Samer Wa'el Abdel Latif Hamadneh

RESEARCH INTERESTS

B2B Marketing, Value Co-Creation, Value Co-Destruction, Supply Chain Management

Scopus Publications

A Mixed-Method Approach on the Evolution of Influencer Marketing and Its Ethical Consideration in UAE
Saleem Mushtaq, Beenish Shameem, Haitham M. Alzoubi, Barween Al Kurdi, Shanmugan Joghee, and Samer Hamadneh
EconJournals
The paper aims to identify the evolution of influencer marketing along with ethical considerations taken in terms of celebrity endorsement. The research also considers ethical considerations, like “transparency and cultural sensitivity,” as vital to successful influencer collaborations. This literature investigates the “evolution of influencer marketing” in the UAE, emphasising the change from celebrity confirmations to micro-influencers. It discovers the role of social media along with the influencer in determining purchasing decisions for the products. The review also classifies gaps in research regarding the influence of local cultural nuances and regulatory frameworks on “consumer behaviour and brand loyalty” in the influencer marketing scenery. The research study employs a mixed-method approach, mixing “quantitative surveys and qualitative interviews,” to discover personalized influencer marketing’s influence in the UAE. It measures consumer perceptions regarding awareness, data privacy, trust, and ethical practices, pointing to uncover key understandings that inform marketing strategies and regulatory frameworks in the area. Based on the findings from the data collected, customers are attracted to influencer marketing even in the UAE where several ethical considerations and regulations have been used. It is used to maintain data privacy, cultural sensitivity, and even transparency in influencer marketing.


Unveiling the Role of Artificial Intelligence: Navigating Personalized Content Marketing, Customer Engagement, and Commitment with Data Transparency and Security
Haitham M. Alzoubi, Beenish Shameem, Saleem Mushtaq, Barween Al Kurdi, Shanmugan Joghee, and Samer Hamadneh
EconJournals
This empirical and quantitative study delves into the complex interplay between personalized content marketing, customer engagement, artificial intelligence (AI), data transparency, security, and customer commitment in the healthcare sector. With the proliferation of digital technologies, organizations are increasingly turning to personalized content marketing strategies to enhance customer engagement and foster long-term commitment. This study investigates how AI serves as a mediator between the relationship of personalized content marketing and customer engagement, ultimately impacting customer commitment. Additionally, the moderating role of data transparency and security is explored to understand their potential to reinforce the link between personalized content marketing and customer engagement. Drawing from a sample of 231 respondents within the healthcare sector, data was collected using a structured questionnaire. The analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS SEM) via Smart PLS 4.0, enabling a robust assessment of the hypothesized relationships. The findings of this study offer significant insights into the role of AI in mediating the link between personalized content marketing and customer engagement, thereby influencing customer commitment. The results demonstrate the moderating effect of data transparency and security, indicating their capacity to strengthen the connection between personalized content marketing and customer engagement. These findings hold implications for healthcare organizations seeking to optimize their marketing strategies in the digital age, fostering deeper engagement and commitment among their customer base.


Examining the effect of virtual reality technology on marketing performance of fashion industry in Jordan
Muhammad Turki Alshurideh, Suhaib Anagreh, Emad Tariq, Samer Hamadneh, Nidal Alzboun, Barween Al Kurdi, and Sulieman Ibraheem Shelash Al-Hawary
Growing Science
This research examined how virtual reality technology affects the marketing performance of the fashion industry in Jordan. Based on a sample composed of 528 online customers, structural equation modeling (SEM) was utilized as a statistical approach for hypothesis testing. The research findings demonstrated that virtual reality technology had a positive significant impact on marketing performance. This examination provides many implications that managers in the fashion industry in Jordan could recognize, the most notable was encouraging them to focus on increased product demos utilizing virtual reality technology in order to improve customers' comprehension of the product and boost their confidence when making purchase decisions.


Utilizing Artificial Intelligence (AI) in enhancing customer-supplier relationship: An exploratory study in the banking industry
Muhammad Alshurideh, Barween Al Kurdi, Samer Hamadneh, Khireddine Chatra, Thouraya Snoussi, Haitham M. Alzoubi, Nidal Alzboun, and Gouher Ahmed
Growing Science
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.


