This paper aims to evaluate the role of AI and ML-driven innovative technologies in enhancing customs operations in Jordan. This research employed a quantitative approach to develop an overall conceptual model that encompasses both the technical and behavioral aspects of intelligent system adoption. The target population consisted of customs officers, border security personnel, and IT personnel responsible for customs clearance and trade facilitation in Jordan. The structured questionnaires were administered to the respondents to measure their perceptions of system effectiveness, satisfaction, performance outcomes, and evasion behavior and yielded a total of 358 valid responses. The research was conducted with proper statistical analysis, and the statistical techniques employed included primary data collected via SPSS Version 29 and advanced modeling using Structural Equation Modeling-Partial Least Squares (SEM-PLS) through the use of SmartPLS 4.0. The results indicated that the measurement model proved to be both valid and reliable, with Cronbach's alpha values exceeding 0.82 and AVE values above 0.50, indicating good internal consistency and convergent validity. Moreover, the structural model achieved good explanatory power, with R² values of 59% for Customs Evasion, 43% for User Satisfaction, and 100% for Digital Performance Indicators. These findings underscore the significance of user satisfaction as a key outcome of system effectiveness and a valuable tool for enhancing performance and deterrence. More specifically, the results shown how Intelligent System Effectiveness presents a positive and significant impact on User Satisfaction (β = 0.656, p < 0.001), which in turn has a high positive effect on both Digital Performance Indicators (β = 1.000, p < 0.001) and Customs Evasion reduction (β = 0.770, p < 0.001). The mediation analysis also confirmed that User Satisfaction fully mediates the relationship between system effectiveness and performance outcome, as well as between system effectiveness and evasion reduction. This research contributes to theory and practice by demystifying the design and implementation of AI-driven customs systems. It illustrates the importance of valuing both technical system quality and user-centric values in achieving and maintaining optimal performance in the digital space, as well as conformance with the law.

This study encroaches on the interactive mechanisms of the digital marketing strategy and its overall effect on the performance of the business within the Jordanian hotel sector. The article presents a survey of 370 professionals working in the field of management and marketing in the hotel and tourism industry to identify complex interdependent relationships among the concept of Search Engine Optimization (SEO), E-Service Quality (ESQ), and efficiency of the implemented digital marketing. To establish the impact of combining the SEO practices with the increased e-service quality on the customer involvement and the business success in general, the authors established and tested three hypotheses with the assistance of the structural equation modeling (SEM): first, the impact of the e-presence optimization on the competitiveness of the business on the market is very strong and positive, which is reflected through both customer engagement and efficient customer acquisition.. E-Service Quality that plays a major role in increasing the customer trust, satisfaction and retention which in turn mediates the positive relationship between digital marketing efforts and the business performance. Furthermore, the paper has established that the digital marketing strategies are a strategic facilitator connecting the level of technological adoption to the level of operational and financial performance measurement. Based on these findings, the paper proposes a long-term commitment to the advancement of the e-service quality, customer-focused digital platforms, and SEO technologies to stabilize the marketing effectiveness and guarantee the business advancement in the Jordanian hospitality sector.

Changes in the global business environment constrain companies to adopt digital technology to enhance their performance and competitiveness. This study aims to analyze the role of managerial capability on operational performance through supply chain digitalization and supply chain adaptability in manufacturing companies in Indonesia. Managerial capability is a key factor that enables organizations to design effective strategies, allocate resources efficiently, and foster internal collaboration and external partnerships. The study has distributed questionnaires to 117 respondents from various middle and top managerial functions within the manufacturing company. The questionnaire was designed using a five-point Likert scale and distributed offline and online using a Google Form link. Data analysis employed Partial Least Squares – Structural Equation Modeling (PLS-SEM) to examine the outer model and inner model. The results indicate that managerial capability has a significant impact on supply chain digitalization and supply chain adaptability, but does not directly affect operational performance. Instead, the effect of managerial capability on operational performance is mediated by supply chain adaptability and the combination of supply chain digitalization and adaptability. Supply chain digitalization plays a crucial role in enhancing supply chain adaptability, ultimately leading to a positive impact on operational performance. These findings confirm that supply chain digitalization not only increases the speed of information flow and transparency but also strengthens the company's ability to adapt to market dynamics. The practical implications of this research are the need for manufacturing companies to continuously develop managerial competencies that support digital technology investments, strengthen an adaptive organizational culture, and foster synergy between internal and external functions. For academics, this research provides a conceptual contribution in explaining the mediating relationship between managerial capabilities, supply chain digitalization, supply chain adaptability, and operational performance in the era of digital transformation.

