This study analyzes the tourism network and destinations after the COVID-19 pandemic using social network analysis (SNA). Analysis of 789 destinations in Thailand has found that the destinations are connected by 1,1175 tourism routes. The network is a sparse network with a low network density. It seems to have a scale-free property that reflects that most destinations have low connectivity and a small number of destinations have high connectivity. The network has a large average path length and low clustering coefficient. Different roles of destinations are identified based on degree, betweenness and closeness centrality. The findings draw implications for vitalizing the sector.

The study aimed to identify the impact of digital transformation and analyze the obstacles and complexities facing the integration of digital technologies into Jordanian Customs and their subsequent impact on achieving strategic flexibility. The study aims to uncover challenges, evaluate their effects, and suggest recommendations to enhance adaptive strategies within Jordanian Customs considering digital transformations. The study included employees in Jordanian General Customs, including customs officials, IT staff, and administrative staff working on digital initiatives. A population of 670 individuals was identified, from whom a purposive sample of (465) directly involved in digital transformation efforts was selected to participate in the study. The study used the descriptive analytical approach to comprehensively investigate the challenges of digital transformation within Jordanian Customs. Surveys, interviews, analysis of regulatory documents formed data collection methods. Quantitative data were subjected to descriptive analysis and regression modeling, while qualitative insights were thematically analyzed to provide a comprehensive understanding of the challenges faced. The analysis revealed the results, the most important of which is that digital transformation has a positive, statistically significant impact in its four dimensions (strategy, organizational culture, transformational leadership, and human resources) in achieving strategic agility in Jordanian Customs, and reveals multi-faceted challenges prevailing within Jordanian Customs, including structural constraints. Infrastructure, resistance to change, cyber security vulnerabilities, and skills gaps among the workforces. The regression analysis highlighted the significant impact of these challenges in hindering the achievement of strategic flexibility within the Customs Department. Based on the results of the study, Jordanian Customs is recommended to take proactive measures to confront the challenges identified. This includes investing in a robust technology infrastructure, implementing targeted training programs to improve employee skills, promoting a culture of innovation, and establishing cross-departmental collaboration to enhance adaptability and strategic flexibility. The study recommended increasing attention to training workers and raising their capabilities to deal with digital transformation positively and improve services.

Mobile Applications offer a new style to service sectors, for instance, in higher education, mobile applications are utilized to provide access to academic resources and academic services. Despite the wealth of mobile applications, they encounter various challenges that have attracted the interest of academia and software developers. The usability issues of mobile applications may cause performance degradation, resulting in the company's loss in terms of cost. This study aims to investigate the usability of the Prince Sattam bin Abdulaziz University (PSAU) mobile application by adopting data mining as a descriptive and predictive process. The first step was gathering data of the usability of the PSAU mobile application using the system usability scale. Afterwards, data was preprocessed into a suitable format to apply data mining methods. Specifically, the explanatory model has been employed to describe and investigate insights related to the usability factors and features of the PSAU mobile application. Furthermore, this study adopted the Four Clustering methods to segment the usability levels of the PSAU mobile application into homogenous groups based on user behavior. Additionally, the predictive model was used to build models for predicting the usability level and Grade and five classification algorithms were employed to predict the usability level and Grade. Most algorithms have given positive results in all performance indicators, where the accuracy rate achieved is 98% to 95% for most methods. The results revealed that the PSAU mobile application has an acceptable usability level, and the data mining methods helped to discover hidden patterns. Furthermore, the findings will help the developers and policymakers understand users' and stakeholders' behavior to find the most common usability problems for each group, and customize the PSAU mobile application.

Reputation management is of more significant consideration for organizations across the globe. However, for relevant purposes, Public Relations accompanied by Artificial Intelligence further play a significant role. Mainly supported by the social exchange theory, this study also focuses on Public Relations practices and Artificial Intelligence as facilitating the pathway to reputation management for online retail organizations in the United Arab Emirates. The researchers selected a sample of n= 330 individuals and analyzed it using Structural Equation Modelling to test the proposed conceptual model. Results revealed that Public Relations practices significantly affect Competitive Value, Online Communication, and Behavior Change. Besides, the effect of Artificial Intelligence on Competitive Value, Online Communication, and Behavior Change also remained significant. Further, the three relevant factors (Online Communication and Behavior Change) significantly affect reputation management, indicating the overall effect of PR practices and AI on reputation management in online retail organizations in the UAE. Hence, it is concluded that PR practices and AI technology have a substantial role in ensuring reputation management. Besides, factors including Competitive Value, Online Communication, and Behavioral Change have a positive role in reputation management, further ensuring attaining the organizational goals. Finally, the researchers discussed the results and highlighted the theoretical implications accordingly.

This research investigates the adoption of Information and Communication Technology (ICT) by Micro, Small, and Medium-Sized Corporations (MSMEs) in Jordan. The research formulates and examines hypotheses on factors affecting ICT adoption morals via the Unified Theory of Acceptance and Use of Technology (UTAUT) and the Technology Acceptance Model (TAM). The suggested concept, which utilizes Structural Equation Modelling (ESM), highlights the critical responsibilities that social influence and perceived utility play in affecting choices to adopt ICT. It is noteworthy that MSMEs confront a multiple of obstacles when it comes to adopting ICT, encompassing restrictions in terms of infrastructure and resources, shortages of human capital, and hardships in the technology environment. Data were gathered from 305 MSMEs, and outcomes shed light on important factors to boost the impact of ICT integration in the special setting of Jordanian MSMEs.

