hypotheses confirms that Attitude, Subjective Norm, Perceived Behavioral Control, Self-Identity, and Personal Moral Norm each contribute uniquely and significantly to explaining Behavioral Intentions.

The results of the Structural Equation Modeling reveal that the predictors collectively explain 42.7% of the variance in Behavioral Intention (R² = 0.427) with an adjusted R² of 0.423, indicating a robust fit of the model. It is demonstrated that all Q² values are positive, as per the criteria outlined by Hair et al. (2017). The predictive relevance of the model is confirmed by a positive Q² value of 0.417, suggesting that the relationships among the constructs are meaningful and can be used to predict Behavioral Intention effectively. Regarding the individual effects of the predictors, the effect sizes (F²) highlight the relative importance of each construct. Personal Moral Norm exhibits the strongest effect on Behavioral Intention (F² = 3.105), followed by Perceived Behavioral Control (F² = 1.969) and Subjective Norm (F² = 2.77). Self-Identity also contributes significantly (F² = 2.139), while Attitude has a comparatively weaker effect (F² = 1.195). These findings shown in

Table 8. R square, adjusted R square, F square, and Q² predict.

Latent Variables	R2	Adj. R2	Q2	F2
BEHAVIORAL INTENTION (I)	0.427	0.423	0.417
ATTITUDE (AT) -> BEHAVIORAL INTENTION (I)		0.011	1.195	0.008
PERCEIVED BEHAVIORAL CONTROL (C) -> BEHAVIORAL INTENTION (I)		0.037	1.969	0.035
PERSONAL MORAL NORM (M) -> BEHAVIORAL INTENTION (I)		0.070	3.105	0.068
SELF-IDENTITY (ID) -> BEHAVIORAL INTENTION (I)		0.023	2.139	0.022
SUBJECTIVE NORM (S) -> BEHAVIORAL INTENTION (I)		0.043	2.77	0.042

underscore the critical role of moral norms and control beliefs in shaping Behavioral Intentions. In conclusion, the magnitude of the observed effects varies as Personal Moral Norm (M) has the strongest effect (β = 0.269), while Subjective Norm (S) follows closely behind with a strong effect (β = 0.207). Perceived Behavioral Control (C) and Self-Identity (ID) have moderate effects (β = 0.189 and β = 0.134, respectively), and Attitude (AT) has the weakest but still significant effect (β = 0.069). These findings align with theoretical expectations in behavioral models where multiple factors contribute to Behavioral Intention.

6. Discussion

Our findings align with the newest literature. For example, Alkhwaldi et al. (2024) confirm that innovative blockchain usage is driven by both technical and ethical determinants, while Febryaningrum and Aligarh (2024) show similar identity–morality influences in digital commerce. These comparisons strengthen the claim that Personal Moral Norms and professional identity are decisive drivers of blockchain adoption.

The results provide compelling empirical support for each construct’s role in the prediction of Behavioral Intention within the extended Theory of Planned Behavior (TPB) model. The structural model suggests that all five constructs—Attitude, Subjective Norm, Perceived Behavioral Control, Self-Identity, and Personal Moral Norm —positively affect Behavioral Intention. However, their impacts are drastically different in terms of strength.

Surprisingly, Personal Moral Norm is the strongest influence, followed by Subjective Norm and Perceived Behavioral Control. Attitude, however, has the weakest but still significant effect. These findings accord with the dominant theory regarding behavior, providing evidence of the need for the integration of personal and social forces in explaining behavior outcomes. The dominance of Personal Moral Norms indicates the preeminence of ethical considerations in shaping adoption intentions. Similarly, the significance of Subjective Norms also emphasizes how support from managers and colleagues in initiating behavioral changes is crucial. Perceived Behavioral Control and Self-Identity, however, suggest the significance of organizations affirming professionals’ self-efficacy as well as identity congruence with blockchain implementation. Although Attitude is significant statistically, its relatively weaker impact suggests that more comprehensive contextual determinants have a greater influence on adoption decisions.

These conclusions are important to organizations and interventions aiming to influence behavior. Not only should interventions address Attitude changes but also moral norms, identity, and social influences to maximize the likelihood of wished-for behavioral change. By addressing both the cognitive and moral elements, this extended TPB model offers sound advice for practitioners and researchers interested in inducing the adoption of new technologies in the workplace.

Our findings are consistent with existing literature. For instance, the work of Ronaghi and Mosakhani (2021) demonstrates that companies operating in principle-driven industries that integrate moral values into decision-making are better able to manage the challenges of emerging technologies and build public trust. In addition, our study lends support to the inclusion of self-perception and ethical standards in predictive models, as Yazdanpanah et al. (2015) did in exploring water conservation behavior in an extended TPB framework. Although their focus was on environmental behavior, our study lends support to the inclusion of self-perception and ethical standards in forecasting models in other contexts. These are beyond the traditional TPB factors and offer more explanatory power for Behavioral Intentions.

