Annals of Information Systems – serie

Managing in the Information Economy: Current Research Issues presents the recent research directions that address the issue of management in this economy. The contributors include leading researchers with interests in a diverse set of topics. While the volume cannot give a complete and comprehensive picture, it can provide introductions to important areas, and point to some important topics for future research. Therefore the book begins with perspectives at the level of the economy as a whole and then progressively addresses industrial structure, sectors, functions (e-commerce) and business practices. Introductions to the main sections and the papers in each section are provided. The volume is organized around six sections: The Information Economy; Structure and the Organization of the Information Economy; Marketing and Ecommerce; Emerging Issues in the Information Economy; Operations in the Information Economy; and Empirical Studies of Business Practices. Please see the Table of Contents and Editor's Introduction for further details.

India is becoming the "global back office" to international supply chains, creating a substantial communications and decision-support infrastructure for large and small enterprises in the global market place to utilize these resources. Decision Support for Global Enterprises consists of peer-reviewed and invited papers with two primary goals: (1) Stimulate creative discussion between academic researchers and the practitioner IS community to improve the research and practice in the area. (2) Increase awareness of the problems and challenges faced by global enterprises that can be met with innovative decision support systems. Limitations are also explored, covering the following topics: (1) the emerging enterprise decision making processes and technologies; (2) decision making in uncertain, changing conditions; (3) the changing infrastructure in organizations and society; (4) the expanding role of web technologies; and (5) emerging theories and practices for managing knowledge and making decisions.

Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Nowadays, knowledge-based management systems include data warehouses as their core components. The purpose of building a data warehouse is twofold. Firstly, to integrate multiple heterogeneous, autonomous, and distributed data sources within an enterprise. Secondly, to provide a platform for advanced, complex, and efficient data analysis. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed among others for discovering trends, patterns of behavior, and anomalies as well as for finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data that more and more often come from WEB-based, XML-based, spatio-temporal, object, and multimedia systems, make data integration and processing challenging. The objective of NEW TRENDS IN DATA WAREHOUSING AND DATA ANALYSIS is fourfold: First, to bring together the most recent research and practical achievements in the DW and OLAP technologies.Second, to open and discuss new, just emerging areas of further development.Third, to provide the up-to-date bibliography of published works and the resource of research achievements for anyone interested in up-to-date data warehouse issues. And, finally, to assist in the dissemination of knowledge in the field of advanced DW and OLAP.

Knowledge management (KM) is a set of relatively-new organizational activities that are aimed at improving knowledge, knowledge-related practices, organizational behaviors and decisions and organizational performance. KM focuses on knowledge processes—knowledge creation, acquisition, refinement, storage, transfer, sharing and utilization. These processes support organizational processes involving innovation, individual learning, collective learning and collaborative decision-making. The “intermediate outcomes” of KM are improved organizational behaviors, decisions, products, services, processes and relationships that enable the organization to improve its overall performance.Knowledge Management and Organizational Learning presents some 20 papers organized into five sections covering basic concepts of knowledge management; knowledge management issues; knowledge management applications; measurement and evaluation of knowledge management and organizational learning; and organizational learning.

Information Technology and Product Development: A Research Agenda presents important new research from varied disciplines aimed at developing new theoretical concepts and insights on the application of IT in product and service innovation. Drawing on the work of researchers in such varied management areas as information services, technology management, marketing, operations, business strategy and organizational behavior, the book redefines the role of IT in product and service development and the organizational and management issues underlying the successful deployment of IT in innovation contexts, and provides a foundation for future research on the diverse types of IT applications in product development and their potential impact on both product and service innovation.Reflecting two critical shifts in the service sector – the increased complexity and convergence in products and services, along with the rise of the Internet and rapid digitization of products and services – the book is organized into three sections. Section 1 presents four chapters that focus on the traditional areas of project and process management; Section 2 presents four chapters focusing on the emerging areas of collaborative innovation and knowledge co-creation; and Section 3 presents one chapter that draws it all together and identifies some of the important themes and issues for future research.This important new work has much to offer academic researchers in management in its in-depth theoretical analysis of the wide range of organizational and management issues associated with the application of IT in product and service development. It will also appeal to researchers and thought-leaders in consulting organizations whose primary area of interest is product development or IT applications.

