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This study investigates the relationships between Supply Chain Collaboration, Risk Management Strategies, Supplier Development, Trust, and Supply Chain Resilience in the Jordanian retail sector. This research aims to analyze the direct impacts of these Supply chain management practices on resilience, as well as mediating effect Trust in between this relation. The study used quantitative data to collect the data from 291 managers and executives in the Jordanian retail sector. The findings suggest that Supply Chain Collaboration and Risk Management Strategies have positive significant effects on Supply Chain Resilience, while Supplier Development has no direct significant effect. The results show that each of the supply chain management practices has significant positive effects on Trust and, therefore, significantly contribute to increasing Supply Chain Resilience. In addition, Trust is identified to play a mediating role in the relationships between trust on both SCMPs and resilience. This paper extends the existing literature on supply chain resilience and provides empirical insights into significant factors that shape in enhancing resilience within the retail trade industry, notably focusing on Jordan. The implications for managers, practitioners and society suggest that collaborative relationships, effective risk management strategies as well trust building initiatives are vital to increase resilience among supply chains. This research is unique as it thoroughly investigates the collaboration between SCM practices, relational variables and resilience in an understudied context providing a new understanding of the interplay of different antecedents at play on resilient supply chains creation.

There are challenges Jordanian Islamic banks face in maintaining and enhancing their competitive advantage in a rapidly evolving and increasingly competitive market. This paper aims to examine the factors that affect Jordanian Islamic banks towards competitive advantage, in addition to examining the roles of strategic intelligence and organizational creativity in enhancing Jordanian Islamic banks' competitiveness. However, this paper relied on the descriptive analytical approach, and the study population included general manager, department manager, branch manager, head of department based on Banks structures and annual reports from 2018 to the end of 2023. A stratified random sample was used, approximately 243 questionnaires were examined. The results indicated that organizational creativity and strategic intelligence play a crucial role in building competitive advantage. Also, organizational creativity contributes to achieving superiority by creating an innovative organizational environment, while strategic intelligence reflects the ability to make smart decisions that enhance competitive effectiveness. This paper also demonstrated the importance of managing and harnessing information effectively in order to enhance strategic intelligence. However, this paper contributes to the understanding of success factors in Islamic banking and provides actionable insights for managers navigating the complexities of the banking sector, emphasizing the importance of innovation, differentiation, and strategic decision-making for sustained growth and competitiveness.

Within the context of the financial industry, the purpose of this research is to investigate the influence that management of scope, time, cost, and quality has on the performance of projects and business overall performance in the financial sector. Following the collection and examination of the study materials, a total of 331 samples were deemed appropriate for analysis by means of the PLS software. According to the findings, the implementation of scope, time, cost, and quality management has a direct and beneficial impact on the enhancement of project performance in the organization that deals with financial matters. As an additional point of interest, the project scope has a favorable impact on the performance of the project through the implementation of work breakdown structure, project scope definition, and scope change control. The formulation of a timetable, the estimation of the duration of activities, and the critical path analysis are all ways in which project time can have an impact on the performance of the project. Additionally, the cost of a project has an impact on the performance of the project through the processes of cost estimation, budgeting, and cost control. And finally, project quality effects positively on project performance and business overall performance through Based on the findings, it appears that the successful management of these four knowledge domains greatly improves the outcomes of the project. To be more specific, Scope Management ensures that the company's goals are aligned with the expectations of the organization, Time Management assists in meeting deadlines, Cost Management optimizes budgets, and Quality Management guarantees that high standards are maintained. Based on the findings of the study, it is concluded that combining these areas results in higher project performance, highlighting the crucial importance of these areas in projects involving the financial industry.

Artificial Intelligence (AI) techs help businesses turn internal and external data into real gold by analyzing customer data, extracting valuable insights, and offering individual solutions. The current study aimed to identify the mediating effect of artificial intelligence and digital experience on the relationship between neuromarketing (emotional appeal and memory encoding) and consumer behavior. The current study was applied to consumers within the MENA region by using an online questionnaire self-administered by (837) individuals. The study hypotheses were all accepted, and results confirmed that there is a mediating effect of AI and digital experience (DX) on the relationship between neuromarketing (emotional appeal and memory encoding) and consumer behavior. The degree to which digital experiences can modulate the association between emotional appeal, memory encoding, and consumer behavior, is not absolute; other factors and external cues that may be integral parts of a seller's marketing campaign remain relevant as well. The marketing strategy, quality of the product, prices, and effect of the enclosing environment influence consumer behavior from the digital dominion. Consequently, the comprehensive study of the digital situation is the premise of comprehending as well as using the mediating influence of digital experience on a consumer's mind. The study supports the idea that it is crucial for digital experience to bring up good feelings and provide opportunities for better information memory. Building visualizations that are appealing, interactive, and immersive to the users is intended to keep them interested and promote remembering. Through this approach, information on the brand can be associated with, recalled, and can become a significant decisive factor in future purchase decision-making.

The Indonesian government currently focuses on high infrastructure development to prepare for connectivity between one city and another. The massive construction of the new government capital is also called the archipelago's capital. This condition impacts companies supporting construction projects, which are growing rapidly. This growth is supported by corporate governance and the cash-holding industry, which supports infrastructure projects for the company's financial performance. This research aims to determine the role of cash holding and corporate governance (board skill, independent director, managerial ownership) on the financial performance of infrastructure-supporting manufacturing companies in Indonesia. The sample used in this research was 83 manufacturing companies listed on the Indonesia Stock Exchange in the 2010-2020 period. This research uses panel data regression as a data analysis method. The results of this research show that managerial ownership significantly impacts increasing cash holding by maintaining the optimization of cash and cash equivalents. The company's managerial ownership cannot impact board skills because many companies still need to accommodate share ownership by management and board-skill-educated doctors. This condition also causes board size skills not to impact increasing cash holding in the company. Board skills have yet to be able to impact financial performance significantly. Managerial ownership and cash holding impact increasing return on assets, thereby increasing financial performance for manufacturing companies that support infrastructure projects. The independent director, as a variable moderator, still needs to be capable of moderating managerial ownership, board skill, and cash holding to improve financial performance. This condition is caused by data from several companies still needing more independent directors. Research provides a practical contribution to the owner as soon as possible, recruiting board members with doctoral education as competent board skills and making independent directors have a vital role in improving financial performance. The theoretical contribution to research is to enrich the theory of corporate governance and financial performance.

