Mohammed A. Al-Sharafi
@utm.my
Universiti Teknologi Malaysia
Mohammed A. Al-Sharafi is currently working at the Department of Information Systems, Universiti Teknologi Malaysia. He obtained his Ph.D degree in Information Systems from the Faculty of Computing, Universiti Malaysia Pahang. He has MSc degree in Management Information System from Yarmouk University, Jordan. He has over 50 publications published in different journals, conferences, and book chapters. Most of his publications were indexed under the ISI Web of Science and Scopus. He is currently interested in research related to the acceptance, adoption, and diffusion of emerging technologies (e.g., cloud computing, Blockchain, OSNs, Big data, and IoT), and Quantitative Methods in Information Systems research.
RESEARCH INTERESTS
Mohammed A. Al-Sharafi is currently working at the Department of Information Systems, Universiti Teknologi Malaysia. He obtained his Ph.D degree in Information Systems from the Faculty of Computing, Universiti Malaysia Pahang. He has MSc degree in Management Information System from Yarmouk Universit
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Noor Islam Jasim, Saraswathy Shamini Gunasekaran, Mohammed A. Al-Sharafi, Muhammed Ibrahim, Abba Hassan, Moamin A. Mahmoud, and Adnan Bakather
Elsevier BV
Noor Al-Qaysi, Mostafa Al-Emran, Mohammed A. Al-Sharafi, Zaher Mundher Yaseen, Moamin A. Mahmoud, and Azhana Ahmad
Elsevier BV
Ebrahim Mohammed Alrawhani, Awanis Romli, and Mohammed A. Al-Sharafi
Elsevier BV
Mostafa Al-Emran, Noor Al-Qaysi, Mohammed A. Al-Sharafi, Mana Khoshkam, Behzad Foroughi, and Morteza Ghobakhloo
Elsevier BV
Ebrahim Mohammed Alrawhani, Awanis Binti Romli, Mohammed A. Al-Sharafi, and Gamal Alkawsi
Informa UK Limited
Behzad Foroughi, Bita Naghmeh‐Abbaspour, Jun Wen, Morteza Ghobakhloo, Mostafa Al‐Emran, and Mohammed A. Al‐Sharafi
Wiley
ABSTRACTIn the era of rapid technological advancement, generative artificial intelligence (AI) has emerged as a transformative force in various sectors, including environmental sustainability. This research investigates the factors and consequences of using generative AI to access environmental information and influence green purchasing behavior. It integrates theories such as the information adoption model, value–belief–norm theory, elaboration likelihood model, and cognitive dissonance theory to pinpoint and prioritize determinants of generative AI usage for environmental information and green purchasing behavior. Data from 467 participants were analyzed using a hybrid methodology that blends partial least squares (PLS) with artificial neural networks (ANN). The PLS outcomes indicate that interactivity, responsiveness, knowledge acquisition and application, environmental concern, and ascription of responsibility are key predictors of generative AI use for environmental information. Furthermore, environmental concerns, green values, personal norms, ascription of responsibility, individual impact, and generative AI use emerge as predictors of green purchasing behavior. The ANN analysis offers a unique perspective and discloses variations in the hierarchy of these predictors. This research provides valuable insights for stakeholders on harnessing generative AI to promote sustainable consumer behaviors and environmental sustainability.
Noor Islam Jasim, Saraswathy Shamini, Mohammed A. Al-Sharafi, Moamin A. Mahmoud, Muhammed Ibrahim, and Abba Hassan
Springer Nature Switzerland
Weiming Wang, Noorminshah A. Iahad, and Mohammed A. Al-Sharafi
Springer Nature Switzerland
Muhammed Ibrahim, Moamin A. Mahmoud, Mohammed A. Al-Sharafi, and Abba Hassan
Springer Nature Switzerland
Ala’a M. Al-Momani, Mohammed A. Al-Sharafi, Mufleh Amin AL Jarrah, and Omar Wassef Hijaeen
AG Editor (Argentina)
Introduction: Most bibliometrics reviews in the prior studies have focused on tracking the evolution, applications, and implications of Big Data in business through different sectors using Web of Science or Scopus databases. Moreover, none of these studies has addressed the differences between developed and developing countries. These gaps indicate that we need a bibliometric review that can identify current trends and unexplored areas. Objectives: This study aims to use a bibliometric approach to examine how Big Data is used in businesses using WoS and Scopus databases. Methods: A Systematic Literature Review was conducted based on the country's economic status using the SPAR-4-SLR protocol for this research. Results: The results show a significant growth in publications since 2013 among developed countries and since 2014 among developing ones such as the United States and the United Kingdom, along with China and India, respectively. Also, Machine Learning Overlaps Artificial Intelligence alongside Analytics, fueling innovative data-driven business processes around Big Data. Conclusions: This article explores the transformative power of Big Data across domains, stressing its ability to cause substantial breakthroughs within the digital economy
Keng-Boon Ooi, Garry Wei-Han Tan, Mostafa Al-Emran, Mohammed A. Al-Sharafi, Alexandru Capatina, Amrita Chakraborty, Yogesh K. Dwivedi, Tzu-Ling Huang, Arpan Kumar Kar, Voon-Hsien Lee,et al.
