Naim Ahmad

Bio: Naim Ahmad is an academic researcher from King Khalid University. The author has contributed to research in topics: Cloud computing & Critical success factor. The author has an hindex of 10, co-authored 27 publications receiving 291 citations.

Enterprise systems: are we ready for future sustainable cities

Abstract: Purpose – This paper aims to revisit the adoption reasons of enterprise systems (ES) and supply chain management systems (SCMS) and to explore the new dimensions of sustainability required to be added in the whole process of adoption of these systems. Moreover, it aims to explore the benefits of ES to organizations and to relate these benefits to the ES adoption in future sustainable city settings. Future cities will have micro-industries requiring dynamic interactions and will be dependent on efficient supply chains. The recent developments in information and communications technology (ICT) such as cloud computing through its dynamic, on-demand and service-based delivery are making it possible to achieve those goals for supply chains. The ES in general and more specifically SCMS have integrated organizations into one seamless mesh. Design/methodology/approach – This paper presents a framework for adoption of sustainable ES in a smart city setting. The framework, firstly, is presented at a macro-level, pa...

E-learning services to achieve sustainable learning and academic performance: An empirical study

Abstract: E-Learning has proven to be the only resort as a replacement of traditional face-to-face learning methods in the current global lockdown due to COVID-19 pandemic. Academic institutions across the globe have invested heavily into E-Learning and the majority of the courses offered in traditional classroom mode have been converted into E-Learning mode. The success of E-Learning initiatives needs to be ensured to make it a sustainable mode of learning. The objective of the current study is to propose a holistic E-Learning service framework to ensure effective delivery and use of E-Learning Services that contributes to sustainable learning and academic performance. Based on an extensive literature review, a proposed theoretical model has been developed and tested empirically. The model identifies a broad range of success determinants and relates them to different success measures, including learning and academic performance. The proposed model was validated with the response from 397 respondents involved with an E-Learning system in the top five public universities in the southern region of Saudi Arabia through the Partial Least Squares regression technique using SmartPLS software. Five main factors (Learner’s Quality, Instructor’s Quality, Information’s Quality, System’s Quality and Institutional Quality) were identified as a determinant of E-Learning service performance which together explains 48.7% of the variance of perceived usefulness of ELS, 71.2% of the variance of use of the E-Learning system. Perceived usefulness of ELS and use of ELS together explain 70.6% of learning and academic performance of students. Hence the framework will help achieve the sustainable and successful adoption of E-Learning services.

Internet of medical things: Architectural model, motivational factors and impediments

Abstract: The field of Internet of Things (IoT) is progressing in a fashion that will transform the complete landscape of future internet. It will further provide opportunities into new domains for automation and integration of real word objects. Medical field is always at the forefront of innovation adoption. There are currently numerous applications of the concept in the medical field such as e-Health and m-Health. This paper has reviewed and proposed the architectural model to implement Internet of Medical Things (IoMT). Moreover using Carley's eight step content analysis technique, motivational factors for the adoption of IoMT have been identified. Finally the paper sheds light on the major impediment such as security and privacy issues. This work will help the medical professionals to smoothly integrate the IoMT in their domain and avoid the major pitfalls.

Relationship Modeling of Critical Success Factors for Enhancing Sustainability and Performance in E-Learning

Abstract: E-learning, a technology-mediated learning approach, is a pervasively adopted teaching/learning mode for transferring knowledge. Some of the motivational factors for its wide adoption are time and location independence, user-friendliness, on-demand service, resource richness, and multi-media and technology driven factors. Achieving sustainability and performance in its delivery is of paramount importance. This research utilizes the critical success factors (CSFs) approach to identify the sustainable E-learning implementation model. Fifteen CSFs have been identified through the literature review, expert opinions, and in-depth interviews. These CSFs have been modeled for interdependence using interpretive structural modeling and Matriced’ Impacts Croise’s Multiplication Appliquee a UN Classement (MICMAC) analysis. Further, the model has been validated through in-depth interviews. The present research provides quantification of CSFs of E-learning in terms of their driving and dependence powers and their classification thorough MICMAC analysis. The E-learning system organizers may focus on improving upon the enablers such as organizational infrastructure readiness, efficient technology infrastructure, appropriate E-learning course design, course flexibility, understandable relevant content, stakeholders’ training, security, access control and privileges, commitment, and being user–friendly and well-organized, in order to enhance the sustainability and performance in E-learning. This study will also help E-learning stakeholders in relocating and prioritizing resources.

The 51 V's Of Big Data: Survey, Technologies, Characteristics, Opportunities, Issues and Challenges

Abstract: Currently Big Data is the biggest buzzword, and definitely, we believe that Big Data is changing the world. Some researchers say Big Data will be even bigger buzzword than the Internet. With fast-growing computing resources, information and knowledge a new digital globe has emerged. Information is being created and stored at a fast rate and is being accessed by a vast range of applications through scientific computing, commercial workloads, and social media. In 2018, over 28 billion devices globally, are connected to the internet. In 2020, more than 50 billion smart appliances will be connected worldwide and internet traffic flow will be 92 times greater than it was in 2005. The usage of such a massive number of connected devices not only increase the data volume but also the velocity of data addition with speed of light on fiber optic and various wireless networks. This fast generation of enormous data creates numerous threats and challenges. There exist various approaches that are addressing issues and challenges of Big Data with the theory of Vs such as 3 V's, 5 V's, 7 V's etc. The objective of this work is to explore and investigate the status of the current Big Data domain. Further, a comprehensive overview of Big Data, its characteristics, opportunities, issues, and challenges have been explored and described with the help of 51 V's. The outcome of this research will help in understanding the Big Data in a systematic way.

Multivariate Data Analysis With Readings

Abstract: Thank you very much for reading multivariate data analysis with readings. As you may know, people have look hundreds times for their favorite books like this multivariate data analysis with readings, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they are facing with some infectious virus inside their desktop computer. multivariate data analysis with readings is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the multivariate data analysis with readings is universally compatible with any devices to read.

The impact of entrepreneurship education in higher education: A systematic review and research agenda

Abstract: Using a teaching model framework, we systematically review empirical evidence on the impact of entrepreneurship education (EE) in higher education on a range of learning outcomes, analysing 159 published articles from 2004-2016. The teaching model framework allows us for the first time to start rigorously examining relationships between pedagogical methods and specific outcomes. Re-confirming past reviews and meta-analyses, we find that EE impact research still predominantly focuses on short-term and subjective outcome measures and tends to severely under-describe the actual pedagogies being tested. Moreover, we use our review to provide an up-to-date and empirically rooted call for less obvious, yet greatly promising, new or underemphasised directions for future research on the impact of university-based entrepreneurship education. This includes, for example, the use of novel impact indicators related to emotion and mindset, focus on the impact indicators related to the intention-to-behaviour transition, and explore the reasons for some of the contradictory findings in impact studies including person-, context- and pedagogical model-specific moderators.