This paper examines the role of vision as a mediating variable of the relationship between organizational factors and IoT adoption in audit firms in the US. Using a combination of analyses based on structural equation modeling (SEM) and artificial neural network (ANN) technology as the primary research methodology. Seven hypotheses were accepted, including one related to the impact of vision on IoT adoption. In general, all accepted hypotheses had a positive effect on IoT adoption. In addition to the direct positive impact of vision on IoT technology adoption, the magnitude of that effect varied depending on the context of each hypothesis. Drawing evidence from the results, this study demonstrates that vision was a partial mediating variable in the relationship between the organizational factor and IoT adoption. As a result, the model can help audit firms adopt IoT technology successfully. On the other hand, it makes essential recommendations for implementing IoT technology in light of the role that vision plays as a mediating variable in this model. The Technology-Organization-Environment (TOE) framework and Diffusion of Innovation theory (DOI) are combined with the vision to improve model predictive power.

Despite its potential to significantly improve the efficiency, effectiveness, transparency, and accountability of construction sector services, the implementation of digital government transformation in many countries has often failed to achieve desired results due to low user adoption. This study introduces a factor model to predict technology readiness and acceptance behavior in the implementation of digital government transformation within construction business licensing and procurement services by integrating the Technology Readiness and Technology Acceptance Models. Survey data collected from construction companies, experts, project managers, and procurement committees in Indonesia were used to test the model through Structural Equation Modelling (SMART-PLS). The findings reveal that positive technological readiness has a significant impact on perceived usefulness and users' intention to use the system. Additionally, it was discovered that a one-point increase in the intention to use led to a 0.625 increase in achievement value. This research contributes to addressing the slow adoption of digital government transformation by exploring intention-to-use behavior in the construction sector.

Failure in digital marketing strategies implementation in building information modeling (BIM) adoption has been observed among some interior design firms. The impact of digital marketing on BIM system adoption among interior design companies was examined in this descriptive analytical research. The research also examined the credibility of BIM system adoption and how the system moderates credibility in the relationship between digital marketing strategies and BIM system adoption. A conceptual model comprising digital marketing strategies (content marketing, social media, and search engines) as independent variables impacting information modeling system adoption as a dependent variable was proposed. The moderating effect of credibility in the relationship between digital marketing strategies and BIM system adoption was examined. Data were gathered through questionnaires delivered online to 300 selected study participants via Google Forms. Usable data from 250 participants and the study hypotheses were analyzed using Structural Equation Modeling (SEM) with Partial Least Square (PLS). The results showed a significant impact of digital marketing strategies (content marketing, social media, and search engines) on BIM system adoption. It also emphasized the moderation of the role of credibility in the relationship between digital marketing strategies (content marketing, social media and search engines). This study can help Jordanian interior design companies to make optimal use of digital marketing strategies (content marketing, social media, and search engines) to adopt the BIM system to increase profits.

This study established and empirically validated a model for predicting factors influencing users' behavioural intentions for using XBRL tools. This study explored the behavioural intention of using XBRL tools from the point of view of users by applying the UTAUT model with the addition of trust and satisfaction. An online survey was conducted by using the modified study model to comply with the research objectives. An online survey of 267 respondents obtained and analysed using structural equation modelling (SEM) and IBM SPSS AMOS. The findings show that trust and satisfaction influenced behavioural intent significantly and positively. In turn, the effort expectancy and performance expectancy had a significant impact on satisfaction. The results showed that in the presence of satisfaction there was no direct effect of effort expectancy and performance expectancy on the behavioural intention to use XBRL tools and the emergence of a direct effect of confidence on the behavioural intention to use XBRL tools. The findings correspond with the previous studies and provide a practical reference for XBRL tool developers and decision-makers involved in developing and using XBRL tools for tagging and analysing financial reporting.

The role of information technology (IT) during the Covid 19 pandemic has made everything in business easy. The role of technology in business during a pandemic also makes it easier for entrepreneurs to navigate buying and selling activities and services. Technology makes it easy to shorten time saving business costs, as in business financial records that make one financial report must record everything manually with technology done automatically with the help of accounting software. Research purposes to test resources-based view theory in relation to the implementation of IT to produce operational performance and financial performance of small and medium enterprises (SMEs). The research was conducted on SMEs in Bali. The research method used to answer the research objectives uses a quantitative test approach Partial Least Square. Based on data analysis, it was found that the development of SME IT Adoption had an effect positive on IT Assimilation, but directly IT Adoption is not able to improve operational performance and financial performance. IT assimilation can improve the operational performance and financial performance of SMEs. Operational performance is not able to mediate the effect of IT adoption on the financial performance of SMEs. IT assimilation is a fully mediating variable in the relationship between IT and the operational performance and financial performance of SMEs in Bali. The results of the study show that IT resource management through a technology-based business competency model can succeed in realizing Organizational Capability that can be used to build business competitiveness if the organization or business unit that adopts it pre-determines IT integration in accordance with the vision, mission, and goals of the organization. This is very important to implement in an effort to adapt to uncertain business world conditions, such as when Covid 19 occurred.

