The role of investor trust in mediating the impact of perceived blockchain integration on perceived stock market efficiency: evidence from the amman stock exchange

1 Introduction

1.1 Context

It is worth mentioning that the present study is situated in a context in which the Amman Stock Exchange has not yet integrated a blockchain-native architecture, and, to the knowledge of the authors, there is at present no public evidence that the exchange has migrated its trading, its clearing, its settlement, or its ownership-record systems to a distributed-ledger infrastructure. The blockchain-related initiatives that are examined in this study form part of a broader digital-modernization agenda that remains at an early and exploratory stage, and, accordingly, the study does not evaluate an operational blockchain system that is already in use. On the contrary, the study examines the perceptions, the expectations, and the attitudes of the market participants toward the prospective adoption of blockchain within the exchange, and it is on this perceptual level that all of the constructs of the study should be understood.

1.2 The problem

Blockchain technology is transforming the financial market field, in that the emergence of blockchain technology has promised to change the traditional ways of trading through the implementation of higher levels of transparency, security and efficiency in the trading process (Eyadat, et al., 2025; Tapscott and Tapscott, 2017). Given that capital markets in different parts of the world are probing blockchain technologies for potential integration, much for understanding how blockchain may influence market efficiency is important both at a practise level as well as a theoretical level. Specifically, the Amman Stock Exchange (ASE) is used as a case study to examine these relationships. The ASE, established in 1999 in Amman, Jordan, is the country’s only official securities market and a representative emerging exchange in the MENA region, the ASE has actively pursued technological modernization, making it a relevant setting in which to examine the potential role of blockchain integration. Since the ASE is a developing market that is currently attempting to modernise its technology. It should be noted that the Amman Stock Exchange has not yet implemented an operational blockchain-based trading, clearing, settlement, or ownership-record infrastructure, and the initiatives examined in this study form part of a broader digital-modernization agenda. Accordingly, this study does not evaluate an existing blockchain system, and it examines the perceptions, the expectations, and the attitudes of market participants toward the prospective adoption of blockchain within the exchange, rather than the realized effects of a technology that is already in operation.

In the financial sector, Blockchain, the distributed ledger system initially developed for the cryptocurrency transactions, has evolved to provide possible solutions to systemic requirements of existing financial markets (Risius and Spohrer, 2017). As such, blockchain can improve the way market participants know information by creating a secure, transparent, and immutable record keeping, reducing information asymmetry, reducing transaction costs and improving overall market efficiency (Chen and Bellavitis, 2020). But the benefits are actually realised subject to the perception of investors and their trust in adopting the technology.

1.3 Research question and objective

Building on the preceding discussion, the research question that guides this study is the following: does the prospective integration of blockchain, as it is perceived by the market participants, relate to the perceived stock market efficiency in the Amman Stock Exchange, and is this relationship mediated by the investor trust? In order to answer this question, the primary objective and the specific objectives of the study are formulated as follows.

Although research on blockchain in financial markets has grown, little is known about how blockchain integration influences investor trust and, through it, market efficiency (Lumineau et al., 2021). Accordingly, the primary objective of this study is to examine the mediating role of investor trust in the relationship between perceived blockchain integration and perceived stock market efficiency in the Amman Stock Exchange (ASE). To achieve this aim, the study pursues five specific objectives. First, it examines the direct effect of perceived blockchain integration on perceived stock market efficiency in the ASE. Second, it investigates the effect of perceived blockchain integration on investor trust. Third, it assesses the effect of investor trust on perceived stock market efficiency. Fourth, it evaluates whether investor trust mediates the relationship between perceived blockchain integration and perceived stock market efficiency. Finally, it identifies which dimensions of blockchain integration, transparency, security, decentralization, and efficiency—most strongly influence investor trust and market efficiency.

1.4 The gap

Although the literature on blockchain in the financial markets has grown in a rapid manner, the existing studies have treated the blockchain mainly in the developed markets, such as Tokyo, the United States, and Europe, and they have placed the emphasis on the technical benefits of the technology, namely, the security, the transparency, and the reduction of the transaction costs. However, these studies have neglected, to a large extent, the psychological dimension and the institutional dimension in the emerging markets, where the trust of the investors is fragile and the regulatory infrastructures are weaker. In the case of the Amman Stock Exchange, which suffers from the information asymmetries, from the shallow market depth, and from the volatility, the prospective integration of blockchain does not necessarily carry the same meaning that it carries in a mature market. Therefore, the gap that is addressed by the present study is not a claim regarding the realized effects of blockchain on the market efficiency, but rather it is a perception-based and behavioral gap, and it consists in the limited understanding of how the market participants in an emerging market perceive the prospective adoption of blockchain, and of how these perceptions are related to the trust and to the perception of the quality of the market.

1.5 Contributions

Accordingly, the present study does not merely add a further case study to the literature, and it advances the literature in a number of respects. First, the study integrates the psychological dimension, and it is represented by the investor trust, as a mediating mechanism within the prospective adoption of blockchain in a developing market, and it is a dimension that the prior literature has considered only in a limited manner. Second, the study develops and tests an empirical dual-pathway model, in which the perceived blockchain integration is related to the perceived market efficiency both in a direct manner and in an indirect manner through the investor trust. Third, the study provides evidence from the Amman Stock Exchange, and it is a representative emerging market in the MENA region, and it thereby extends the geographical scope of the literature beyond the developed markets. Fourth, the study derives implications for the regulators and for the administrators of the exchanges regarding the sequencing of the technological deployment and the building of the trust.

1.6 Scientific and professional interest

The interest of this study is, on the one side, scientific, and, on the other side, professional. From the scientific side, the study contributes to the theory of the trust-mediation in the adoption of the financial technologies, and it does so by demonstrating, at the perceptual level, the mechanism through which the favorable perceptions of the attributes of blockchain are related to the trust and, through the trust, to the perception of the efficiency of the market in an emerging-market setting. From the professional side, the study offers guidance to the administrators of the exchanges and to the regulators, and it suggests that the security-related features and the communication that builds the trust should be prioritized in the early phases of any prospective deployment, in order to strengthen the favorable perceptions of the participants of the market.

