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Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics
Businesses are collecting massive amounts of data every day as a way to better understand their processes, competition, and the markets they serve. This data can be used to increase organizational productivity and performance; however, is essential that organizations collecting large data sets have the tools available to them to fully understand the data they are collecting. Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics takes a critical look at methods for enhancing an organization’s operations and day-to-day activities through the effective use of data. Focusing on a variety of applications of predictive analytics within organizations of all types, this critical publication is an essential resource for business managers, data scientists, graduate-level students, and researchers.
Personnel Literature
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Research in Progress
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Organization design and its impact on the digital innovation process and the digital innovation outcome
The book has the objective to demystify the hyper-complex world of organization design and digital innovation. It shows how organization design as a management discipline can help organizations to better master digital innovation challenges. At the same time, it discusses how organization design frameworks need to be further developed to successfully act as a driver for innovation in a digital world. While the digital age brings tremendous new opportunities, it also brings the specific challenge that companies' organization designs must be adjusted. This book shows how companies organize for innovation in the digital world by presenting thirteen practical cases from various industries.
Strategic Planning Workbook for Nonprofit Organizations, Revised and Updated
In an environment of increased competition, funding cuts, and other pressures, strategic planning is a sound management tool for nonprofits. This workbook provides a guide for developing, implementing, and updating a strategic plan. Sample plan and blank worksheets are included.
Principles of Managerial Statistics and Data Science
Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business students Through a statistical perspective, this book introduces readers to the topic of data science, including Big Data, data analytics, and data wrangling. Chapters include multiple examples showing the application of the theoretical aspects presented. It features practice problems designed to ensure that readers understand the concepts and can apply them using real data. Over 100 open data sets used for examples and problems come from regions throughout the world, allowing the instructor to adapt the application to local data with which students can identif...
The SAGE Handbook of Research Management
The Handbook of Research Management is a unique tool for the newly promoted research leader. Larger-scale projects are becoming more common throughout the social sciences and humanities, housed in centres, institutes and programmes. Talented researchers find themselves faced with new challenges to act as managers and leaders rather than as individual scholars. They are responsible for the careers and professional development of others, and for managing interactions with university administrations and external stakeholders. Although many scientific and technological disciplines have long been organized in this way, few resources have been created to help new leaders understand their roles and...
Handbook of Research on Organizational Transformations through Big Data Analytics
Big data analytics utilizes a wide range of software and analytical tools to provide immediate, relevant information for efficient decision-making. Companies are recognizing the immense potential of BDA, but ensuring the data is appropriate and error-free is the largest hurdle in implementing BDA applications. The Handbook of Research on Organizational Transformations through Big Data Analytics not only catalogues the existing platforms and technologies, it explores new trends within the field of big data analytics (BDA). Containing new and existing research materials and insights on the various approaches to BDA; this publication is intended for researchers, IT professionals, and CIOs interested in the best ways to implement BDA applications and technologies.
Basic Business Statistics: Concepts and Applications
Student-friendly stats! Berenson’s fresh, conversational writing style and streamlined design helps students with their comprehension of the concepts and creates a thoroughly readable learning experience. Basic Business Statistics emphasises the use of statistics to analyse and interpret data and assumes that computer software is an integral part of this analysis. Berenson’s ‘real world’ business focus takes students beyond the pure theory by relating statistical concepts to functional areas of business with real people working in real business environments, using statistics to tackle real business challenges.
Big Data: Concepts, Methodologies, Tools, and Applications
The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.
