Adoption Of Computing Research Articles

Perceived Usefulness, Perceived Ease of Use, Facilitating Condition, Social Influence, and Personal Innovativeness of Accounting Students Cloud Computing Adoption

This study aims to test the influence of perceived usefulness, perceived ease of use, facilitating condition, social influence, and personal innovativeness in cloud computing adoption. This research is important because of the high demands of understanding student technology which can be started by adopting cloud computing in learning. Students can use cloud computing to share information, assignments, and work that can be accessed with various devices. This research was conducted on students at two state universities in Indonesia. The study used SEM in the analysis process. This research was conducted on students at two state universities in Indonesia. The results of questionnaire to 126 students indicate that the intention to use the cloud is determined by the perceived ease of use and facilitating condition. Three other variables used, perceived usefulness, social influence, and personal innovativeness were not shown to have an effect on cloud computing adoption intentions. The implication of this research is continuous research related to the use of information systems in learning.

Cloud Computing Adoption and Use: A Systematic Review

ABSTRACT The advent of Cloud Computing has brought tremendous growth to businesses. Enterprises, known for their cost savings, flexible and scalable features, are better managed today. Unfortunately, high dependency on service providers, data security issues, and high set-up costs are becoming major issues along with low adoption rates in developing countries. Despite the infrastructure deficit, there is a need for studies to focus on theories of adoption and use. Therefore, this study aims to systematically review empirical studies on the adoption and use of cloud computing in general to identify relevant factors determining organizational intention to use, actual use, and the impact of cloud computing services on performance. This study investigated the causal factors responsible for the adoption, use and performance of cloud computing through a systematic literature review. This study examined 150 related studies in various databases such as IEEE Xplore, Emerald, Springer link and Science Direct. Thirty-six (36) main factors were identified and the results showed that thirteen factors appeared most frequently: top management support, relative advantage, compatibility, security, complexity, technology readiness, firm size, competitive pressure, trial, cost savings, Perceived usefulness, perceived ease of use and personal innovativeness. Most of these factors are related to technology. This study serves as a foundation for future research and advancement of theory development in the adoption, use, and performance of cloud computing. It also provides inside information on user preferences and is crucial for service providers, business owners and government. Keywords: Cloud Computing, adoption, systematic literature review, determinants, utilization, performance.

Improvement of the Secure Integration of IoT and Cloud Computing using Hybrid Encryption

Wireless Sensor Network (WSN) is an essential technology in many Internet of Things (IoT) applications, and since sensor nodes suffer from limited resources, it has become possible to overcome storage capacity problems using cloud computing, the integration of Internet of Things (IoT) with cloud computing (CC) seeks to achieve new levels of efficiency in service delivery. Security and privacy are key factors that slow down the rapid and widespread adoption and deployment of both IoT and cloud computing. In the proposed model, an integrated IoT system with cloud computing was developed starting from the analysis, and design, to the implementation to connect IoT devices with the cloud, the security is achieved by using a hybrid encryption mechanism which provides the performance advantages of symmetric and asymmetric encryption algorithms. Where the Elliptic Curve Cryptography (ECC) algorithm is used for key generation and AES (Advanced Encryption Standard) algorithm is used for encryption and decryption of the sensors' data to provide a reliable computing environment. We have implemented the proposed system and showed the results of using CONTIKI COOJA 3.0 that connected with the cloud service provider, Evaluate a set of performance metrics such as power consumption, packet delivery ratio, and the algorithm execution time, in addition to verifying network immunity against the black hole attack.

Acceptance of a flipped classroom to improve university students’ learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT)

Higher education has given the flipped classroom a lot of attention as a result of its pedagogical success. As a result of the adoption of social media, smartphones, and computers in the classroom, new strategies for providing online courses, such as flipped classrooms, have evolved. To further understand the effects of such technology integration in teaching, the study looked at the responses of 213 undergraduate students at King Faisal University. For a semester, participants took their regular classes in a flipped classroom. The participants answered a survey made expressly for this study to find out if they would still be willing to use flipped classes following this experience. A structural equation modeling approach was used to analyze the research paradigm, which is based on the technological adoption model. The findings demonstrated that each variable category had a favorable influence on perceived usefulness and perceived ease of use. Perceived utility and ease of use serve as mediating elements in the relationship between independent variables and attitudes toward adopting flipped classrooms. Additionally, the findings indicated that ATFC and BIFC have a positive influence on the acceptance of flipped classrooms. In terms of education and learning, the utilization of classroom instruction is positively impacted by both ATFC and BIFC. These findings show that attitudes toward blended learning and intentions to use flipped classrooms have the biggest impacts on the adoption of the concept in Saudi Arabia higher education.