1.7 Structure of the paper

The remainder of this paper is organized as follows. Section two presents the review of the literature, and it is divided into the empirical review and the theoretical framework, from which the hypotheses of the study are derived. Section three describes the methodology of the research, and it includes the design, the population and the sampling, the measurement of the variables, and the specification of the model. Section four reports the results, and it includes the descriptive statistics, the assessment of the measurement model, and the assessment of the structural model. Section five presents the discussion of the results, and it confronts them with the findings of the prior literature. Finally, section six presents the conclusion, and it includes the theoretical implications, the practical implications, and the limitations, together with the directions for the future research.

2 Literature review

2.1 Empirical review

This section reviews the empirical literature in a critical manner, and it does not present the prior studies as a simple juxtaposition, and it rather places their results in tension with one another. On one side, several studies report clear benefits of the blockchain, such as the reduction of the counterparty risk and the improvement of the post-trade processes, while, on the other side, other studies emphasize the practical limitations that appear at the stage of the implementation, such as the case of the Tokyo Stock Exchange. As for the emerging markets, the empirical evidence remains scarce, and it is on this point that the review identifies the gap, that is, the absence of studies that link the blockchain, the trust, and the efficiency within a single empirical framework, and particularly in the developing markets such as the Amman Stock Exchange.

2.1.1 Blockchain technology in financial markets

Fintech is the debutant but growing headache in the financial market, which aims at making processes for executing transactions and record keeping fundamentally different, without blockchain technology. According to Nakamoto (2008), blockchain can be defined as a distributed and decentralised ledger that chronologically records transactions across network of several computers, and records cannot be manipulated or retroactively altered without the approval of the network. Compared to traditional centralised systems, architecture of this kind offers much better security, transparency and immutability (Tapscott and Tapscott, 2017).

The blockchain applications in the financial markets range from the cryptocurrencies to smart contracts, automated clearing and settlement and transparent ownership records (Yermack, 2017). There are studies that have pointed out the potential benefits of capital markets via integration with blockchain (Alamaren, et al., 2026). Disintermediation was shown by Collomb and Sok (2016), following which there is reduction of transaction costs, and by Mendling et al. (2018) that process transparency and auditability have been improved. It is shown further by Chiu and Koeppl (2019) that blockchain based settlement systems can mitigate counterparty risk and shorten settlement times in securities trading.

The growing integration of blockchain-based assets into the broader financial system has drawn increasing scholarly attention to their interconnectedness with traditional and sustainable asset classes. Using volatility-spillover and connectedness frameworks, Alamaren et al. (2024) examined the dynamic linkages among leading cryptocurrencies in the market. In a related study, Alamaren et al. (2025) adopted a quantile-connectedness approach to analyze the transmission mechanisms linking Bitcoin with financial market revealing that connectedness intensifies during extreme market conditions.

However, research into blockchain implementation in already established exchanges is still limited empirically. In this research Aoyagi and Adachi (2018) analysed the blockchain initiatives of Tokyo Stock Exchange and found significant improvement in the post-trade process, but also mentioned challenges in implementation of the blockchain. Hawlitschek et al. (2018), on a similar note, studied the Blockchain attributes against their respective market participation, and found out that transparency and security are key drivers of adoption. While these studies contain valuable information, they do not completely delve into how psychological mechanisms impact market results given the blockchain integration.

More recent work has reinforced and extended these findings. Systematic reviews of blockchain in financial services document a rapid maturation from proof-of-concept toward tokenization of securities, post-trade infrastructure, and settlement (Ali et al., 2020). Subsequent studies have examined how distributed-ledger adoption reshapes trust relationships among market participants and intermediaries (Kowalski et al., 2021), while research on the banking and exchange sectors has highlighted persistent organizational and regulatory barriers to large-scale deployment (Saheb and Mamaghani, 2021). These contributions confirm that the value of blockchain in capital markets depends not only on technical capability but also on participant acceptance—an aspect that remains under-examined in emerging-market exchanges such as the ASE.

Taken together, the existing literature presents a mixed rather than a uniformly positive picture, and it is important to distinguish the technical promises of blockchain from the challenges that appear at the stage of implementation. On one side, several studies report gains in transparency, in settlement speed, and in cost reduction, while on the other side a growing body of work warns from unresolved problems of regulation, of governance, of privacy, of scalability, and of interoperability, which constrain the large-scale deployment of the technology in established exchanges. In addition, it is necessary to distinguish between public and permissionless blockchains, permissioned or consortium distributed ledgers that are more common in regulated financial infrastructures, and conventional digital systems that are sometimes described as blockchain without possessing its core properties, because these arrangements differ completely in their implications for trust and for governance. On the basis of this discussion, the gap that is addressed by the present study is not a claim regarding the realized effects of blockchain on market efficiency, but rather a perception-based and behavioral gap, that is, a limited understanding of how market participants in an emerging market perceive the prospective adoption of blockchain, and of how these perceptions are related to trust and to the perception of market quality.

2.1.2 Investor trust in financial markets

A fundamental element in functioning of financial markets is trust, especially in case of uncertainty and risk (Guiso et al., 2008). Eyadat, et al. (2025) investigates the influence of Blockchain technology on reducing cybersecurity risks in financial transactions of commercial banks in Jordan. In financial markets, investor trust encompasses confidence in the fairness, reliability, and integrity of market mechanisms, participants, and regulatory frameworks (Giannetti and Wang, 2016). Consistently, research has shown that higher levels of trust result in a higher propensity to participate in market, lower risk premia and greater efficiency of capital allocation (Sapienza and Zingales, 2012).

