This book develops a common understanding between the client and the provider in each of the four stages of strategic outsourcing. These stages range from discovery, where the parties envision their future collaboration; planning, where they lay the ground work for the contract and the project; building, where they effectively carry out the work; and lastly to running, where they orchestrate the relationship on a daily basis to ensure that the new, enlarged company achieves the results sought. In a simple yet direct style, it highlights the dos and don'ts the parties should bear in mind at each stage of the process and combines both the client's and the provider's perspectives by comparing their respective involvement at each stage of the process and considering, equally, their obligations in establishing a balanced relationship. The book is primarily intended for those in the private sector with experience of dealing with complex outsourcing situations and who are looking for the small or bigger differentiators that will support their decisions and actions. The target audiences include, on the client side: CCOs, CIOs, lawyers, procurement managers, outsourcing consultants and IT Service managers and, on the provider side: account managers, bid managers, outsourcing project managers, operation managers and service managers. However, it is also useful for anybody involved in outsourcing who is seeking to develop a global understanding of the main processes and roles upstream and downstream in the chain.

This book is intended to spark a discourse on, and contribute to finding a clear consensus in, the debate between conceptualizing a knowledge strategy and planning a knowledge strategy. It explores the complex relationship between the notions of knowledge and strategy in the business context, one that is of practical importance to companies. After reviewing the extant literature, the book shows how the concept of knowledge strategies can be seen as a new perspective for exploring business strategies. It proposes a new approach that clarifies how planned and emergent knowledge strategies allow companies to make projections into the uncertain and unpredictable future that dominates today's economy.

This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the "supply demand reparation method" and "continuous allocation method." In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a "least cost ration formulation application for cattle"; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves. The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.

This book constitutes the refereed proceedings of the 12th IFIP WG 8.9 Working Conference on Research and Practical Issues of Enterprise Information Systems, CONFENIS 2018, held as part of the World Computer Congress, WCC 2018, in Poznan, Poland, in September 2018. The 12 full papers presented in this volume were carefully reviewed and selected from 28 submissions. They were organized in topical sections named: EIS management and case studies; data management and applications for EIS; collaborative and social interaction; and data access, security, and privacy.

This book examines the role that Information and Communication Technologies (ICTs) play in growth and economic development promotion, specifically for developing countries. It highlights multiple methodologies for quantifying the impact of ICTs. This includes quantitative and qualitative methods, but also novel, conclusive and informative methodological approaches for measuring ICTs influence on economic development. The book highlights trends, perspectives, and success stories for different developing countries. ICTs bring new business models, innovations, capital-labor substitution, improved goods and services to developing markets. Because they can spread rapidly, with little cost and require minimal skills for usage, ICTs create a solid background for social and economic gains. They enable significant reduction in information asymmetries, which improves access to economic activities for multitude of agents, fostering participation, inter alias in labor market of disadvantaged societal groups. After almost two decades of rapid diffusion of ICT in developing world, this book seeks to assess the real benefits and consequences of ICTs adoption in developing countries. The chapters use broad, real-world based evidence to provide a better understanding of the precise nature of new technologies and their impact of the country`s economy and society.

This book constitutes the proceedings of the BPM Forum held during the 16th International Conference on Business Process Management, BPM 2018, which took place in Sydney, Australia, in September 2018. The BPM Forum hosts innovative research which has a high potential of stimulating discussions. The papers selected for the forum are expected to showcase fresh ideas from exciting and emerging topics in BPM, even if they are not yet as mature as the regular papers at the conference. The 14 papers presented in this volume were carefully reviewed and selected from a total of 113 submissions. They were organized according to the tracks of the conference: foundations; engineering; management.

Melanie Holloway explores a cloud broker offering service level agreement negotiation and monitoring as a service to consumers. She proposes a negotiation mechanism, which enables the achievement of economically efficient agreements, and an approach for reliable consumer side availability monitoring in conjunction with strategies for robust monitor placement. The author addresses the loss of control of consumers over critical aspects, specifically quality of service, when using services from the cloud.Basically, the cloud computing paradigm places the responsibility for resource management on the provider side. Hence, the control over cloud service performance is very limited on the consumer side.

This descriptive, practical guide explains how to build a commercially impactful, operationally effective and technically robust IoT ecosystem that takes advantage of the IoT revolution and drives business growth in the consumer IoT as well as industrial internet spaces. With this book, executives, business managers, developers and decision-makers are given the tools to make more informed decisions about IoT solution development, partner eco-system design, and the monetization of products and services. Security and privacy issues are also addressed. Readers will explore the design guidelines and technology choices required to build commercially viable IoT solutions, but also uncover the various monetization and business modeling for connected products.