This study investigates the impact of internationalization barriers on the export performance of Jordanian small and medium-sized enterprises (SMEs). The aim of this study is to investigate how the export performance of SMEs in the furniture industry is influenced by external and internal barriers and what significance these have for international performance. Based on a quantitative research design, data was collected from 318 small and medium-sized Jordanian companies through a survey. Partial least squares structural equation modeling (PLS-SEM) examined the impact of external barriers, including political, economic, legal and socio-cultural challenges, as well as internal barriers, such as financial, management and market-related barriers, on export performance. However, most barriers - whether internal or external - are domestic and have a greater impact on export performance than barriers from abroad. This study enriches RBV theory in relation to the internationalization of small and medium-sized enterprises by providing evidence that firm-specific resources and capabilities are key factors for SMEs both when they face export barriers and when they achieve better performance in foreign activities. The findings provide practical implications for managers, policy makers and practitioners interested in the internationalization of Jordanian SMEs. An important limitation is the cross-sectional design, one-country context, and self-report in survey research. Future studies are recommended to use a longitudinal design, mediating and moderating mechanisms. This study is innovative as it involves a combined investigation of firm-external and firm-internal export barriers and their effects on the internationalization success of Jordanian SMEs.

This study investigates the impact of various IT tools on project management efficiency within the public sector, specifically examining the mediating role of team communication quality. The study utilized a quantitative approach, data was collected from 197 public sector organizations across Jordan, Saudi Arabia, and Lebanon. The study employed PLS-SEM to analyze the relationships between project management software, communication platforms, collaboration tools, team communication quality, and project management efficiency. The findings confirm that project management software, communication platforms, and collaboration tools each positively influence project management efficiency. Moreover, the study reveals the crucial mediating role of team communication quality. Specifically, the positive impact of these IT tools on project management efficiency is significantly channeled through their ability to enhance team communication. These findings underscore the importance for public sector organizations to not only invest in diverse IT tools but also to prioritize initiatives that foster effective team communication to maximize project success and overall organizational efficiency.

This study investigates the ways in which collaboration may provide a competitive advantage in global marketing through focused strategy, differentiation, and cost leadership. The study uses Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyze data and present a comparative analysis of separate and combined strategic approaches. The result of the study implies that differentiation is the main factor influencing the variation in collaborative competitive advantage, which accounts for the largest percentage of explained variance (R² = 0.729). Whereas the combined model also shows a high level of explanatory ability (R² = 0.693). The path coefficient shows that differentiation, focused strategy, and cost leadership have a positive impact on competitive advantage. The integrated model also shows significant indirect effects, highlighting the benefits of combining several strategies. These results suggest that in order to optimize resource allocation and enhance market positioning, firms should adopt a comprehensive approach that incorporates many techniques. This study contributes to the existing research in strategic management by emphasizing the importance of a cohesive strategy in sustaining a competitive advantage in the fast-evolving digital marketing field.

Organizations are increasingly acknowledging the vital impact of talent management on boosting their performance. Effective talent management within the central bank is crucial, as it plays an indispensable role in maintaining economic stability and advancing the nation’s financial well-being. The study aims to examine the role of talent management, transformational leadership, organizational climate, employee engagement, employee performance, and organizational commitment in increasing the central bank’s performance. The study uses a quantitative approach by collecting data from 600 sample employees of Bank Indonesia in 30 divisions of departments at the head office, 45 domestic representative offices, and 5 foreign representative offices. The data was analyzed using Structural Equation Modelling-LISREL. The finding shows that transformational leadership has a positive impact on talent management. Talent management has a positive impact on organizational climate, employee engagement, and organizational commitment. Organizational climate has a positive impact on employee engagement. Employee engagement has a positive impact on organizational commitment. Organizational climate, employee engagement, and organizational commitment have a positive impact on employee performance, while talent management does not have a positive impact on employee performance. Employee performance, organizational commitment, and talent management have a positive impact on organizational performance. The study offers valuable insights into talent management practices within central banks. It serves as a guide for central bank management and human capital professionals in formulating policies to enhance performance amidst disruptive times. Additionally, educators can leverage these findings to develop curricula that align more closely with industry demands and produce competent graduates ready to excel on the global stage.

The research investigated the relationship among Key Performance Indicators (KPIs), risk assessment capabilities and value creation in service sector firms. The study also sought to examine the effect of KPI`s components on risk assessment & value capitalisation, and how they either facilitate or hinder implementation, monitoring and continuous improvement processes. In this context, a quantitative cross-sectional research design was applied using an online survey of shared middle and senior managers in service organizations. After filtering, the final version of segmented sample included a total of 215 respondents engaged in different service businesses. The analysis was determined using Partial Least Squares Structural Equation Modeling. The results showed that all components of KPIs have significant positive relationships with risk assessment and value improvement outcomes First, performance drivers were found to be the most significant predictor of both constructs. As such, the results show that both risk assessment and value improvement had a positive effect on implementation/monitoring processes which in turn enabled continuous improvements. Performance measurement, risk management and value creation in service organizations: A performance at-risk-based conceptual model. The results have numerous managerial, practical and policy implications for the service sector. This drives home the necessity of creating integrated KPI systems that include risk assessment and value improvement factors. In building on existing theory, the study is of substantial interest in that it provides empirical evidence for these organizational mechanisms related to service organizations. Resilient Organizations in the Service Sector picture of Resilience across Performance Management with KPIs, Risk Assessment and Value Creation strategies offering a comprehensive foundation for sustainable organizational success.

This study investigates the critical role of IT infrastructure and project flexibility in achieving project success within the financial sector. Based on resource-based theory and the dynamic capabilities perspective, we propose a conceptual model wherein IT infrastructure influences project success both directly and indirectly through its impact on project flexibility. Data collected from 190 financial sector professionals were analyzed using PLS-SEM. Our findings provide strong support for all hypothesized relationships. Specifically, we find that IT infrastructure has a significant positive impact on both project success and project flexibility. Furthermore, project flexibility is found to mediate the relationship between IT infrastructure and project success, indicating that a robust IT infrastructure contributes to project success, in part, by fostering greater project flexibility. These findings indicate the strategic importance of IT infrastructure investments for financial institutions seeking to enhance project outcomes in a rapidly changing and increasingly competitive landscape.