However, the determinants of investment trust have been a well studied issue. Nevertheless, institutional factors as regulatory quality, investor protection frameworks and governance mechanisms affect the formation of trust quite strongly (La Porta et al., 2006). Besides, market transparency, quality of information disclosure, and attributes connected to the fairness of the transaction processes generate significant trust building (Pevzner et al., 2015). Trust is also affected by the technological system underlying market operations such as system reliability and security features and quality of user interface (Brosnan et al., 2019).

For instance, trust issues might be of utmost salience in emerging markets such as Jordan where there is lack of institutional strength, information asymmetry, and market volatility (Al-Smadi, 2018). The perceptions of market transparency and the regulatory effectiveness had a significant influence on investor confidence in the Amman Stock Exchange, Al Khouri and Balqasem (2006). Likewise, Saadi-Sedik and Petri (2006) found that trust was one of the major factors that explain the variations in the trading volume of Middle Eastern markets, namely, Jordan.

Recent fintech-adoption research continues to position trust as a central explanatory mechanism. Studies grounded in technology-acceptance and trust frameworks show that perceived security, transparency, and regulatory assurance remain the dominant antecedents of users’ willingness to adopt blockchain-enabled financial services (Kowalski et al., 2021), consistent with the trust-mediation logic advanced in the present study.

2.1.3 Market efficiency in emerging markets

The one fundamental assumption in financial market theory (Fama, 1970) is that security prices reflect all available information, also known as market efficiency. Markets that are efficient allocate scarce resources in the optimum way, discover prices most accurately, reduce transaction costs (Lo, 2004). The other point is that whilst emerging markets typically possess characteristic inefficiencies relating to information asymmetries, illiquidity, weak institutional infrastructure and limited technological infrastructure (Bekaert and Harvey, 2003).

As in many emerging markets, the Amman Stock Exchange has faced efficiency difficulties. Based on the ASE, Al-Jarrah et al. (2011) reported significant deviation from weak-from efficiency and this was attributed to information asymmetry and limited market depth. Maghyereh (2005) reports similar persistence of pricing anomalies in violation of efficient market hypotheses as well. The implication of these inefficiencies is a misallocation of capital, investment choices, and development of the overall economy.

Potential mechanisms for improving market efficiency in emerging contexts have been identified to be technological advancements. In developing exchanges, Brogaard et al. (2014) showed that the implementation of automated trading systems leading to improvement in price discovery processes and market quality. Also, Weber et al. (2019) discovered that the use of electronic trading platforms in the latter (emerging) markets led to more liquidity and lower trading costs. Research on the impact of blockchain to market efficiency, however, is limited and still in its infancy in the context of the Middle East.

2.2 Theoretical framework and hypothesis development

This study integrates technology acceptance theory (Davis, 1989), trust theory (McKnight et al., 2002), and market efficiency theory (Fama, 1970) to develop a comprehensive framework examining relationships between blockchain integration, investor trust, and market efficiency. In integrating these perspectives, the framework treats the perceived attributes of blockchain, namely, transparency, security, decentralization, and operational efficiency, as sources of perceived usefulness and of perceived transparency that shape both technology trust and institutional trust, and it is through this trust that more favorable perceptions of market quality are expected to arise. Accordingly, the efficient market hypothesis is employed only as a conceptual background for defining the dimensions of perceived market quality, such as perceived liquidity, perceived price discovery, and perceived transaction costs, and it is not used as a test of objective informational efficiency, because the study measures perceptions rather than realized market outcomes.

In order to construct the causal mechanism that justifies the empirical model, and not merely to review the prior studies, the theoretical framework draws upon a set of complementary theories. These theories are the Information Asymmetry Theory (Akerlof, 1970), the Efficient Market Hypothesis (Fama, 1970), the Signaling Theory (Spence, 1973), the Agency Theory (Jensen and Meckling, 1976), the Technology Acceptance Model (Davis, 1989), the Institutional Trust Theory (McKnight et al., 2002), and the Behavioral Finance perspective (Barberis and Thaler, 2003). On the basis of these theories, the conceptual mechanism of the study is articulated as follows: the perceived adoption of blockchain is expected to be associated with a perceived reduction of the information asymmetries, and, through it, with a greater perceived transparency and a better perceived quality of the information, and this in turn is expected to increase the trust of the investors, and the increased trust is expected to be associated with a stronger perceived participation and with a better perceived price discovery, and, finally, with a more favorable perception of the efficiency of the market. It should be noted that, because the study measures the perceptions rather than the realized outcomes, this mechanism is framed at the perceptual level, and the hypotheses that are presented in the following sub-sections are derived directly from it.

2.2.1 Blockchain integration and stock market efficiency

There are several features that blockchain technology could supply that would directly increase market efficiency. There can be nearinstant settlement, less intermediaries and work can be automated (Chiu and Koeppl, 2019) which can reduce transation costs. In addition, blockchain’s ability to keep an unalterable record of the who, when, where, and what of everything can also improve the way that information is disseminated, meaning better price discovery is possible (Yermack, 2017).

Starting from empirical evidence, it is observed that blockchain adoption has brought improvement in efficiency of several markets. According to Weber et al. (2019), it significantly reduced post-trade processing time and cost for European securities market. For instance, Aoyagi and Adachi (2018) also recorded benefits associated with faster transaction speed and decreased risk of settlement caused using a blockchain in the Tokyo Stock Exchange. Following these theoretical arguments and empirical findings, we hypothesize the following.

H1 Perceived blockchain integration positively influences perceived stock market efficiency in the Amman Stock Exchange.

