Unlike some other reproductions of classic texts (1) We have not used OCR(Optical Character Recognition), as this leads to bad quality books with introduced typos. (2) In books where there are images such as portraits, maps, sketches etc We have endeavoured to keep the quality of these images, so they represent accurately the original artefact. Although occasionally there may be certain imperfections with these old texts, we feel they deserve to be made available for future generations to enjoy.

This textbook provides a concise introduction to Management Information Systems. It introduces core concepts in an accessible style and adopts a contemporary approach that reflects the opportunities and challenges faced as businesses and technologies continue to evolve. Key features: ·       Coverage of key issues including sustainability and green IT, ethics and privacy, smart technologies, corporate social responsibility and big data ·       Definition boxes to consolidate understanding of key terms ·       Illustrative examples to engage and apply theory in the real-world ·       Pause for thought boxes to check understanding and encourage reflection ·       End of chapter case studies to illustrate key topics in practice, encourage critical thinking, application of knowledge and enhance learning ·       Comprehensive online support including PowerPoints, tutor’s guide and testbank of questions This textbook is suitable for undergraduate and postgraduate students studying introductory Management or Business Information Systems courses with no prior knowledge. Dr Tomayess Issa is a Senior Lecturer at Curtin University, Australia. Dr Theodora Issa is a Senior Lecturer at Curtin University, Australia. Dr Sarita Hardin-Ramanan is Head Faculty of IT at Curtin University, Mauritius. Dr Bilal Abu Salih is a Associate Professor at The University of Jordan, Jordan. Dr Lydia Maketo is a Lecturer at Curtin University, Australia. Dr Rohini Balapumi is a Lecturer at Curtin University, Australia. Dr S. Zaung Nau is a Lecturer at Curtin University, Australia. Dr Raadila Hajee Ahmud-Boodoo is a Teaching Instructor at Curtin University, Australia.

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.

This scarce antiquarian book is included in our special Legacy Reprint Series. In the interest of creating a more extensive selection of rare historical book reprints, we have chosen to reproduce this title even though it may possibly have occasional imperfections such as missing and blurred pages, missing text, poor pictures, markings, dark backgrounds and other reproduction issues beyond our control. Because this work is culturally important, we have made it available as a part of our commitment to protecting, preserving and promoting the world's literature.

This scarce antiquarian book is included in our special Legacy Reprint Series. In the interest of creating a more extensive selection of rare historical book reprints, we have chosen to reproduce this title even though it may possibly have occasional imperfections such as missing and blurred pages, missing text, poor pictures, markings, dark backgrounds and other reproduction issues beyond our control. Because this work is culturally important, we have made it available as a part of our commitment to protecting, preserving and promoting the world's literature.

This scarce antiquarian book is included in our special Legacy Reprint Series. In the interest of creating a more extensive selection of rare historical book reprints, we have chosen to reproduce this title even though it may possibly have occasional imperfections such as missing and blurred pages, missing text, poor pictures, markings, dark backgrounds and other reproduction issues beyond our control. Because this work is culturally important, we have made it available as a part of our commitment to protecting, preserving and promoting the world's literature.

This textbook provides a concise introduction to Management Information Systems. It introduces core concepts in an accessible style and adopts a contemporary approach that reflects the opportunities and challenges faced as businesses and technologies continue to evolve. Key features: ·       Coverage of key issues including sustainability and green IT, ethics and privacy, smart technologies, corporate social responsibility and big data ·       Definition boxes to consolidate understanding of key terms ·       Illustrative examples to engage and apply theory in the real-world ·       Pause for thought boxes to check understanding and encourage reflection ·       End of chapter case studies to illustrate key topics in practice, encourage critical thinking, application of knowledge and enhance learning ·       Comprehensive online support including PowerPoints, tutor’s guide and testbank of questions This textbook is suitable for undergraduate and postgraduate students studying introductory Management or Business Information Systems courses with no prior knowledge. Dr Tomayess Issa is a Senior Lecturer at Curtin University, Australia. Dr Theodora Issa is a Senior Lecturer at Curtin University, Australia. Dr Sarita Hardin-Ramanan is Head Faculty of IT at Curtin University, Mauritius. Dr Bilal Abu Salih is a Associate Professor at The University of Jordan, Jordan. Dr Lydia Maketo is a Lecturer at Curtin University, Australia. Dr Rohini Balapumi is a Lecturer at Curtin University, Australia. Dr S. Zaung Nau is a Lecturer at Curtin University, Australia. Dr Raadila Hajee Ahmud-Boodoo is a Teaching Instructor at Curtin University, Australia.