A multi-objective Flexible Job-shop Scheduling technique for hospitals is proposed using DPSO-AIW i.e. discrete particle swarm optimization with adaptive inertia weight method. The approach encodes the layer of the chromosomes using an operation sequence (OS) and machine assignment (MA) which is a two-layer coding structure. Global selection based on the operation (GSO) of MA and random selection of OS are coupled in the initial population. Rapid non-dominated sorting yields fronts of non-domination, which are necessary for getting the Pareto optimum solution. The diversity of the population is increased during the evolution process by adaptive adjustment of the variation of the weight of inertia, expressed by ω. Then, the Pareto optimal solution found during the process is kept in the Pareto optimal solution set (POS). The discrete particle swarm optimization algorithm is utilized to solve the values of the next generation chromosomes in the discrete domain directly. Lastly, comparisons with certain current techniques and numerical simulation based on two sets of international standard examples are performed, which are already established. The findings from the comparison show that the suggested DPSO-AIW is practical, effective, and more feasible for solving the problem related to the Multi-objective Flexible Job-shop Scheduling Problem.

To effectively manage the challenges associated with meeting schedules, costs, and quality requirements in construction projects, it is crucial to address potential risk factors. Despite extensive research on risk management in construction, a significant gap persists concerning the uniformity of risk factors and their effects across various construction project types, geographical locations, and cultural contexts. This research presents a structured three-step approach to risk management, covering risk identification, analysis, and response. The methodology is applied to both the General Construction (GC) and Banking Construction (BC) sectors in Egypt, involving industry professionals through surveys. Quantitative analysis using the Relative Importance Index (RII) and Fuzzy-set theory gauges the influence of each risk factor, while Spearman Ranked Correlation tests differentiate risk profiles between sectors. A comparative analysis highlights Egypt-specific risk factors versus regional or global factors. Key risk factors with high centrality scores are identified, and optimal risk reduction strategies are selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The study reveals significant sector-specific risk differences and highlights the need for tailored risk management strategies. Key contributions include identifying vital risk factors, comparing them globally and regionally, and proposing effective mitigation strategies to enhance project timelines, costs, and quality.

This study investigates the impact of different leadership styles on project success, specifically examining the mediating role of team collaboration. This study utilized a diverse sample of 202 respondents representing five distinct national contexts: Jordan, Saudi Arabia, China, Australia, and the United Arab Emirates. PLS-SEM were employed to analyze the relationships between transformational leadership, transactional leadership, laissez-faire leadership, team collaboration, and project success. Our findings reveal that both transformational and transactional leadership styles are positively associated with project success. Conversely, laissez-faire leadership demonstrated a negative relationship with team collaboration but did not directly predict project success. Importantly, team collaboration was found to mediate the relationship between both transformational leadership and project success, as well as between transactional leadership and project success. However, the hypothesized mediating role of team collaboration between laissez-faire leadership and project success was not supported. These findings underscore the critical role of leadership style and team collaboration in achieving project success, offering valuable insights for organizations and project managers seeking to optimize leadership practices and foster collaborative work environments.

The high quality of public services is a guarantee for the public of easy and efficient access. Good quality public services can help increase people's productivity, reduce unnecessary bureaucracy, and encourage more active participation from all walks of life. In addition, government transparency serves as the main basis for building a relationship of mutual trust between the government and society. Through the application of information and communication technology, E-Government allows the government to provide public services more efficiently, quickly and easily. This research aims to analyze the influence of information technology, administrative management, and knowledge management practices on the success of E-Government. This type of research is quantitative research using a questionnaire. Respondents were selected using a random sampling method from various groups in the public sector in the DKI Jakarta province. A total of 380 questionnaires were distributed to respondents, and 264 questionnaires were successfully returned. However, there were 21 questionnaires that were not filled in completely. Finally, 243 questionnaires were analyzed further. Questionnaire measurements used a Likert scale of 1 - 7. The data in this study were analyzed using SmartPLS 4 software. The results of this study conclude that the implementation of information technology has a significant relationship with knowledge management practices. However, the relationship between information technology and e-government in this study was not proven to be significant. Administrative management has a significant relationship with knowledge management practices but has no significant effect on E-Government. Knowledge management practices have a significant influence on E-Government and there is interaction between information technology and knowledge management practices, as well as between administrative management and knowledge management practices on E-Government.

This study explores the factors affecting CliQ payment service adoption in Jordan as it represents a major shift in the Jordanian market to Fintech and mobile marketing. This study presented a distinctive model by integrating the “unified theory of acceptance” and the “technology acceptance model” TAM with the “use of technology UTAUT” to measure the behavioral intention of consumers and the satisfaction of the users towards utilizing the CliQ service. The study measured the linkage between four predictors (perceived usefulness, social influence, perceived ease of use, and financial risk) as well as both utilizers’ intention to CliQ service usage and utilizers’ satisfaction with using the service, along with observing the association between these predictors to determine their contribution to the users’ satisfaction mediated by the users’ intention to utilize the service mentioned above. A survey instrument was distributed to 604 respondents, and it was developed and validated by academics, as a pilot test. As well as a pre-test. Hypotheses were tested with multiple linear regression analysis using SmartPLS software to interpret path coefficients, and reliability and validity within the outer model were tested through correlation analysis. Additionally, internal consistency was explored by applying Cronbach’s alpha. The outcomes proved that the predictors significantly affect both utilizers’ behavioral attitudes and satisfaction with using the CliQ service, except for financial risk. The data analysis also indicated a significant indirect influence of all the independent variables on utilizers’ satisfaction through behavioral intention to utilize the CliQ service, except for financial risk, which had an insignificant indirect influence on utilizers’ satisfaction through behavioral intention for service usage. The findings of the current article close the gap found in the literature concerning measuring usability to enhance user satisfaction and adoption of Fintech services. Therefore, bank managers and policy planners can find insights for developing and improving mobile banking apps.