2.2.2 Blockchain integration and investor trust

The very distinctive features of blockchain: transparency, immutability, and security, are strongly consistent with the antecedents of trust found in the literature. Transparent transaction recording technology of the technology could reduce the information asymmetry problem being a significant obstacle in the development of trust in financial markets (Lumineau et al., 2021). Furthermore, the cryptographic security of blockchain can also help to strengthen the sense of system reliability and data integrity for strengthening trust creation (Sas and Khairuddin, 2017).

There exist positive relationships between blockchain attributes in different contexts, according to empirical evidence. According to Sadhya and Sadhya (2018), perceived transparency and security of blockchain systems are very significant predictors of trust in cryptocurrency exchanges. Further, Osmani et al. (2020) show that blockchain based verification systems create greater trust than traditional tracking systems in supply chain cases as well. Building on these theoretical foundations and on the evidence, we hypothesize.

H2 Perceived blockchain integration positively influences investor trust in the Amman Stock Exchange.

2.2.3 Investor trust and market efficiency

According to trust theories, increasing levels of trust help to reduce psychological barriers to sharing the market, lead to increase in the volume of intermediary activity, and foster more efficient price discovery (Guiso et al., 2008). Investors rely more on market prices as accurate measure of fundamental value and are more willing to supply liquidity and trade when they trust market mechanisms (Giannetti and Wang, 2016).

It has been proven in previous research that trust is related to certain dimensions of market efficiency. According to Ng et al. (2009), higher trust levels were associated with a decrease in bid-ask spreads and transaction costs in Asian markets. Moreover, Pevzner et al. (2015) showed that trust made the speed of information incorporation into security prices quicker and thus made the informational efficiency better. These theoretical arguments and empirical results provide the basis for our hypothesis.

H3 Investor trust positively influences perceived stock market efficiency in the Amman Stock Exchange.

2.2.4 The mediating role of investor trust

Blockchain technology provides several technical capabilities that could increase market efficiency directly, but the complete realization of these benefits may necessitate acceptance and trust by users in the systems. According to technology acceptance models, the users’ acceptance of technology can be explained, at least in part, to their perception of uselessness and ease of use (Davis, 1989). In the case of financial markets, investor perceptions and trust may be especially important in the process of whether technological innovations lead to an improvement in efficiency.

The findings and literature suggest that trust usually acts as a mediator in the relationships between system characteristics and user behaviors in the financial context. According to Gefen et al. (2003) trust mediated the relationship between website quality features and the intention to buy online. Furthermore, Zhou (2012) proposed that mobile payment system characteristics exerted effects on usage behavior through trust. Following this reasoning, we hypothesize.

H4 Investor trust mediates the relationship between perceived blockchain integration and perceived stock market efficiency in the Amman Stock Exchange.

The theoretical framework posits that blockchain integration may enhance market efficiency both directly through technological mechanisms and indirectly by building investor trust. This dual-pathway model provides a more comprehensive understanding of how technological innovations translate into market outcomes.

3 Research methodology

3.1 Research design

This study uses a quantitative research design based on structural equation modelling (SEM) for the analysis of how blockchain integration is related to investor trust and stock market efficiency. The market participants’ perception of these variables at a given point in time, referred to as a cross-sectional approach, this approach permits the examination of these variables. The research design is useful to hypothesis testing and evaluation of both direct and indirect relationships among variables, which makes it appropriate for studying the role of investor trust as a mediator in the relationship between blockchain and efficiency.

It should be noted that the study adopts, in a deliberate manner, a perception-based measurement approach, and, accordingly, all of the constructs are perceptual by their design, in the sense that they capture the perceptions of the participants of the market and not the realized institutional outcomes. In order to reflect this position in a transparent manner, the title of the study and the labels of the constructs were revised so that they refer to the perceived blockchain integration and to the perceived stock market efficiency, rather than to an observable institutional implementation or to an objective informational efficiency in the sense of Fama (1970). Consequently, the estimated relationships should be interpreted as associations among the favorable perceptions, and they should not be read as the demonstrated effects of an operational blockchain system on the realized efficiency of the market.

3.2 Population and sampling

Investors, financial analysts, stockbrokers and regulatory officials who are part of the active role played in the Amman Stock Exchange (ASE) constitute the target population of the study. Lastly, these stakeholders have hands-on-subject-matter experience with blockchain adoption initiatives in the marketplace to provide informed perspectives regarding these impacts on trust and efficiency metrics. Respondents reported perceptions based on the ASE’s ongoing blockchain-related modernization initiatives; the extent of full deployment remains limited, and constructs should be interpreted as perceptions of an emerging rather than fully operational system. It provides complete insight from different market perspectives by its diversified population.

Then, stratified random sampling techniques are utilized to ensure proportional representation among different stakeholder groups. Participation roles of the participants (retail investors, institutional investors, financial intermediaries and regulators) and levels of experience with blockchain technology provided the sample stratification.

To obtain a sample size of 400 respondents, a power analysis for structural equation modelling and the complexity of the proposed model are used as a basis. As stated by Hair et al. (2019), the minimum sample requirements for SEM analysis are satisfied, and enough to account for non-response. Based on appropriate permissions and ethical considerations, ASE investor databases, brokerage client lists and professional association memberships are used to construct the sampling frame.

With respect to the data-collection procedure, the sampling frame was constructed from the combined records of licensed brokerage client lists, the investor registry that is maintained through the central depository, and the membership lists of the relevant professional associations, and this combined frame was used in order to draw the stratified sample. Within each stratum, the participants were selected through systematic random selection, and the questionnaire was distributed through both electronic and in-person channels. A total of 417 questionnaires were distributed, and after the removal of the incomplete responses, the responses that did not pass the attention and consistency checks, and the responses that contained missing values, 400 usable questionnaires were retained, which corresponds to a valid response rate of approximately 95.9 percent. Missing values were handled through listwise deletion, so that only the complete and the valid cases entered the analysis.

