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.

The IoT ecosystem faces increasingly complex security challenges due to the rapid growth of global IoT devices. Security risks related to device identification and credential compromise are on the rise, especially with the proliferation of IoT devices in various aspects of life. This research highlights the need to address these vulnerabilities through the development of robust security protocols, aiming to create a more secure IoT ecosystem and enhance user trust in this technology. The objective of the research is the development of an innovative IoT security protocol; High-Accuracy Device Identification and Resilience Against Credential Compromise (HADIRACC). This paper contributes significantly to enhancing the security and reliability of the IoT ecosystem. The research methods employed encompass the development of security protocols, the development of a proximity-based solution, and the classification of IoT devices using data processing techniques and machine learning-based classification. This study involves the collection and pre-processing of datasets, training different classifiers using 70% of the dataset, and testing the classifiers using the remaining 30%. The proposed protocol can effectively enhance the security of IoT devices by addressing various scenario-based attacks. Furthermore, the results of the analysis of the five classifiers used in this study indicate that Random Forest has the highest F1 score accuracy, reaching 88.8%. This suggests that Random Forest, as a classifier, can make the most accurate predictions compared to other classifiers.

In recent years, E-Commerce has experienced a very significant increase. E-commerce provides a broad overview of technology, processes and practices that can be carried out without using paper as a means of transactions. E-commerce can be a solution to the paper waste problem which is an environmental issue that can lead to social problems. Thus, e-commerce has a vital role in achieving business sustainability performance. E-commerce has had a big influence on the social and economic growth of today's society. Business management's ability to manage financial information is an important indicator in influencing Micro, Small and Medium Enterprises’ (MSME's) business performance. Good managements’ financial literacy equips MSMEs with knowledge and skill empowering MSMEs to make informed financial decisions, manage resources effectively and promote sustainable development. This research aims to analyze the relationship between E-Commerce and the sustainability performance of MSMEs and analyze the relationship between financial literacy and its positive and significant relationship with the sustainability performance of MSMEs. The research method uses a descriptive method with a quantitative approach. The population in this research are MSMEs managers in Indonesia who have comprehensive knowledge regarding the operations and performance of MSMEs. In this study, researchers used a simple random sampling technique with a sample size of 478 MSME managers. Data analysis in this research uses the Partial Least Square (PLS) technique which is an alternative method based on the variance of the variables used. The stages of data analysis are validity testing, reliability testing and hypothesis testing. The independent variables in this research are e-commerce and financial literacy, while the dependent variable is MSME sustainability performance. The results of this research show that e-commerce has a positive and significant relationship with MSME sustainability performance and financial literacy has a positive and significant relationship to MSME sustainability performance. In addition, e-commerce has a significant influence on the sustainability performance of MSMEs because the presence of e-commerce is one of the marketing alternatives used to reach more vendors and customers which can change the supply chain leads to social problem solution such as food distribution. Further, e-commerce may minimize traveling long distances for shopping resulting to the carbon footprint reduction. MSMEs have the same opportunity to use e-commerce as an alternative to maximize performance. However, not all MSMEs have the capability to use and utilize e-commerce optimally. After all, knowing good financial management will make it easier to make sustainable decisions since the higher the level of financial literacy, the MSME players can optimize their sustainability performance.

This study explores the factors influencing personal brand identity and their impact on successful personal branding. It examines the positive influence of social media usage, self-expression, professionalism, and self-disclosure on personal brand identity, while also considering the inconsistent findings regarding the role of self-efficacy. The study finds that social media usage, self-expression, professionalism, and self-disclosure play crucial roles in developing a strong personal brand identity, which is essential for achieving successful personal branding. However, the findings on self-efficacy's influence on personal brand identity are inconsistent with previous research. This study contributes to the understanding of personal brand identity and provides valuable insights for individuals and organizations seeking to develop and maintain strong personal brands.

Previously, studies reported inconclusive findings while analyzing the influence of factors affecting online purchase intention. Also, most studies were conducted in the context of developed countries, limiting us to a specific context. Hence, for comprehensive understanding, this study aims at examining the factors affecting the online purchase intention in the e-commerce industry of Jordan. The survey was conducted to collect data from university students in Jordan. Structural equation modeling was employed to analyze the data. Findings show that attitude, subjective norms, perceived behavioral control are positively associated with online purchase intention. However, perceived risks are negatively associated with online purchase intention. Although all factors are significantly related to online purchase intention, the attitude has a greater influence. This study adds value to the theory of planned behavior and consumer behavior by examining attitude, subjective norm, perceived behavioral control, and perceived risks as important predictors of online purchase intention. Besides, this study suggests that online retailers must keep their commitments, promises, and customers’ interests in mind while developing e-commerce strategies.

