Blockchain is a cutting-edge distributed ledger technology that allows trading online without a centralised

authority. Blockchain is the most likely technology to be used in the upcoming technological transformation

affecting the industry. Numerous sectors, such as the real estate industry, require new technology to increase

market efficiency, safety, and transparency, as transaction amounts can be substantial. This study employs a

quantitative research method to investigate the role of blockchain technology in the Malaysian real estate market,

pilot test was conducted to evaluate the research model and determine Cronbach's Alpha values above the

recommended threshold of 0.60, indicating excellent reliability of the constructs. One study finding is that real

estate negotiators will likely use blockchain technology to alter the market. Fundamentally, it is for this reason

that additional study on the topic and technological advancements are necessary for a successful application in

the Malaysian real estate market.

Keywords: Blockchain, Technology Adoption, Unified Theory of Technology Acceptance and Usage

(UTAUT), Real Estate

The rapid advancement of technology is reshaping traditional industries, creating demand for systems that can

accelerate operations while ensuring greater security and transparency (Tapscott, 2016). One sector significantly

months from listing to the completion of ownership transfer (Donovan & Ho, 2020). While legally essential, the

Sales and Purchase Agreement (SPA) requires multiple steps, including legal reviews, financing, deposits, and

state authority approvals, further extending transaction timelines (Crowston & Wigand, 2010; James, 2022).

These inefficiencies slow down the market and reduce investor confidence.

Blockchain technology has recently emerged as a promising solution to these issues. Initially developed to

support cryptocurrencies such as Bitcoin, blockchain has evolved into a versatile system for secure data storage,

asset registration, and automated transactions (Swan, 2015). Its unique features, decentralisation, immutability,

transparency, and cryptographic security, enable more efficient and tamper-proof processes. By leveraging smart

contracts, blockchain can automate transaction steps, reduce reliance on intermediaries, and significantly shorten

completion times.

involving multiple intermediaries, lengthy legal procedures, and numerous administrative steps (Donovan & Ho,

2020). These processes create delays, increase transaction costs, and reduce market efficiency. Moreover,

information asymmetry persists in nearly all real estate transactions, forcing buyers and sellers to bear significant

costs related to information search, contracts, and supervision (Lantmäteriet et al., 2016). Such inefficiencies

limit transparency and trust and discourage local and foreign investors from engaging in the property market.

Blockchain technology has been proposed to address these challenges, offering features such as immutability,

transparency, decentralisation, and automation through smart contracts (Swan, 2015). By reducing reliance on

intermediaries, improving verification processes, and enabling secure information sharing, blockchain has the

potential to transform the real estate sector. However, its adoption in Malaysia remains early, with limited

empirical research exploring the factors influencing its implementation.

influence, facilitating conditions, and the adoption of blockchain technology in Malaysia's real estate sector. By

addressing this gap, the research offers both theoretical and practical insights into how blockchain can be

leveraged to mitigate inefficiencies, increase transparency, and enhance the overall effectiveness of real estate

transactions.

In this study, the dependent variable is the adoption of blockchain technology within the Malaysian real estate

market. Blockchain is a decentralised and trustless data transaction system that eliminates the need for third-

party verification by recording and validating transactions across a distributed network (Peters & Efstathios,

2016). As a chronological public ledger, blockchain maintains a database of records called "blocks," securely

cryptography to enhance security further, protecting the ledger from unauthorized access and manipulation

(Peters & Efstathios, 2016).

Blockchain can be implemented as either a public ledger or a private ledger. Public blockchains, such as Bitcoin,

use cryptoeconomic incentives to achieve consensus among participants, while private blockchains typically rely

on permissions and do not require the same level of computational validation. Beyond its applications in

cryptocurrency, blockchain has expanded into various other industries. For instance, Ethereum has enabled the

integration of smart contracts, allowing automated execution of agreements without intermediaries. At the same

time, Nasdaq's Linq platform illustrates how blockchain can be leveraged for secure and transparent trading of

private securities (Backlund, 2016).