In order to address the requirement that the respondents possess sufficient knowledge to provide informed assessments, participation was restricted to stakeholders with active experience in the Amman Stock Exchange, and a question on familiarity with blockchain technology was included so that the level of familiarity could be measured and reported, as is shown in Table 1. As the distribution in Table 1 indicates, the majority of the respondents reported at least a moderate level of familiarity, whereas a small proportion reported limited familiarity, and this variation is acknowledged among the limitations of the study. This approach made it possible for the analysis to retain the diversity of the market participants, while at the same time making the knowledge base of the sample transparent to the reader.

TABLE 1. Demographic profile.

Bold values indicate the total row for each demographic variable (n = 400; 100%).

3.3 Variables and measurements

3.3.1 Independent variable: Perceived blockchain integration

The conceptualization of blockchain integration is defined as the perceived implementation and usage of blockchain technology in stock market activities. This construct is operationalized using a multidimensional scale adapted from prior blockchain and information-systems research (e.g., Hawlitschek et al., 2018; Sadhya and Sadhya, 2018), capturing four core dimensions. To distinguish blockchain-level efficiency from the study’s dependent variable, one dimension is labeled operational efficiency and refers specifically to perceived transaction speed, cost reduction, and process streamlining at the technology level, as opposed to overall market efficiency. The four dimensions are as follows.

• Transparency: Measured through items that assessed items related to the perceived improvements of transaction visibility, record accessibility, and information disclosure (5 items).
• Security: Measured through items regarding data protection, fraud prevention capabilities, and system integrity (5 items).
• Decentralization: Measured through items measuring perceived dis-intermediation, reduced reliance on central authorities, and distributed control (5 items).
• Efficiency: Measured through items regarding transaction speed, cost reductions, and process streamlining (5 items).

All items are measured on five-point Likert scale (Strongly Disagree one to Strongly Agree 5). Previous literature such as (Zhao et al., 2020) have shown strong reliability (Cronbach’s α > 0.85) of the composite scale.

3.3.2 Mediating variable: Investor trust

Trust in investors in blockchain market mechanisms is operational as an expectation of reliability, security, and integrity of blockchain enabled market mechanisms. According to Guiso et al. (2008), McKnight et al. (2002), this construct is measured through three distinct dimensions based on levels of established trust scales.

• Perceived Reliability: This dimension measures how trustworthy investors consider its functional reliability and accuracy in financial transactions. System dependability, data integrity, manipulation resistance, and information accuracy (5 items).
• Regulatory Confidence: This dimension assesses investors’ confidence in the regulatory and legal regimes for the adoption of blockchain. It gives confidence in regulatory oversight, legal protections, compliance standards and governance mechanisms (5 items).
• Market Stability: This dimension measures the rise of the blockchain investors’ tenement to the extent that the technology creates stability in the entire market and reduces the rate of systemic risk. This dimension concerned with perceptions of uncertainty reduction, fraud prevention, manipulation mitigation and improvements in transparency (5 items).

All items are measured on five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). However, there is evidence of previous similar trust scales obtaining high reliability, highest Cronbach’s α > 0.85 in the financial technology context (Lumineau et al., 2021; Pilkington, 2016).

3.3.3 Dependent variable: Perceived stock market efficiency

Consistent with the study’s behavioral focus, the dependent variable is defined as perceived stock market efficiency, that is, market participants’ perceptions of the extent to which market operations deliver accurate price discovery, adequate liquidity, and low-cost transactions, rather than objective market indicators (e.g., bid-ask spreads, realized volatility, liquidity ratios). This perceptual construct is measured through three dimensions based on Yermack (2017).

• Liquidity: Measured through items related to trading volume, market depth and execution speed (5 items).
• Price Discovery: Measured through items related to information incorporation speed, price accuracy and reduced anomalies (5 items).
• Transaction Costs: Measured through items related to explicit costs (fees, commissions), and implicit costs (bid-ask spreads, market impact) (5 items).

All the items are five-point Likert scale ranging from (1) ‘strongly disagree’ to (5) ‘strongly agree’. Prior studies (Yermack, 2017) proved the good reliability of the composite scale (Cronbach’s α > 0.82).

3.3.4 Instrument development and validation

The measurement instrument was developed on the basis of previously validated scales, and each construct was operationalized through items that were adapted from established sources in the blockchain, the trust, and the market-efficiency literature, as is indicated in the preceding sub-sections (for example, Hawlitschek et al., 2018; Sadhya and Sadhya, 2018; McKnight et al., 2002; Yermack, 2017). The wording of the items was adapted to the context of the Amman Stock Exchange, and the instrument was reviewed by experts in order to assess the content validity, the clarity, and the relevance of the items, after which minor modifications were made in response to their comments. Because the questionnaire was administered in a bilingual setting, the instrument was translated from English into Arabic, and the accuracy and the equivalence of the meaning were verified before the administration of the questionnaire.

3.4 Model specification

This study uses Structural Equation Modeling (SEM) with SmartPLS to examine the relationships between blockchain integration, investor trust, and stock market efficiency. As direct, indirect as well as mediating effects can be tested in complex models, inclusion of latent variables which are measured through several observed indicators as well as handling nonnormal data distributions (a common case in financial market research), SEM is particularly suitable for this research. The structure of the conceptual model is presented in Figure 1.

The direct effect of blockchain integration on stock market efficiency is tested (H1), as well as its direct effect on investor trust (H2). Investor trust’s impact on market efficiency (H3) and its mediating role in the blockchain-efficiency relationship (H4) are also examined.

4 Results

4.1 Demographic profile

The demographic profile of the 400 respondents is presented in Table 1. Most participants were between 26 and 45 years old (65%), with the largest group (34%) in the 36–45 age range. Educational background was predominantly at the bachelor’s level (52%), followed by master’s degree holders (34%). In terms of occupation, retail investors constituted the largest group (43%), followed by institutional investors (21%). The majority of respondents had 6–10 years of experience in financial markets (33%), with over a quarter (27%) having more than 10 years of experience. Regarding familiarity with blockchain technology, most respondents (40%) were moderately familiar, while only 4% considered themselves experts and 9% were not familiar at all.

