Basics of qualitative research: Grounded theory procedures and techniques

This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

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Qualitative Research in Information Systems

Presentacio sobre l'Oficina de Proteccio de Dades Personals de la UAB i la politica Open Science. Va formar part de la conferencia "Les politiques d'Open Data / Open Acces: Implicacions a la recerca" orientada a investigadors i gestors de projectes europeus que va tenir lloc el 20 de setembre de 2018 a la Universitat Autonoma de Barcelona

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General data protection regulation

https://cyberleninka.org/article/n/854933.pdf

Social media analytics – Challenges in topic discovery, data collection, and data preparation

Empirical studies of geographically distributed agile development communication challenges

There is a growing interest in IoT-enabled smart buildings. However, the storage and analysis of large amount of high-speed real-time smart building data is a challenging task. There are a number of contemporary Big Data management technologies and advanced analytics techniques that can be used to deal with this challenge. There is a need for an integrated IoT Big Data Analytics (IBDA) framework to fill the research gap in the Big Data Analytics domain. This paper presents one such IBDA framework for the storage and analysis of real time data generated from IoT sensors deployed inside the smart building. The initial version of the IBDA framework has been developed by using Python and the Big Data Cloudera platform. The applicability of the framework is demonstrated with the help of a scenario involving the analysis of real-time smart building data for automatically managing the oxygen level, luminosity and smoke/hazardous gases in different parts of the smart building. The initial results indicate that the proposed framework is fit for the purpose and seems useful for IoT-enabled Big Data Analytics for smart buildings. The key contribution of this paper is the complex integration of Big Data Analytics and IoT for addressing the large volume and velocity challenge of real-time data in the smart building domain. This framework will be further evaluated and extended through its implementation in other domains.

Towards an IoT Big Data Analytics Framework: Smart Buildings Systems

The software community is showing significant interest in agile software development methods and it is therefore desirable to have an analytical tool to evaluate current agile software development methods in practice. The purpose of this paper is to propose a 4-Dimensional Analytical Tool (4-DAT) for researchers and practitioners for the purpose of analysis and comparison of agile methods. 4-DAT will facilitate the examination of agile methods from four perspectives or dimensions: method scope characterization, agility characterization, agile values (agile manifesto) characterization and software process characterization. The tool is intended for use by software practitioners to compare and analyse agile methods. A report that is generated with the help of 4-DAT can be used for decision making regarding the adoption of an appropriate agile method.

/pdf/measuring-agility-and-adaptibility-of-agile-methods-a-4-2cuc804nb7.pdf

Measuring agility and adaptibility of agile methods: A 4 dimensional analytical tool

https://opus.lib.uts.edu.au/bitstream/10453/97828/4/IoT-enabled%20EISC%20Architecture%20for%20Elderly%20People%20-%20Final%20Accepted.pdf

IoT-enabled emergency information supply chain architecture for elderly people: The Australian context

/pdf/devops-concepts-practices-tools-benefits-and-challenges-4zut0wxge7.pdf

Asif Qumer Gill

Papers

Empirical studies of geographically distributed agile development communication challenges

Towards an IoT Big Data Analytics Framework: Smart Buildings Systems

Measuring agility and adaptibility of agile methods: A 4 dimensional analytical tool

IoT-enabled emergency information supply chain architecture for elderly people: The Australian context

DevOps: Concepts, Practices, Tools, Benefits and Challenges