Special Issue Big Data And Business Analytics

"The chapters in this volume offer useful case studies, technical roadmaps, lessons learned, and a few prescriptions todo this, avoid that.'"-From the Foreword by Joe LaCugna, Ph.D., Enterprise Analytics and Business Intelligence, Starbucks Coffee CompanyWith the growing barrage of "big data," it becomes vitally important for organizations to mak

Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. A must for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance.

A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Knowledge management (KM) has become an evolving discipline since the early 1990s, when organizations started perceiving knowledge as a valuable resource. This field of research has its origin in many disciplines, such as: information and IT management, computer science, enterprise management, organization science, human resource management and even philosophy, offering many potential research perspectives and approaches. For more than three decades, organizations of various types have been undertaking efforts to apply knowledge management, in order to benefit from a competitive advantage. Researchers and practitioners from diversified industries, and with different backgrounds, have tried to answer the question how to successfully manage knowledge, knowledge work and knowledge workers, still leaving much space for further research avenues Now, after all those years of research, some old questions have still not been answered and some new ones have arisen. During the pre-conference workshop on “The future of KM: short-time goals and long-term vision”, organized in Barcelona before the European Conference on Knowledge Management 2017 and conducted by myself and my colleague, Dr Sandra Moffett from Ulster University (UK), we asked the participants what their idea of the future of KM was. We could observe many different voices and approaches: some very pessimistic that KM is probably coming to an end, but mostly very promising that there are still many unexplored aspects of KM we should focus on and there is still a plethora of issues related to knowledge management that should be examined. Similar voices can be detected in the flagship article written by Meliha Handzic, who claims that KM definitely has a future, although it may not be without some challenges and obstacles to overcome. This paper links the past (three evolutionary stages of KM called fragmentation, integration and fusion) with the future of KM (three new trends named extension, specialization and reconceptualization). The author also suggests that KM should embrace different approaches under the “KM Conceptual Umbrella”, highlighting the possibility of addressing many themes, ideas or tools linked with knowledge. All the past and future evolutionary stages of KM are described in detail, together with the challenges that the KM field might face in the future. In the second paper, by Philip Sisson and Julie J. C. H. Ryan, the authors present a mental model of knowledge as a concept map being an input to KM research. The authors used qualitative methods, together with system engineering and object analysis methods, to collect various concepts and relate them. The issue of knowledge is elementary in knowledge management and showing the links between particular knowledge terms is of very high value to all KM researchers. Although the length of this article may constitute a challenge, it is definitely worth the effort as it illustrates many multifaceted, multilayered and multidimensional aspects of knowledge. The third paper by Karl Joachim Breunig and Hanno Roberts discusses another valid issue of value creation in the context of knowledge flow. The authors try to answer the question: How can we express knowledge in such a way that it can be monetized and made accessible to specific managerial interventions? Building on the previous extant studies and authors’ ideas, the paper points out that boundary spanners play a focal role in the monetization efforts of knowledge. In the fourth paper by Regina Lenart-Gansiniec one can read about crowdsourcing and the virtual knowledge sharing taking place in this process. The phenomenon of crowdsourcing is still under-researched and not much is known about the virtual exchange of knowledge in crowdsourcing and its benefits, such as co-creation, participation or gaining new ideas, and potential sources of innovations. Apart from the examination of the potential benefits of virtual knowledge sharing, the author also analyses ways of measuring virtual knowledge sharing in the process of crowdsourcing. The fifth paper by Kaja Prystupa concerns knowledge management processes in small entities and the role played by organizational culture. As the aim of this paper, the author set the examination of organizational culture in small Polish companies with the application of a symbiotic-interpretive perspective. Interesting outcomes of this study are: the confirmed role of organizational culture in KM initiatives, the importance of the founder and the industry, and the threat posed by organizational growth, which should be well-managed from the perspective of organizational culture so as not to hinder organizational performance. The sixth and the final paper, by David Mendes, Jorge Gomes and Mário Romão, deals with ways of creating intangible value through the use of a corporate employee portal. The authors undertake the effort to explain how such a portal fosters the creation of organizational values built on intangible assets. As the research confirms, an employee portal can be considered as a strategic tool for promoting organizational culture and cooperation, through information and communication fluxes and through the teamwork of collaborative functionalities. This issue of JEMI integrates contributions from Bosnia and Herzegovina, the United States, Norway, Poland and Portugal. I would like to express my gratitude to all the authors who contributed to this special issue, proving that knowledge management is still a valid topic, and offering abundant research opportunities. I would also like to express my sincerest thanks to the anonymous reviewers who contributed highly to the selection of the best submissions for this issue and guided the authors to further improvements in their works. Finally, I would like to pay special thanks to Dr Anna Ujwary-Gil, Editor-in-Chief of JEMI, for her kind invitation to prepare this special issue and her continual support at each stage of its preparation. I do hope that the readers of JEMI find the selected papers valuable and that they enrich their knowledge on KM issues. Additionally, I do believe that the collected works will be inspiring and offer some future directions for the examination of the knowledge management field. Dr. Małgorzata Zięba Guest Editor, JEMI Assistant Professor, Gdansk University of Technology, Poland