Transform your IT organization from one weighed down by set practices to one with a DevOps culture and a cloud-first strategy that is optimized by automation and other lean practices. In this engaging read, you will discover the opportunities, challenges, lessons, and rewards that CA Technologies encountered when making their agile and DevOps transformation. In Enterprise DevOps Framework author Shamayel Farooqui shows you how agile adoption will enable your organization to stay ahead in an ever-changing business environment and meet your customers' needs. He includes detailed references to key concepts such as agile, hybrid and cloud technology, infrastructure management, and process automation. What You'll Learn Establish the focus areas for your IT organization Prepare for the challenges of transforming your enterprise to a DevOps, agile organization Know the key steps for executing an enterprise DevOps strategy Build a strong team of DevOps individuals focused on improving the efficiency of your organization through Agile methodologies, automation, cloud adoption, and "infrastructure as code" practices Who This Book Is For IT administrators, operational personnel, cloud professionals, DevOps professionals, human resources professionals, managers, and C-level staff

This volume introduces a series of different data-driven computational methods for analyzing group processes through didactic and tutorial-based examples. Group processes are of central importance to many sectors of society, including government, the military, health care, and corporations. Computational methods are better suited to handle (potentially huge) group process data than traditional methodologies because of their more flexible assumptions and capability to handle real-time trace data. Indeed, the use of methods under the name of computational social science have exploded over the years. However, attention has been focused on original research rather than pedagogy, leaving those interested in obtaining computational skills lacking a much needed resource. Although the methods here can be applied to wider areas of social science, they are specifically tailored to group process research. A number of data-driven methods adapted to group process research are demonstrated in this current volume. These include text mining, relational event modeling, social simulation, machine learning, social sequence analysis, and response surface analysis. In order to take advantage of these new opportunities, this book provides clear examples (e.g., providing code) of group processes in various contexts, setting guidelines and best practices for future work to build upon. This volume will be of great benefit to those willing to learn computational methods. These include academics like graduate students and faculty, multidisciplinary professionals and researchers working on organization and management science, and consultants for various types of organizations and groups.

Walden shows why most customer experience management fails to improve the customer's real experience and how to concentrate on the subjective emotional perceptions that drive the customer's actual "experience" rather than the quantitative service efficiency metrics gathered by most CX tools. Customer experience management is not about managing every objective "experience" your customers have with you. It's about understanding, measuring and creating "experiences" that customers "value". So while service and efficiency are wonderful things, they represent "business as usual"; the ticket to the game, the platform from which "experiences" are created not the experience itself! The message of this book is that businesses are at risk! Their uber focus on efficiency is leading them to miss the chance to connect more closely with their customer base and deliver on the creative potential of their brand. They ignore the fact that technology is an enabler of the "experience" it is not "the experience". Customers are not data - they are people: living, breathing, contradictory, infuriating bundles of cognitive and emotionally-driven responses to stimuli. "Experience" deals with how customers think, feel and behave - the things that motivate them to act which go beyond frequently forgettable efficiency. This means differentiating by providing new and better experiences based on a deeper understanding of what motivates customers to buy. To do that we must leave the objective, quantitative, world of quality management and enter the subjective, qualitative, world of customer's psychology. Walden reboots our understanding of customer experience, showing us what it means, how to measure it, what we need to do to manage it and how we can gain financially from it. Understand, measure, create and do - but first of all, understand.

This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naive techniques. This part also covers hot topics such as Factor Analysis, Discriminant Analysis and Multidimensional Scaling (MDS).

This book provides a technical approach to a Business Resilience System with its Risk Atom and Processing Data Point based on fuzzy logic and cloud computation in real time. Its purpose and objectives define a clear set of expectations for Organizations and Enterprises so their network system and supply chain are totally resilient and protected against cyber-attacks, manmade threats, and natural disasters. These enterprises include financial, organizational, homeland security, and supply chain operations with multi-point manufacturing across the world. Market shares and marketing advantages are expected to result from the implementation of the system. The collected information and defined objectives form the basis to monitor and analyze the data through cloud computation, and will guarantee the success of their survivability's against any unexpected threats. This book will be useful for advanced undergraduate and graduate students in the field of computer engineering, engineers that work for manufacturing companies, business analysts in retail and e-Commerce, and those working in the defense industry, Information Security, and Information Technology.