This study provides an analytical view of the correlation between several factors that influence the credibility of information available through various sources on the Internet. The most critical factors include information quality, source credibility, argument strength, message credibility, and average credibility. Additionally, the study explores the impact of gender and years of experience as demographic variables on the nature and size of these relationships. The study relied on a critical review of previous related literature. In addition, it adopted an analytical approach using a sample of 300 Internet users through a questionnaire designed based on the study hypotheses. Most of these relationships were found to be at an average level, except for the relationship between source credibility and information credibility. No statistical indicators were observed. Consequently, the researchers acknowledge the need for caution when generalizing these results to society. The study also found that the gender of the recipient and the number of years of experience did not necessarily play a mediating role in the relationship between the tested factors and the credibility of information received via the Internet.

This research investigates how social media content marketing impacts customer engagement and it gives more weight to consumer cognition as an intermediary means. According to the study, digital communication has transformed significantly in our modern era, from simple communicative and content-sharing platforms to social media networks evolved into major marketing platforms. Organizations now fundamentally bring about transformations in their interaction with consumers depending on how they choose to use these public forums. As well, this paper begins to provide a comprehensive review of the social media content marketing literature, with topics such as augmented reality, credibility of content, user-generated content, and customer perceptions. The paper has a survey sample of 350 managers from relevant organizations, selected to provide a broad representative range across fields and industries. This study, under the Technology Acceptance Model, aims to understand better, how consumers accept and employ social media content marketing. Research questions to be addressed in this forthcoming paper include an investigation into how consumer belief serves to mediate the relation between social media content marketing and customer engagement Additionally, it aims to investigate the extent to which consumer cognition intervenes in this link, and whether consumers' beliefs moderate results of an interaction with social media platform contents source (such as reading a blog or watching a video). With this theoretical framework and the related literature, the project aims to provide significant insights and make a more successful marketing practice.

Social Networking Sites (SNS) play an important role in human psychological well-being. This research explores the effects of perceived overload on the passive usage intention of SNS among Malaysian users through SNS fatigue and anxiety by employing a Cognition-Affect-Conation (C-A-C) model. Cross-sectional survey research was carried out and the research acquired responses from 383 SNS users. Data was analyzed through PLS-SEM. The outcomes noted that perceived cognitive overload, perceived information overload, SNS fatigue, and anxiety are positive antecedents of SNS passive usage intention. The research brings valuable insights into the formation of passive usage intention of SNS and provides implications for service providers and users.

The purpose of this study is to explore how various online marketing tools, including Content Marketing, Email Marketing, Social Media Marketing, and SEO, affect customers' decisions to purchase Internet services. The study utilized a survey distributed through simple random sampling, with 410 questionnaires given to Zain Telecom customers in Zarqa city. After excluding incomplete questionnaires, 385 were analyzed using multiple regressions, descriptive analysis, and reliability tests. Results showed that all independent variables had a significant impact on customers' purchasing decisions of Internet services, with Email Marketing having the strongest relationship. The study recommends further investment in Email Marketing strategies to improve customer retention and acquisition.

Regulators and recent academics are now paying attention to digital marketing because it has become a complete marketing resource that might propel a firm toward success. As a result, the current study explores the impact of several digital advertising channels, including mobile, e-mail, and digital retargeting, on customer purchasing behavior in the Information Technology (IT) business in the UAE. The current research also examines the moderating effects of marketing tactics at the intersection of mobile advertising, digital retargeting, e-mail marketing, and customer purchasing choices in the IT sector of the UAE. To collect data for this study quantitatively, questionnaires were employed to solicit information from respondents, which was then analyzed using smart-PLS. The findings showed that digital retargeting, mobile, and e-mail marketing positively affect customer purchasing behavior in the UAE's IT sector. The results also demonstrated that marketing tactics drastically reduced the associations between mobile, e-mail, and consumer purchasing decisions in the UAE's IT sector. This study gave policymakers recommendations on better focusing on digital advertising, which could boost the organization's success.

The rapid progress of TICs has generated different ways to modify and transfer information, which implies the generation of new forms of knowledge. The objective of this study is to establish the relationship between digital competencies and university teaching performance in public higher education in Huancayo. The study is of a basic type with a quantitative approach and correlational level, developed with the partition as a sample of 272 teachers and 387 students who develop teaching-learning activities at the UNCP. The data were analyzed and modeled through structural equations based on PLS. The research arrived at the following results: a value of 0.890 in Spearman's Rho correlation coefficient and a significance level of .000, which shows that there is a high positive relationship between the study variables; likewise, the hypothesis is accepted. general which considers that there is a significant relationship between digital competencies and teaching performance in the classroom.

The study aimed to evaluate how cloud technology implementation would affect Jordanian industrial businesses' financial statements' integrity across a range of variables (financial condition, income, cash flow, owners' equity). The investigation involved employees from financial and internal audit departments, including various job titles. A random sample of 150 questionnaires was distributed among the study population, with a 96% response rate (145 retrieved). Respondents were scored using a Likert five-point scale on the 44-paragraph questionnaire. To accomplish its goals, the study used a descriptive-analytical methodology and statistical techniques such as path analysis (using AMOS) and simple linear regression analysis (using SPSS). According to the study, the implementation of cloud accounting has a statistically significant effect on the quality of financial statements by Dimension (statement of financial position, income statement, statement of cash flows, and list of equity), according to the study. Applying cloud accounting has a statistically significant effect on the internal control system, and the internal control system has a statistically significant impact on the accuracy of financial statements. Furthermore, cloud accounting has a statistically significant impact on the quality of financial statements in Jordanian industrial companies through the internal control system as an intermediate variable. The study made several recommendations in light of the earlier findings, the most significant of which are: determining the internal control system's current state both before and after cloud accounting was implemented; creating and executing a robust internal control system compliant with international accounting standards; and assessing the suitability of cloud accounting solutions through thorough evaluations. The report also emphasized how crucial it is to set up ongoing audit and internal control systems to evaluate how well the internal control and cloud accounting systems are working together.