Blockchain technology is increasingly being leveraged in the real estate sector to reduce inefficiencies, enhance

transparency, and streamline transaction processes. In the United States, blockchain-based platforms such as

Propy have enabled end-to-end property transactions that eliminate intermediaries, thereby reducing

administrative costs and transaction time (Ooi, Soh, & Soh, 2022). In Sweden, the Lantmäteriet pilot utilised

tenants to execute digital tenancy agreements and property sales online, reducing paperwork and promoting trust

in real estate transactions (Yong, Tay, & Khong, 2022). These global examples address persistent challenges in

conventional real estate markets, including lengthy transaction timelines, high intermediary costs, and

information asymmetry, by utilising immutable records and decentralised ledgers to enhance transparency,

efficiency, and trust in property transactions.

The extent to which individuals employ a particular technology for a specific activity is referred to as

performance expectations (Davis et al., 1989). Performance expectations are explicitly specified in UTAUT as

a measure of how technology is used to assist people in completing specific tasks (Venkatesh et al., 2012). The

use of perception, increased effectiveness, productivity, and ease of getting information are the four factors that

Effort expectations measure how easy a technology is to use. It is described as the ease with which current

technology or technical items may be used (Venkatesh et al., 2012). In adoption technology, one of the most

significant aspects to consider when assessing consumer technology use patterns and intents is effort expectations

(Casey & Wilson-Evered, 2012). According to one study, ease of use, sophistication, and simplicity were the

three characteristics predicted to influence effort. Perceived ease of use refers to how simple people perceive a

technology to be in terms of its use (Venkatesh et al., 2012). The ease of use of new technology is determined

by its simplicity (Jeng & Tzeng, 2012). The word "complexity" describes how difficult it is to learn and use new

technology (Rogers et al., 2005)

H2: Effort expectancy has a significant impact on the adoption of blockchain technology in Malaysia's real estate

intentions (Yellow & Gao, 2014). "The degree to which a person feels he or she must employ a new system

based on the ideas of others," Venkatesh et al. (2012) define social influence. Leong et al. (2013) defined social

effect as an individual's belief that many people should embrace a new technology. Venketesh et al. (2003) state

that social influence comprises three variables: subjective norms, social factors, and image. Social influence can

be classified into social norms and critical mass (Huang & Kao, 2014).

Individuals' views that organisational and technical infrastructure or resources exist to facilitate the usage of the

technology or system are facilitating conditions (Venkatesh et al., 2012). Facilitating conditions also refers to

the extent to which users believe that organisational and technological infrastructure can help them acquire the

knowledge and skills necessary to use new technologies. According to Venkatesh et al. (2003), variables like

perceived behavioural control and compatibility significantly impact facilitating conditions. The UTAUT

paradigm suggests that users' perceptions of convenience influence their adoption of technology. The cause is

the user's surrounding environment, which motivates or forces users to decline adoption (Venkatesh et al., 2012).

According to Akour and Dwairi (2011) and Alwahaishi and Snáe (2013), behavioural intentions to use

technology are affected by convenience.

According to the UTAUT theory, four primary elements determine the intention and use of information

technology. The primary elements of UTAUT, among the variables, include performance expectancy (PE), effort

expectancy (EE), social influence (SI), facilitating conditions (FC), behavioural intention (BI), usage behaviour,

gender, age, experience, and voluntariness to use. UTAUT aims to identify fundamental aspects and possibilities

that influence the prediction of behavioural intentions to take advantage of new technologies and techniques

Facilitating Condition is classified as a strong relationship towards Blockchain Adoption, as the correlation

These results showed the Pearson correlation coefficients among the independent variables —Performance

Expectancy (IV1), Effort Expectancy (IV2), Social Influence (IV3), and Facilitating Conditions (IV4) — and

the dependent variable, Blockchain Adoption (DV). All correlation coefficients are positive and significant at

independent variables collectively explain 51.3% of the variance in blockchain adoption. This indicates a

moderately strong relationship between the predictors — Performance Expectancy, Effort Expectancy, Social

Influence, and Facilitating Conditions — and the dependent variable.