This reference book shows how the Zero Outage method leads to more stability in operations, more reliability in projects and, ultimately, to greater customer satisfaction. It explains why clear standards for platforms, processes and personnel are essential for ensuring high ICT quality from end to end and what to look out for during changes - the most common cause of IT outages. Readers also learn how to resolve errors as quickly as possible and permanently eliminate them, and why industry-wide collaboration will only be possible with a shared standard of quality. This book is a practical introduction to making your ICT world even more failsafe and efficient. The authors share key knowledge in quality management and offer an exclusive insight into their extensively tested and continually enhanced formula for success: the Zero Outage approach.

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.

This book discusses the fusion of mobile and WiFi network data with semantic technologies and diverse context sources for offering semantically enriched context-aware services in the telecommunications domain. It presents the OpenMobileNetwork as a platform for providing estimated and semantically enriched mobile and WiFi network topology data using the principles of Linked Data. This platform is based on the OpenMobileNetwork Ontology consisting of a set of network context ontology facets that describe mobile network cells as well as WiFi access points from a topological perspective and geographically relate their coverage areas to other context sources. The book also introduces Linked Crowdsourced Data and its corresponding Context Data Cloud Ontology, which is a crowdsourced dataset combining static location data with dynamic context information. Linked Crowdsourced Data supports the OpenMobileNetwork by providing the necessary context data richness for more sophisticated semantically enriched context-aware services. Various application scenarios and proof of concept services as well as two separate evaluations are part of the book. As the usability of the provided services closely depends on the quality of the approximated network topologies, it compares the estimated positions for mobile network cells within the OpenMobileNetwork to a small set of real-world cell positions. The results prove that context-aware services based on the OpenMobileNetwork rely on a solid and accurate network topology dataset. The book also evaluates the performance of the exemplary Semantic Tracking as well as Semantic Geocoding services, verifying the applicability and added value of semantically enriched mobile and WiFi network data.

This book examines how digital technologies enable collaboration as a way for individuals, teams and businesses to connect, create value, and harness new opportunities. Digital technologies have brought the world closer together but also created new barriers and divides. While it is now possible to connect almost instantly and seamlessly across the globe, collaboration comes at a cost; it requires new skills and hidden 'collaboration work', and the need to renegotiate the fair distribution of value in multi-stakeholder network arrangements. Presenting state-of-the-art research, case studies, and leading voices in the field, the book provides academics and professionals with insights into the diverse powers of collaboration in the digital age, spanning collaboration among professionals, organisations, and consumers. It brings together contributions from scholars interested in the collaboration of teams, cooperatives, projects, and new cooperative systems, covering a range of sectors from the sharing economy, health care, large project businesses to public sector collaboration.

This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions. Transparent data mining solutions with desirable properties (e.g. effective, fully automatic, scalable) are covered in the book. Experimental findings of transparent solutions are tailored to different domain experts, and experimental metrics for evaluating algorithmic transparency are presented. The book also discusses societal effects of black box vs. transparent approaches to data mining, as well as real-world use cases for these approaches.As algorithms increasingly support different aspects of modern life, a greater level of transparency is sorely needed, not least because discrimination and biases have to be avoided. With contributions from domain experts, this book provides an overview of an emerging area of data mining that has profound societal consequences, and provides the technical background to for readers to contribute to the field or to put existing approaches to practical use.

This book embarks on a mission to dissect, unravel and demystify the concepts of Web services, including their implementation and composition techniques. It provides a comprehensive perspective on the fundamentals of implementation standards and strategies for Web services (in the first half of the book), while also presenting composition techniques for leveraging existing services to create larger ones (in the second half). Pursuing a unique approach, it begins with a sound overview of concepts, followed by a targeted technical discussion that is in turn linked to practical exercises for hands-on learning. For each chapter, practical exercises are available on Github. Mainly intended as a comprehensive textbook on the implementation and composition of Web services, it also offers a useful reference guide for academics and practitioners. Lecturers will find this book useful for a variety of courses, from undergraduate courses on the foundational technology of Web services through graduate courses on complex Web service composition. Students and researchers entering the field will benefit from the combination of a broad technical overview with practical self-guided exercises. Lastly, professionals will gain a well-informed grasp of how to synthesize the concepts of conventional and "newer" breeds of Web services, which they can use to revise foundational concepts or for practical implementation tasks.