In the ever-evolving landscape of supply chain management, the quest for efficiency has become paramount. This abstract explores a groundbreaking solution that combines the power of permissioned blockchain technology with innovative data reduction strategies to redefine how supply chains operate. Traditional supply chain systems often grapple with data overload, causing delays, inaccuracies, and operational inefficiencies. However, this abstract presents a promising approach that unleashes efficiency by harnessing the capabilities of a permissioned blockchain. Through data reduction techniques tailored to the needs of supply chain management, this approach streamlines the flow of information while maintaining security and trust among participants. This paper seeks into the technical foundations of permissioned blockchains, highlighting their suitability for supply applications where confidentiality and controlled access are imperative. Furthermore, it examines various data reduction methodologies, emphasizing their role in minimizing redundant data, optimizing communication, and enabling real-time decision-making. The impact of this innovative approach on supply chain stakeholders is profound. It reduces data related bottlenecks, enhances transparencies, and fosters collaboration among participants. Additionally, it provides a scalable framework adaptable to diverse supply chain ecosystems. As supply chain efficiency becomes increasingly important in our interconnected world, this permissioned blockchain-driven data reduction strategy offers a compelling vision for the future. It promises to unlock a new era of streamlined operations, cost savings, and improved customer satisfaction, ultimately shaping the next generation of supply chain management.

A Distributed Denial of Service (DDoS) attack occurs when an attacker tries to disrupt a network, service or website by flooding huge numbers of packets on the internet traffic. Detecting DDoS attacks serves the goal of spotting and addressing them promptly to reduce their effects on the network, system or service being targeted. Detecting Distributed Denial of Service (DDoS) attacks is crucial, for people, companies and network managers. The detection of DDoS attacks has ranging uses in industries such as network security safeguarding websites, managing cloud services ensuring the security of online systems and services. Detecting DDoS attacks is essential for safeguarding infrastructure upholding service availability and guaranteeing the security of online systems and services. To achieve this objective, we proposed a framework to detect DDoS attacks including six steps. In step one, we start by gathering information, which includes network activity and system records, for operations as well as instances of DDoS attacks. Step two, we identify characteristics of the data collected such as patterns in network traffic, packet details, IP addresses, types of protocols used and more. Step three, we utilize algorithms for feature selection such as Salp Swarm Algorithm (SSA), Gray Wolf Algorithm (GWA), Particle Swarm Algorithm (PSO) to pinpoint the features that can distinguish between normal activities and DDoS attack patterns. After that in step four, we divide the processed dataset into sections for training and testing purposes to develop and assess the machine learning models such as SVM (support vector machine), and KNN (K-nearest neighbor). Step five we develop a classification model using machine learning techniques like decision trees, forests, support vector machines (SVM) logistic regression models or neural networks. Finally, we assess the effectiveness of models through metrics such as accuracy rates, precision levels, recall rates, and F1 scores. The results show that the proposed models achieve high results (99.9%). In summary detecting DDoS attacks is crucial for protecting networks, systems and online services against disruptions.

The increasing amount of IoT devices increases the size of network traffic data, causing an increase in the incidence of security breaches in IoT networks. Cybercriminals have developed malware to compromise the security of sensitive data, among other cyber threats. In the presence of inadequate and robust security mechanisms, sensitive data is prone to vulnerability. Hence, protecting data in the IoT environment is becoming a mandatory task. Various approaches have addressed malware detection using network data features. However, there is still room for improvement in developing superior techniques and utilizing more comprehensive datasets. This paper presents a novel lightweight ensemble voting classifier to detect malware traffic by deploying the best possible network data. The merits of the correlation coefficient and Opposition-Based Crow Search Algorithm (OCS) have been leveraged to compute the best possible features. Another advantage of this proposed experiment is its focus on a dataset tailored to malware traffic features. This focus enables highly accurate malware detection. After feature selection using OCS, the proposed malware classifier is trained and validated with both 5-fold and 10-fold cross-validation techniques. The tested results confirm that the presented malware classifier performs best using a minimal feature set, which is highly advantageous for IoT networks due to resource constraints.

This research aims to analyze the sustainability challenges in small and medium-scale enterprises in Indonesia, focusing on marketing orientation, social media marketing, and three domains of business performance, namely economic, social and environmental aspects. Data from 238 respondents in Pekalongan, Central Java Province, Indonesia, were analyzed using the SEM-PLS method. These findings support six hypotheses revealing the impact of marketing orientation on various aspects of business performance (economic/social/environmental) and the influence of social media marketing on economic, environmental, and social dimensions. The results have significant implications for SMEs in Indonesia. The findings highlight the need for improvement in sustainability practices, such as increasing alignment between marketing orientation and social media marketing strategies.

This study investigates the mediating role of competitiveness in the relationship between FinTech adoption and banking performance in the Middle Eastern region. A quantitative research design is employed, utilizing survey data from banking professionals across multiple countries. The data is analyzed using PLS-SEM modelling. The results show a positive and statistically significant impact of FinTech integration on the competitiveness of financial institutions and the performance of banks. On the other hand, the mediation of competitiveness is involved in the process of FinTech adoption and bank efficiency, suggesting that banking institutions that can utilize FinTech advantageously have greater chances of translating the benefits of FinTech adoption into better performance. This study supports the literature by providing a practical example of the use of FinTech as a factor for competitiveness and improving the performance of banks in the Middle East. These findings have huge managerial and practical implications and can help large banks gain competitive advantage and effectively integrate FinTech platforms to achieve real improvements. The value of this research is that it fills the gap in the existing literature, i.e. the role of competition as a mediating factor. By combining studies on competitive strategy approaches with those on technological innovation theory, this study combines a complete worldview related to the performance of banks in the digital age.

A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by using quantitative research design as a methodology. The results of hypothesis testing give strong evidence supporting the positive and significant correlations between the proposed hypotheses and the efficiency of data management recovery. This study finds that the presence of a data center in an organization demands the development of a solid plan for the most effective usage of a software program to handle data recovery.

This research aims to analyze the influence of e-leadership behavior on employee commitment at the immigration office, the influence of the e-Work Environment on employee commitment at the immigration office, and the influence of e-Job satisfaction on employee commitment at the immigration office. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between two or more variables. In this way we can build a theory that functions to predict and control a phenomenon. The population in this study were all immigration office employees. In this research, an analysis model is used, namely Structural Equation Modeling (SEM). The respondents for this research were 678 immigration office employees who were determined using a simple random sampling method. Research data was obtained by distributing online questionnaires via social media. The instrument used in this research uses a Likert scale 7 scale. The data analysis stage of this research is testing the outer model and inner model. The outer model test consists of convergent validity, discriminant validity and composite reliability and the inner model test, namely hypothesis testing or significance testing. The results of data analysis show that e-leadership behavior has a positive and significant relationship to employee commitment at the immigration office, the e-Work Environment has a positive and significant relationship to employee commitment, and e-Job satisfaction has a positive and significant relationship to employee commitment at the immigration office.