The F-change value of 74.802 (p < 0.001) confirms that the overall regression model is statistically significant,

meaning the combination of predictors reliably explains the variation in blockchain adoption among real estate

negotiators. In practical terms, this suggests that over half of the changes in adoption behaviour can be attributed

to these four UTAUT-based factors, demonstrating the model's strong explanatory power.

TABLE V ANOVA

for predicting the adoption of blockchain technology in Malaysia's real estate market. In other words, the model

explains a substantial proportion of variance in blockchain adoption, confirming that these UTAUT-based

predictors are relevant and meaningful in this context.

In the correlation analysis, the strongest positive relationship was observed between Effort Expectancy and

Blockchain Adoption (r = 0.704, p < 0.001). This strong correlation suggests that real estate negotiators who

perceive blockchain systems as easy to understand, user-friendly, and uncomplicated to implement are

significantly more likely to adopt them. In practical terms, this implies that the perceived ease of use is a central

driver of adoption among practitioners, particularly in environments where digital proficiency and exposure to

advanced technology are still in development. This finding aligns with prior UTAUT-based studies (e.g.,

Venkatesh et al., 2003; Casey & Wilson-Evered, 2012), which consistently highlight effort expectancy as a

substantial and statistically significant effect on the dependent variable. Together with an adjusted R² value of

0.513 (as reported in the model summary), the analysis reveals that approximately 51.3% of the variance in

blockchain adoption can be explained by the four predictors. This indicates a robust explanatory power of the

model and supports the proposed hypotheses (H1–H4).

Table IV presents the coefficients of the multiple regression analysis. The findings indicate that all four

independent variables —Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating

Conditions —positively and significantly influence blockchain adoption among real estate negotiators in

Malaysia.

Performance Expectancy recorded a significant effect (B = 0.323, β = 0.293, t = 2.385, p = 0.018), indicating

that higher perceptions of blockchain usefulness are associated with greater adoption levels. Effort Expectancy

would remain limited without the influence of the identified predictors. Overall, the results confirm that all four

variables significantly affect blockchain adoption, with Effort Expectancy emerging as the strongest predictor in

this study.

TABLE VII Hypothesis

Use of Technology (UTAUT), which identifies perceived usefulness, perceived ease of use, social influence, and

enabling conditions as the main factors that encourage technology adoption (Venkatesh et al., 2003; Venkatesh

et al., 2012).

found that users in developing contexts are more willing to adopt technologies that are straightforward and user-

One possible explanation for this finding is the lower level of digital literacy and limited training opportunities

within Malaysia’s real estate industry. Many negotiators still depend on traditional, manual procedures and have

Expectancy in explaining adoption behaviour.

context. Similarly, Social Influence and Facilitating Conditions are significant, indicating that peer support,

professional endorsement, and organisational readiness play meaningful roles in encouraging adoption. These

results are consistent with Salim (2012) and Alwahaishi and Snášel (2013), who found that a supportive

environment and positive social norms increase users' confidence in adopting new technologies.

Overall, these findings suggest that the strength of UTAUT factors may vary depending on the local context. In

developing countries like Malaysia, where awareness of technology and infrastructure is still growing, ease of

use and supportive conditions have a greater impact on adoption than performance-related benefits. This supports

the argument by Venkatesh et al. (2012) that contextual and demographic factors can shape how users respond

to different elements of the UTAUT model.

that the UTAUT model is suitable for explaining the acceptance of new technologies in industries that are still

developing their digital capabilities.

From a practical perspective, the findings provide several important recommendations. BOVAEA should

organise structured blockchain awareness and training programs to improve the digital skills of real estate

negotiators. Government regulators need to establish clear policies and provide incentives to promote the

adoption of blockchain technology and enhance technological infrastructure. Real estate firms should start

utilising blockchain-based platforms to demonstrate how technology can expedite, enhance transparency, and

increase the security of property transactions.

Although the study provides valuable insights, it has some limitations. The sample size of 281 respondents and

the focus on the real estate sector limit the generalisation of the results. The use of self-reported data may also