4.2 Descriptive statistics

Table 2 presents descriptive statistics for all research variables. For blockchain integration, transparency scored highest (M = 4.21, SD = 0.72), followed by decentralization (M = 4.03, SD = 0.78), and efficiency (M = 3.95, SD = 0.69), with security rating lowest (M = 3.84, SD = 0.81). The overall blockchain integration construct showed a high degree of approval (M = 4.01, SD = 0.75).

TABLE 2. Descriptive statistics.

Bold values indicate the overall construct-level scores (Blockchain integration, Investor trust, Stock market efficiency), aggregated across their respective dimensions.

For investor trust, market stability achieved the highest score (M = 3.89, SD = 0.79), followed by perceived reliability (M = 3.78, SD = 0.83), and regulatory confidence (M = 3.52, SD = 0.91). The overall investor trust construct showed a high degree of approval (M = 3.73, SD = 0.84).

Among stock market efficiency variables, transaction costs scored highest (M = 4.08, SD = 0.74), followed by price discovery (M = 3.82, SD = 0.69), and liquidity (M = 3.67, SD = 0.76). The overall stock market efficiency construct showed a high degree of approval (M = 3.86, SD = 0.73).

4.3 Measurement model assessment

4.3.1 Factor analysis

Table 3 presents the factor loadings for all measurement items. All items demonstrated acceptable loadings on their respective constructs, with values ranging from 0.433 to 0.648. According to Hair et al. (2019), factor loadings above 0.4 are considered acceptable for exploratory research. For blockchain integration dimensions, factor loadings ranged from 0.517 to 0.648. For investor trust, loadings ranged from 0.485 to 0.602. For stock market efficiency, ranged from 0.433 to 0.595. It should be noted that all of the latent variables in this study were specified as reflective constructs, and the three focal variables, that is, perceived blockchain integration, investor trust, and perceived stock market efficiency, were modeled as reflective higher-order constructs, in which each higher-order construct is represented by its reflective first-order dimensions and is estimated through the two-stage approach. It is also worth mentioning that a considerable number of the individual loadings fall below the more conventional threshold of 0.70, and although these items were retained because the construct-level reliability and the average variance extracted that are reported in Table 4 remain within the accepted limits, the modest size of the individual loadings is acknowledged as a limitation of the measurement model and is discussed further among the limitations of the study.

TABLE 3. Factor loading.

TABLE 4. Construct reliability and validity.

4.3.2 Reliability and validity assessment

Table 4 presents the reliability and validity metrics for all constructs. Internal consistency reliability was assessed using Cronbach’s alpha and composite reliability. All constructs demonstrated acceptable reliability with Cronbach’s alpha values ranging from 0.724 to 0.840, exceeding the recommended threshold of 0.7 (Nunnally and Bernstein, 1994). Composite reliability values ranged from 0.824 to 0.868, well above the recommended threshold of 0.7 (Hair et al., 2019).

Convergent validity was assessed using Average Variance Extracted (AVE). All constructs demonstrated acceptable convergent validity with AVE values ranging from 0.545 to 0.588, exceeding the recommended threshold of 0.5 (Fornell and Larcker, 1981). This indicates that the constructs explain more than 50% of the variance in their respective indicator variables.

4.3.3 Discriminant validity and collinearity assessment

Discriminant validity was assessed using the Heterotrait-Monotrait ratio (HTMT) as shown in Table 5. All HTMT values were below the conservative threshold of 0.85 (Henseler et al., 2015), ranging from 0.700 to 0.845, indicating good discriminant validity between constructs. This confirms that each construct is empirically distinct from other constructs in the model. With specific regard to the possible conceptual proximity between the operational-efficiency dimension of perceived blockchain integration and perceived stock market efficiency, the Heterotrait-Monotrait ratio between the technology-level Efficiency dimension and Stock Market Efficiency is 0.700, and the ratio between Blockchain Integration and Stock Market Efficiency is 0.706, and both of these values remain below the conservative threshold of 0.85, which provides empirical support that the two constructs are distinct. It should be noted, however, that the operational-efficiency dimension refers to the perceived speed, the perceived cost, and the perceived streamlining of processes at the level of the technology, whereas perceived market efficiency refers to the perceived liquidity, the perceived price discovery, and the perceived transaction costs at the level of the market as a whole, and this conceptual distinction is maintained throughout the analysis, while the possibility of a residual overlap is acknowledged among the limitations.

TABLE 5. Discriminant validity (heterotrait-monotrait ratio).

Multicollinearity was assessed using Variance Inflation Factor (VIF) values as shown in Table 6. All VIF values ranged from 1.076 to 1.412, well below the threshold of 5 (Hair et al., 2019), indicating the absence of multicollinearity concerns in the model.

TABLE 6. Variance inflation factor (VIF).

4.3.4 Common method bias

Because all variables were collected from the same respondents using the same instrument at a single point in time, common method bias (CMB) was assessed using complementary procedures. As the primary diagnostic, a full collinearity assessment was conducted following Kock (2015); all VIF values (1.076–1.412, Table 6) fall well below the conservative 3.3 threshold, indicating that common method variance does not materially bias the structural estimates. Harman’s single-factor test is additionally reported, and no single factor accounted for the majority of the variance; consistent with current methodological guidance, however, this test is treated only as supplementary evidence given its limited diagnostic power. Procedural remedies, including respondent anonymity and the separation of construct items in the questionnaire, were also applied ex ante. Taken together, these results indicate that common method bias is substantially mitigated; nevertheless, as with any single-source, cross-sectional design, it cannot be entirely ruled out, and this residual limitation is acknowledged among the study’s limitations.