The COVID-19 pandemic has led to different health outcomes, including long COVID (LCo) and mental health (MH) disorders, impacting millions globally. To enable early healthcare diagnosis, including the prediction of MH conditions and LCo, various research studies have utilized machine learning (ML) techniques. However, there is still a gap in understanding the mental health of recovered COVID-19 patients with long COVID using ML techniques. This study aims to bridge this gap by developing and evaluating ML models, including support vector machine, multilayer perceptron (MLP), k-nearest neighbor, gradient boosting, voting classifier, and extreme gradient boosting, tailored for mental health and long COVID datasets from recovered COVID-19 patients. Additionally, feature selection methods, e.g., Recursive Feature Elimination (RFE) and Extra Trees (ET), and optimized models with hyper-parameter tuning will be employed. Our experiments utilize the dataset of recovered COVID-19 patients. Among these ML models, the MLP with ET-based features achieved the highest accuracy and AUC scores in this dataset, with 1.00 and 0.97 ± 0.02, respectively. The research reveals the high prevalence and risk factors of mental health disorders and long COVID from the dataset. These findings will contribute to personalized healthcare strategies for individuals navigating the complexities of post-COVID-19 recovery, integrating machine learning insights into mental health and long COVID support.

Information and Communication Technologies (ICT) affect all aspects of our daily lives. Using them is considered a symbol of modernization and social advancement. The global expansion and interconnection of ICT offers a significant opportunity to promote the advancement of humanity, bridge the digital gap and promote the growth of societies built on knowledge. In this study, we analyzed and identified the most influential factors in the adoption of ICT in education from the data set called “Final Survey-Digital Inclusion Teachers” of the Plurinational State of Bolivia, which consists of 871 instances and 189 columns. We performed feature selection by carefully combining the results of three feature selection methods: filter (chi-square, ANO-VA and mutual information), wrapper (RFE) and intrinsic (Classification And Regression Trees, Random Forest, Gradient Boosting and XGBoost). The results demonstrated that a teacher's motivation for curricular planning that includes ICT, teaching experience and the institutional environment are key factors in the adoption of these technologies in education. Furthermore, we identified that the Random Forest algorithm is the most appropriate for analyzing and predicting the adoption of ICT in education, we affirmed this after this algorithm obtained the highest values in four of the six metrics evaluated: a sensitivity of 77.7%, an F1 Score of 77.9%, a Cohen's Kappa coefficient of 60.8% and a Jaccard Score of 64.3%. These results suggest that Random Forest is the most effective algorithm to analyze the factors related to the adoption of ICT in educational environments.

Online grocery shopping has emerged as a prominent choice, significantly accelerated by the COVID-19 pandemic. This study delves into the factors impacting customer satisfaction in the realm of online grocery shopping, focusing on the mediating influence of perceived risk. The research, conducted with a sample size of 462, employed a convenience sampling technique for data collection. The data analysis was performed using Excel, SPSS, and Structural Equation Modeling (SEM) through AMOS. The findings reveal that perceived product quality plays a pivotal role in positively and significantly influencing customer satisfaction within the online grocery shopping sphere. Conversely, perceived convenience, while positively correlated, exhibits insignificance in impacting customer satisfaction. Furthermore, this study highlights the existence of full mediation between perceived convenience and customer satisfaction, mediated by a variable, as evidenced by the non-zero values in the range of .040 to .105. This research underscores the importance for businesses engaged in online grocery retail to prioritize convenience as an essential element to enhance customer satisfaction.

This study examines the extent of adoption of electronic payment methods in Jordanian banks and compares them with traditional alternatives. Focusing on banking customer behavior, we conducted a comprehensive survey among banking customers to uncover insights on trust, perceived benefits, financial literacy, ease of use, security and cost considerations. By analyzing the data collected using the questionnaire study tool, we reveal the motivations behind customers’ electronic payment preferences. By highlighting these factors, our research contributes to the understanding of the evolving payment landscape and provides actionable insights to enhance the adoption of electronic payment in Jordan’s financial system, in line with global technological trends. The results of the study revealed that all study variables had a significant impact (trust, ease of use, perceived security, and cost of service) on the use of electronic payment methods. In addition, gender, number of years of dealing with the bank, and type of electronic payment used more than once by customers in the banking sector did not have a significant impact.

Using the frameworks of the Theory of Use and Gratification (UGT) and the Unified Theory of Acceptance and Use of Technology (UTAUT2), this study explores the factors that influence individual behavior and behavioral goals in the adoption of digital banking. Partial Least Square-Structural Equation Modeling (PLS-SEM) is used in the analysis of research data using the program SmartPLS 3.2.9 professional. There are 432 people in the research sample that filled out questionnaires. The results show that behavioral intentions are strongly influenced by the integration of UGT-UTAUT2 by 60.3%. Performance and effort expectations are influenced by cognitive needs, effort expectations are influenced by affective needs, and social influence is impacted by social needs. Behavioral intentions for the use of digital banking are shaped by a combination of factors such as price value, hedonic motivation, habits, facilitating conditions, and effort expectations. The relationship between behavioral intentions, affective and cognitive needs is mediated by effort expectations. In the context of using digital banking, habits and behavioral intentions are important factors that influence behavior; in contrast, cognitive needs, affective needs, performance expectations, and social influence have no direct effect on behavioral intentions.

