This study investigated the impact of triple project constraints including time, cost, and quality on construction projects. The main goal was to examine several construction-related barriers, most of which were caused by time delays, cost overruns, and poor project quality. In addition, improper cost estimation planning can occasionally result in overestimation or underestimation, which can cause construction projects to be delayed or tasks to go unfinished. To improve the construction industry's routine and produce successful projects that satisfy its stakeholders, the study aims to investigate the impact of project cost, project quality, and project time with a moderating function for organizational support. A questionnaire survey was held, and overall findings indicate that managing triple constraints significantly impacts on the success of construction projects. Organizational support also moderates the detrimental effects of project cost, project quality, and project duration on the success of construction projects.

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.

The main goal of this research is to study and investigate the impact of data management and analysis tools on improving organizational behavior within three IT service firms in Jordan. This research focuses on choosing three data management and analysis tools: Database analysis tool, data processing tool, and big data processing tool and how these tools could positively influence enhancing employee performance and organizational behavior. It accomplishes this within the distinct framework of three Jordanian IT service firms. The research supposed that combining big data analysis, integrated data processing, and database analysis is necessary to enhance organizational behavior and employee performance, as indicated by the findings. Furthermore, the research highlights the potential for IT service firms in Jordan to benefit from emerging database analysis technologies, promote the use of integrated data processing techniques, and leverage big data analysis for their own benefit. This can enhance corporate behavior and employee performance. Data was distributed and collected from three Jordanian IT service firms, and all collected data was analyzed using AMOS. The study's findings offer valuable recommendations for enhancing the operational efficiency of IT service firms in similar business environments, emphasizing the crucial importance of comprehending and purposefully employing database-related technologies for sustained prosperity.

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.

Cryptocurrencies are crucial in modern commerce and finance, whether at the national, corporate, or individual level. They serve as fundamental currencies for buying and selling, enabling various business transactions. However, the rise of cybercrime has brought about concerns regarding their operations, potential breaches in encrypted currencies, and the security systems managing them. The frequency of attack tactics and the motivation of attackers seeking financial gain are well-known. Many cryptocurrencies lack the necessary algorithms, techniques, and knowledge to effectively detect and mitigate malware, making them vulnerable targets for hackers. In this study, machine learning techniques are employed to detect malicious code in digital currencies. Additionally, a comparison of these techniques is conducted to determine the most suitable algorithm and technology, Furthermore, this study highlights the importance of effective malware detection in securing cryptocurrencies. Three datasets of different sizes were used, each yielding distinct results based on dataset size. The AdaBoost model demonstrated superior performance when applied to the short dataset, while the decision tree model performed best with the medium-sized dataset. Conversely, the Naive Bayes model consistently produced the worst results, while the large-size KNN model achieved the highest performance.

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.

Agriculture products are one of the main income sources of developing countries. This study analyzes the road transport system (network) to reveal the network’s structural properties and identifies hubs that consolidate agricultural products to export to China via the China-Laos railway. Analysis of 20 provinces in the Northeast of Thailand has found that the network has 340 districts connected by 1,015 transport routes. The network is sparse, in which all districts cannot be connected to each other. The network has low connectivity efficiency but has high intra-connectivity among districts in the same province. In addition, the network has a modularity structure that can develop the communities. Hubs consolidating agricultural products of the region are Na Khu, Kuchinaria, Mueng Chiyaphum, Nam Phong, Na Wa, Mueang Mukdahan, Prasat and Rasi Salai. The findings of the study draw implications for the government, sector and exporters to design and improve their operations and services.

Recently, due to the tremendous development in information and communication technology, the world is moving rapidly towards digitization in all areas of life. In the financial context, Financial Technology (Fintech) has the potential to transform the financial sector by offering innovative digital solutions, but its adoption depends on various individual, organizational, and environmental factors. This research paper aims to identify and analyze the determinants that influence the intention to adopt fintech. A self-administered survey was utilized to collect the necessary data. Data were analyzed using SPSS version 26 for descriptive analysis as well as SmartPLS version 3.0 by implementing the PLS algorithm and Bootstrapping techniques. This study finds that intention to adopt Fintech is affected by perceived usefulness, perceived ease of use, trust, social influence, and facilitating conditions. This study also examined the relationships between these variables. The findings will provide insights for fintech stakeholders, policymakers, and researchers to foster a conducive environment for Fintech adoption and usage.

Small and Medium Enterprises (MSEs) are one of the people's economic enterprises that have an essential role in advancing the Indonesian economy. Improving the overall, optimal and sustainable performance of SMEs business increases contribution to the economy in provinces in Indonesia, one of which is Bali Province, the province with the highest absorption of SMEs in Indonesia, namely 10 percent of its population. Denpasar City, as the capital of Bali Province, is the center of trade in Bali, especially the relatively even distribution of SMEs in every sub-district in Denpasar City. This research aims to analyze the role of live streaming in moderating the influence of entrepreneurial marketing and e-commerce on the performance of fashion SMEs in Denpasar City. The research involved 134 fashion SMEs in Denpasar City as samples. Data collection was carried out by distributing questionnaires. Then, the data was analyzed using SmartPLS. The test results of live-streaming commerce moderating the influence of e-commerce adoption on business performance show that live-streaming commerce moderates with a quasi-moderation type the influence of e-commerce adoption on business performance. Live streaming commerce moderates the influence between the independent variable e-commerce adoption and the dependent variable business performance and influences business performance.

The digital economy is a phenomenon that has emerged in today's modern era. Digitalization is expected to be able to support the progress of the economic aspect. However, it turns out that not all people in parts of the world are able to keep up with this change in the phenomenon of economic digitalization. This study aims to identify, classify, and analyze the factors that influence the conditions of acceptance of the digital economy in developed and developing countries as measured through the Digital Economy Acceptance Index (DEAI). This research used a quantitative approach with research objects from countries in the world during the past years. The methods used in this research are composite index and multivariate statistical cluster analysis. The results showed that countries with high DEAI consisted of the United States, Canada, Japan, Australia, New Zealand, Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Netherlands, Spain, Sweden, Switzerland, and Singapore. Countries with moderate DEAI consist of Greece, Italy, Portugal, Brunei Darussalam, China, Indonesia, Malaysia, South Africa, Libya, Brazil, Philippines, Thailand, Vietnam, Iran. As well as countries that have low DEAI, namely Cambodia, Myanmar, Egypt, Laos, India, Pakistan, and Sri Lanka.