4.4 Structural model assessment

Following the validation of the measurement model, this section evaluates the structural relationships between blockchain integration, investor trust, and stock market efficiency. The structural model assessment examines the predictive power, direct effects, and mediating relationships hypothesized in the research framework. Figure 2 presents the results of the PLS-SEM bootstrapping procedure, displaying path coefficients, R-squared values, and factor loadings that illustrate the strength and significance of both direct and indirect relationships among the constructs, providing visual support for the hypothesis testing results discussed below.

4.4.1 Model fit and predictive power

Table 7 presents the R-squared values for the endogenous variables. The model explains 72.1% of the variance in investor trust (R² = 0.721) and 74.2% of the variance in stock market efficiency (R² = 0.742). According to Hair et al. (2019), these values indicate substantial predictive power in the structural model, as R² values above 0.5 are considered moderate and values above 0.75 are considered substantial.

TABLE 7. R-Squared values.

4.4.2 Direct effects

Table 8 presents the results of the direct effect hypotheses testing. Hypothesis H1, which proposed that blockchain integration positively influences investor trust, was supported (β = 0.849, t = 26.031, p < 0.001). Among blockchain integration dimensions, security had the strongest effect on investor trust (β = 0.269, t = 19.941, p < 0.001), followed by efficiency (β = 0.259, t = 17.204, p < 0.001), decentralization (β = 0.247, t = 16.305, p < 0.001), and transparency (β = 0.244, t = 21.529, p < 0.001).

TABLE 8. Direct effects.

Hypothesis H2, which proposed that investor trust positively influences stock market efficiency, was also supported (β = 0.448, t = 8.143, p < 0.001).

Hypothesis H3, which proposed that blockchain integration positively influences stock market efficiency, was supported (β = 0.448, t = 8.147, p < 0.001). Among blockchain integration dimensions, security had the strongest direct effect on stock market efficiency (β = 0.142, t = 7.893, p < 0.001), followed by efficiency (β = 0.136, t = 7.447, p < 0.001), decentralization (β = 0.130, t = 7.478, p < 0.001), and transparency (β = 0.129, t = 7.586, p < 0.001).

4.4.3 Indirect effects and mediation analysis

Table 9 presents the results of the mediation analysis. Hypothesis H4, which proposed that investor trust mediates the relationship between blockchain integration and stock market efficiency, was supported (β = 0.380, t = 7.486, p < 0.001).

TABLE 9. Indirect effects (mediation analysis).

The mediation effect was further analyzed for each dimension of blockchain integration. The indirect effect of security on stock market efficiency through investor trust was significant (β = 0.121, t = 7.458, p < 0.001). Similarly, significant mediating effects were found for efficiency (β = 0.116, t = 7.399, p < 0.001), transparency (β = 0.109, t = 7.794, p < 0.001), and decentralization (β = 0.111, t = 7.217, p < 0.001).

The presence of both significant direct effects (blockchain integration → stock market efficiency) and significant indirect effects (blockchain integration → investor trust → stock market efficiency) indicates partial mediation (Zhao et al., 2020). This suggests that while blockchain integration directly enhances stock market efficiency, a significant portion of this effect is realized through the enhancement of investor trust.

4.5 Summary of hypothesis testing

Table 10.

5 Discussion

The results of this study can be interpreted in the light of the behavioral mechanism that links the perception of the attributes of blockchain to the perception of market quality through investor trust. The finding that investor trust partially mediates the relationship between perceived blockchain integration and perceived stock market efficiency indicates that a part of the association operates through a psychological channel, in which favorable perceptions of transparency, of security, of decentralization, and of operational efficiency strengthen the confidence of the investors in the reliability and in the integrity of the market mechanisms, and this confidence is in turn associated with more favorable perceptions of liquidity, of price discovery, and of transaction costs. This pattern is consistent with the prior research that positions trust as a central mechanism in the adoption of financial technologies (Gefen et al., 2003; Zhou, 2012), and it is also in line with the studies that emphasize security and transparency as the dominant antecedents of trust in blockchain-enabled settings (Sadhya and Sadhya, 2018; Kowalski et al., 2021).

When the present findings are confronted with the findings of the prior empirical literature, a number of points of convergence and of divergence appear. On one side, the strong association that is observed between the perceived blockchain integration and the investor trust is consistent with the studies that document the improvements in the post-trade processes and the reduction of the settlement risk in the developed exchanges, such as the Tokyo Stock Exchange (Aoyagi and Adachi, 2018) and the European securities markets (Weber et al., 2019). On the other side, this favorable perceptual pattern stands in contrast with the studies that emphasize the organizational barriers and the regulatory barriers that constrain the large-scale deployment of the technology (Saheb and Mamaghani, 2021), and this contrast suggests that the expectations of the participants may run ahead of the realized institutional capacity. Moreover, the fragility of the trust and the inefficiencies that characterize the Amman Stock Exchange, and which are reported in the prior evidence on the weak-form efficiency and on the pricing anomalies of the exchange (Al-Jarrah et al., 2011; Maghyereh, 2005), may explain why the perceived trust carries a greater weight in this emerging-market setting than it carries in the mature markets, in which the institutional infrastructures are stronger. Accordingly, the confrontation of the results with the literature reinforces the interpretation of the findings as a perception-based contribution, and it does not support their interpretation as evidence of the realized effects of the blockchain on the efficiency of the market.

