Savvas Papagiannidis

Bio: Savvas Papagiannidis is an academic researcher from Newcastle University. The author has contributed to research in topics: The Internet & Social media. The author has an hindex of 25, co-authored 127 publications receiving 2566 citations. Previous affiliations of Savvas Papagiannidis include Northumbria University.

Cloud computing adoption by SMEs in the north east of England: A multi‐perspective framework

Abstract: – The purpose of this paper is to contribute to a growing body of research on cloud computing, by studying the small to medium‐sized enterprise (SME) adoption process. If SMEs have access to scalable technologies they could potentially deliver products and services that in the past only large enterprises could deliver, flattening the competitive arena., – By adopting the Technological, Organisational and Environmental (TOE) framework as a theoretical base, this qualitative exploratory study used semi‐structured interviews to collect data in 15 different SMEs and service providers in the north east of England. The north east of England was selected as it is a region that aspires to become home to innovative digital firms and most of the companies in the region are SMEs., – The main factors that were identified as playing a significant role in SME adoption of cloud services were: relative advantage, uncertainty, geo‐restriction, compatibility, trialability, size, top management support, prior experience, innovativeness, industry, market scope, supplier efforts and external computing support. In contrast, this study did not find enough evidence that competitive pressure was a significant determinant of cloud computing adoption., – These findings have important implications and great value to the research community, managers and information and communication technologies (ICT) providers, in terms of formulating better strategies for cloud computing adoption. For service providers, using the research model in this study can assist in increasing their understanding of why some SMEs choose to adopt cloud computing services, while seemingly similar ones facing similar market conditions do not. Also, cloud computing providers may need to improve their interaction with SMEs which are involved in the cloud computing experience, in an effort to create a healthy environment for cloud computing adoption, and to remove any vagueness surrounding this type of technology., – This study is an attempt to explore and develop an SME cloud computing adoption model that was theoretically grounded in the TOE framework. By adopting the TOE framework this study has shown that the three contexts of this framework (technological, organisational, and environmental) are connected to each other.

Using Multivariate Statistics

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Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Abstract: 1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Estimation and Inference in Econometrics

Abstract: Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.