In today's competitive business environment, the implementation of Customer Relationship Management (CRM) strategies is essential for firms to succeed. The purpose of this study is to investigate the relationship between CRM, customer satisfaction, and business profitability in the Jordanian logistics industry. Specifically, the study examines how customer satisfaction mediates the effect of three key CRM on business profitability. To achieve this, Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze data collected from 384 employees of logistics firms in Jordan. The results of the study suggest that CRM positively affects customer satisfaction, and that customer satisfaction has a significant mediating effect on the relationship between CRM and business profitability. The findings of this study have important implications for logistics firms seeking to improve their business profitability through the adoption of CRM. By focusing on the three key CRM (Customer Identification, Customer Acquisition, and Customer Analytics), firms can improve their customer satisfaction levels, which, in turn, can lead to improved business profitability. This study adds to the growing body of literature on CRM practices and their impact on business profitability, particularly in the context of the Jordanian logistics industry.

In Jordan, there are entrepreneurial companies in need of resources, and their resources available in the digital world are not sophisticated enough to utilize data analytics in effective decision-making processes. Thus, an understanding of the possible role which a digital human resource management can play to fill in some of these vacancies and to improve the project management in such situations becomes very important. In this study, it is aimed to examine whether digital transformation of human resource management acts as a mediation variable between business intelligence (direct) and project management (indirect) or not. In testing the hypothesis used method of data collection was the method of survey and the method of research used in the study was quantitative research. The Stratified random sampling technique was used and 400 questionnaires were distributed, however, 361 questionnaires were analyzed with business intelligence and digital HR proficient employees in entrepreneurial companies in Jordan. Data Analysis was carried out using the technique of 'Structural Equation Modeling (SEM)' and analysis by using SPSS and Smart PLS software. The results indicated that the impact of the business intelligence on the project management at beta level is strong (beta = 0.735, p < 0.001). Furthermore, business intelligence influences the Digital Transformation (beta = 0.697, p < 0.001) that consequently has a positive impact on project management (beta = 0.163, p < 0.001). Considering the obtained findings, it can be said that the Digital transformation of HRM can be a partial mediator between business intelligence and project management. This study makes a contribution to Resource Based-View as it considers digital transformation of HRM a capability that uses technologies as a way to achieve competitive advantage.

This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are promises through which AI-driven marketing will meet business goals and be huge at societies' values.

The current research scrutinizes the relationship between the three model commitment components (affective, normative, and calculative commitment) and their various influences on customer loyalty. This is particularly in the banking sector setting in Jordan. A self-reported questionnaire was distributed to collect primary data for analysis. 333 completed questionnaires were analyzed via using PLS software to extract the effect of e-service quality on the relationship between customer commitment and loyalty. The results of this study demonstrate that the affective type of commitment has a positive impact on customer loyalty followed by normative commitment and lately by calculative commitment. Moreover, the results show that the influence of the dimensions of customer’s commitment on loyalty is moderated by e-service quality. This study indicates that affective commitment elements (self-identification, sense of belonging and emotional attitudinal components) are essential for customers when they deal with their bank. On the other hand, the cost associated with leaving has shown to have the weakest impact on customer loyalty. Companies must know that customers may switch even though the cost associated with leaving is high.