How metaverse can enhance customer awareness, interest, engagement and experience: A practical study
Muhammad Alshurideh, Barween Al Kurdi, Anwar Al-Gasaymeh, Mohammad Abuhashesh, Asma Jdaitawi, Haitham M. Alzoubi, Samer Hamadneh, and Enass Alquqa
Growing Science
The future of the Internet lies in the utilization of contemporary virtual technology, the metaverse is a virtual ecosystem for communication and interaction. This study aims to determine how the metaverse can enhance customer awareness, interest, engagement and experience. The study population consists of customers of retail clothing stores. A questionnaire was developed to collect study data and distribute it electronically. The number of respondents reached (77) customers. Using path coefficients, the results indicate that metaverse can enhance customer awareness, interest, engagement and experience.


Entrepreneurial leadership: key to sustainable innovation and competitiveness in Islamic insurance companies in Jordan
Muhammad Turki Alshurideh, Alaa Alsharif, Enass Khalil Alquqa, Samer Hamadneh, Sulieman Al-Hawary, Ala’a Al-Momani, and Hasan Khaled AlAwamleh
Emerald
Purpose This study delves into the significant impact of entrepreneurial leadership (EL), organizational innovation (OI) and competitive advantage (CA) on the sustainability of organizations in the Jordanian Islamic insurance sector. This study aims to unravel the intricate dynamics among these pivotal factors, highlighting their collective role in the sustained success and resilience of Islamic insurance companies in Jordan. By examining the synergistic interplay between EL, OI and CA, the research seeks to offer invaluable insights into cultivating a sustainable future for these institutions. Design/methodology/approach This study adopts a positivist, quantitative approach to investigate the relationships between EL, OI, CA and organizational sustainability (OS). Data collection was achieved through questionnaires in a cross-sectional analysis of these variables. Convenience sampling yielded 389 valid responses, an 81% response rate, ensuring a thorough understanding of the dynamics within this framework. Findings The findings from the study on Jordanian Islamic insurance companies highlight the critical role of EL in influencing organizational dynamics. The research establishes a positive relationship between EL and both OI and OS. Furthermore, it identifies a significant positive correlation between EL and CA, underscoring the importance of leadership in securing a competitive edge. This study also emphasizes the vital role of OI in bolstering OS and confirms that a strong CA enhances OS, reinforcing the interconnectivity of these essential organizational components. Practical implications This study provides important insights for professionals in the insurance sector, especially those within the Jordanian Islamic insurance industry. It emphasizes the crucial role of EL in fostering innovation, competitiveness and sustainability. By understanding the significance of EL, companies can adopt more dynamic and effective strategies in leadership, organizational development and strategic planning, thereby enhancing their overall performance and resilience. Originality/value By conceptualizing EL and OS as second-order constructs, this study seeks to provide a detailed understanding of how EL catalyzes OI, CA and sustainability in an organizational context. This approach contributes significantly to the broader discussion on EL and OS, particularly within the Arab region and specifically in Jordan, offering nuanced insights into their roles and interrelations in shaping organizational dynamics.


Artificial Intelligence in Identifying Market Opportunities: Revolutionizing Entrepreneurial Strategy and Innovation
Muhammad Turki Alshurideh, Bilal Zakarneh, Samer Hamadneh, Gouher Ahmed, Channaganu Paramaiah, and Haitham M. Alzoubi
IEEE
This study focuses on how Artificial Intelligence (AI) affects market analysis and the exploring of market possibilities, in the Abu Dhabi hospitality industry. The study also examines how effective entrepreneurial strategies mediate this relationship while considering the influence of market volatility. To gather data a quantitative research method is used with 221 participants from the Abu Dhabi hospitality industry in the UAE. The research model is evaluated using Structural Equation Modeling (SEM) through SmartPLS 4.0 allowing for an analysis of the proposed connections. Initial data analysis suggests that utilizing AI in market analysis has an impact on identifying market opportunities. Additionally, the study finds that effective entrepreneurial strategy development acts as a mediator in this relationship meaning that the positive effects of AI are partly explained by how well entrepreneurial strategies implemented. Moreover, market volatility plays a moderating role, in influencing how strongly AI utilization relates to discovering market opportunities.