Globalization entails manufacturing companies improving their competitiveness to be superior to competitors. This study investigates the role of ERP implementation in improving business performance through supply chain integration, external supply chain integration, and flexibility. The research surveyed manufacturing companies that were implementing ERP technology adequately. Data was collected from 99 manufacturing companies in East Java that have implemented ERP. The study used judgmental sampling with criteria for employees who have worked for two years and permanent employees and have a role as a critical user or end user of one of the ERP modules in the company department. Data analysis used SmartPLS software version 4.0. The results showed that ERP implementation enhances internal supply chain integration by 0.708, external supply chain integration by 0.491, and supply chain flexibility by 0.244. By responding quickly to interdepartmental needs and integrating systems between functions, internal supply chain integration affects external supply chain integration by 0.373, supply chain flexibility by 0.249, and business performance by 0.196. External supply chain integration affects supply chain flexibility by 0.445 and performance by 0.360. Moreover, supply chain flexibility, described by the flexibility of employee working hours as needed, on-time product delivery, and production processes, impacted business performance by 0.378. The study results provide practical contributions for corporate information technology managers to invest in upgrading ERP software and hardware to maintain integration with a single database in making quick and appropriate decisions. A theoretical contribution to increase competitiveness with supply chain strategy and technology integration.

This study attempts to study the impact of the moderating role of internal audit between cloud accounting and limiting creative accounting practices in commercial banks. The study utilized a descriptive and analytical approach. The target population of this research consists of all employees of the 13 Jordanian commercial banks listed on the Amman Stock Exchange, while the number of employees in commercial banks is (22,407) employees. This led to the use of a simple random sample of (400) employees. The results found that there is a positive effect of the moderating role of internal audit on the impact of cloud accounting on reducing creative accounting practices in commercial banks. The study suggests that future studies should give recommendations and proposals to improve and develop cloud accounting and internal auditing in commercial banks, increase transparency, monitoring and compliance in accounting and financial operations, and reduce the risks associated with cloud accounting and creative accounting practices.

This research focuses on studying the effect of using social media platforms on customer behavior and business objectives in Jordan. The research chose three of the most famous platforms of social media and those platforms are Facebook, Instagram, and Twitter. By using a quantitative model this research collected around 350 research questionnaires using digital surveys designed by using Google drive and distributed online on previous social media platforms. The research analysis process is executed by using AMOS software, and this comprised structural equations (SEM) modeling and regression analyses. The research study output found strong effects and relationships between social media platforms engagement and a variety of consumer expenditure variables, including brand loyalty, product suggestions, and purchase decisions. Important components of each platform, including user interaction, influencer endorsements, and content relevancy, were also identified by the study as having a direct effect on consumer behavior. The research also showed how businesses may achieve their marketing objectives, boost customer engagement, and enhance their reputation by utilizing social media strategies. The significance of social media website platforms in shaping consumer behavior and propelling business success is highlighted by these studies. To reach their goals and have the most influence on customer decisions, businesses should think about using platform-specific features and investing in targeted social media advertising.

The main objective of this research was to find out how well cloud computing works for teaching kids in the early grades to think critically. Participants in the study were a group of early childhood students from schools in the Mafraq Governorate. The duration of the trial was set at one month. Sixty students participated in the study; thirty were randomly assigned to the experimental group and thirty to the control group. Following the intervention, the experimental group performed better than the control group on tests measuring reasoning, interpretation, analysis, and assessment skills. Both in the follow-up assessment and in the time immediately after the intervention, the experimental group and the control group did not vary from one another in terms of critical thinking skill scores.

The research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.

The main objective of this study was to examine the effectiveness of a teaching program utilizing cloud computing in enhancing the writing skills of students with autism. The research comprised a group of kids diagnosed with ASD who attended schools situated in the Al-Mafraq Governorate. The initial intention was for the experiment to last for a duration of 30 days. A total of 30 students were included in the study, with 15 students randomly assigned to the experimental group and the remaining 15 students assigned to the control group. Following the implementation of the intervention, the experimental group demonstrated a higher level of performance on assessments measuring language and content abilities compared to the control group. There were no significant differences seen in the writing proficiency scores of the experimental group, both at the follow-up assessment and immediately after the intervention.

Despite certain advancements, the incorporation of artificial intelligence in universities is still inadequate. The requirement for students will continue for a while, although the development of artificial intelligence-based chatbots in schools has limited the role of students. The research aimed to assess the willingness of Jordanian learners in higher education to use artificial intelligence-powered chatbots for instructional purposes. The present research suggests nine hypotheses derived from the UTAUT2 model to assess students' desire to use artificial intelligence-based chatbots in learning. The pupils' information was gathered and examined using PLS-SEM. The research results showed that nine hypotheses were confirmed. The outcomes indicate that learners are interested in adopting artificial intelligence-based chatbots into their studies. The research's findings will supply administrators at higher education with valuable insights into the effectiveness of artificial intelligence-based chatbots in learning. Moreover, the findings will help developers of artificial intelligence-based chatbots, higher learning administrators, and legislators execute artificial intelligence-based chatbots that fulfil modern educational requirements.

The purpose of this study is to investigate the moderating role of digital marketing strategies on innovation through Artificial Intelligence (AI) mediating impact in Small and Medium Enterprises within Saudi Arabia. Advanced analytics tools analyzed data from KSA SMEs to establish the role of AI, customer behavior, and experiences in product and process innovation. Artificial intelligence boosts product and process innovation with unconventional customer knowledge. Integrating AI combined with digital marketing to improve decisions and efficiency, to increase understanding of customer dynamics for sustaining growth and promoting collaborations. Using AI-empowered digital marketing strengthens Saudi SMEs advancement by promptly reacting to market motions. Sustainability practices attract the environmentally conscious consumer. This research provides actionable insights for SMEs who want to employ digital marketing and AI strategies and contribute to building an economic environment in Saudi Arabia.

Customer satisfaction is the bedrock of e-commerce. This study identifies the factors and consequences of the perceived flow of consumers with shopping websites. The research scrutinizes the association linking purchase intentions arising from customer satisfaction, website quality and perceived flow by incorporating the model of Stimulus Organism Response. The data were collected from online shoppers using purposive sampling targeted through social media. The data from 270 respondents have been analyzed using SmartPLS incorporating the Partial Least Square-Structural Equation Modeling. The assessment showed an important beneficial impact of website usability, their security, functionality, and privacy features on the perceived flow of customers. Furthermore, perceived flow has been found to affect customers’ purchase intentions as well as satisfaction, and lastly, purchase intention is induced by how satisfied customers are with their shopping experience. The findings identify how important perceived flow functions in enhancing purchase intentions and customer satisfaction online. The findings can be noteworthy for online businesses and banks to improve online shopping experience and transactions.