This handbook brings together a variety of approaches to the uses of big data in multiple fields, primarily science, medicine, and business. This single resource features contributions from researchers around the world from a variety of fields, where they share their findings and experience. This book is intended to help spur further innovation in big data. The research is presented in a way that allows readers, regardless of their field of study, to learn from how applications have proven successful and how similar applications could be used in their own field. Contributions stem from researchers in fields such as physics, biology, energy, healthcare, and business. The contributors also discuss important topics such as fraud detection, privacy implications, legal perspectives, and ethical handling of big data.

This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap.

This book provides a state-of-the-art perspective on intelligent process-aware information systems and presents chapters on specific facets and approaches applicable to such systems. Further, it highlights novel advances and developments in various aspects of intelligent process-aware information systems and business process management systems. Intelligence capabilities are increasingly being integrated into or created in many of today's software products and services. Process-aware information systems provide critical computing infrastructure to support the various processes involved in the creation and delivery of business products and services. Yet the integration of intelligence capabilities into process-aware information systems is a non-trivial yet necessary evolution of these complex systems. The book's individual chapters address adaptive process management, case management processes, autonomically-capable processes, process-oriented information logistics, process recommendations, reasoning over process models, process portability, and business process intelligence. The primary target groups are researchers and PhD/Master students in the field of information systems.

This proceedings volume presents the latest on the theoretical approach of the contemporary issues evolved in strategic marketing and the integration of theory and practice. It highlights strategic research and innovative activities in marketing. The contributed chapters are concerned with using modern qualitative and quantitative techniques based on information technology used to manage and analyze business data, to discover hidden knowledge and to introduce intelligence into marketing processes. This allows for a focus on innovative applications in all aspects of marketing, of computerized technologies related to data analytics, predictive analytics and modeling, business intelligence and knowledge engineering, in order to demonstrate new ways of uncovering hidden knowledge and supporting marketing decisions with evidence-based intelligent tools. The chapters from the proceedings of the 5th International Conference on Strategic Innovative Marketing 2016 cover areas such as social media marketing innovation, sustainable marketing, customer satisfaction strategies, customer relationship management, marketing research and analytics. The papers have been written by scientists, researchers, practitioners and students that demonstrate a special orientation in strategic marketing, all of whom aspire to be ahead of the curve based on the pillars of innovation. This proceedings volume shares their recent contributions to the field and showcases their exchange of insights on strategic issues in the science of innovation marketing.

This book seeks to promote the structured, standardized and accurate use of software measurement at all levels of modern software development companies. To do so, it focuses on seven main aspects: sound scientific foundations, cost-efficiency, standardization, value-maximization, flexibility, combining organizational and technical aspects, and seamless technology integration. Further, it supports companies in their journey from manual reporting to automated decision support by combining academic research and industrial practice. When scientists and engineers measure something, they tend to focus on two different things. Scientists focus on the ability of the measurement to quantify whatever is being measured; engineers, however, focus on finding the right qualities of measurement given the designed system (e.g. correctness), the system's quality of use (e.g. ease of use), and the efficiency of the measurement process. In this book, the authors argue that both focuses are necessary, and that the two are complementary. Thus, the book is organized as a gradual progression from theories of measurement (yes, you need theories to be successful!) to practical, organizational aspects of maintaining measurement systems (yes, you need the practical side to understand how to be successful). The authors of this book come from academia and industry, where they worked together for the past twelve years. They have worked with both small and large software development organizations, as researchers and as measurement engineers, measurement program leaders and even teachers. They wrote this book to help readers define, implement, deploy and maintain company-wide measurement programs, which consist of a set of measures, indicators and roles that are built around the concept of measurement systems. Based on their experiences introducing over 40,000 measurement systems at over a dozen companies, they share essential tips and tricks on how to do it right and how to avoid common pitfalls.

This supplement text bridges the gap between the fundamentals of how businesses operate (processes) and the tools that business people use to accomplish their tasks (systems). The authors have developed this text for an introductory MIS or general business course to establish a fundamental understanding of business processes. Business students, regardless of their functional discipline, will be able to apply the real-world concepts discussed in this text immediately upon entering the workforce.

As more and more businesses adopt enterprise systems globally, it becomes increasingly important for business schools to offer a process-based curriculum to better reflect the realities of modern business. Given the integration of business operations and enterprise systems, Magal and Word have designed this text to reflect, in a "practical and accessible" format, how real-world business processes are managed and executed.