This study investigates AI bias in financial technology (FinTech)-based supply chain management in Pakistan. The study employs Structural Equation Modeling (SEM) to analyze data from diverse respondents. Hypotheses examine the relationships between AI integration, algorithm diversity, employee training, data quality, regulatory compliance, organizational culture, and AI bias. The findings reveal that higher AI integration leads to increased AI bias, Algorithm diversity reduces AI bias, while employee training decreases bias, Quality and diversity of data negatively correlate with AI bias, and regulatory compliance lowers bias. In addition, organizational culture mediates the relationship between AI integration and AI bias. This research contributes a holistic understanding of AI bias factors, guiding ethical AI adoption. Policymakers can use these insights to shape regulations, and industry practitioners can make informed decisions.

Social media usage has increased tremendously in recent years. However, when users cannot control their social media usage, it might have some negative impacts on personal and social life, which lead to the cyberloafing phenomenon. This study aims to examine the influence of cyberloafing activities (sharing, shopping, gaming, accessing online content, real-time updating) and social media addiction among netizens. This study utilized Uses and Gratification Theory (U&G) as a theoretical basis to explain the framework. The quantitative method was implemented in this study. An online survey questionnaire was used to collect data and 318 valid respondents were generated. Partial Least Square Structural Equation Modelling via Smart-PLS was used to analyze the data. The study showed that two cyberloafing activities, namely real-time updating and sharing significantly impact social media addiction. However, the other cyberloafing activities (accessing online content, gaming, shopping) do not contribute to social media addiction. This study may help students and employees to be cognizant of the symptoms of cyberloafing and social media addiction. In addition, it also helps government agencies such as Malaysian Communication and Multimedia Commission (MCMC) to produce strategies that can address addiction among netizens and youths. Conclusion, implications, and future research directions were discussed.

In India, higher education institutions (HEIs) are realizing the value of green interaction, which includes using social media (S.M.) in an environmentally responsible manner. However, there needs to be more consistency on the adoption's present status, the particular tactics used, and the advantages that follow. The current research investigates the various aspects of sustainable communication and its benefits in HEIs throughout India. Through a questionnaire approach, the research enrolled learners across India. The study model's conceptual structure was validated, and its assumptions were proven through the implementation of a quantitative survey. The number of accepted samples was calculated using a conceptual model, and data analysis was performed using the structural equation model (SEM). There were 500 respondents in the study, ranging in age and academic degree and from different institutions of higher learning. The age range of 280 women and 220 men was 80% between 19 and 28. Respondents employed prominent S.M. sites (Twitter, LinkedIn, and Facebook) with purpose and had robust computer abilities. The results demonstrated that inspiration for employing S.M., S.M. characteristics, and information exchange had a favorable impact on students' opinions of user-friendliness and the benefits of digital learning platforms, raising their adoption of them. The research strategy in this investigation delivers suggestions for additional exploration into how HEIs in India may maximize the advantages and utilization of digital learning systems and can be an efficient structure for similar study ventures.

Research on e-government and good governance is still rarely carried out, even though e-government and good governance are important factors in government companies. This research aims to analyze the relationship between e-government and financial performance, the relationship between employee competency variables on financial performance, and the relationship that good governance variables have on financial performance. The method of this research is quantitative through surveys, research data was obtained by distributing online questionnaires to 590 managers of government companies who were selected using a simple random sampling method, and an online questionnaire was designed using statements item with a Likert scale from 1 to 7. Data analysis used Structural Equation Modelling (SEM) with the SmartPLS 3.0 software tool to analyze research data. The stages of data analysis are validity testing, reliability testing, and significance testing of hypothesis testing. The results of this research show that e-government had a positive and significant effect on financial performance, and employee competence had a positive and significant effect on financial performance. Moreover, good governance had a positive and significant effect on financial performance. The novelty of this research is the creation of a new model of the relationship between e-government and financial performance, employee competence and financial performance, and good governance and financial performance which has not existed in previous studies. The practical implication of this research is that to improve the financial performance of government companies, we must implement e-government by increasing employee competency and implementing good governance.

Businesses heavily depend on social media to engage with customers, utilizing various platforms for interaction, feedback, and promoting products. The influence of social media on customer trust, loyalty, and satisfaction is a prominent subject. This study seeks to comprehend how businesses leverage social media to attain these objectives, utilizing both qualitative and quantitative methods. The initial exploratory phase collected qualitative data from 24 business enterprises, employing grounded theory techniques such as open, axial, and selective coding to pinpoint the primary factors affecting customer trust, satisfaction, and loyalty. Building on the insights from the exploratory study, the research proposes a model and hypotheses. The subsequent confirmatory study employs a quantitative approach, collecting data from 300 respondents in Jordan and utilizing Structural Equation Modeling (SEM) for analysis. Results underscore the pivotal roles of personalization, user-generated content, communications, word-of-mouth, emotions, promotions, and customer support as social media directions in shaping customer trust, satisfaction, and loyalty. This research provides valuable insights into the dynamics of how social media shapes customer relations, offering guidance to businesses navigating this ever-evolving landscape.