According to the W3C Semantic Web Activity [1]: The Semantic Web provides a common framework that allows data to be shared and reused across appli- tion, enterprise, and community boundaries. This statement clearly explains that the Semantic Web is about data sharing. Currently, the Web uses hyperlinks to connect Web pages. The Semantic Web goes beyond that and focuses on data and envisions the creation of the web of data. On the Semantic Web, anyone can say anything about any resource on the Web. This is fully based on the concept of semantic - notations, where each resource on the Web can have an assigned meaning. This is done through the use of ontologies as a formal and explicit representation of domain concepts and their relationships [2]. Ontologies are formally based on description logics. This enables agents and applications to reason over the data when searching the Web, which has not previously been possible. Web 2. 0 has gradually evolved from letting the Web users play a more active role. Unlike the initial version of the Web, where the users mainly “consumed” content, users are now offered easy-to-use services for content production and publication. Mashups, blogs, wikis, feeds, interface remixes, and social networking/tagging s- tems are examples of these well-known services. The success and wide adoption of Web 2. 0 was in its reliance on social interactions as an inevitable characteristic of the use and life of the Web. In particular, Web 2.

Web-based applications provide the power of desktop and server applications with the exibility and accessibility of the web. Using web browsers, users can securely access applications from anywhere within the reach of the company intranet or extranet. The special issue strives to explore the advanced web-based information systems and database applications in healthcare area. Healthcare organizations are undergoing major reorganizations and adjustments to meet the increasing demands of improved healthcare access and quality, as well as lowered costs. As the use of information technology to process medical data increases, much of the critical information necessary to meet these challenges is being stored in digital format. Web-enabled information technologies can provide the means for greater access and more effective integration of healthcare information from disparate computer applications and other information resources. This book presents studies from leading researchers and practitioners focusing on the current challenges, directions, trends, and opportunities associated with heal- care organizations and their strategic use of web-enabled technologies. Managing healthcare information systems with web-enabled technologies is an excellent ve- cle for understanding current and potential uses of Internet technology in the broad areas of healthcare and medical applications.

Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Metaheuristics support managers in decision-making with robust tools that provide high-quality solutions to important applications in business, engineering, economics, and science in reasonable time frames, but finding exact solutions in these applications still poses a real challenge.

Intelligence and Security Informatics (ISI) is defined as the study of the development and use of advanced information systems and technologies for national, international, and societal security-related applications. With the rise of global terrorism, the field has been given an increasing amount of attention from academic researchers, law enforcement, intelligent experts, information technology consultants and practitioners.SECURITY INFORMATICS is global in scope and perspective. Leading experts will be invited as contributing authors from the US, UK, Denmark, Israel, Singapore, Hong Kong, Taiwan, Europe, etc. It is the first systematic, archival volume treatment of the field and will cover the very latest advances in ISI research and practice. It is organized in four major subject areas: (1) Information and Systems Security, (2) Information Sharing and Analysis in Security Informatics, (3) Infrastructure Protection and Emergency Responses, and (4) National Security and Terrorism Informatics.

The Semantic Web has been a very important development in how knowledge is disseminated and manipulated on the Web, but it has been of particular importance to the flow of scientific knowledge, and will continue to shape how data is stored and accessed in a broad range of disciplines, including life sciences, earth science, materials science, and the social sciences. After first presenting papers on the foundations of semantic e-science, including papers on scientific knowledge acquisition, data integration, and workflow, this volume looks at the state of the art in each of the above-mentioned disciplines, presenting research on semantic web applications in the life, earth, materials, and social sciences. Drawing papers from three semantic web workshops, as well as papers from several invited contributors, this volume illustrates how far semantic web applications have come in helping to manage scientific information flow.

This volume of Annals of Information Systems will acknowledge the twentieth anniversary of the founding of the International Society for Decision Support Systems (ISDSS) by documenting some of the current best practices in teaching and research and envisioning the next twenty years in the decision support systems field. The volume is intended to complement existing DSS literature by offering an outlet for thoughts and research particularly suited to the theme of describing the next twenty years in the area of decision support.Several subthemes are planned for the volume. One subtheme draws on the assessments of internationally known DSS researchers to evaluate where the field has been and what has been accomplished. A second subtheme of the volume will be describing the current best practices of DSS research and teaching efforts. A third subtheme will be an assessment by top DSS scholars on where the DSS discipline needs to focus in the future. The tone of this volume is one of enthusiasm for the potential contributions to come in the area of DSS; contributions that must incorporate an understanding of what has been accomplished in the past, build on the best practices of today, and be be integrated into future decision making practices.The primary questions raised by this volume are:What will information systems-based decision support entail in twenty years?What research is needed to realize the envisioned future of information systems-based decision support?How will the teaching of information systems-based decision support change over the next twenty years?What are the best practices of teaching in the decision support area that can be leveraged to best disseminate DSS knowledge advances to students and practitioners?

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis.

