Manufacturers employ AI for monitoring vehicle mileage, inspecting components, and scheduling maintenance. Past studies underscore the need for auto-related plans to prioritize environmental protection, concentrating on AI-driven environmental solutions promoted by AI for Good. AI enhances brand success by improving investment, technology, and promotional capabilities. This study emphasizes consistency in AI application across the automotive value chain for brand sustainability. A web-based poll surveyed 120 AI users in marketing, HR, sustainability, as well as 180 sustainability specialists and regulators. The primary goal is to assess, via structural model evaluation, how extraneous variables affect the development of AI-powered brand sustainability strategies. The study highlights AI's sustainability benefits in the automotive industry improving transportation safety, forecasting maintenance, and creating eco-friendly vehicles. However, challenges involve over-reliance on AI, predicting human behavior, and addressing sustainability threats. AI development should consider regional differences, prioritizing openness, policy harmony, and consumer agency. These findings aid marketing and HR professionals in devising customer-centric long-term plans.

Diversity, equity, and inclusion (DEI) are crucial for commercial success, fostering innovation, fresh ideas, and mutual respect. Prioritizing DEI is vital for businesses to connect with a broader customer base. A study examined how effective diversity management influences a brand's diverse customer base and DEI policies. It explored the impact of DEI culture, workforce, evaluation practices, product issue resolution, and diversity partnerships on customers. Multinational entities surveyed, with 176 online HR and marketing experts participating. Likert scales, gauged responses, and structured equation modeling analyzed data. The study found that embedding DEI into company culture, maintaining diverse personnel, monitoring DEI performance, addressing DEI challenges with products, and engaging diverse partners positively affect a varied customer base. The research emphasizes that multicultural team leaders must prioritize diversity management for successful implementation, providing a theoretical and statistical framework for effective DEI policies across diverse clienteles.

This study aims to investigate the impact of leadership styles (transformational leadership style, transactional leadership style, and Laisser-Faire leadership style) on employees’ innovative work at Al-Ahliyya Amman University Employees. It follows the descriptive analytical approach by distributing a questionnaire to a sample of 461 employees following the convenience sampling technique. The findings show a positive statistically significant impact of transformational leadership style on employees’ innovative work behavior, while there was a negative statistically significant impact of transactional and Laisser-faire leadership styles on the employees’ innovative work behavior at Al-Ahliyya Amman University Employees.

Given that social media (SM) has become an integral part of the daily lives of university students and their main window to communicate with the world around them, higher education institutions can no longer help but adopt it as a major part of their marketing strategy and as a major communication channel to enhance their ability to retain their current students and attract new students. Therefore, this study aims to reveal the role of Social Media Marketing (SMM) in promoting student satisfaction factors at Al-Ahliyya Amman University (AAU) and improving their experience, which must have a significant successive impact, starting from enhancing the university's image, to expanding the spread of positive eWOM, and ultimately, increase students' loyalty to the university, To create a practical framework for building a marketing strategy that invests in SMM to enhance student loyalty, relevant literature was evaluated. Business school students were surveyed using a paper questionnaire distributed to students to increase interest and accuracy in answering, to extract conclusions from the data and model variables, a structural equation modelling using Smart-PLS was used. The survey results indicate that (AAU) has not invested sufficiently in promoting some of the satisfaction factors of its students and improving their experience. But in general, it affected somewhat positively the loyalty of its students. The research has important theoretical and practical implications.

AI is tanking different functions of businesses, and marketing is no exception. Digital marketing is gaining pace with the advancement in technology and the internet. The research aims to find the answer to the research question that marketers can benefit from AI in content creation for the digital market. The study also finds the relevance and use of AI in content creation and develops an AI infrastructure adoption model for content creators in digital marketing. The findings of this study were compiled using a systematic literature review that adhered to the Preferred Reporting Items for Systematic Reviews (PRISMA) statement and the criteria established by Meta-Analyses. The findings revealed that using AI in content creation provides personalized data, which helps the creators make relevant, targeted, and specific content. The research also finds that AI alone is not mature enough to carry out the whole content creation procedure as there is some limitation attached, especially regarding ethical implications. That’s why human surveillance of AI systems involved in content creation for the digital market is needed.

Given the widespread adoption of social media as a primary information source, organizations can no longer do without it. The importance of social media in creating sustainable company strategies has increased in tandem with the public's growing knowledge of sustainability issues. This study examines how marketing and social media can create brand sustainability plans. To create a practical framework for creating sustainability strategies, the relevant literature was evaluated. Market managers and digital marketers were surveyed using an online questionnaire. To extract conclusions from the data and model variables, a structural equation model was used. Findings from the survey indicate that businesses are increasingly turning to social media to share information with stakeholders, solicit opinions, and collect information for use in developing sustainability plans. Market managers play a vital role in ensuring the sustainability of their businesses. The research has theoretical and managerial implications.

The purpose of the study is to present a digital marketing data analytics model to analyze campaign efficacy and inform strategy based on website performance, social media metrics, email marketing performance, customer data for targeting and personalization, and customer journey analysis. This model defines campaign success criteria for strategy. A statistical analysis approach was used to analyze the data for the research. Data was gathered through a survey. This study analyzes demographic parameters descriptively using the structural equation model (SEM). From comprehensive surveys, 125 digital media and 115 online shop subjects responded. Sampled were 240 people. According to the findings, social media data, customer journey research, successful advertising, and informed approaches are highly correlated. Compared to the previous study, website performance evaluation does not match the marketing plan's success. The model's results can be used by any company that communicates with clients online.

In online shopping enterprises, AI technology has been widely used to provide accurate and fast personalized consumer services. This research demonstrates the use of AI technology in the e-commerce business, specifically online enterprises, to determine different effects. The study was conducted in Jordan and involved about 230 participants. The study evaluated different impacts of AI, such as e-payment and stimulating consumers' sentiments. The study used the Stimulus–Organism–Response model (SOR) empirical model, which states that the examination of human processes differs from that of the machine assessment. The model classified the AI technology experienced by the customers' when they visit online to do purchasing. Online purchasing behaviors can be influenced by insight, accuracy, and interaction experience. Also, the perceived value was used as a mediating variable from the prospects of perceived hedonic and utility value. The research integrated empirical research models such as SEM and SPSS to analyze the data on the effects of three-dimension. The results indicated that the AI technology accuracy, interactive experience, and insight significantly affected customers' perceived hedonic and utilitarian values.