Preliminary insight into cloud computing adoption in a developing country

doi:10.1108/JEIM-09-2014-0094

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Preliminary insight into cloud computing adoption in a developing country

Journal Article•DOI•

Preliminary insight into cloud computing adoption in a developing country

Prince Kwame Senyo¹, John Effah¹, Erasmus Addae²•Institutions (2)

University of Ghana¹, South Texas College²

23 Jun 2016-Journal of Enterprise Information Management (Emerald Group Publishing Limited)-Vol. 29, Iss: 4, pp 505-524

TL;DR: The findings indicate that relative advantage, security concern, top management support, technology readiness, competitive pressure and trading partners’ pressure were the TOE factors found to be significant in CCA in a developing country context.

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Abstract: Purpose – The purpose of this paper is to investigate the determinants of cloud computing adoption (CCA) in a developing country context through the lens of the technology, organisation and environment (TOE) framework. Design/methodology/approach – The study was carried out using the quantitative research methodology based on a survey of 305 organisations from different industries in Ghana. Based on the TOE framework, a conceptual model consisting of ten hypotheses were proposed and tested through a confirmatory factor analysis and logistic regression analysis. Findings – The findings indicate that relative advantage, security concern, top management support, technology readiness, competitive pressure and trading partners’ pressure were the TOE factors found to be significant in CCA in a developing country context. Conversely, firm size, scope, compatibility and regulatory support were found to be insignificant. Originality/value – This study provides insights into CCA across different industries in a dev...

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Journal Article•DOI•

Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions

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Hanan Elazhary¹•Institutions (1)

Information Technology University¹

15 Feb 2019-Journal of Network and Computer Applications

TL;DR: This paper attempts to disambiguate emerging computing paradigms and explain how and where they fit in the above three areas of research and/or their intersections before it becomes a serious problem.

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225 citations

Journal Article•DOI•

Cloud computing research: a review of research themes, frameworks, methods and future research directions

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Prince Kwame Senyo¹, Erasmus Addae², Richard Boateng¹•Institutions (2)

University of Ghana¹, Austin Community College District²

01 Feb 2018-International Journal of Information Management

TL;DR: The findings indicate that extant cloud computing literature tends to skew towards the technological dimension to the detriment of other under researched dimensions such as business, conceptualization and application domain.

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198 citations

Cites background from "Preliminary insight into cloud comp..."

...Thus, the issue of jurisdiction is identified as a major challenge hindering cloud computing development especially in developing countries where laws are always playing catchup with technology (Senyo et al., 2016)....
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...In this study, cloud computing is defined as the delivery of IT infrastructure and applications as a service on-demand to individuals and organizations via Internet platforms (Senyo et al., 2016)....
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Journal Article•DOI•

Unearthing antecedents to financial inclusion through FinTech innovations

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Prince Kwame Senyo¹, Ellis L.C. Osabutey²•Institutions (2)

University of Southampton¹, University of Roehampton²

01 Dec 2020-Technovation

TL;DR: In this article, the authors adopt the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Prospect theory to understand the antecedents that influence users' behavior toward financial technologies.

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110 citations

Journal Article•DOI•

Cloud computing adoption and its impact on SMEs’ performance for cloud supported operations: A dual-stage analytical approach

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Abul Khayer¹, Md. Shamim Talukder², Yukun Bao¹, Md. Nahin Hossain¹•Institutions (2)

Huazhong University of Science and Technology¹, North South University²

01 Feb 2020-Technology in Society

TL;DR: Results of SEM and neural network analysis indicate that the most significant predictor of cloud adoption is server location followed by facilitating conditions, relative advantage, service quality, top management support, computer self-efficacy, perceived risks, cloud provider's influence, and resistance to change.

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109 citations

Journal Article•DOI•

A hybrid multi-criteria decision-making method for cloud adoption: Evidence from the healthcare sector

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Mahak Sharma¹, Rajat Sehrawat•Institutions (1)

National Institute of Industrial Engineering¹

01 May 2020-Technology in Society

TL;DR: Whether the benefits of CCA outweighs its barriers is answered, thereby exploring the potential (and future) of CC for the advancement of healthcare provision.

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48 citations

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References

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Book•

Diffusion of Innovations

[...]

Everett M. Rogers

01 Jan 1962

TL;DR: A history of diffusion research can be found in this paper, where the authors present a glossary of developments in the field of Diffusion research and discuss the consequences of these developments.