Expanding TPB to add self-perception and personal ethical standards is further supported by the expanding body of literature across several fields of behavioral studies. The convergence has specific implications for a professional environment such as accounting and auditing, whose employees’ own image and ethical perceptions significantly impact their actions. Our research combining these factors presents a deeper perspective on the usage of blockchain technology in professional environments. This expanded perspective offers insights that are applicable to researchers and practitioners who study the interaction among technology, identity, and morality.

6.1. Managerial Implications

The study’s implications for managers provide direction for businesses that wish to promote the application of blockchain in auditing and accounting services by pointing out factors and personal identification factors, as well as conventional technical acceptance factors. The importance of norms serves as a motivator for companies to promote the application of blockchain technology among professionals by underlining its advantages, like increased transparency and accountability, as suggested by Chatterjee et al.’s (2023) research, which points to the need to address issues in an effort to increase stakeholders’ willingness to adopt and embrace new technologies.

To boost motivation and commitment to practices at work, it is suggested to rely on peer encouragement and approval from leaders. Building a work environment that values the use of technology as a shared objective can influence Attitudes within the organization. As noted by Jassem et al. (2024), endorsements from leadership act as cues that encourage a culture of innovation in sectors where trust is paramount. It is essential to empower employees by providing training and access to resources that can enhance their skills and confidence levels, in the accounting and auditing field. Empowered employees are more adept at incorporating blockchain systems into their tasks to boost organizational performance.

Finally, connecting the integration of technology with one’s professional identity enhances dedication by associating the use of technology with how individuals see themselves. When integrating technology is portrayed as consistent with one’s duties and beliefs, it strengthens the moral and ethical foundation of accounting and auditing professionals. This emphasizes the significance of presenting the blockchain not as a tool but as a part of the ethical norms and obligations intrinsic to professional conduct.

In summary, these key points suggest that using a combination of values, social impact, empowerment, and professional identity is essential to support the introduction of blockchain technology in accounting and auditing services. This strategy may assist companies in overcoming challenges related to implementing technology and promoting a work environment that encourages behavior, transparency, and creativity.

6.2. Theoretical Implications

This study extends the Theory of Planned Behavior (TPB) through the incorporation of Self-Identity and Personal Moral Norms, demonstrating their central contribution to the explanation of decision-making mechanisms of adopting technology in workplace settings. Our findings validate Conner and Armitage’s (1998) argument that the extension of TPB with variables such as Self-Identity and moral norms enhances its explanatory capacity in a range of behavioral contexts. With the integration of these constructs, we overcome the limitations of the classical TPB model, which has a tendency to overlook the influence of values and identity. This addition becomes relevant in professional settings such as auditing and accounting, where ethical duties and trustworthiness are concerns of utmost priority. Thus, our research reinforces the necessity of extending the TPB so that it can include the interplay among cognitive, social, and moral variables in the development of Behavioral Intentions.

Our research supports recent research, for instance, by J. Cao et al. (2023), which analyzed waste sorting behavior and concluded that individuals’ sense of self and moral beliefs are better predictors of behavior than just TPB variables alone. Similarly, our research highlights the superiority of Personal Moral Norms as the best predictor of intentions to embrace blockchain technology, followed by Subjective Norms and Perceived Behavioral Control. These results contribute weight to the growing consensus in the literature that ethics and Self-Identity are powerful determinants of behavior, often beating Attitude, social norms, and perceived control as explanations. In confirming and extending these findings, our research provides additional evidence for the integration of Self-Identity and moral standards into theories of behavior.

Our theoretical base is also complemented by the work of Hyde and White (2009). Their research on organ donation intentions showed that moral norms and identity are important predictors of behavior, particularly in cases with significant personal and social interests. Our research replicates these outcomes, demonstrating that the application of blockchain technology in a professional context is also influenced by ethical considerations and professional identity. This congruence suggests that our results are not only applicable to technology adoption but are also indicative of a general trend of behavioral research emphasizing the importance of values and identity in decision-making. Taken together, these studies collectively corroborate the need for adding Self-Identity and moral norms to the TPB to explain more sophisticated behaviors.