The current research aims to expose the value of Instagram's features and content and investigate how cognitive functions mediate the relationship between Instagram's content-related elements (informative material, user-generated content, augmented reality content, entertainment, trustworthiness, sociability) and consumer affection and behavior. This study employed a random sample strategy and gathered 292 responses. The tool AMOS 22 (Analysis of a Moment Structure) examined the data efficiently. Results show that all Instagram content marketing elements affect cognitive engagement, where augmented reality content has rated the highest effect, then user-generated content, trustworthiness, informative material, entertainment, and sociability, consequently. Then cognitive engagement affects affection and behavior.

During the innovation era and in the highly competitive environment, big data capabilities (BDCs) play a pivotal role in shaping competitive dynamics; the influence of these technologies on small and medium-sized enterprises (SMEs) operating in the retail sector is critically significant. This study is specifically focused on the retail industry, with a particular emphasis on how BDCs impact the project success, business continuity, and sustainability of SMEs within this industry. Our theoretical model was tested using a survey of 300 operations managers working in SMEs in the retail sector in the Middle East. PLS-SEM was conducted to analyze our collected data. Our results reveal that BDCs enhance project success and promote sustainability practices. The findings also reveal that BDCs have no impact on business continuity. By shedding light on the nuanced impact of BDCs on SMEs in the retail sector, this study contributes valuable insights to the existing literature, offering a deeper understanding of how these technological capabilities can drive success and sustainability in a highly competitive market environment.

This research aims to investigate the role of internet marketing, word-of-mouth and brand awareness on purchasing decisions in online stores. The respondent sampling technique used in this research is a non-probability sampling technique, which uses a purposive sampling technique. The responses to this research were from 468 online store consumers. Measurements of “Internet Marketing”, “Word of Mouth Communication”, “Brand Awareness” and “Purchasing Decisions” were carried out using a seven-point Likert scale, ranging from strongly agree (1) to strongly disagree (7). In this research, the data was analyzed using the Partial Least Square (PLS) method with SmartPLS version 3.0 software. The stages of research data analysis are outer model testing, namely unified validity and reliability, inner model testing and hypothesis testing. Based on the results of data analysis, it is concluded that internet marketing, word-of-mouth and brand awareness had positive and significant effects on purchasing decisions. Better internet marketing will improve consumer purchasing decisions, brand awareness plays an important role in consumer purchasing decisions, and consumers will carry out word-of-mouth activities and tell other people about consumer experiences after consuming products, electronic word of mouth can help consumers in making buying decisions. Based on the results of data analysis, the study provides managerial implications as follows: online stores should evaluate the Internet marketing strategy used by the company by looking for information about what is currently trending among the public and forming a special team to carry out Internet marketing strategies to make them more attractive and creative and provide more complete information regarding products are marketed so that they attract consumers to make purchasing decisions.

Smart contracts offer automation for various decentralized applications but suffer from vulnerabilities that cause financial losses. Detecting vulnerabilities is critical to safeguarding decentralized applications before deployment. Automatic detection is more efficient than manual auditing of large codebases. Machine learning (ML) has emerged as a suitable technique for vulnerability detection. However, a systematic literature review (SLR) of ML models is lacking, making it difficult to identify research gaps. No published systematic review exists for ML approaches to smart contract vulnerability detection. This research focuses on ML-driven detection mechanisms from various databases. 46 studies were selected and reviewed based on keywords. The contributions address three research questions: vulnerability identification, machine learning model approaches, and data sources. In addition to highlighting gaps that require further investigation, the drawbacks of machine learning are discussed. This study lays the groundwork for improving ML solutions by mapping technical challenges and future directions.

This study aimed to investigate the effect of cloud computing (CC) and company size on accounting information quality. Data were collected using an online questionnaire which followed the Technology Acceptance Model (TAM). The research sample consisted of 178 respondents from accountants and audit offices in the Emirate of Riyadh. The study adopted a Smart PLS in hypothesis testing. The study's results indicated just a positive relationship between perceived benefit and quality of accounting Information. In addition, there was a clear influence of company size on the relationship between CC and accounting information quality.