Probing Determinants Affecting Intention to Adopt Cloud Technology in E-Government Systems

Adopting e-government services presents numerous challenges for governmental sectors in developing countries. These problems can fail some projects involving e-government. Therefore, a solution is required to address these problems. This paper presents a conceptual model and measurement to identify crucial factors that impact cloud computing technology in e-government to address the issues with e-government. According to the recent studies on technology adoption models, a theoretical model is proposed in this study. Extracting items from the literature and adapting them, creates the measurement scales for the proposed model’s structures. Through the use of face validity, pre-testing, and a pilot study, the authors confirm the scales’ content validity and reliability. The data used for this study were collected by the authors from 40 information technology IT professionals for the pilot study in the top 10 government departments in Libya who are responsible for many IT decisions in e-government. In this study, the authors first examine the reliability of the scale using Cronbach’s alpha and perform exploratory factor analysis to assess the scales’ validity. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). The findings demonstrate that the scale measurements satisfy the standard requirements for the validity and reliability According to previous studies on cloud computing adoption from the IS perspectives, this paper theoretically provides a combination model for investigating the cloud-based implementation services to provide a more comprehensive model and the objective is to develop an empirical instrument for analyzing countries’ e-government adoption of cloud computing.

Intelligent data deduplication with Deep Transfer Learning Enabled Classification Model for Cloud-based Healthcare System

The extensive adoption of cloud computing (CC) enabled healthcare systems in attaining medical data from different data sources sustained by heterogeneous cloud providers. Data deduplication (DD) is a proficient method to effectually share and store data in the cloud server. At the same time, deep learning (DL) models can be applied for effective decision-making in the cloud-based healthcare system. With this motivation, this study develops an Intelligent DD with Deep Transfer Learning Enabled Classification Model for Cloud-based Healthcare System (IDDTLC-CHS) model. The presented IDDTLC-CHS model aims to accomplish effective DD and classification in the cloud-enabled healthcare environment. For DD, the neighbourhood correlation sequence (NCS) algorithm is employed which generates optimum code words and is then compressed by Deflate model. Besides, the data classification module involves a series of processes namely fuzzy c-means (FCM) segmentation, Xception feature extraction; bidirectional gated recurrent unit (BiGRU), and seagull optimization algorithm (SGO). The SGO algorithm is applied for optimal adjustment of the parameters involved in the BiGRU model. To assess enhanced outcomes of the IDDTLC-CHS model, a wide-ranging simulation analysis is carried out using the benchmark dataset. The comparative analysis reported the betterment of the IDDTLC-CHS model compared to other recent approaches.

THE GAMIZED FORM OF TEACHING STUDENTS WITH DISABILITIES THROUGH THE USE AND UTILIZATION OF THE COMPUTER

Obviously, the gamified form of computer use and utilization in the teaching of students with disabilities has not been sufficiently investigated and studied regarding its contribution to their development and promotion. In this sense, the specific topic was chosen to examine to what extent this way and form of computer adoption and use affects, on the one hand, the processes and the result of the educational process and learning of these individuals/students, on the other hand, the their pedagogical and academic image and performance in all areas. Regarding the method of preparation of the specific work, the critical-interpretative review of the domestic and foreign language literature on this subject was selected and used. The results of the research demonstrate a significant trend and increase in the rates of computer use in the aforementioned form in the teaching and learning of people/students with disabilities, while regarding its contribution to the positive increase in their academic performance there is insufficient evidence from various scientific studies to support the above assumption.