The purpose of this study is to determine the effect of the Technology-Organization-Environment (TOE) on e-business adoption and the impact of e-business adoption on the value chain of Small and Medium Enterprises (SMEs). The study uses a quantitative approach where the respondents are 389 SMEs that use e-business in Indonesia. Partial Least Square - Structural Equation Modeling analysis is used in this study to analyze data and test hypotheses. The study results describe that technology, organization, and environment significantly influence the e-business adoption of SMEs. Furthermore, e-business adoption has a substantial impact on the value chain of SMEs. The study provides an overview of SMEs in Indonesia to determine the factors used as references in e-business adoption and how good e-business adoption will add value to businesses, especially in the value chain.

The objective of this research is to determine the factors that can effectively predict adoption of mobile commerce in Nigeria. In doing this, 192 questionnaires were analyzed using Smart PLS-SEM. While majority of previous studies revealed negative relationship between perceived risk and system usage, the result of this study however indicated a positive relationship with mobile commerce adoption especially with the incorporation of perceived fun that tends to make mobile commerce platforms to be enjoyable. The study provides further insights into how perceived risk and fun can be used to increase the rate of adoption of mobile commerce by coming up with policies that can be used to improve the platform while marketability of mobile commerce can be enhanced.

Small and Medium Enterprises (SMEs) play a major role in most developing countries because they are able to improve and develop the economy. e-Commerce is also an important topic in vari-ous research fields as it brings about benefits to these countries. However, the adoption of e-Commerce by SMEs in developing countries is low due to several factors. Therefore, a parsimony framework has been proposed to investigate the factors which influence the adoption of e-Commerce among SMEs in West Malaysia. Three factors are considered in this research, namely Perceived Barriers, Organization Readiness, and Competitor Pressures. Questionnaires were used for data collection while SmartPLS was used to analyze the data. The results showed that Perceived Barriers contain negative significant influence on the adoption of e-Commerce among medium-sized SMEs, but not for small-sized SMEs. Organization Readiness shows a huge difference between small and medium-sized SMEs. Competitor Pressures are important for both small and medium-sized SMEs. In conclusion, the results obtained will assist and enable stakeholders to restructure e-Commerce applications which fulfill the needs of their organization and therefore, increase the effectiveness of the organization.

While many small and medium enterprises (SMEs)recognize the benefits of Big Data Analytics (BDA) for digital transformation, they face challenges in implementing this technology, highlighting the need for more research on its adoption by SMEs. The objective of this study is to amalgamate the Technology Organization Environment (TOE) framework with the Diffusion of Innovation (DOI) theory, aiming to dissect the factors that sway BDA adoption in Jordanian SMEs. Additionally, the study delves into how perceived usefulness impacts this adoption process. Utilizing structural equation modeling, the study examined data from 388 managers in Jordan. The study validates all its hypotheses, revealing that variables like relative advantage, compatibility, complexity, top management support, competitive pressure, and security influence perceived usefulness, which subsequently has a positive impact on BDA adoption. This research presents a range of theoretical and practical insights.

As time passes, social media, which was formerly used as a means of communication between users, is experiencing a transition as a means for broadcasting information, conducting business, advertising, and even political campaigning. In elections, social media is also used to discredit political opponents to reduce the electability of opposing candidate. Spreading hate speech and fake news to undermine the electability of opposing candidate is a common violation of the law committed by supporters of one candidate over another. Considering that the number of social media users increases annually at a very rapid rate, the hazard of social media abuse has the potential to grow. In 2022, Indonesia had 191 million social media users in January 2022. Obviously, this will make the election situation more tumultuous and has the potential to cause societal divisions. The government must have a control system in place to screen social media content that can be considered illegal. In this study, fake news and hate speech are classified using the Bidirectional Gated Recurrent Unit (BiGRU). Lastly, K-Prototype was used to do clustering based on categorization dimensions and probable distribution to identify which clusters had the greatest risk of breaking the law, creating confusion, and dispersing broadly throughout society. It is hoped that the clusters that are created will represent the levels of priority of tweet data that requires prompt attention from the government to prevent it from spreading and inciting social unrest. Based on the results of the analysis, the BiGRU fake news model yields a F1-score of 95%, while the BiGRU hate speech model yields a F1-score of 90%. Clustering data using K-Prototype in this research can reduce the number of tweet data from 13,183 to 1,791 data. These new data are considered as a priority that must be pursued in preventing social media disputes.