Finally, the theoretical contribution of our research is the contribution to the growing literature of research that complements the TPB in addressing its loopholes. Through the inclusion of Self-Identity and Personal Moral Norms, we extend the initial contributions of Conner and Armitage (1998), J. Cao et al. (2023), and Hyde and White (2009), demonstrating that these variables enhance the predictive ability of the model for technology adoption. Our study not only aligns with these existing studies but also extends their findings into the arena of blockchain adoption within accounting and auditing services. Our expanded model reflects a more in-depth understanding of the determinants of Behavioral Intentions and is valuable advice for researchers and practitioners who seek to examine the interaction among technology, ethics, and professional identity.

6.3. Limitations and Future Research

This study makes valuable contributions to the nature of moral norms in blockchain adoption and Self-Identity in accounting and auditing. However, there are several limitations that must be taken into consideration and some future research recommendations to extend these findings.

One limitation is that the study focuses on a specific industry sector (accounting and auditing) and, therefore, its generalizability to other environments may be limited. Experts in specific locations or sectors may have mixed opinions regarding the implementation of blockchain technology due to organizational, cultural, and environmental settings. For instance, Tiron-Tudor et al. (2021) emphasize that there is the need to adopt various empirical research from different settings to enhance understanding. Future research should specifically obtain data from various geographic settings as well as industries to enhance findings’ comprehensiveness and authenticity. This would allow for comparison across contexts to reveal potential differences in adoption processes and the contribution of ethical and identity motivators.

A further limitation concerns the sampling method: participants were recruited via the Prolific platform, which may introduce self-selection bias. Moreover, the majority of respondents originated from Eastern Europe, restricting cultural diversity and limiting generalizability beyond this region. Another limitation stems from reliance on self-reported Behavioral Intentions rather than actual adoption behaviors, which may overestimate real adoption likelihood. Future studies should employ longitudinal designs to test causality and track how adoption Attitudes evolve over time, as blockchain regulation and organizational readiness change. Comparative research across industries (supply chain, banking, and healthcare) and across regions (Asia, Africa, and North America) would further validate whether moral and identity factors hold similar weight across contexts. Future models could also integrate organizational culture, regulatory frameworks, and cost–benefit considerations as moderators to provide a fuller picture of adoption decisions.

The current study enriches the TPB with the incorporation of Self-Identity and Personal Moral Norms but does not fully analyze other probable contributing factors. For example, organizational cultures, regulatory frameworks, and technological readiness are significantly contributing to technology adoption, according to Lombardi et al. (2021). They intersect with individual-level constructs and influence organizational as well as institutional decision-making processes. Subsequent research would have to encompass these other variables so that a more sophisticated and multidimensional technology adoption model can be formulated.

In conclusion, this research makes an addition to the literature by broadening the TPB to include Self-Identity and Personal Moral Norms within the context of the adoption of blockchain technology by accountants and auditors. However, its shortcomings offer some avenues for further research. Broadening the scope of studies to include diverse participant samples would enhance the generalizability of findings. Conducting longitudinal studies will identify cause-and-effect relationships and how they evolve across time. In addition, incorporating variables such as organizational cultures, regulatory frameworks, and technological readiness will give a wider picture of the process of technology adoption. These inclusions will not only refine existing theoretical frameworks but also be beneficial to firms and policymakers as they confront the dynamically evolving process of blockchain adoption.

7. Conclusions

This study demonstrates that aligning technological actions with professionals’ identity and moral values significantly facilitates blockchain adoption in accounting and auditing. The findings suggest that conventional factors by themselves do not fully account for all the driving forces behind the uptake of technology in settings where reliability and openness are factors to take into account. Blockchain’s influence on the transformation of accounting information systems involves a restructuring of duties, with a focus placed upon ethical deliberations (Tan & Low, 2019).

This research contributes to the literature by offering a nuanced view of the factors influencing blockchain adoption in accounting and auditing. By applying the extended TPB framework, we not only identify the determinants of Behavioral Intention but also highlight the importance of addressing barriers and leveraging opportunities for successful implementation. Furthermore, the inclusion of Self-Identity and Personal Moral Norms provides insights into the psychological and ethical dimensions of technology adoption, which are often overlooked in existing studies.

As such, understanding oneself not only impacts how individuals view themselves and their professional identity in relation to technology use but also plays a role in influencing how organizations behave in adopting blockchain technology. Companies that see themselves as pioneers are more likely to explore options which can influence where they stand strategically in a tech-focused market environment.

In summary, the study emphasizes the necessity of a more comprehensive approach than simply promoting the efficacy and societal impact of the blockchain in accounting and auditing services. It underscores the necessity of prioritizing standards and professional identity with Personal Moral Norms influencing adoption decisions. Future research should further these notions by exploring techniques that integrate technologies with organizational ethics and personal values to foster a more adaptive and resilient professional environment.