Precursors of Cloud Computing Adoption in Selected Banks in Kenya

Purpose: The study analyzed the precursors of adoption of cloud computing in selected banks in Kenya. Specifically, the study sought to establish the effect of data security on adoption of cloud computing in selected banks in Kenya, to establish how organizational culture affects adoption of cloud computing in selected banks in Kenya, to establish how supplier lock- in affects adoption of cloud computing in selected banks in Kenya and to establish how regulatory policy affects adoption of cloud computing in selected banks in Kenya.
 Methodology: The study employed descriptive research design and inferential statistics. The target population was 366 ICT staff from 3 selected banks namely NCBA, KCB Bank and Equity bank. The selected banks had the largest market share according to published CBK supervisory report for year 2020. The sample size was 191 respondents. A structured questionnaire was used to collect the data. Responses in the questionnaires were tabulated, coded and processed by use of a computer statistical package for social sciences version 28 (SPSS) program to analyze the data. The responses from the open-ended questions were listed to obtain proportions appropriately and then reported by descriptive narrative. Descriptive statistics like mean, standard deviation were used. The ANOVA test was used to establish the findings from the study and results presented in graphs and charts.
 Findings: Cloud computing adoption was evaluated for the select commercial banks across three areas namely core-banking systems, middle office and compliance systems and back-office, data science and innovation systems over a period of five years. The respondents indicated that no more than one cloud computing project was either in planning, implementation, failed or completed stages, indicating that despite the perceived benefits of cloud computing there are precursors that need to be addressed if the commercial banks are to fully embrace cloud computing.
 Unique contribution to theory, practice and policy: In terms of policy, the findings of the study will be important to regulators like CA, CBK and other institutions that regulate financial institutions in coming up with relevant guidelines when it comes to handling customer data within Cloud Computing environment. It gives banking sector perspective of some of the issues that require attention if the envisaged benefits of clod computing are to be fully realized. This is important not only to the policy makers but also to the cloud service providers . Additionally, the findings give a theoretical basis of validating the antecedents of cloud computing adoption in the banking sector in Kenya and this can be extended to the rest of the world. The findings give a practical perspective of the real concerns the banks have to contend with from a practical perspective and therefore very critical in advancement of cloud computing technologies.

To adopt or not to adopt? The determinants of cloud computing adoption in information technology sector

This research is mainly focused on the adoption of cloud computing in the information technology (IT) industry of a developing country, Pakistan by using the theoretical lens of technology acceptance model (TAM) and Elaboration Likelihood Model (ELM). Cloud computing, being one of the latest technologies in the field of IT, has been recently adopted by organizations around the globe, although developing nations have recently started using this technology in their supply chain processes. This study involved the employees of IT industry working in the capital city of Pakistan, i.e. Islamabad. Sample respondents consisted of 213 employees of the IT based organization. Data was collected online by employing structured questionnaires based on past literature. The results revealed that there exists a positive and significant relationship between perceived security, argument advantage, source credibility and perceived usefulness. Additionally, the outcome of the study supported the significant relationships between perceived usefulness and attitude towards adoption of cloud computing, perceived usefulness and intention to adopt cloud computing, and attitude towards cloud computing and intention to adopt cloud computing. The research study has managerial and practical implications. It is one of first of its kind that explores some of the factors leading to adoption of cloud computing in of IT companies in Pakistan.

The TOEQCC Framework for Sustainable Adoption of Cloud Computing at Higher Education Institutions in the Kingdom of Jordan

The extensive use of cloud computing influences changes in managing information technology and communication systems. The term “Cloud Computing” refers to a new management information system that emphasizes the distribution of various computer services across the internet, such as the World Wide Web. Security and privacy concerns and the deployment of resources in shared settings are only a few of the difficulties posed by cloud computing. This study’s overarching goal is to aid Jordanian higher education institutions (JHEIs) in making informed decisions about cloud computing by creating a framework that considers the most important elements influencing adoption. This study, therefore, presents a framework for the adoption of cloud computing in JHEIs by modifying the Diffusion of Innovation (DOI) theory, the Technology Acceptance Model (TAM), and the Technology, Organization, and Environment (TOE) framework. To better understand the elements influencing the adoption of cloud computing in the context of JHEIs, the authors offer a framework they call the Technology-Organization-Environment-Quality of Cloud Computing Adoption (TOEQCC), which builds on the fundamental theories and proposed models. The study aimed to solve the problem of cloud computing adoption at higher educational institutions through suggesting a new framework, which aims to improve the awareness of cloud computing factors as well as the roadmap for the adoption process. Eleven different Jordanian universities (both governmental and private) collaborated on this study. In addition to gathering data from the Jordanian Minister of Higher Education (JMHE) and the Jordanian Higher Education Accreditation Commission, the research team also performed three focus groups with Jordanian students and distributed three hundred questionnaires (JHEAC). NVivo was used to analyze the data following the steps: data reduction, data visualization, and conclusion drawing/verification. Statistics and frequency data are shown in tables, pie charts, bar charts, and column charts. Other tools were employed, such as Microsoft Visio and Microsoft Business Intelligence.

Probing the factors influencing cloud computing adoption in healthcare organizations: A three-way interaction model

The purpose of this study is to probe the influencing factors of cloud computing adoption in healthcare organizations. The study used the extended technology acceptance model (TAM) and motivation model (MM) to broaden the research model. The study proposed awareness, cost reduction, perceived security and privacy, and compatibility as extended factors of TAM. The study also proposed two-way interaction impacts of resistance to change and two-way and three-way interaction impacts of MM factors (extrinsic and intrinsic motivation). The research model was empirically tested on 512 responses gathered through a survey questionnaire by structural equation modeling. The finding concluded that all four extended factors significant predictors of TAM factors. Furthermore, resistance to change is significantly negative, and MM factors significantly positive moderate the relationship between behavioral intention and adoption of cloud computing. The MM factors also have significant three-way interaction impacts. The study's findings contributed more insight into the literature and practice of cloud computing adoption.