This volume of Annals of Information Systems will acknowledge the twentieth anniversary of the founding of the International Society for Decision Support Systems (ISDSS) by documenting some of the current best practices in teaching and research and envisioning the next twenty years in the decision support systems field. The volume is intended to complement existing DSS literature by offering an outlet for thoughts and research particularly suited to the theme of describing the next twenty years in the area of decision support.Several subthemes are planned for the volume. One subtheme draws on the assessments of internationally known DSS researchers to evaluate where the field has been and what has been accomplished. A second subtheme of the volume will be describing the current best practices of DSS research and teaching efforts. A third subtheme will be an assessment by top DSS scholars on where the DSS discipline needs to focus in the future. The tone of this volume is one of enthusiasm for the potential contributions to come in the area of DSS; contributions that must incorporate an understanding of what has been accomplished in the past, build on the best practices of today, and be integrated into future decision making practices.

Online communities are among the most obvious manifestations of social networks based on new media technology. Facilitating ad-hoc communication and leveraging collective intelligence by matching similar or related users have become important success factors in almost every successful business plan. Researchers are just beginning to understand virtual communities and collaborations among participants currently proliferating across the world. Virtual Communities, Social Networks and Collaboration covers cutting edge research topics of utmost real-world importance in the specific domain of social networks. This volume focuses on exploring issues relating to the design, development, and outcomes from electronic groups and online communities, including: - The implications of social networking,- Understanding of how and why knowledge is shared among participants,- What leads to participation, effective collaboration, co-creation and innovation,- How organizations can better utilize the potential benefits of communities in both internal operations, marketing, and new product development.

New requirements and technological advances occurring in healthcare, information systems, and information technology have influenced the evolving role of healthcare information systems and related technology, and this book will help bring the field up to date.

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making.

This volume explores emerging research and pedagogy in analytics, collaboration, and decision support with an emphasis on business intelligence and social media. In general, the chapters help understand where technology involvement in human decisions is headed. Reading the chapters can help understand the opportunities and threats associated with the use of information technology in decision making. Computing and information technologies are reshaping our global society, but they can potentially reshape it in negative as well as positive ways. Analytics, collaboration and computerized decision support are powerful decision aiding and decision making tools that have enormous potential to impact crisis decision making, regulation of financial systems, healthcare decision making and many more important decision domains.Many information technologies can potentially support, assist and even decide for human decision makers. Despite the potential, some researchers think that we know the answers to how these technologies will change society. The "Wisdom of Crowds" or "Big Data" become the topic of the day and are soon replaced with new marketing terms. In many ways, mobile technology is just another form factor to adapt decision support capabilities too and experiment with new capabilities. The cloud is a nebulous metaphor that adds to the mystery of information technology. Wireless technology enables the ubiquitous presence of analytics and decision support. With new networking capabilities, collaboration is possible anywhere and everywhere using voice, video and text. Documents can be widely shared and massive numbers of documents can be carried on a small tablet computer. Recent developments in technologies impact the processes organizations use to make decisions. In addition, academics are looking for ways to enhance their pedagogy to train students to be more adept in understanding how emerging technology will be used effectively for decisionmaking in organizations.The chapters are based on papers originally reviewed at the Special Interest Group on Decision Support Systems (SIGDSS) Workshop at the 2013 International Conference on Information Systems (ICIS 2013). Ultimately this volume endeavors to find a balance between systematizing what we know, so we can teach our findings from prior research better, and stimulating excitement to move the field in new directions.

This important new volume presents recent research in healthcare information technology and analytics.  Individual chapters look at such issues as the impact of technology failure on electronic prescribing behavior in primary care; attitudes toward electronic health records; a latent growth modeling approach to understanding lifestyle decisions based on patient historical data; designing an integrated surgical care delivery system using axiomatic design and petri net modeling; and failure in a dynamic decision environment, particularly in treating patients with a chronic disease.Other chapters look at such topics as the impact of information technology integration in integrated delivery systems; operations and supply chain control for inventory management in a health system pharmacy; decision-theoretic assistants based on contextual gesture recognition; evaluating emergency response medical information systems; clinical decision support in critical care; virtual worlds in healthcare; and natural language processing for understanding contraceptive use at the VA.

This book provides a principled approach to classification using the available data in a model which combines information from the social network and the healthcare models. It presents studies from leading researchers and practitioners focusing on the current challenges, directions, trends and opportunities associated with healthcare delivery systems and their supporting wireless and mobile health technologies. mHealth Ecosystems and Social Networks in Healthcare is divided into two parts. Part I covers the area of mHealth Ecosystems. Chapters include topics on adoption of cloud based mHealth services, the socio-economic impact of mHealth, as well as self-management of health and disease. In Part II, Social Networks in Healthcare are highlighted. Chapters cover social media and patient support, virtual knowledge sharing and knowledge management and also web-based applications in health care. Ultimately this book is an excellent source of comprehensive knowledge and literatureon the topics of mobile health ecosystems and social networks in healthcare.