AI-Driven Talent Acquisition Systems: Transforming Recruitment Strategies in the Digital Age
Samer Hamadneh, Muhammad Turki Alshurideh, Enass Khalil Alquqa, Amer Al Kassem, Kakul Agha, and Haitham M. Alzoubi
IEEE
This empirical study focuses on the efficacy and efficiency of recruitment strategies in healthcare industry driven by organizational size, complexity as well as AI-based systems used for talent acquisition. These factors exert their influence through the mediating position that quality of candidate-job fit plays in this study. This research is conducted in the health sector in Dubai, United Arab Emirates with a valid sample of 309 employees from both public and private healthcare institutions. One of the main objectives is to measure how Al-driven, organizational size and complexity impacts efficacy and efficiency in recruitment strategies. In the case of health care, this study also considers how candidate-job fit quality mediates in such a relationship. In a quantitative way, there is an application of random sampling. The participants of this study were the employees in Dubai's health care industry, and a valid sample was formed from 309 respondents. To evaluate the hypotheses and model the interactions between the variables, the study uses partial least squares structural equation modelling, or PLS SEM. The research underscores the importance of organizational size and complexity and adds to the expanding body of knowledge on the use of AI in talent acquisition in the healthcare industry. The study intends to offer practical insights for healthcare organizations looking to improve their recruiting strategies through the implementation of AI-driven systems by investigating the mediating role of candidate-job match quality.


Machine Learning Applications in Social Media Marketing: Innovating Customer Engagement and Brand Building
Barween Al Kurdi, Muhammad Turki Alshurideh, Samer Hamadneh, Deepak Kalra, Sunita Marwaha, and Haitham M. Alzoubi
IEEE
The influence of using machine learning in social media marketing on consumer engagement and brand strength in the UAE retail sector is examined in this quantitative empirical study. The research uses an exploratory design and evaluates the hypotheses using structural equation modelling. Data were gathered from 237 respondents who represented the marketing, administrative, and IT departments of 27 significant retail businesses and shopping centers using a convenient sampling technique. The preliminary findings indicate to a positive correlation between machine learning use in social media marketing and consumer engagement as well as brand strength. Additionally, the research investigates into the mediating influence of content personalization, assuming that the extent of personalization is a critical factor in augmenting the associations that are observed. The study also looks into the moderating effect of the variety of social media platforms that are used. This study investigates whether the influence of machine learning on brand strength and consumer engagement differs depending on the range of platforms used in retail industry social media marketing strategy. Marketing experts could get benefit from the findings of the research to be useful in optimizing their social media marketing strategies by using machine learning technologies strategically, creating personalized content, and taking platform diversity into account


Exploring the impact of metaverse adoption on supply chain effectiveness: A pathway to competitive advantage
Muhammad Turki Alshurideh, arween Al Kurdi, Sara Yasin, Yousef Damra, Anwar Al-Gasaymeh, Haitham M. Alzoubi, Samer Hamadneh, Nidal Alzboun, and Enass Khalil Alquqa
Growing Science
In the rapidly evolving landscape of supply chain management, the advent of the metaverse presents a novel frontier with significant potential for enhancing operational effectiveness and excellence. This study aims to examine the effect of metaverse adoption on various dimensions of the supply chain, including resilience, agility, flexibility, and performance. Utilizing a quantitative research approach, the research analyzes survey data from a significant sample size of 737 organizations that have adopted metaverse technology into their supply chain operations. The employment of partial least squares structural equation modeling (PLS-SEM) offers a comprehensive understanding of the metaverse's role in enhancing the dynamism and efficiency of supply chains. This study contributes to the emerging field of digital transformation in supply chain management by providing empirical evidence on the effectiveness of metaverse technology. It bridges the gap in literature regarding the practical application of advanced digital solutions in enhancing supply chain operations and sets a foundation for future research in this area.