Is cloud computing the digital solution to the future of banking?

This study investigates the impact of banks’ strategic move to cloud computing on bank performance and risk-taking. Based on a novel index of banks’ exposure to cloud computing, we find that banks’ adoption of cloud computing is associated with lower cost efficiency, higher profit efficiency, and greater operational risk using data on Chinese banks over the period 2008–2019. We also find that cloud computing interacts with other newly emerging technologies, leading to synergy gains in cost efficiency and operational risk control but with a substitutive effect on profit efficiency from blockchain. The findings are of timely policy importance and practical relevance for regulators, policy-makers, and bank managers.

A Mixed Methods Systematic Analysis of Issues and Factors Influencing Organizational Cloud Computing Adoption and Usage in the Public Sector: Initial Findings

A Mixed Methods Systematic Analysis of Issues and Factors Influencing Organizational Cloud Computing Adoption and Usage in the Public Sector: Initial Findings

Algorithmic TCAMs: Implementing Packet Classification Algorithms in Hardware

The adoption of cloud computing and the deployment of new services require more and more computing and networking resources in large data centers. In particular, there is a need for faster, rich featured switches. Today, switching integrated circuits can handle more than 50 Tb/s and are expected to reach 100 Tb/s next year. This trend is likely to continue, approaching petabit capacities in a few years. At the same time, switches need to support more advanced packet classification features. This poses many challenges to the designers of switching integrated circuits, creating a need for innovations to move forward. One of those challenges is to support programmable packet classification with large rulesets at wire speed using limited silicon footprint. Unfortunately, traditional solutions like ternary content addressable memories (TCAMs) have high cost in area and power, and therefore are not a viable option for large on-chip rulesets, so new alternatives are needed. In the last two decades, researchers have extensively studied the problem of packet classification, proposing many algorithms based on standard memories, mostly targeting software implementations. These packet classification algorithms could be a solution to enable large on-chip classification rulesets using standard memories. However, porting the standard packet classification algorithms to a hardware implementation is not a trivial task, due to the different requirements and the different kinds of memory and computing resources available on application-specific integrated circuit (ASIC) switching chips. This article describes a packet classification design tailored for high-speed switching integrated circuits, which is currently used in the NVIDIA® Mellanox® Spectrum® switching ASIC product line, illustrating how to solve the mismatch between the usual software-based classification algorithms and the specific requirements of a hardware implementation.

An Exploratory Study on Cloud Computing Adoption in few Selected Financial Organisations

An Exploratory Study on Cloud Computing Adoption in few Selected Financial Organisations

University Educational Administration Management Platform Integrating Distributed Real-time Cloud Computing System

The prosperity of the economy has made the society develop rapidly, and the traditional education management system can no longer meet the needs of the modern society. Under the background of college enrollment expansion, it has brought new challenges to school management and development. In recent years, the evolution and widespread adoption of virtualization, service-oriented architecture, autonomous, and utility computing have converged to give birth to a new paradigm: cloud computing. Cloud computing allows on-demand delivery of software, hardware, and data as a service. Cloud computing has the characteristics of massive processing and storage capacity, high efficiency, virtualization, and low cost. It has changed the traditional way of accessing software and hardware, providing users with convenient services and computing resources, which has achieved remarkable results in the related fields. Meanwhile, cloud computing plays an important role in education and teaching through its wide application in various fields. Based on this, this paper aims to study the application of distributed real-time cloud computing system in educational administration management in colleges and universities. This paper establishes a university educational administration management platform based on the cloud service computing system, and applies the management technology and distributed storage technology of the cloud computing platform. The system constructed in this paper significantly improves the utilization of CPU and memory. The research results of this paper showed that the response speed of the educational administration management system built through cloud computing has been significantly improved, with an average response time of 1.3s and an error of less than 0.4.

Determinants of Mobile Cloud Computing Adoption by Financial Services Firms

Prior studies have found that mobile cloud computing could bring substantial cost savings to firms, ultimately resulting in reduced transaction cost to customers. Despite this, financial firms in Fiji are slow adopters of mobile cloud computing. The study identifies the challenges faced by financial firms in the adoption of mobile cloud computing to advance the literature on innovation adoption with evidence from a unique context – a Pacific island country. The context is important as the issues are likely to be similar in other developing and remote island countries but the extant research is largely confined to developed countries. Our findings suggest that the lack of mobile cloud computing policy, infrastructure constraints, and security constraints, among others are the main barriers to the adoption thereof. The study contributes by presenting a revised model based on factors that emerged from the study.

