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.

This study provides a comprehensive overview of the field of enhancing the customer-supplier relationship through big data technology and artificial intelligence (AI), reveals existing gaps and offers promising solutions for future research. SMART PLS-4 software was used to analyze the data collected, the results led to the existence of significant relationships between artificial intelligence and enhancing the relationship between the supplier and the customer (customer interaction, customer communication, customer participation, customer learning, customer experience, customer feedback). The study contributes to developing a conceptual model through the application of artificial intelligence in managing customer relationships with suppliers in the banking industry. The study contributes to developing a conceptual model through the application of artificial intelligence in managing customer relationships with suppliers in the banking industry setting. Which supports increasing knowledge in this field and helps managers develop appropriate strategies. This research is the first of its kind to organize and discuss the literature related to using artificial intelligence within the customer-supplier relationship management setting, which provides great importance to the process of using and developing artificial intelligence technology and understanding recent trends in how to develop customer–supplier relationships within the technology era.

This research aims to study the factors influencing customer retention of E-Marketplace businesses by applying the SOR theory and the mediating effect by examining the relationship between value perception, customer engagement, brand loyalty, and customer retention variables by creating a model based on the SOR theory to study the influence of environmental factors that will lead to customer retention mechanisms. The study focused on a sample group of 426 people who have used E-Marketplace services using an online questionnaire as a research tool. The model was analyzed using the CFA and the hypothesis was tested using the SEM analysis. The results showed that stimuli (S), such as customer value perception, had a strong positive influence and a crucial role in the development and creation of a mechanism for assessing individuals' internal feelings (O) on two variables, customer engagement, brand loyalty, and directly influence customer retention. Furthermore, significant evidence also showed that brand loyalty has an important role as a mediator between customer value perception and customer retention, which is the outcome factor (R) of this study. This structural model can explain customer engagement and retention up to 86.50 percent. Therefore, this research has value as a theory and guideline in formulating an operational strategy for E-Marketplace businesses.

The COVID-19 pandemic caused significant changes in many aspects especially towards small medium entrepreneurs (SMEs) as many of SMEs need to shut down their business due to movement control order (MCO) conducted by Malaysia government as SMEs cannot reach their customers. Previous studies show that having an effective digital marketing strategy in place might leave businesses vulnerable to severe setbacks towards SMEs. This research proposal aims to carry out and prove the possible potential effects and factors that influence digital marketing implementation towards online consumers in Selangor during COVID-19 pandemic. The methodology of this paper uses a descriptive qualitative approach by analyzing various previous literature on digital marketing scope of study. The sample size of the study is 235 respondents who were selected based on convenience sampling. The finding has discovered that there is a significant relationship between customer loyalty with implementation of digital marketing towards online consumers in Selangor during COVID-19 pandemic and there is a significance relationship between brand awareness and the implementation of digital marketing towards online consumer in Selangor during COVID-19 pandemic.

This study is to examine the effects of service quality, customer relationship learning, product quality, and customer engagement on increasing customer value. The researchers propose a model, and plan to show the concept of customer engagement variables as intervening variables. The study population includes the customers of Bank Jatim and uses the SEM analysis and the purposive sampling method for 384 respondents. The proposed model shows customer engagement acts as a good intervening variable. Customer value increases, as customer engagement increases. Finally, customer relationship learning determines the value of the existence of customer engagement in bank service customers.