Empowering Supply Chain Management System with Machine Learning and Blockchain Technology
Muhammad Turki Alshurideh, Samer Hamadneh, Haitham M. Alzoubi, Barween Al Kurdi, Mohammed T. Nuseir, and Ahmad Al Hamad
Springer International Publishing



Robot-Based Security Management System for Smart Cities Using Machine Learning Techniques
Ahmad Qasim Mohammad AlHamad, Samer Hamadneh, Mohammed T. Nuseir, Muhammad Turki Alshurideh, Haitham M. Alzoubi, and Barween Al Kurdi
Springer International Publishing



The Impact of Demand Forecasting on Effective Supply Chain with Mediating Role of Strategic Planning in the UAE Pharmaceutical Industry
Haitham M. Alzoubi, Muhammad Turki Alshurideh, Mohammed T. Nuseir, Barween Al Kurdi, Ahmad AlHamad, and Samer Hamadneh
Springer International Publishing



The Impact of Customisation Strategy and Product Variety on Operational Performance in the UAE Construction Industry
Ahmad AlHamad, Barween Al Kurdi, Mohammed T. Nuseir, Haitham M. Alzoubi, Muhammad Turki Alshurideh, and Samer Hamadneh
Springer International Publishing



A Critical Review of Cloud Computing Architecture Empowered with Blockchain Technology
Ahmad Qasim Mohammad Al-Hamad, Samer Hamadneh, Mohammed T. Nuseir, Haitham M. Alzoubi, Barween Al Kurdi, and Muhammad Turki Alshurideh
Springer International Publishing



Automated Sales Management System Empowered with Artificial Intelligence
Muhammad Turki Alshurideh, Mohammed T. Nuseir, Barween Al Kurdi, Haitham M. Alzoubi, Samer Hamadneh, and Ahmad AlHamad
Springer International Publishing



Investigating the Online Buying Behavior in the UAE Online Retail Industry: The Role of Emotional Intelligence and Customer Perception
Muhammad Turki Alshurideh, Barween Al Kurdi, Enass Khalil Alquqa, Haitham M. Alzoubi, Samer Hamadneh, and Ahmad AlHamad
Springer International Publishing



Digital Sustainability and Strategic Supply Chain for Achieving a Competitive Advantage: An Empirical Evidence from Telecommunication Industry in the UAE
Enass Khalil Alquqa, Barween Al Kurdi, Haitham M. Alzoubi, Muhammad Turki Alshurideh, Samer Hamadneh, and Ahmad Al Hamad
Springer International Publishing



The Impact of Team Creativity and Continuous Improvement on Time-to-Market: An Empirical Evidence from the UAE Electronics Industry
Enass Khalil Alquqa, Muhammad Turki Alshurideh, Barween Al Kurdi, Haitham M. Alzoubi, Ahmad AlHamad, and Samer Hamadneh
Springer International Publishing



IoMT-Based Model to Predict Chronic Asthma Disease in Elderly People Using Machine Learning Techniques
Ahmad Qasim Mohammad AlHamad, Mohammed T. Nuseir, Samer Hamadneh, Muhammad Turki Alshurideh, Haitham M. Alzoubi, and Barween Al Kurdi
Springer International Publishing



The Mediating Role of Cyber Resilience in the Impact of Innovation Capabilities on Supply Chain Performance: Empirical Evidence from the UAE Petroleum Industry
Mohammed T. Nuseir, Samer Hamadneh, Barween Al Kurdi, Muhammad Turki Alshurideh, Haitham M. Alzoubi, and Ahmad AlHamad
Springer International Publishing



The Impact of Social Media Marketing on Online Buying Behavior via the Mediating Role of Customer Perception: Evidence from the Abu Dhabi Retail Industry
Barween Al Kurdi, Mohammed T. Nuseir, Muhammad Turki Alshurideh, Haitham M. Alzoubi, Ahmad AlHamad, and Samer Hamadneh
Springer International Publishing



The Mediating Role of Information Sharing in the Effect of Blockchain Strategy Information Security on E-Supply Chain in the UAE Real Estate Industry
Samer Hamadneh, Haitham M. Alzoubi, Enass Khalil Alquqa, Ata Al Shraah, Muhammad Turki Alshurideh, and Barween Al Kurdi
Springer International Publishing



The Impact of Information Sharing and Delivery Time on Customer Happiness: An Empirical Evidence from the UAE Retail Banking Industry
Muhammad Turki Alshurideh, Barween Al Kurdi, Enass Khalil Alquqa, Haitham M. Alzoubi, Samer Hamadneh, and Ahmad Al Hamad
Springer International Publishing



Role of Explainable Artificial Intelligence (EAI) in Human Resource Management System (HRMS)
Mohammed T. Nuseir, Muhammad Turki Alshurideh, Haitham M. Alzoubi, Barween Al Kurdi, Samer Hamadneh, and Ahmad AlHamad
Springer International Publishing