Human resources that are of high quality create a competitive advantage for companies, thus Human Resource Management (HRM) and High-Performance Work Systems (HPWS) that are good become key success factors that need to be considered by every company. This study aims to investigate the influence of Human Resource Management (HRM) and High-Performance Work Systems (HPWS) on Information Technology (IT) Performance and Competitive Advantage of a company. The method used in this study is a quantitative approach with a questionnaire as the data collection method. The research sample consisted of 191 supervisors, managers, and executives of manufacturing companies located in Medan, Indonesia. Data analysis was conducted using SmartPLS 4.0 software. The results showed that Human Resource Management significantly affects IT Performance but does not directly affect Competitive Advantage. Meanwhile, HPWS Capability does not affect IT Performance but significantly affects Competitive Advantage. IT Performance significantly affects Competitive Advantage. IT Performance also mediates the relationship between Human Resource Management and Competitive Advantage. However, it is not significant in mediating the relationship between HPWS Capability and Competitive Advantage. These findings underscore that Human Resource Management (HRM) and High-Performance Work Systems (HPWS) play pivotal roles in shaping Information Technology (IT) performance and competitive advantage within companies, thus impacting the overall success and sustainability of companies.

With flexible learning, students are actively engaged in their own education and are held to high standards of performance. Online academic courses make it easier for students to receive personalized education because they provide students with more flexibility to concentrate on what is most important to them and give them greater control over their own education. This study’s objective was to investigate whether there is a correlation between how well students succeed in online classes and the extent to which they make use of the schedule and the geographical and resource flexibility offered by such programmes. This article uses a developing approach for predicting and classifying the flexibility in online learning of students who are at risk of failing due to academic and demographic variables. The K-nearest neighbours (KNN) method, the random forest (RF) method, and the logistic regression method were used to categorise the students participating in flexible online learning. The information for the dataset came from Kaggle, and it was gathered for use in testing machine learning. The dataset had a total of 1,875 instances representing 11 different features. Also, accuracy, precision, sensitivity and f-score metrics were applied to evaluate the system. The results show that the RF algorithm has a high accuracy percentage of 85%. The empirical findings demonstrate that students formed distinct patterns of learning time, location and access to knowledge. This suggests that flexibility was used to a significant degree. Patterns in learning time and the availability of learning materials were shown to have a substantial relationship with the accomplishments of the students. Understanding flexibility use habits may help adapt lessons and boost collaboration among similar students.

In the digital era the research study discusses the role of government policy, negative emotions and digital trust in cyber violence, therefore this research adds to the literature and provides references regarding the important role of government policy on cyber violence is very limited. This research aims to investigate the relationship between digital distrust and cyber violence, and the relationship between government policy and cyber violence. The research method used in this research is associative research. Associative research is research that aims to determine the relationship between the hubs of two or more variables. In this way, we can build a theory that functions to predict and control a phenomenon. The population in this study were all students who had studied using e-learning or digital platforms. In this study, the number of respondents was 543 high school students throughout Indonesia. The sampling technique used in this research is nonprobability sampling. In this research, the data collection method used was the questionnaire method. The instrument used to measure this research variable is a 5-point Likert scale. Data processing in this research uses SmartPLS software. The stages of data analysis in this research are the outer model test which includes convergent validity, discriminant validity and composite reliability as well as inner model analysis, namely hypothesis testing. The results of this research are that digital distrust has a positive and significant relationship to cyber violence, negative emotions have a positive and significant relationship with cyber violence, and government policy has a positive and significant relationship with cyber violence. This research adds to the literature and provides references regarding the important role of government policy, digital distrust, and negative emotions in cyber violence. Indonesia, the government needs to implement and evaluate new regulations related to cybercrimes. The government must establish new regulations to combat cybercrime.

The evolution of technology and the widespread adoption of smart mobile devices like smartphones and tablets have significantly altered tourists' behavior using tourism services. Based on The Unified Theory of Acceptance and Use of Technology, this research aims to investigate the factors affecting Gen-Y's inclination to use tourism apps in Vietnam. The model was tested using structural equation modeling (SEM) in quantitative methodology with 337 users from Vietnam. The result showed that five factors positively impact the intention behavior of using mobile tourism applications: performance expectancy, effort expectancy, social influence, trust, and perceived security. Moreover, the findings propose practical implications and provide valuable insights for tourism app developers, marketers and operators in developing more effective tourism apps.

In this digital era, all human activities have moved towards digital. The digital era has provided significant changes in all aspects of life, one of which is the educational aspect. Digital technology has opened up new education opportunities but also presents challenges that must be faced. Almost all sectors, including education in the industry 5.0 era, have digitized, namely by utilizing sophisticated information technology. Era Society 5.0, is an era that will make it easier for human life to interact and transition to the digital era. Thus, the use of digital technology for every aspect of life, especially the education sector, is very necessary since it will reflect the level of competitiveness of a country. This research aims to analyze the relationship between e-learning and performance, digital leadership and performance, and the relationship between digital innovation and performance. This type of research uses quantitative research methods. The population in this research is all high school teachers who have used e-learning platforms and have carried out digital innovation. The sampling technique used in this research was a simple random sampling technique and the total sample of respondents from this research was 489 teachers. The type of data used in this research is primary data and the data search tool used is an online questionnaire using a Likert scale. The data analysis is to use structural equation modelling. The results show that e-learning had a positive and significant relationship with performance, digital leadership had a positive and significant relationship with performance and digital innovation had a positive and significant relationship with performance.

The increasing popularity of intelligence systems in accounting and auditing domains has led to the interest towards drivers of blockchain technology adoption. Consequently, this empirical study inspected the antecedent constructs with direct and indirect impact on blockchain technology adoption in the accounting domain. Data were gathered from 346 accountants employed in Information technology (IT) companies, through an online survey. Structural equation modeling with Smart PLS 4 was employed for research model testing. Out of thirteen proposed direct hypotheses, twelve were accepted. Mainly, the obtained empirical results confirmed effort expectancy impacting blockchain technology adoption the most. Furthermore, the obtained results also confirmed the mediation role of effort expectancy and performance expectancy.