Mohammad Mousa Mousa

Purpose: This study examines customers’ adoption of artificial intelligence (AI) in the Jordanian telecommunications sector by extending the technology acceptance model (TAM). Specifically, it aims to investigate the effects of perceived usefulness, perceived ease of use and perceived anthropomorphism on actual use of AI, while testing customer intention as a mediator and technology trust as a moderator. Design/methodology/approach: A quantitative approach was employed. Data were collected through self-administered questionnaires from customers of telecommunications companies in Jordan. Using stratified random sampling, 482 questionnaires were distributed, and 438 valid responses were analyzed. Partial least squares structural equation modeling using SmartPLS 4 was applied to assess the measurement model, structural relationships, mediation effects and moderation effect. Findings: The results show that perceived ease of use and perceived anthropomorphism significantly and positively influence customers’ intention to adopt AI, whereas perceived usefulness has no significant effect. Customer intention significantly predicts actual AI use and mediates the relationships between perceived ease of use, perceived anthropomorphism and actual AI use. However, intention does not mediate the relationship between perceived usefulness and actual AI use. Technology trust significantly moderates the relationship between customer intention and actual AI use. Practical implications: Telecom providers should design AI-enabled services that are simple, intuitive, human-like and trustworthy. Managers should also communicate the tangible benefits of AI more clearly to strengthen customers’ usefulness perceptions and encourage sustained usage. Originality/value: This study extends TAM by integrating perceived anthropomorphism and technology trust into a mediated-moderated model of AI adoption in an underexplored Middle Eastern telecommunications context.

الهدف: هدفت هذه الدراسة إلى التعرف إلى أثر الاتصالات التسويقية المتكاملة على النية الشرائية لعملاء شركات التأمين في مدينة رام الله. التصميم/ المنهجية / النهج: تكون مجتمع الدراسة من عملاء شركات التأمين في مدينة رام الله. اعتمد الباحثون على المنهج الوصفي والتحليلي، وتم توزيع استبيانات على عينة ملائمة للدراسة بلغت (336) مفردة. استرد الباحثون (295) استبانة صالحة للتحليل الإحصائي باستخدام برنامج Smart-PLS لتحليل البيانات. النتائج: أظهرت الدراسة وجود أثر إيجابي للاتصالات التسويقية المتكاملة (الإعلان، تنشيط المبيعات، التسويق المباشر) على النية الشرائية لعملاء شركات التأمين، باستثناء البيع الشخصي الذي لم يظهر له تأثير إيجابي. كما بينت النتائج أن العمر والنوع الاجتماعي لهما تأثير إيجابي على النية الشرائية، بينما لم يظهر التعليم وسنوات الخبرة أي تأثير معنوي على النية الشرائية. الأصالة/ القيمة: تُقدم هذه الدراسة رؤى مهمة حول تأثير الاتصالات التسويقية المتكاملة على النية الشرائية للعملاء، وتبرز أهميتها مقارنةً بالأبحاث السابقة التي تناولت الموضوع في سياقات أخرى. التوصيات: - ضرورة دراسة الأسباب الكامنة وراء ضعف ثقة...

Artificial intelligence (AI) marketing technologies are reshaping customer engagement in service sectors, yet their performance within integrated digital ecosystems remains poorly understood. Existing research often examines AI tools in isolation, overlooking how the holistic quality of the virtual customer experience (VCE) shapes their impact on consumer decisions, particularly in intangible service contexts such as telecommunications. This study addresses this gap by investigating the influence of four AI technologies—chatbots, dynamic pricing, voice search, and visual search—on purchasing decisions, with VCE tested as a critical moderating mechanism. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) and survey data from 487 telecommunications customers in Saudi Arabia, the findings confirm significant positive direct effects for all four AI tools. Moreover, the VCE significantly amplifies these individual relationships and further strengthens their combined contribution to decision quality, enabling the model to explain 71.2% of the variance in purchasing decisions. The results indicate that competitive advantage in AI-enabled service markets depends not on deploying isolated technologies, but on orchestrating a coherent, high-quality virtual experience ecosystem. By integrating the Technology Acceptance Model (TAM) and Stimulus–Organism–Response (SOR) framework, this study advances the theoretical understanding of how AI and experience design jointly enhance digital decision-making. Practically, it underscores the need for managers to prioritize integrated VCE design to drive sustainable consumption and strengthen customer loyalty in increasingly digital service environments.