This research aims to analyze the relationship between brand image and visiting decisions, digital marketing and visiting decisions, and brand image with digital marketing. This research method is quantitative through surveys, research data was obtained by distributing online questionnaires to 489 tourism industry managers who were selected using a simple random sampling method, and the online questionnaire was designed using statement items with a Likert scale of 1 to 7. Data analysis used a structural equation model based on covariance (CB-SEM) with SmartPLS 4.0 software to analyze research data. The independent variables are brand image and digital marketing, and the dependent variable is the decision to visit. The stages of data analysis are validity testing, reliability testing, model suitability testing and significance testing of hypothesis testing. The results of this research are that brand image has a positive and significant relationship with the decision to visit, digital marketing has a positive and significant relationship with the decision to visit, and brand image has a positive and significant relationship with digital marketing. Based on the results of this research, several suggestions can be made that tourism must explore the potential of various digital marketing channels. From the results of this research, the channel with the lowest contribution is the presence on social media which is still very minimal and the quality of the newsletter is less attractive. The researcher's next suggestion is to take advantage of the marketing potential of social media. Tourism does not only rely on guest recommendations to get the next guests but must be more active in various marketing efforts, especially digital marketing because the enormous potential in disseminating information about tourism's unique selling points through digital media is unlimited.

The purpose of this study is to analyze the relationship between digital orientation and student innovation culture, the relationship between student creativity and student innovation culture and the relationship between e-learning and student innovation culture. This study uses a specific quantitative study by investigating the relationship between variables. These variables are measured using a research instrument, namely a questionnaire, so that the data obtained are in the form of numbers that can be analyzed through statistical calculations. The quantitative research method is chosen in this study because it uses data in the form of numbers that are analyzed by statistical calculations, and aims to test the established hypothesis. This study collects primary data using a survey method, namely distributing questionnaires to respondents in the form of Google Forms designed using a Likert scale of 1 to 5, which later the results of the questionnaire will be processed using the PLS-SEM application. Respondents in this study are 427 teachers who taught in elementary schools in Indonesia elementary school students, the sampling technique used is simple random sampling where each member of the population is given an equal opportunity to be selected as a sample. The results of this study are: Digital orientation has a positive effect on student innovation culture, Student creativity has a positive effect on student innovation culture and the influence of e-learning has a positive effect on student innovation culture. Digital learning is an educational innovation that can improve the quality of learning and support modern education. The benefits of e-learning include: Learning can be done anytime and anywhere, so it can reach more students, The teaching and learning process can be done more effectively and cost-effectively.

Mental stress is a growing global health concern, closely linked to psychological, behavioral, and physiological disorders. Accurate and early prediction of mental stress is crucial for timely interventions and improved health outcomes. Despite numerous studies leveraging machine learning (ML) techniques for stress classification, many have overlooked the integration of systematic feature selection and comprehensive model evaluation, limiting generalizability and interpretability. To address these gaps, this study proposes a robust ML-based framework that combines optimized feature selection methods - Recursive Feature Elimination (RFE), Extra Trees (ET), and Boruta - with various classification algorithms including Random Forest (RF), K-Nearest Neighbors (KNN), Decision Tree (DT), Multilayer Perceptron (MLP), Support Vector Machine (SVM), Gradient Boosting, and voting classifier. The models were evaluated using 10-fold cross-validation and ranked using the TOPSIS multi-criteria decision-making approach. The experimental results demonstrate high predictive performance across models (accuracy ≥ 0.98), with RF, DT, MLP, and Gradient Boosting achieving perfect accuracy (1.00). Among all configurations, the RF-Boruta model emerged as the most optimal (TOPSIS score: 0.914558). These findings highlight the effectiveness of combining systematic feature optimization with ML classification for accurate and interpretable stress prediction, offering valuable insights for data-driven mental health interventions.