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Abstract: Contents Preface CHAPTER 1. ELEMENTS OF DIFFUSION CHAPTER 2. A HISTORY OF DIFFUSION RESEARCH CHAPTER 3. CONTRIBUTIONS AND CRITICISMS OF DIFFUSION RESEARCH CHAPTER 4. THE GENERATION OF INNOVATIONS CHAPTER 5. THE INNOVATION-DECISION PROCESS CHAPTER 6. ATTRIBUTES OF INNOVATIONS AND THEIR RATE OF ADOPTION CHAPTER 7. INNOVATIVENESS AND ADOPTER CATEGORIES CHAPTER 8. DIFFUSION NETWORKS CHAPTER 9. THE CHANGE AGENT CHAPTER 10. INNOVATION IN ORGANIZATIONS CHAPTER 11. CONSEQUENCES OF INNOVATIONS Glossary Bibliography Name Index Subject Index

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38,750 citations

Journal Article•DOI•

Multivariate Data Analysis

[...]

Joseph F. Hair

01 Jan 1973

TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.

...read moreread less

Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

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37,124 citations

Journal Article•DOI•

Diffusion of innovations

[...]

Thomas W. Valente¹•Institutions (1)

University of Southern California¹

01 Mar 2003-Genetics in Medicine

TL;DR: Upon returning to the U.S., author Singhal’s Google search revealed the following: in January 2001, the impeachment trial against President Estrada was halted by senators who supported him and the government fell without a shot being fired.

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23,419 citations

"Preliminary insight into cloud comp..." refers background in this paper

...Rogers (2003) posits that any innovation that exhibits favourable, appealing and easy-of-use characteristics diffuses more quickly than those that exhibit less of these attributes....
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...Low et al. (2011), Alshamaila et al. (2013) Tan et al. (2008), To and Ngai (2006), Wang et al. (2010), Rogers (2003) Security Concerns The fear of vulnerabilities in cloud computing systems....
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...Hong and Zhu (2006), Tan et al. (2008), Rogers (2003), To and Ngai (2006), Oliveira and Martins (2010), Wang et al. (2010) Organisation Firm Size Refers to the magnitude of an organisation in terms of number of employees, target market size and capital investment....
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...The “degree to which an innovation is perceived as being consistent with existing value, past experiences, and needs of receivers” (Rogers, 2003, p. 240) is referred to as compatibility....
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...Relative advantage is defined as “the degree to which an innovation is perceived as being better than the idea it supersedes” (Rogers, 2003, p. 299)....
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Journal Article•DOI•

Multivariate Data Analysis

[...]

Xianggui Qu

01 Feb 2007-Technometrics

TL;DR: This book deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material.

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Abstract: Chapter 3 deals with probability distributions, discrete and continuous densities, distribution functions, bivariate distributions, means, variances, covariance, correlation, and some random process material. Chapter 4 is a detailed study of the concept of utility including the psychological aspects, risk, attributes, rules for utilities, multidimensional utility, and normal form of analysis. Chapter 5 treats games and optimization, linear optimization, and mixed strategies. Entropy is the topic of Chapter 6 with sections devoted to entropy, disorder, information, Shannon’s theorem, demon’s roulette, Maxwell– Boltzmann distribution, Schrodinger’s nutshell, maximum entropy probability distributions, blackbodies, and Bose–Einstein distribution. Chapter 7 is standard statistical fare including transformations of random variables, characteristic functions, generating functions, and the classic limit theorems such as the central limit theorem and the laws of large numbers. Chapter 8 is about exchangeability and inference with sections on Bayesian techniques and classical inference. Partial exchangeability is also treated. Chapter 9 considers such things as order statistics, extreme value, intensity, hazard functions, and Poisson processes. Chapter 10 covers basic elements of risk and reliability, while Chapter 11 is devoted to curve fitting, regression, and Monte Carlo simulation. There is an ample number of exercises at the ends of the chapters with answers or comments on many of them in an appendix in the back of the book. Other appendices are on the common discrete and continuous distributions and mathematical aspects of integration.

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19,893 citations

"Preliminary insight into cloud comp..." refers background or methods in this paper

...However, it has been argued that the significance of the p-value is as a result of large sample size (Hair et al., 2009)....
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...The target population was organisations operating in Ghana and the sampling technique adopted was a stratified random sampling since it allows selection of a balance sample of the population from the subpopulation (Hair et al. 2009)....
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...The confirmatory factor analysis (CFA) was conducted using AMOS version 22 on the dataset to measure the model results since CFA helps to determine if a test of validity on a hypothesized model can be reproduced (Hair et al. 2009; Byrne 2010)....
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...Lastly, the level of significance and hypotheses testing of individual independent variable is performed using the Wald test and significant values respectively (Hair et al., 2009)....
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Report•DOI•

The NIST Definition of Cloud Computing

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Peter Mell, Timothy Grance

28 Sep 2011

TL;DR: This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.

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Abstract: Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.

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15,145 citations

"Preliminary insight into cloud comp..." refers background in this paper

...There are three main cloud service delivery models: software-as-a-service (SaaS), platform-as-a-service (PaaS), and infrastructure-as-a-service (IaaS) (Mell and Grance, 2009)....
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...Cloud service deployment and delivery models Cloud services are offered through four deployment models, namely private, public, community, and hybrid (Mell and Grance, 2009)....
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