Facing growing sustainability challenges and the critical priority of digital transformation, this study explores, through the lens of the dynamic capability view, the links between big data, sustainable performance, and green supply chain in a circular economy logic, filling a notable gap in emerging markets, particularly the pharmaceutical sector. Our study proposes an original conceptual model linking big data analytics to the circular economy, tested with 275 employees from the Saudi pharmaceutical sector. The results, obtained through state-of-the-art PLS-SEM modeling, indicate a significant positive impact of big data analytics on sustainable performance and green supply chain management within the circular economy framework. The study also reveals the crucial mediating role of sustainable performance and green supply chain management in the relationship between big data analytics and the circular economy. Our study proposes an integrated framework for understanding how digital technologies support the circular economy in emerging markets, with practical implications for pharmaceutical sector actors and policymakers, in line with Saudi Arabia’s Vision 2030.

This study investigates the determinants of chatbot adoption intention in Jordan's civil status and passport department, with a particular focus on technology trust as a moderating variable. Drawing on the Technology Acceptance Model (TAM), we developed and tested hypotheses regarding chatbot adoption factors. The research employed a quantitative approach, collecting data from 687 valid respondents out of 743 distributed questionnaires. Analysis using Smart-PLS software revealed that most examined factors positively influenced adoption intentions, with one notable exception: ease of use showed no significant impact on user attitudes. The findings confirmed that positive attitudes toward chatbots significantly enhanced adoption intentions, while trust in technology strengthened this attitude-intention relationship. This study extends existing theoretical frameworks by providing empirical evidence from a Middle Eastern context, specifically in Jordan's public sector, offering valuable insights for both researchers and practitioners implementing chatbot solutions in public services. The results particularly emphasize how trust in technology shapes user acceptance in the Jordanian context, contributing new perspectives to the current understanding of chatbot adoption dynamics.

This study focused on examining the effects of marketing artificial intelligence on customer attitudes towards the products offered by Palestinian cellular telecommunications companies. The study population includes customers of telecommunications companies in the city of Nablus .The study tool was distributed to a Purposive Sample of )357( individuals ,as chosen by the researchers .A total of 324 valid questionnaires were retrieved for statistical analysis. The study utilized a descriptive and analytical approach ,with the statistical program )SPSS( being employed .The study found that marketing artificial intelligence variables have a positive impact on customer attitudes towards use .The study proposed several recommendations ,one of which is to enhance the skills of workers in the cellular communications sector in utilizing artificial intelligence technologies .This can be achieved through intensive training courses focused on this field.

This study aimed to assess the influence of advertising content on social media platforms on the satisfaction levels of customers of Palestinian cellular telecommunications companies, specifically Jawwal and Ooredoo, in Ramallah. The study employed a convenience sampling method to distribute questionnaires, resulting in a response rate of 91%. The findings of the study indicated a positive correlation between social media advertising content and customer satisfaction, particularly concerning its dimensions, namely credibility, enjoyment, excitement, and information. Moreover, the study underscored the respondents’ keen interest in understanding the impact of social media advertising content on customer satisfaction. Recommendations included avoiding the repetition of content to prevent diminishing levels of excitement and interest among consumers. Moreover, the study advocated for the engagement of specialized personnel to oversee advertising posts on social media platforms, fostering trust and interaction between customers and the company. Additionally, the study advised seeking expertise in digital marketing to optimize the company’s marketing strategies, emphasizing the importance of credibility and trust in advertising endeavors.

This Study to identify Testing the effectiveness of Influential Factors Affecting Customers’ Intention to use Chatbots. The study found a high impact of the influencing factors (Ease of Use, Trust, Benefit, Interaction) on customers’ intention to use chatbots, & Telecommunications companies’ reliance on chatbot systems in service provision processes contributes significantly to raising the level of service provided by them. The study recommended that encouraging researchers to conduct more studies concerned with chatbots & addin, g other influential factors to measure intention to use, work to keep pace with Technological developments, Educating Customers about the Use of Chatbots.