Informa UK Limited
Ibrahim Arpaci, Mohammed A. Al-Sharafi, and Moamin A. Mahmoud
Elsevier BV
Mostafa Al-Emran, Mohammed A. Al-Sharafi, Behzad Foroughi, Mohammad Iranmanesh, Rawan A. Alsharida, Noor Al-Qaysi, and Nor'ashikin Ali
Elsevier BV
Gamal Alkawsi, Nazrita Ibrahim, Mohammed A. Al-Sharafi, Abdulsalam Salihu Mustafa, Husni Mohd Radzi, and Luiz Fernando Capretz
Elsevier BV
Ala'a Al-Momani, T. Ramayah and Mohammed A. Al-Sharafi
Elsevier BV
Safwan Maghaydah, Mostafa Al-Emran, Piyush Maheshwari, and Mohammed A. Al-Sharafi
Elsevier BV
Gamal Alkawsi, Mohammed A. Al-Sharafi, and Qasim AlAjmi
Springer Science and Business Media LLC
Mostafa Al-Emran, Noor Al-Qaysi, Mohammed A. Al-Sharafi, Hussam S. Alhadawi, Hurmat Ansari, Ibrahim Arpaci, and Nor’ashikin Ali
Informa UK Limited
Osama Mohammad Alkhasoneh, Hamiza Jamaludin, Abdul Rahman i Bin Zahar, and Mohammed A. Al-Sharafi
Emerald
PurposeDespite the widespread use of social media globally, SMEs exhibit a below-average adoption rate. This raises critical questions about the reasons behind SMEs' limited engagement with this ubiquitous platform. The primary objective of this research is to explore the factors influencing the utilization of social media by small and medium-sized enterprises (SMEs) and assess its influence on brand awareness and customer engagement in the Jordanian context.Design/methodology/approachThis study utilizes a quantitative research approach to examine SMEs' adoption of social media. Data are collected from 290 SMEs in Jordan through paper-based and online surveys employing purposive sampling. The validity of the proposed model is confirmed using a partial least squares (PLS) approach, specifically employing SmartPLS 4 for analysis.FindingsThe results reveal that the examined model successfully captures the dynamics of social media usage among SMEs, shedding light on the significant drivers influencing their decision to use social media in their activities. The findings also underscore the pivotal role of social media usage in SMEs, particularly in enhancing brand awareness and fostering customer engagement within the Jordanian business landscape.Originality/valueThis study significantly contributes to the existing literature by highlighting the practical implications of social media activity, specifically in the context of SMEs. Using the UTAUT2 model to examine the drivers of social media use among SMEs and extend it to assess the broader impact of social media usage on brand awareness and customer engagement adds uniqueness to the study, providing a more nuanced view of social media usage in the SME sector.
Muhammed Ibrahim, Moamin A. Mahmoud, Mohammed A. Al-Sharafi, Abba Hassan, Noorminshah A. Iahad, and Saraswathy Shamini Gunasekaran
Springer Nature Switzerland
Ali Al-Tahitah, Ala’a Al-Momani, Mohammed A. Al-Sharafi, Mohammed Abdulrab, and Mohammed A. Hajar
Springer Nature Switzerland
Mohammed A. Hajar, Mohammed A. Al-Sharafi, Nazrita Ibrahim, Daing Nasir Ibrahim, Ahmed Saleh Al-Matari, Basheer Al-Haimi, and Ali Al-Tahitah
Springer Nature Switzerland
Abba Hassan, Moamin A. Mahmoud, Mohammed A. Al-Sharafi, Muhammed Ibrahim, Noorminshah A. Iahad, and Saraswathy Shamini Gunasekaran
Springer Nature Switzerland