Augmented reality (AR) has garnered considerable interest for its potential to motivate engagement and advance customer-brand interactions. This study explored the impact of reality congruence (RC) of AR-menus on brand information sharing (BIS) in fast-food restaurants, particularly among Generation Z (Gen Z), as well as the mediating effects of usefulness of AR menu (UAR) and brand positivity (BP) on this relationship. Media Richness Theory (MRT) was employed as the theoretical umbrella for developing the study model. To validate the research model, we employed structural equation modeling (PLS-SEM) with a sample of 209 respondents. The results demonstrate that reality congruence of AR menus is a relevant predictor of Gen Z members’ behavior in sharing information about the brand. Furthermore, this relationship was mediated by the UAR and BP. The findings also demonstrated that UAR and BP had a sequential mediating effect on the relationship between the RC of AR-menu and BIS. This revolutionary study revealed that RC of AR-menu in restaurants fosters positive behaviors in fast food settings. By highlighting AR's potential to create engaging dining experiences for Gen Z members, this study offers valuable insights for service businesses, marketing managers, and the hospitality industry. Addressing this gap in existing research emphasizes the importance of adopting innovative technologies to enhance Gen Z's customer experience and engagement in the restaurant industry.

Researchers have developed different backoff algorithms to help boost how well IEEE 802.11 distributed coordination function (DCF) performs. The standard approach, known as binary exponential backoff (BEB), is commonly used, but alternatives exist. One alternative that has gained attention is the Fibonacci incremental backoff (FIB), mainly because it is shown to be quite effective. This paper introduces a novel backoff method that’s inspired by the Euler spiral curve. To assess its performance, we performed simulations comparing the proposed approach with both BEB and FIB. We focused on key performance measures like network throughput and end-to-end delay, particularly in mobile ad hoc networks. The results are encouraging: our method delivers better throughput than both BEB and FIB. However, it does come with a trade-off. It does exhibit slightly higher end-to-end delay compared to FIB.

The rapid advancement of drone technology has expanded their applications across various sectors, necessitating robust real-time decision-making systems. Traditional algorithms often falter in dynamic and unpredictable environments. This paper introduces a fuzzy logic-based approach to enhance the decision-making capabilities of autonomous drones. Utilizing Monte Carlo simulations, the proposed model was evaluated through three distinct experiments involving 300, 600, and 950 scenarios respectively. The first experiment demonstrated an obstacle avoidance efficiency of 82.00%, an 8.00% reduction in energy consumption, a decision accuracy of 95.33%, and a mission success rate of 79.33%. The second experiment showed an avoidance efficiency of 82.50%, maintaining the energy consumption reduction at 8.00%, with a decision accuracy of 95.83% and a mission success rate of 78.33%. The third experiment achieved an avoidance efficiency of 82.11%, with an 8.00% reduction in energy consumption, a decision accuracy of 95.26%, and a mission success rate of 78.31%. These results highlight the superior performance of fuzzy logic in real-time decision-making for autonomous drones compared to traditional methods.

Eco-friendly business practices range from energy efficiency to sustainable management; therefore, the implementation of these practices not only has the potential to mitigate environmental impacts, but also to improve the long-term competitiveness and sustainability of companies. In this study we analyze eco-friendly business practices and their impact on environmental sustainability in companies in a region of the Peruvian Amazon. A quantitative, non-experimental approach was considered, with an explanatory design; for which, a sample size of 200 companies was considered, which were randomly selected, to which two instruments were applied, the first with 7 indicators and the second with 3, valid, with an alpha of 0.720 and 0.670 respectively, assessing structural equation modeling. The results show that eco-friendly business practices are oriented towards sustainability (C.R. = 19.280), as well as preventive and eco-efficient practices (C.R. = 5.023, C.R.= 14.185); these findings can serve as a basis for the creation or improvement of public policies that promote eco-friendly business practices, encouraging companies to adopt measures that favor environmental sustainability. Therefore, eco-friendly business practices have a positive impact on environmental sustainability in companies in a region of the Peruvian Amazon; in addition, preventive practices and eco-efficient practices have a positive impact on environmental sustainability in companies in a region of the Peruvian Amazon.