Data governance in healthcare information systems: A systematic literature review

Background: This study aimed to investigate data governance (DG) related to challenges associated with healthcare information systems (HIS), by reviewing guidelines emerging from academic sources as part of a consolidated systematic literature review (SLR). The research contributed theoretically towards the body of knowledge, by reviewing challenges and guidelines related to DG within the healthcare environment. It contributed practically to the body of knowledge through understanding the healthcare information’s systems status. The study also contributed methodologically and significantly to SLR strategies.Objectives: The objective of this study was to understand the features of HIS; acquire information about DG success and understand the influence noted on DG.Method: The study conducted an SLR over the period 2010–2020. Literature collection was not only restricted to South African publications but was extended to international sources. This study adapted a mono method.Results: The study revealed that many organisations have realised that the only method to fix the data problem is the implementation of effective DG. With the increased adoption and rise of cloud computing, DG is gaining interest amongst specialists.Conclusion: The shift from paper-based systems led organisations to seek organisational change through digital transformation. The proper collection and utilisation of electronic healthcare record is the foundation of the digital healthcare. Many organisations value DG as a promising method of maintaining data as a valuable asset.

Identifying Challenges for Clients in Adopting Sustainable Public Cloud Computing

Sustainable Cloud Computing is the modern era’s most popular technology. It is improving daily, offering billions of people sustainable services. Currently, three deployment models are available: (1) public, (2) private, and (3) hybrid cloud. Recently, each deployment model has undergone extensive research. However, relatively little work has been carried out regarding clients’ adoption of sustainable public cloud computing (PCC). We are particularly interested in this area because PCC is widely used worldwide. As evident from the literature, there is no up-to-date systematic literature review (SLR) on the challenges clients confront in PCC. There is a gap that needs urgent attention in this area. We produced an SLR by examining the existing cloud computing models in this research. We concentrated on the challenges encountered by clients during user adoption of a sustainable PCC. We uncovered a total of 29 obstacles that clients confront when adopting sustainable PCC. In 2020, 18 of the 29 challenges were reported. This demonstrates the tremendous threat that PCC still faces. Nineteen of these are considered critical challenges to us. We consider a challenge a critical challenge if its occurrence in the final selected sample of the paper is greater than 20%. These challenges will negatively affect client adoption in PCC. Furthermore, we performed three different analyses on the critical challenges. Our analysis may indicate that these challenges are significant for all the continents. These challenges vary with the passage of time and with the venue of publication. Our results will assist the client’s organization in understanding the issue. Furthermore, it will also help the vendor’s organization determine the potential solutions to the highlighted challenges.

Development and Evaluation of a Cloud Computing Adoption Framework (CCAFF) for Retail Banks in Bahrain

The Information Technology era supports the adoption of Cloud Computing (CC) on a large scale in many business fields, at which the Financial Institutions (i.e., Banking sector) is not an exception. Several gaps were found during an attempted literature reviewing. While several CC methods, strategies, or frameworks have been proposed or utilized for CC adoption in many economic sectors including the Financial institutes (FI)- Banking, it is still a relatively new initiative in many other countries including Bahrain. While Enterprise Architecture (EA) is claimed to be a leading information and business management discipline to develop an architecture that guides the transformation to CC adoption of an enterprise from a baseline state to a target state. However, there is an evident lack of scholarly articles on the development of CC adoption frameworks from EA perspective. Also, it was found that scholarly articles in the evaluation of CC adoption framework are scarce. To address those gaps, this paper aims at developing and evaluating a CCAFF for the CC adoption in Bahraini Banks by adapting a tailored version of the Open Group Architecture Framework (TOGAF) and embedding a tailored version of an enterprise cloud adoption strategy (ECAS) and then evaluating the CCAFF based on several criterions. A six phased Design Science Research Methodology (DSRM) is employed to design the research report, guide, and develop the CCAFF, while the exploratory nature of the research necessitates the employment of a holistic single Case Study strategy for an FI-01 bank, based on semi structured interviews and document analysis data collection techniques. Alongside, the data was analyzed using pattern matching technique. For the CCAFF evaluation, Delphi technique was employed at which seven experts in two rounded panels contribute to the evaluation findings based on six criterions. The evaluation findings demonstrated promising results in terms of ease of use (86.4%), usefulness (84.6%), decision making support (86.6%), comprehensiveness (85.8%), time efficiency (84.8%), and usage intention (84.8%).