At the same time, the magnitude of some of the estimated coefficients, and in particular the very strong association between perceived blockchain integration and investor trust, should be interpreted with caution, and it should not be read as evidence of a large realized effect of the technology on the market. Several alternative explanations may contribute to the size of these coefficients. First, because all of the variables were measured from the same respondents through the same instrument at a single point in time, a part of the observed association may reflect common method variance and favorable response tendencies rather than a purely substantive relationship, and although the full collinearity assessment and the procedural remedies that are reported in Section 4.3.4 suggest that this bias is substantially mitigated, it cannot be entirely excluded. Second, a form of technological optimism may be present, in which the respondents who hold a generally positive attitude toward modernization tend to evaluate all of the constructs in a favorable manner. Third, the familiarity of the respondents with blockchain, which varies across the sample as is shown in Table 1, may influence the strength and the consistency of their assessments. Fourth, the conceptual proximity between some of the perceptual constructs may introduce a degree of construct redundancy that inflates the estimated relationships. For these reasons, the coefficients are best understood as describing associations among favorable perceptions, rather than as demonstrated effects on realized market outcomes.

Finally, it is important to distinguish clearly between the expected benefits of blockchain and the realized outcomes in the market. The present study measures the expectations and the perceptions of the market participants regarding the prospective adoption of blockchain in the Amman Stock Exchange, and it does not measure objective market indicators such as bid-ask spreads, realized volatility, or liquidity ratios. Consequently, the findings describe how favorable perceptions of blockchain are associated with trust and with favorable perceptions of the functioning of the market, and they should be regarded as propositions concerning the potential effects of blockchain, which remain to be tested against objective data once an operational system is in place.

6 Conclusion

6.1 Theoretical implications

This study makes several important theoretical contributions to the understanding of blockchain technology implementation in emerging financial markets. First, the research extends the technology acceptance theory by empirically demonstrating that blockchain integration not only directly influences stock market efficiency but also works through the psychological mechanism of investor trust. This dual-pathway model advances our understanding of how technological innovations translate into improved market outcomes, confirming the importance of user perceptions in technology adoption contexts (Davis, 1989; McKnight et al., 2002).

Second, this study contributes to trust theory in financial markets by identifying specific technological attributes—transparency, security, decentralization, and efficiency—that build investor trust. The findings reveal security as the strongest predictor of investor trust (β = 0.269), highlighting the critical importance of robust security measures in blockchain implementations for financial markets. This aligns with previous research emphasizing security concerns as a primary barrier to blockchain adoption (Sadhya and Sadhya, 2018).

Third, the research advances market efficiency theory by empirically validating the role of trust as a significant mediator in the blockchain-efficiency relationship. The substantial mediation effect (β = 0.380) supports the proposition that enhancing market efficiency requires not only technological solutions but also addressing psychological barriers to market participation (Guiso et al., 2008; Giannetti and Wang, 2016).

6.2 Practical implications

The findings offer several practical implications for market regulators, exchange administrators, and policymakers. First, the strong association between perceived blockchain integration and perceived stock market efficiency (β = 0.448) indicates that market participants hold favorable expectations regarding the modernization agenda of stock exchanges, particularly in emerging markets like the Amman Stock Exchange. The results should not be read as evidence that such investments will necessarily yield tangible improvements in market efficiency, and any realized gains in transaction processing, in price discovery, and in liquidity remain propositions that should be tested once an operational system is in place.

Second, the identification of investor trust as a significant mediator highlights the need for comprehensive implementation strategies that address both technological and psychological aspects. Market authorities should complement technological deployment with targeted communication and education campaigns to build investor confidence in blockchain systems. The relatively lower score for regulatory confidence (M = 3.52) compared to other trust dimensions suggests that strengthening regulatory frameworks and clearly communicating governance mechanisms should be prioritized.

Third, the differential impact of blockchain dimensions provides guidance for implementation sequencing. Security features showed the strongest association with both investor trust and perceived market efficiency, suggesting that robust security measures should be prioritized in early implementation phases to establish a foundation of trust. Transparency features, which received the highest approval rating (M = 4.21), should be emphasized in market communications to leverage existing positive perceptions.

6.3 Limitations and future research directions

This study is intentionally positioned as a foundational, perception-based examination of the blockchain–trust–efficiency mechanism in an emerging market where objective blockchain-era market data are not yet available. We acknowledge that a survey-based PLS-SEM design cannot establish causality or capture realized market outcomes. Future research should triangulate these perceptual findings with objective market indicators (bid-ask spreads, liquidity, volatility), adopt longitudinal or event-study designs around actual implementation milestones, and use experimental or mixed-method approaches to strengthen causal inference.

Several limitations of this study present opportunities for future research. First, the cross-sectional design captures perceptions at a specific point in time, limiting causal inferences. Future studies could use longitudinal designs to track changes in investor trust and market efficiency as blockchain implementation progresses, providing stronger evidence for causal relationships. Relatedly, because all constructs were measured from the same respondents using a single self-report instrument, the design is exposed to common method bias. Although the full collinearity assessment, Harman’s test, and procedural remedies (Section 4.3.4) indicate that this bias is substantially mitigated, it cannot be entirely eliminated; future work should incorporate temporal or source separation, marker variables, or objective market data to further reduce this concern.

Second, while the sample size was adequate for PLS-SEM analysis, the geographic focus on the Amman Stock Exchange limits generalizability. Comparative studies across multiple emerging markets with varying levels of blockchain adoption would enhance external validity and identify contextual factors affecting the blockchain-trust-efficiency relationship.

Third, this study focused primarily on investor perceptions rather than objective market efficiency metrics. Future research could triangulate perceptual data with objective market indicators (e.g., bid-ask spreads, liquidity ratios, price volatility) to strengthen empirical connections between blockchain implementation and market performance.

Finally, future studies could explore additional mediating variables beyond investor trust, such as market participation levels, information dissemination speed, or trading behavior changes, to develop a more comprehensive understanding of the mechanisms through which blockchain enhances market efficiency.

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Footnotes

Edited by: Rim El Khoury, Lebanese American University - Byblos Campus, Lebanon

Reviewed by: Marjori Klinczak, Unifatec PR, Brazil

A.Jagdish Mohan Rao, KLEF Deemed to be University, India

Gilles Brice Mbakob, University of Douala, Cameroon